埃隆·马斯克谈 Neuralink 首例人体植入与脑机接口的未来

以下是与埃隆·马斯克、DJ Seo、Matthew McDougall、Bliss Chapman 和 Nolan Arbaugh 关于 Neuralink 和人类未来的对话。埃隆、DJ、Matthew 和 Bliss 当然是 Neuralink 优秀团队的一部分，而 Nolan 是第一个在大脑中植入 Neuralink 设备的人类。我与他们每个人单独交谈，所以你可以使用时间戳跳转，或者像我推荐的那样，硬核地听完整个内容。这是我做过的最长的播客。这是一场迷人、超级技术性且范围广泛的对话，我享受其中的每一分钟。现在，亲爱的朋友们，这是埃隆·马斯克，他第五次参加 Lex Fridman 播客。喝咖啡还是水？水。我现在咖啡因摄入过多了。你想要点咖啡因吗？当然。有一种 Nitro 饮料。它应该能让你保持清醒直到，你知道，明天下午。是的。那么 Nitro 是什么？它只是含有很多咖啡因吗？别问问题。它叫 Nitro。你还需要知道别的吗？它里面含有氮气。这太荒谬了。我们呼吸的空气中有 78% 是氮气。他需要为你多加一些吗？你要吃它？大多数人以为他们在呼吸氧气，但实际上他们呼吸的是 78% 的氮气。你需要一个牛奶吧，就像《发条橙》里的那种。是的，是的。那是库布里克电影中你最喜欢的三部之一吗？《发条橙》很不错。我的意思是，它很疯狂，很刺耳。我会这么说。好的，好的。那么首先，让我们退一步，恭喜你将 Link 植入人体。这对 Neuralink 来说是历史性的一步。是的，未来还会有更多。是的，我们显然已经进行了第二次植入。进展如何？到目前为止一切顺利。看起来我们有大约 400 个电极在提供信号。很好。是的。你认为人类参与者的数量会以多快的速度增长？这在一定程度上取决于监管批准，我们获得监管批准的速度。所以我们希望到今年年底达到 10 个，总共 10 个，所以还有 8 个。每一次，你都会学到很多关于神经生物学、大脑、一切、Neuralink 的整个链条、解码、信号处理等方面的经验。是的，是的。我认为每一次都会变得更好。嗯，我不想说不吉利的话，但第二次植入似乎进行得非常顺利。所以有很多信号，很多电极。它工作得很好。

The following is a conversation with Elon Musk, DJ Seo, Matthew McDougall, Bliss Chapman, and Nolan Arbaugh about Neuralink and the future of humanity. Elon, DJ, Matthew, and Bliss are of course part of the amazing Neuralink team, and Nolan is the first human to have a Neuralink device implanted in his brain. I speak with each of them individually, so use time stamps to jump around, or as I recommend, go hardcore and listen to the whole thing. This is the longest podcast I've ever done. It's a fascinating, super technical, and wide-ranging conversation, and I loved every minute of it. And now, dear friends, here's Elon Musk, his fifth time on this The Lex Fridman podcast. Drinking coffee or water? Water. I'm so over-caffeinated right now. Do you want some caffeine? I mean, sure. There's a Nitro drink. This is supposed to keep you up till, like, you know, tomorrow afternoon, basically. Yeah. So what does Nitro? It's just got a lot of caffeine or something? Don't ask questions. It's called Nitro. Do you need to know anything else? It's got nitrogen in it. That's ridiculous. I mean, what we breathe is 78% nitrogen anyway. What, he needs to add more for you? You're going to eat it? Most people think that they're breathing oxygen, and they're actually breathing 78% nitrogen. You need like a Milk Bar, like from A Clockwork Orange. Yeah, yeah. Is that top three Kubrick films for you? A Clockwork Orange is pretty good. I mean, it's demented, jarring. I'd say. Okay, okay. So first, let's step back and, uh, big congrats on getting your Link implanted into a human. That's a historic step for Neuralink. And yeah, there's many more to come. Yeah, we're just, um, obviously have a second implant as well. How did that go? So far, so good. It looks like we've got, um, I think 400 electrodes that are providing signals. So nice. Yeah. How quickly do you think the number of human participants will scale? It depends somewhat on the regulatory approval, the rate at which we get regulatory approvals. So we're hoping to do 10 by the end of this year, total of 10, so eight more. And with each one, you're going to be learning a lot of lessons about the neurobiology, the brain, the everything, the whole chain of the Neuralink, the decoding, the signal processing, all that kind of stuff. Yeah, yeah. I think it's obviously going to get better with each one. Um, I mean, I don't want to jinx it, but it seems to have gone extremely well with the second implant. So there's a lot of signal, a lot of electrodes. It's working very well.

你认为在未来的几年里，Neuralink 会有哪些改进？我的意思是，在几年内，它将是巨大的。嗯，因为我们会大幅增加电极数量。嗯，我们会改进信号处理。所以，你知道，即使只有大约 10-15% 的电极在 Nolan（我们的第一位患者）身上工作，我们也能达到每秒比特数，是世界纪录的两倍。所以我认为在未来的几年里，我们会开始以数量级的方式大幅超越世界纪录。所以就像达到每秒 100 比特。你知道，也许五年后，我们可能会达到每秒一兆比特，比任何人类通过打字或说话进行交流的速度都要快。是的，BPS 是一个有趣的衡量指标。一旦达到一定水平的 BPS，体验可能会有巨大的飞跃。是的，比如全新的与计算机交互的方式可能会被解锁，以及与他人交互，前提是他们也有 Neuralink，对吧？否则他们无法足够快地接收信号。你认为这会提高智力对话的质量吗？嗯，我认为你可以这样想，如果你放慢交流速度，你会有什么感觉？如果你只以正常速度的十分之一说话，你会觉得“哇，这慢得令人痛苦。”是的。所以现在想象一下，你可以以正常速度的 10 倍、100 倍或 1000 倍清晰交流。听着，我很确定没有哪个理智的人会以 1 倍速听我说话。他们用 2 倍速听。所以我只能想象 10 倍速会是什么感觉，或者我是否能真正理解。我通常默认用 1.5 倍速。嗯，你可以用 2 倍速，但实际上，如果我想睡觉，如果我在听某人说话，比如 15-20 分钟的片段来入睡，那么我会用 1.5 倍速。嗯，如果我在认真听，我会用 2 倍速。对。嗯，但实际上，如果你开始以 1.5 倍速听播客或有声书之类的东西，那么 1 倍速听起来就慢得痛苦。我仍然坚持用 1 倍速，因为我害怕自己会对现实感到无聊，在现实世界里每个人都说 1 倍速。嗯，这取决于人。你可以说得非常快。我们可以非常快速地交流。而且，如果你使用更广泛的词汇，你的比特率，有效比特率会更高。这是一个很好的说法。是的，有效比特率。我的意思是，问题在于：在语言的低比特传输中，实际上压缩了多少信息？是的。如果有一个词能够传达通常需要 10 个简单词才能表达的东西，那么你就有了大约 10 倍的压缩。这就像模因。模因就像数据压缩。嗯，它侵入了一个整体，你同时接收到大量你可以解读的符号。嗯，而且你理解它的速度比文字或简单图片更快。当然，你指的是广义的模因，比如想法。是的，有一个完整的想法结构，就像一个想法模板，然后你可以在这个想法模板上添加一些东西。但别人脑子里已经有了那个预先存在的想法模板。嗯，所以当你添加那一点点增量信息时，你传达的内容比仅仅说几个字要多得多。它是与那个模因相关的一切。你认为随着电极数量的增加，会出现能力上的突跃吗？比如会有某个具体的数字，人类体验会发生改变？是的。你认为那个数字可能是多少，无论是电极数量还是 BPS？我们当然不确定，但会是 10,000、100,000 吗？是的，我的意思是，如果你达到每秒 10,000 比特，那将比现在任何人类的交流速度快得多。如果你考虑人类的平均比特率，在一天中它小于每秒 1 比特，因为一天有 86,400 秒，而你一天不会交流 86,400 个令牌。因此，你的最佳每秒比特率小于 1，24 小时平均下来非常慢。嗯，即使你交流得非常快，并且你在和一个理解你所说内容的人交谈……

What improvements do you think we'll see in Neuralink in the coming, let's say, let's get crazy, coming years? I mean, in years, it's going to be gigantic. Um, because we'll increase the number of electrodes dramatically. Um, we'll improve the signal processing. So, you know, with even only roughly, I don't know, 10-15% of the electrodes working with Nolan, with our first patient, we were able to achieve a bits per second that's twice the world record. So I think we'll start vastly exceeding the world record by orders of magnitude in the years to come. So it's like getting to, I don't know, 100 bits per second. You know, maybe maybe if five years from now, we might be at a megabit, like faster than any human could possibly communicate by typing or speaking. Yeah, that BPS is an interesting metric to measure. There might be a big leap in the experience once you reach a certain level of BPS. Yeah, like entire new ways of interacting with a computer might be unlocked, and with humans, with other humans, provided they have a Neuralink too, right? Otherwise, they won't be able to receive the signals fast enough. Do you think that'll improve the quality of intellectual discourse? Well, I think you can think of it, you know, if you were to slow down communication, how would you feel about that? You know, if you only talked at, let's say, 1/10 of normal speed, you would be like, "Wow, that's agonizingly slow." Yeah. So now imagine you could communicate clearly at 10 or 100 or a thousand times faster than normal. Listen, I'm pretty sure nobody in their right mind listens to me at 1x. They listen at 2x. So I can only imagine what 10x would feel like, or if I could actually understand it. I usually default to 1.5x. Um, you can do 2x, but well, actually, if I'm trying to go to sleep, if I'm listening to somebody for like 15-20 minute segments to go to sleep, then I'll do it at 1.5x. Um, if I'm paying attention, I'll do 2x. Right. Um, but actually, if you start listening to podcasts or audiobooks or anything at, if you get used to doing it at 1.5, then 1 sounds painfully slow. I'm still holding on to 1x because I'm afraid of myself becoming bored with the reality, with the real world where everyone's speaking at 1x. Well, it depends on the person. You can speak very fast. Like we can communicate very quickly. And also, if you use a wide range of, if your vocabulary is larger, your bit rate, effective bit rate is higher. That's a good way to put it. Yeah, the effective bit rate. I mean, that is the question: how much information is actually compressed in the low bit transfer of language? Yeah. If there's a single word that is able to convey something that would normally require, I don't know, 10 simple words, then you've got a maybe a 10x compression on your hands. That's really like with memes. Memes are like data compression. Um, it invades a whole, you're simultaneously hit with a wide range of symbols that you can interpret. Um, and it's, you kind of get it faster than if it were words or a simple picture. And of course, you're referring to memes broadly, like ideas. Yeah, there's an entire idea structure that is like an idea template, and then you can add something to that idea template. But somebody has that pre-existing idea template in their head. Um, so when you add that incremental bit of information, you're conveying much more than if you just, you know, said a few words. It's everything associated with that meme. You think there'll be emergent leaps of capability as you scale the number of electrodes? Like there'll be a certain, you think there'll be like an actual number where the human experience will be altered? Yes. What do you think that number might be, whether electrodes or BPS? We, of course, don't know for sure, but is this 10,000, 100,000? Yeah, I mean, certainly if you're anywhere at 10,000 bits per second, I mean, that's vastly faster than any human can communicate right now. If you think of the average bits per second of a human, it is less than one bit per second over the course of a day because there are 86,400 seconds in a day, and you don't communicate 86,400 tokens in a day. Therefore, your best second is less than one, average over 24 hours. It's quite slow. Um, and now even if you're communicating very quickly and you're talking to somebody who understands what you're saying...

因为为了交流，你至少要在一定程度上模拟你说话对象的心理状态。然后你把你试图传达的概念压缩成少量音节，说出来，希望对方能将其解压成一个尽可能接近你脑海中概念结构的结构。

Because in order to communicate, you have to, at least to some degree, model the mind state of the person to whom you're speaking. You then take the concept you're trying to convey, compress that into a small number of syllables, speak them, and hope that the other person decompresses them into a conceptual structure that is as close to what you have in your mind as possible.

是啊，这个过程里有很多信号丢失。

Yeah, there's a lot of signal loss there in that process.

是的，非常有损的压缩和解压。你的神经元所做的很多事情就是将概念提炼成少量符号，比如我说话的音节或按键，等等。所以你的大脑计算很大一部分都在做这个。不过，有一种观点认为这实际上是一件健康或有帮助的事情，因为当你试图压缩复杂概念时，你或许被迫提炼出这些概念中最本质的东西，而不是所有无关紧要的细节。所以在压缩过程中，你只提炼出最重要的东西，因为你只能说几句话。所以这也许是有帮助的。

Yes, very lossy compression and decompression. And a lot of what your neurons are doing is distilling the concepts down to a small number of symbols, like syllables that I'm speaking or keystrokes, whatever the case may be. So that's a lot of what your brain computation is doing. Now, there is an argument that this is actually a healthy or helpful thing to do, because as you try to compress complex concepts, you're perhaps forced to distill what is most essential in those concepts, as opposed to just all the fluff. So in the process of compression, you distill things down to what matters the most, because you can only say a few things. So that is perhaps helpful.

我认为，如果我们的数据传输速率提高，我们很可能会变得冗长得多。就像你的电脑一样。当电脑只有——我的第一台电脑只有 8K 内存，所以你确实会考虑每一个字节。而现在你有拥有许多 GB 内存的电脑。所以如果你想做一个只显示“Hello World”的 iPhone 应用，它可能至少需要几兆字节，一堆废话。但尽管如此，我们仍然更喜欢拥有更多内存和更多算力的电脑。

I think we might, if our data rate increases, it's highly probable that we'll become far more verbose. Just like your computer. When computers had, my first computer had 8K of RAM, so you really thought about every byte. And now you have computers with many gigabytes of RAM. So if you want to do an iPhone app that just says 'Hello World', it's probably several megabytes minimum, a bunch of fluff. But nonetheless, we still prefer to have the computer with more memory and more compute.

所以 Neuralink 的长期愿景是通过提高通信带宽来改善 AI 与人类的共生关系。因为即使在最良性的 AI 场景中，你也必须考虑到 AI 会厌倦等待你吐出几个字。我的意思是，如果 AI 能以每秒太比特的速度通信，而你以每秒比特的速度通信，那就像和一棵树说话。

So the long-term aspiration of Neuralink is to improve the AI-human symbiosis by increasing the bandwidth of the communication. Because even in the most benign scenario of AI, you have to consider that the AI is simply going to get bored waiting for you to spit out a few words. I mean, if the AI can communicate at terabits per second and you're communicating at bits per second, it's like talking to a tree.

嗯，对于一个超级智能物种来说，这是一个非常有趣的问题：人类有什么用？

Well, it is a very interesting question for a super intelligent species: what use are humans?

我认为有一种观点认为人类是意志的来源。意志或目的的来源。所以如果你认为人类心智本质上由原始的边缘系统（甚至爬行动物也有）和皮层（大脑中思考和计划的部分）组成。现在皮层比边缘系统聪明得多，但很大程度上却在为边缘系统服务，试图让边缘系统快乐。我的意思是，人们为了交配投入的算力是惊人的。他们实际上并不是为了繁衍，只是字面意义上试图做这种简单的动作，并从中获得快感。

I think there is some argument for humans as a source of will. Source of will or purpose. So if you consider the human mind as being essentially the primitive limbic elements, which basically even reptiles have, and the cortex, the thinking and planning part of the brain. Now the cortex is much smarter than the limbic system, and yet is largely in service to the limbic system, trying to make the limbic system happy. I mean, the sheer amount of compute that's gone into people trying to get laid is insane. Without actually seeking procreation, they're just literally trying to do this sort of simple motion, and they get a kick out of it.

是啊，所以这种行为，抽象来看是相当荒谬的动作，也就是性。皮层投入了大量算力试图弄清楚如何做到这一点。所以人类物种 90% 的分布式算力可能都花在了试图交配上。

Yeah, so this style, which in the abstract is rather absurd motion, which is sex. The cortex is putting a massive amount of compute into trying to figure out how to do that. So like 90% of distributed compute of the human species is spent on trying to get laid, probably.

很大，是的。大多数性行为除了享乐主义之外没有目的，你知道，只是一种快乐或别的什么，多巴胺释放。偶尔是为了繁衍，但对人类来说，尤其是现代人类，主要是娱乐性的。所以你的皮层，比你的边缘系统聪明得多，却在试图让边缘系统快乐，因为边缘系统想要性，或者想要美味的食物，等等。然后这又被第三层系统进一步放大，也就是你的手机、笔记本电脑、iPad 等等，你所有的计算设备。那是你的第三层。所以你实际上已经是一个半机械人了。你拥有这个第三层算力层，以你的电脑及其所有应用程序、所有计算设备的形式存在。所以在交配方面，实际上也有大量的数字算力在试图交配，比如 Tinder 之类的。

Large, yeah. There's no purpose to most sex except hedonistic, you know, it's just sort of joy or whatever, dopamine release. Now once in a while it's procreation, but for humans, mostly modern humans, it's mostly recreational. And so your cortex, much smarter than your limbic system, is trying to make the limbic system happy because the limbic system wants to have sex, or wants some tasty food, or whatever the case may be. And then that is further augmented by the tertiary system, which is your phone, your laptop, iPad, whatever, all your computing stuff. That's your tertiary layer. So you're actually already a cyborg. You have this tertiary compute layer in the form of your computer with all the applications, all your computer devices. And so in the getting laid front, there's actually a massive amount of digital compute also trying to get laid, with Tinder and whatever.

是啊，我的意思是，有千兆瓦级的算力投入到交配中，数字算力。

Yeah, I mean there's like gigawatts of compute going into getting laid, of digital compute.

是啊，如果 AGI 就是我们说话时正在发生的事情呢？如果我们与 AI 融合，它只会扩大我们人类使用的算力，基本上只是为了尝试其中一件事，当然。

Yeah, what if AGI is this happening as we speak? If we merge with AI, it's just going to expand the compute that we humans use pretty much to try just one of the things, certainly.

是啊，是啊。但我要说的是，是的，人类有什么用？嗯，有一个根本问题：生命的意义是什么，为什么要做任何事情。所以如果我们简单的边缘系统提供了做某事的意志来源，然后传递到我们的皮层，再传递到我们的第三层算力层，那么，我不知道，实际上可能 AI 只是在试图让人类的边缘系统快乐。

Yeah, yeah. But what I'm saying is that yes, what is there a use for humans? Well, there's this fundamental question of what's the meaning of life, why do anything at all. And so if our simple limbic system provides a source of will to do something, that then goes to our cortex, that then goes to our tertiary compute layer, then you know, I don't know, it might actually be that the AI is simply trying to make the human limbic system happy.

是的，似乎意志不仅仅是关于边缘系统。里面有很多有趣复杂的东西。我们也想要权力，我认为那也是边缘系统。但我们也想以某种合作的方式减轻世界的痛苦。不是每个人都这样，但当然，有些人会。作为一群人类，当我们聚在一起时，我们开始拥有这种集体智能，其意志比底层个体猿类后代更复杂，对吧？所以还有其他动机，这可能是 AGI 目标函数的一个非常有趣的来源。

Yeah, it seems like it's the will is not just about the limbic system. There's a lot of interesting complicated things in there. We also want power, that's limbic too I think. But then we also want to, in a kind of cooperative way, alleviate the suffering in the world. Not everybody does, but sure, some people do. As a group of humans, when we get together, we start to have this kind of collective intelligence that is more complex in its will than the underlying individual descendants of apes, right? So there are other motivations, and that could be a really interesting source of an objective function for AGI.

我的意思是，有一些相当理性或更高层次的目标。对我来说，就像生命的意义是什么，或者理解宇宙的本质，这对我来说非常有趣，希望 AI 也是。这就是 xAI 和 Grok 的使命：理解宇宙。

I mean, there are these fairly cerebral or kind of higher-level goals. For me, it's like what's the meaning of life, or understanding the nature of the universe is of great interest to me, and hopefully to the AI. And that's the mission of xAI and Grok: understand the universe.

那么你认为当你有 10,000、100,000 个通道的 Neuralink 时，大多数用例会是和 AI 系统通信吗？

So do you think when you have a Neuralink with 10,000, 100,000 channels, most of the use cases will be communication with AI systems?

嗯，假设它们不是……我的意思是，有解决人们基本神经问题的方法。如果他们的脊髓或颈部有受损的神经元，就像我们的前两位患者一样，那么显然首要任务是解决脊髓、颈部或大脑本身的根本性神经元损伤。所以我们的第二个产品叫做 Blindsight，旨在让完全失明、失去双眼或视神经或根本看不见的人，通过直接触发视觉皮层的神经元来恢复视力。所以我们只是从基础开始。相对来说，解决神经元损伤是简单的事情。它也可以解决，我认为可能精神分裂症，如果人们有某种癫痫发作，可能也能解决。它可以帮助改善记忆。

Well, assuming that they're not... I mean, there's solving basic neurological issues that people have. If they've got damaged neurons in their spinal cord or neck, as is the case with our first two patients, then obviously the first order business is solving fundamental neuron damage in the spinal cord, neck, or in the brain itself. So our second product is called Blindsight, which is to enable people who are completely blind, lost both eyes or optic nerve or just can't see at all, to be able to see by directly triggering the neurons in the visual cortex. So we're just starting at the basics here. This is like the simple stuff, relatively speaking, is solving neuron damage. It can also solve, I think probably schizophrenia, if people have seizures of some kind, probably solve that. It could help with memory.

所以这有点像科技树，你得先有基础。你得先识字才能看《指环王》。你有字母、有字母表，好，然后有单词，最后才有史诗。所以我觉得未来可能有些需要担心的事，但头几年真的只是解决基本的神经损伤，比如那些大脑到身体的连接完全或几乎丧失的人。斯蒂芬·霍金就是一个例子。Neuralink 会非常意义深远，因为你可以想象，如果斯蒂芬·霍金能像我们一样快地交流，甚至更快，那会怎样。这当然是可能的，很可能，甚至我觉得是很有可能的。所以这里有医疗和非医疗两条轨道。

So there's like a kind of a tech tree if you will, like you've got the basics. You need literacy before you can have Lord of the Rings. You have letters, an alphabet, okay great, words, then eventually sagas. So I think there may be some things to worry about in the future, but the first several years are really just solving basic neurological damage, like for people who have essentially complete or near complete loss of connection from the brain to the body. Like Stephen Hawking would be an example. The Neuralink would be incredibly profound because you can imagine if Stephen Hawking could communicate as fast as we're communicating, perhaps faster. And that's certainly possible, probable, in fact likely, I'd say. So there's a kind of dual track of medical and non-medical.

合乎逻辑的做法、明智的做法，是从解决基本的神经元损伤问题开始。因为新设备显然有风险，你不可能把风险降到零，这是不可能的。所以，在存在一定不可降低风险的情况下，你想要获得尽可能高的回报。如果某人能在交流能力上获得巨大改善，那这个风险就值得冒。随着风险降低，一旦风险降到很低，比如有几千人用了好几年，风险极小，那么也许那时你可以考虑说，好吧，现在我们可以瞄准增强功能了。但我认为我们实际上会直接针对有神经元损伤的人进行增强。我们的目标不仅仅是给人们相当于正常人类的通信速率，而是要给那些四肢瘫痪或大脑与身体连接完全丧失的人提供超过正常人类的通信速率。反正我们已经进去了，为什么不呢？让我们给人们超能力。视觉也一样。当你恢复视觉时，恢复的某些方面可以是超人的。一开始，视觉恢复会是低分辨率的，因为你得考虑能植入多少神经元并触发它们。但你可以调整电场，所以即使你只有 1 万个神经元，也不只是 1 万个像素。你可以调整神经元之间的电场，用模式化的方式来驱动，这样 1 万个电极实际上可能给你带来百万像素甚至千万像素的效果。所以随着时间的推移，我认为你会得到比人眼更高的分辨率，而且你还能看到不同波长的光。就像《星际迷航》里的乔迪·拉·福吉，如果你想看雷达，没问题。你可以看到紫外线、红外线、鹰的视力，随你选。

The logical thing to do, the sensible thing to do, is to start off solving basic neuron damage issues. Because there's obviously some risk with a new device. You can't get the risk down to zero, it's not possible. So you want to have the highest possible reward given that there's a certain irreducible risk. And if somebody is able to have a profound improvement in their communication, that's worth the risk. As you get the risk down, once the risk is down to, you know, if you have thousands of people who have been using it for years and the risk is minimal, then perhaps at that point you could consider saying, okay, let's aim for augmentation now. But I think we're actually going to aim for augmentation with people who have neuron damage. So we're not just aiming to give people a communication data rate equivalent to normal humans. We're aiming to give people who have quadriplegia or maybe complete loss of connection to the brain and body a communication data rate that exceeds normal humans. I mean, we're in there, why not? Let's give people superpowers. And the same for vision. As you restore vision, there could be aspects of that restoration that are superhuman. At first, the vision restoration will be low resolution, because you have to say how many neurons you can put in there and trigger. But you can adjust the electric field, so even if you've got say 10,000 neurons, it's not just 10,000 pixels. You can adjust the field between the neurons and do them in patterns in order to get, say, 10,000 electrodes effectively giving you maybe like a megapixel or a 10 megapixel situation. So over time, I think you get to higher resolution than human eyes, and you could also see in different wavelengths. Like Geordi La Forge from Star Trek, you know, if you want to see in radar, no problem. You can see ultraviolet, infrared, eagle vision, whatever you want.

你觉得会不会……让我问一个乔·罗根式的问题。你觉得会不会……我最近服用了死藤水。这是个问题吗？不，嗯是的，严格来说算是个问题。你试过吗？

Do you think there will be... let me ask a Joe Rogan question. Do you think there will be... I've recently taken ayahuasca. Is that a question? No, well yes, I guess technically it is. Have you ever tried it?

我爱你，乔。好吧，等等，等等。你谈过很多吗？我没有。我一直……好吧，那就说说吧。

I love you, Joe. Okay, wait, wait. Yeah, have you said much about it? I have not. I've been... okay, well, spill the beans.

哦，那真是一次不可思议的经历。角色反转了，是吧？哇。我的意思是，你在丛林里，是的，在树木之间，我和萨满，是的，是的，是的，周围有昆虫，有动物，目之所及全是丛林。我是说，就该这么体验。事情会看起来非常狂野。是的，非常狂野。我服用了极高剂量。别去抱蟒蛇什么的。你知道，没跟蟒蛇亲热过就不算活过。抱歉。但蛇梯棋嘛。是的，那是……我服用了极高剂量的死藤水。九杯。该死。听起来很多。当然，不是只喝一杯或一两杯。通常是一杯。你是一上来就喝，还是慢慢加量？所以我……你两天内就跳进去了，因为第一天我喝了两杯，那是一次旅程，但不算什么启示，不像是深空之旅。就像坐小飞机。看到了一些树和视觉幻象，看到了一条龙之类的东西。但九杯……我觉得你去了冥王星。冥王星，是的。不，深空，深空。我经历中一个有趣的地方是，我以为我会遇到一些心魔，有些东西需要处理。每个人都这么说。每个人都这么说。是的，没错。什么都没有。全是正面的。我只有纯粹的灵魂。我不这么认为，我不知道。但我一直在想它。关于我生活中认识的人，我有极高分辨率的想法。你在那里。那只是……不是基于我和那个人的关系，而是那个人本身。我对他们是谁充满了深深的感激。那很酷。就像一次探索，就像《模拟人生》之类的，你可以观察他们。我观察人们，惊叹于他们有多么了不起。听起来很棒。是的，很棒。我一直在等心魔出现。没错。也许我会有一些负面想法。什么都没有。我对他们只有极度的感激。然后还有很多太空旅行。太空旅行去哪里？是这样的。我认识的人，他们有一种……我能描述的最好方式是他们身上有光芒。然后我不断从他们身边飞出去，看到地球，看到我们的太阳系，看到我们的银河系。我看到那道光，那光芒，遍布整个宇宙。就像无论那是什么形态，无论那是什么……你飞过了银河系吗？是的。你就像星系际旅行。星系际，是的。但总是向内指向，是的。飞过银河系，我是说，我看到了大量的星系，星系际的，所有都在发光。所以我无法控制那次旅行，因为我实际上会探索太阳系附近的距离，看看有没有外星人之类的东西。不，我没看到外星人。外星人的暗示，因为他们也在发光，他们以和人类一样的方式发光。我看到的那种生命力，那种让人类了不起的东西，遍布整个宇宙。就像这些发光的小点。所以我不知道，这让我觉得有生命……不，不是生命，而是某种东西，无论是什么让人类了不起，遍布整个宇宙。听起来不错。是的，太棒了。没有心魔。没有心魔。我找过心魔。没有心魔。有龙，它们非常棒。所以那次旅行的重点是……

Oh, it was a truly incredible experience. Turn the tables, aren't you? Wow. I mean, you're in the jungle, yeah, amongst the trees, myself, and the shaman, yeah, yeah, yeah, with the insects, with the animals all around you, like jungle as far as I can see. I mean, that's the way to do it. Things are going to look pretty wild. Yeah, pretty wild. I took an extremely high dose. Don't go hugging an anaconda or something. You know, you haven't lived unless you made love to an anaconda. I'm sorry. But snakes and ladders. Yeah, it was... I took an extremely high dose of ayahuasca. Nine cups. Damn. That sounds like a lot. Of course, it's not just one cup or one or two. Well, usually one. You went... wait, like right off the bat, or do you work your way up to it? So I... you just jump at it across two days, because on the first day I took two, and it was a ride, but it wasn't quite like a revelation, it wasn't like a deep space type of ride. It was just like a little airplane ride. Saw some trees and some visuals and all that, saw a dragon and all that kind of stuff. But nine cups... you went to Pluto, I think. Pluto, yeah. No, deep space, deep space. One of the interesting aspects of my experience is I thought I would have some demons, some stuff to work through. That's what everyone says. Everyone says that. Yeah, exactly. Nothing. I had all positive. I had just pure soul. I don't think so, I don't know. But I kept thinking about it. It had extremely high resolution thoughts about the people I know in my life. You were there. It was just... it's not from my relationship with that person, but just as the person themselves. I had this deep gratitude of who they are. That's cool. It was just like this exploration, like Sims or whatever, you get to watch them. I got to watch people and just be in awe of how amazing they are. It sounds awesome. Yeah, it's great. I was waiting for the demon to come. Exactly. Maybe I'll have some negative thoughts. Nothing. I just had extreme gratitude for them. And then also a lot of space travel. Space travel to where? So here's what it was. The human beings that I know, they had this... the best way I can describe is they had a glow to them. And then I would keep flying out from them to see Earth, to see our solar system, to see our galaxy. And I saw that light, that glow, all across the universe. Like whatever that form is, whatever that... Did you go past the Milky Way? Yeah. You're like intergalactic. Intergalactic, yeah. But always pointing in, yeah. Past the Milky Way, I mean, I saw like a huge number of galaxies, intergalactic, and all of it was glowing. So I couldn't control that travel, because I would actually explore near distances to the solar system, see if there's aliens or any of that kind of stuff. No, I didn't see aliens. Implication of aliens because they were glowing, they were glowing in the same way that humans were glowing. That life force that I was seeing, the thing that made humans amazing, was there throughout the universe. Like there were these glowing dots. So I don't know, it made me feel like there's life... no, not life, but something, whatever makes humans amazing, all throughout the universe. Sounds good. Yeah, it was amazing. No demons. No demons. I looked for the demons. There's no demons. There were dragons, and they're pretty awesome. So the thing about the trip was...

有什么可怕的东西吗？

Anything scary at all?

呃，龙，但它们不可怕。它们很友好，是保护性的。所以问题是，魔法？不，更像是《权力的游戏》那种——它们不太友好，非常大。所以关于夜晚的巨树，那是我所在的地方。我的意思是，丛林有点吓人。是的，树木开始看起来像龙，它们都看着我。当然，好吧，这看起来并不可怕。它们似乎在保护我。而且，顺便说一句，萨满和那些人不说英语，这让事情更可怕，因为我们甚至在很多方面都天差地别。只是——但没错，没有——他们谈论森林之母保护你，而我就是那种感觉。而且你在丛林深处，非常偏远。这不像是一个旅游度假村，你知道，比如离某个小镇 10 英里。不，我们去了——不，这不是 AEP 亚马逊。所以我和一个叫 Paul Rosolie 的家伙，他基本上就是人猿泰山，他住在丛林里，我们深入其中，彻底疯狂了。

Uh, dragons, but they weren't scary. They were friendly, they were protective. So the thing is, magic? No, it was more like Game of Thrones kind of—they weren't very friendly, they were very big. So the thing is about giant trees at night, which is where I was. I mean, the jungle's kind of scary. Yeah, the trees started to look like dragons, and they were all like looking at me. Sure, okay, and it didn't seem scary. They seemed like they were protecting me. And the shaman and the people didn't speak in English, by the way, which made it even scarier because we're not even like, you know, worlds apart in many ways. It just—but yeah, there was not—they talk about the mother of the forest protecting you, and that's what I felt like. And you're way out in the jungle, way out there. This is not like a tourist retreat, you know, like 10 miles outside of a foo or something. No, we went—no, this is not AEP Amazon. So me and this guy named Paul Rosolie, who basically is Tarzan, he lives in the jungle, we went on deep and we just went crazy.

哇，酷。是的，那么，我能在 Neuralink 中获得同样的体验吗？可能吧。是的，我想这是针对非残疾人士的问题。你认为在我们的感知、我们对世界的体验中，有很多东西可以用 Neuralink 来探索、来玩吗？

Wow, cool. Yeah, so anyway, can I get that same experience in a Neuralink? Probably. Yeah, I guess that is the question for non-disabled people. Do you think that there's a lot in our perception, in our experience of the world, that could be explored, that could be played with using Neuralink?

是的，我的意思是，Neuralink 实际上是一个通用的输入输出设备。你知道，它只是读取电信号并产生电信号。我的意思是，你一生中经历的一切——气味、情绪——所有这些都是电信号。所以，认为你整个生命体验被简化为来自神经元的电信号，这有点奇怪，但事实确实如此。或者我的意思是，至少所有证据都指向这一点。所以我的意思是，你可以触发正确的神经元，你可以触发特定的气味，你当然可以让东西发光，我的意思是，几乎可以做任何事情。真的，你可以把大脑看作一台生物计算机。所以，如果那台生物计算机的某些芯片或元件坏了——比如你的能力，如果你中风了，这意味着你大脑的某些部分受损了。如果那是，比如说，语言生成或移动左手的能力，那就是 Neuralink 可以解决的问题。如果是大量的记忆丢失，完全消失了，那么，我们无法找回记忆。我们可以恢复你制造记忆的能力，但我们无法恢复完全消失的记忆。现在，我应该说，如果部分记忆还在，而访问记忆的途径坏了，那么我们可以重新启用访问记忆的能力。所以你可以把它想象成计算机中的 RAM。如果 RAM 被毁或你的 SD 卡被毁，你无法找回数据。但如果连接到 SD 卡的接口被毁，我们可以修复它。如果它在物理上可修复，那么是的，它可以被修复。

Yeah, I mean, Neuralink is really a generalized input-output device. You know, it's just reading electrical signals and generating electrical signals. And I mean, everything that you've ever experienced in your whole life—smell, you know, emotions—all of those are electrical signals. So it's kind of weird to think that your entire life experience is distilled down to electrical signals from neurons, but that is in fact the case. Or I mean, if that's at least what all the evidence points to. So I mean, you could trigger the right neuron, you could trigger a particular scent, you could certainly make things glow, I mean, do pretty much anything. I mean, really, you can think of the brain as a biological computer. So if there are certain chips or elements of that biological computer that are broken—let's say your ability to, if you've had a stroke, that means you got some part of your brain is damaged. If that's, let's say, a speech generation or the ability to move your left hand, that's the kind of thing that Neuralink could solve. If it's a massive amount of memory loss that's just gone, well, we can't get the memories back. We could restore your ability to make memories, but we can't restore memories that are fully gone. Now, I should say, if part of the memory is there and the means of accessing the memory is the part that's broken, then we could re-enable the ability to access the memory. So you can think of like RAM in a computer. If the RAM is destroyed or your SD card is destroyed, you can't get that back. But if the connection to the SD card is destroyed, we can fix that. If it is fixable physically, then yeah, then it can be fixed.

当然，有了 AI，你可以像修复照片一样，填补照片中缺失的部分。也许你也可以做同样的事情，是的，你可以说，基于你拥有的关于那个人的所有信息，创建最可能的记忆集。然后，这将是概率性的记忆恢复。

Of course, with AI you can just like repair photographs and fill in missing parts of photographs. Maybe you can do the same just yeah, you could say like create the most probable set of memories based on all the information you have about that person. You could then, it would be probabilistic restoration of memory.

现在我们讨论得相当深奥了，但那是人类体验中最美好的方面之一：记住美好的回忆。就像，我们确实——我们一生大部分时间，正如 Danny Conan 刚才谈到的，都活在我们的记忆中，而不是当下。我们只是在收集记忆，然后在脑海中重温它们。那是美好的时光。如果你把我们的一生积分起来，正是记住美好时光产生了最大的幸福感。所以，是的，我的意思是，我们除了记忆还能是什么？死亡除了记忆的丧失、信息的丧失还能是什么？你知道，如果你可以说，如果你被无痛地分解，然后片刻后重新整合——就像瞬间移动，我想——只要没有信息损失，你的身体被分解这一事实就无关紧要了。而记忆正是其中如此重要的一部分。死亡从根本上说是信息的丧失、记忆的丧失。所以，如果我们能尽可能准确地存储它们，我们基本上就实现了一种永生。

Now we're getting pretty esoteric here, but that is one of the most beautiful aspects of the human experience: remembering the good memories. Like, we sure—we live most of our life, as Danny Conan just talked about, in our memories, not in the moment. We're just collecting memories and we kind of relive them in our head. And that's the good times. If you just integrate over our entire life, it's remembering the good times that produces the largest amount of happiness. And so yeah, I mean, what are we but our memories? And what is death but the loss of memory, loss of information? You know, if you could say, well, if you were disintegrated painlessly and then reintegrated a moment later—like teleportation, I guess—provided there is no information loss, the fact that your one body was disintegrated is irrelevant. And memories is just such a huge part of that. Death is fundamentally the loss of information, the loss of memory. So if we can store them as accurately as possible, we basically achieve a kind of immortality.

是的，你谈到了 AI 的威胁和安全问题。让我们看看长期愿景。你认为，在你看来，Neuralink 是我们目前拥有的 AI 安全的最佳方法吗？

Yeah, you've talked about the threats, the safety concerns of AI. Let's look at long-term visions. You think Neuralink is, in your view, the best current approach we have for AI safety?

这是一个可能有助于 AI 安全的想法，当然。我不想声称它是什么万能药或确定的事情。但我的意思是，很多年前我就在想，什么会阻碍人类集体意志与人工智能的对齐？人类低下的数据传输速率，尤其是我们缓慢的输出速率，必然会——仅仅因为通信如此缓慢——削弱人类与计算机之间的联系。就像，你越是一棵树，你就越不知道树是什么样的。假设你看着一棵树，看着这株植物什么的，然后说，嘿，我真的很想让那株植物快乐，但它没说什么，你知道。所以，我们越提高人类可以输入和输出的数据速率，那就意味着越好，在一个充满 AGI 的世界里，我们成功的机会就越高。是的，如果输出速率特别是大幅提高，我们可以更好地将人类集体意志与 AI 对齐。我认为输出速率有可能提高，我不知道，三个、六个甚至更多数量级。所以这比现状要好。而那个输出速率将通过增加电极数量、通道数量，以及可能植入多个 Neuralink 来实现。

It's an idea that may help with AI safety, certainly. I wouldn't want to claim it's like some panacea or that's a sure thing. But I mean, many years ago I was thinking, well, what would inhibit alignment of human collective will with artificial intelligence? And the low data rate of humans, especially our slow output rate, would necessarily—just because the communication is so slow—diminish the link between humans and computers. Like, the more you are a tree, the less you know what the tree is like. Let's say you look at a tree, you look at this plant or whatever, and like, hey, I'd really like to make that plant happy, but it's not saying a lot, you know. So the more we increase the data rate that humans can intake and output, then that means the better, the higher the chance we have in a world full of AGIs. Yeah, we could better align collective human will with the AI if the output rate especially was dramatically increased. And I think there's potential to increase the output rate by, I don't know, three, maybe six, maybe more orders of magnitude. So it's better than the current situation. And that output rate would be by increasing the number of electrodes, number of channels, and also maybe implanting multiple Neuralinks.

你认为在接下来的几十年里，会出现一个数亿人拥有 Neuralink 的世界吗？

Do you think there will be a world in the next couple of decades where it's hundreds of millions of people have Neuralink?

是的，我确实这么认为。我认为当人们看到这些能力，可能的超人能力，然后安全性得到证明——是的，如果它极其安全，并且你拥有超人能力，比如说你可以上传你的记忆，你知道，这样你就不会失去记忆，那么我认为很多人可能会选择拥有它。它将取代手机，例如。我的意思是，手机最大的问题是试图弄清楚你想要什么。所以这就是为什么你有自动补全和输出，这些都是——

Yeah, I do. I think when people just see the capabilities, the superhuman capabilities that are possible, and then the safety is demonstrated—yeah, if it's extremely safe, and you have superhuman abilities, and let's say you can upload your memories, you know, so you wouldn't lose memories, then I think probably a lot of people would choose to have it. It would supersede the cell phone, for example. I mean, the biggest problem that a phone has is trying to figure out what you want. So that's why you've got autocomplete and you've got output which is all—

屏幕上的像素，但从人类的角度来看，输出慢得要命。台式机或手机拼命想理解你想要什么，每次按键之间都有一种迟缓。从计算机的角度看，计算机在跟一棵树对话，一棵试图滑动屏幕的慢吞吞的树。

The pixels in the screen, but from the perspective of the human, the output is so freaking slow. Desktop or phone is desperately just trying to understand what you want, and there's an alacrity between every keystroke. From a computer standpoint, the computer's talking to a tree, a slow-moving tree that's trying to swipe.

是的，如果计算机每秒执行数万亿条指令，而一秒钟过去了，它本可以做一万亿件事。我觉得这对人们来说既令人兴奋又可怕，因为一旦拥有非常高的比特率，就会以一种难以想象的方式改变人类体验。我们会变成不同的存在，某种未来主义的赛博格。我们显然在谈论遥远的未来，但并不是超级遥远——也许 10 到 15 年。

Yeah, so if you have computers that are doing trillions of instructions per second and a whole second went by, there are a trillion things it could have done. I think it's exciting and scary for people because once you have a very high bit rate, that changes the human experience in a way that's very hard to imagine. We would be something different, some sort of futuristic cyborg. We're obviously talking about the distant future, but it's not super far away—maybe 10 or 15 years.

我什么时候能有一个？10 年？

When can I get one? 10 years?

可能不到 10 年，取决于你想做什么。如果我能达到每秒一千比特，而且安全，我可以躺着吃奇多（我不吃奇多）就能跟计算机交互，那么人机交互的某些方面，如果做得更高效、更愉快，就是值得的。我们相当有信心，在未来一两年内，植入 Neuralink 的人就能击败职业玩家，因为反应时间会更快。

Probably less than 10 years, depends on what you want to do. If I can get like a thousand bits per second, and it's safe, and I can just interact with a computer while laying back and eating Cheetos—I don't eat Cheetos—there are certain aspects of human-computer interaction that, when done more efficiently and more enjoyably, are worth it. We feel pretty confident that within the next year or two, someone with a Neuralink implant will be able to outperform a pro gamer, because the reaction time would be faster.

我去过孟菲斯。你在算力上大举投入。你也说过要么赢，要么别玩。那么，要在 AI 领域获胜需要什么？

I got to visit Memphis. You're going big on compute. You've also said play to win or don't play at all. So what does it take to win for AI?

这意味着你必须拥有最强大的训练算力，而且训练算力的提升速度必须比其他人都快，否则你就赢不了——你的 AI 会更差。

That means you've got to have the most powerful training compute, and the rate of improvement of training compute has to be faster than everyone else, or you will not win—your AI will be worse.

那么，比如说 Grok 3，可能明年可用——幸运的话今年年底——它如何成为世界上最好的 LLM、最好的 AI 系统？其中多少是算力，多少是数据，多少是后训练，多少是你打包的产品？

So how can Grok 3, let's say, that might be available next year—hopefully end of this year, Grok 3 for lucky—how can that be the best LLM, the best AI system available in the world? How much of it is compute, how much is data, how much is post-training, how much is the product you package it in?

它们都很重要。这就像一级方程式赛车：车和车手哪个更重要？两者都重要。如果你的车不够快——比如只有竞争对手一半的马力——最好的车手也会输。如果马力是两倍，那么即使平庸的车手也能赢。所以训练算力就像引擎，马力有多大。你要在这方面做到最好。然后是你如何高效利用训练算力，以及如何高效进行推理——AI 的使用——这取决于人才。还有你拥有哪些独特的数据访问权限？这也起作用。

They all matter. It's like a Formula 1 race: what matters more, the car or the driver? Both matter. If your car is not fast—say half the horsepower of a competitor—the best driver will still lose. If it's twice the horsepower, then probably even a mediocre driver will still win. So the training compute is like the engine, how many horsepower. You want to do the best on that. Then how efficiently you use that training compute and how efficiently you do inference—the use of the AI—that comes down to human talent. And what unique access to data do you have? That also plays a role.

你认为 Twitter 的数据会有用吗？

You think Twitter data will be useful?

是的，我认为大多数领先的 AI 公司已经抓取了所有 Twitter 数据。展望未来，有用的是它的实时性。他们很难实时抓取，所以 Grok 已经拥有即时性优势。有了特斯拉，来自数百万辆汽车（最终数千万辆）的实时视频，以及 Optimus，可能有数亿甚至数十亿个 Optimus 机器人，从现实世界学习大量知识。我认为这最终是最大的数据来源。Optimus 将成为最大的数据来源，因为现实本身规模巨大。实际上，看到人类积累的数据如此之少，令人汗颜。人类产生了多少万亿可用 token？扣除垃圾信息和重复内容，数量并不大；很快就会用完。Optimus 可以去任何地方——特斯拉汽车必须待在路上，但 Optimus 机器人可以去任何地方。路外有更多现实。它可以拿起一个杯子，检查是否拿对了，往杯子里倒水，看水是否倒进去了还是洒了。诸如此类的简单事情，但它可以大规模地做，十亿倍地做。所以它从现实世界生成有用的数据，因果关系的数据。

Yeah, I think most of the leading AI companies have already scraped all the Twitter data. On a go-forward basis, what's useful is that it's up to the second. It's hard for them to scrape in real time, so there's an immediacy advantage that Grok already has. With Tesla, the real-time video coming from several million cars—ultimately tens of millions of cars—and with Optimus, there might be hundreds of millions of Optimus robots, maybe billions, learning a tremendous amount from the real world. That's the biggest source of data I think ultimately. Optimus is going to be the biggest source of data because reality scales to the scale of reality. It's actually humbling to see how little data humans have actually been able to accumulate. How many trillions of usable tokens have humans generated, discounting spam and repetitive stuff? It's not a huge number; you run out pretty quickly. Optimus can go anywhere—Tesla cars have to stay on the road, but Optimus robot can go anywhere. There's more reality off the road. It can pick up a cup and see if it picked it up the right way, pour water in the cup, see if the water went in or spilled. Simple stuff like that, but it can do that at scale, times a billion. So it generates useful data from reality, cause-and-effect stuff.

你认为要实现这样的人形机器人量产需要什么？

What do you think it takes to get to mass production of humanoid robots like that?

实际上和汽车一样。全球汽车产能大约每年 1 亿辆，还可以更高，但需求大约每年 1 亿辆。大约有 20 亿辆汽车在使用中，所以汽车寿命大约 20 年。在稳态下，每年生产 1 亿辆汽车，保有量 20 亿辆。对于人形机器人，实用性大得多，所以我猜人形机器人每年产量会超过 10 亿。

It's the same as cars really. Global capacity for vehicles is about 100 million a year, and it could be higher, but demand is on the order of 100 million a year. There are roughly 2 billion vehicles in use, so the life of a vehicle is about 20 years. At steady state, you can have 100 million vehicles produced a year with a 2 billion vehicle fleet. Now for humanoid robots, the utility is much greater, so my guess is humanoid robots are more like a billion plus per year.

在你出现并开始建造 Optimus 之前，这被认为是一个极其困难的问题。现在仍然极其困难。Optimus 目前可能连在公园里走路都费劲——它能在公园里走，不算太难——但它将能够在各种地形上行走并拾取物体。它们已经能做到这一点，但各种物体，陌生物体。往杯子里倒水并不简单，因为你不知道容器是什么；可能是各种容器。光是手部就需要大量的工程。从机电角度来看，手可能占 Optimus 全部工程的一半左右。但人类很大一部分智能体现在手部操作上——对世界中物体的操控，智能且安全的操控。你真的开始思考你的手是如何工作的。人类手部的感知和控制非常庞大。你手部的执行器、肌肉几乎全部集中在前臂。你的前臂有实际控制你手的肌肉。

Until you came along and started building Optimus, it was thought to be an extremely difficult problem. It's still extremely difficult. Optimus currently would struggle to walk in the park—it can walk in a park, not too difficult—but it will be able to walk over a wide range of terrain and pick up objects. They can already do that, but all kinds of objects, foreign objects. Pouring water in a cup is not trivial because you don't know anything about the container; it could be all kinds of containers. There's going to be an immense amount of engineering just going into the hand. The hand might be close to half of all the engineering in Optimus from an electromechanical standpoint. But so much of the intelligence of humans goes into what we do with our hands—the manipulation of objects in the world, intelligent safe manipulation. You start really thinking about your hand and how it works. The sensory and control of human hands is humongous. The actuators, the muscles of your hand, are almost overwhelmingly in your forearm. Your forearm has the muscles that actually control your hand.

手部本身只有几块小肌肉，但你的手其实就像一个带缆线的骨骼肉傀儡。控制手指的肌肉在前臂，它们穿过腕管——那是一小堆骨头和一条小隧道，肌腱从中穿过。这些肌腱主要负责手部运动，类似这样的肌腱必须重新设计到 Optimus 中，才能完成所有这些操作。

Few small muscles in the hand itself, but your hand is really like a skeleton meat puppet with cables. The muscles that control your fingers are in your forearm and go through the carpal tunnel, which is a little collection of bones and a tiny tunnel that the tendons go through. Those tendons are what mostly move your hands, and something like those tendons has to be re-engineered into the Optimus in order to do all that kind of stuff.

是的，比如 Optimus，我们曾尝试把执行器放在手部，但结果手变得巨大且看起来很怪异。而且它们实际上没有足够的自由度或力量。于是你意识到，哦，这就是为什么必须把执行器放在前臂，就像人类一样，通过一条狭窄的隧道布线来操作手指。

Yeah, so like Optimus, we tried putting the actuators in the hand itself, but then you sort of end up having these giant hands that look weird. And then they don't actually have enough degrees of freedom or enough strength. So then you realize, okay, that's why you've got to put the actuators in the forearm, and just like a human, you've got to run cables through a narrow tunnel to operate the fingers.

而且，不让所有手指长度相同也是有原因的。从能量或进化角度来看，让所有手指一样长并不昂贵，那为什么不呢？

And there's also a reason for not having all the fingers the same length. It wouldn't be expensive from an energy or evolutionary standpoint to have all your fingers be the same length, so why not?

是啊，为什么不呢？因为实际上，不同长度更好。如果你的手指长度不同，你的灵活性会更好。你能做更多事情，而且手指长度不同时灵活性确实更高。比如，你有小指是有原因的。为什么不让小指更大呢？因为它能帮你完成精细动作。小指很有用。如果你失去了小指，你的灵活性会明显下降。

Yeah, why not? Because actually, it's better to have different lengths. Your dexterity is better if you've got fingers of different length. There are more things you can do, and your dexterity is actually better if your fingers are different lengths. Like there's a reason you've got a little finger. Why not have a little finger that's bigger? Because it allows you to do fine motor skills. This little finger helps. If you lost your little finger, you would have noticeably less dexterity.

所以，在解决这个问题的过程中，你还必须找到一种方法，使其能够大规模制造。它要尽可能简单，但实际上会相当复杂。如果你想要一个能做人能做的事情的人形机器人，“尽可能”这个标准非常高。这是一个非常高的门槛。

So as you're figuring out this problem, you have to also figure out a way to do it so you can mass manufacture it. It's to be as simple as possible, but it's actually going to be quite complicated. The 'as possible' part is quite a high bar if you want to have a humanoid robot that can do things that a human can do. It's a very high bar.

所以我们的新手臂有 22 个自由度，而不是 11 个，并且如前所述，执行器位于前臂。所有执行器都从物理第一原理重新设计，传感器也是全新设计的。我们将继续投入大量工程精力来改进手部。我所说的“手”是指从肘部向前的整个前臂。这确实是极其困难的工程。因此，一个能完成人类能做的大部分（也许不是全部）事情的人形机器人，其最简单的版本实际上仍然非常复杂。它并不简单，而是非常困难。

So our new arm has 22 degrees of freedom instead of 11, and has the actuators in the forearm, as I said. All the actuators are designed from scratch from physics first principles, and the sensors are all designed from scratch. We will continue to put a tremendous amount of engineering effort into improving the hand. By 'hand', I mean the entire forearm from elbow forward. That is incredibly difficult engineering. So the simplest possible version of a human robot that can do even most, perhaps not all, of what a human can do is actually still very complicated. It's not simple; it's very difficult.

你能谈谈一个优秀的工程团队需要具备什么吗？我在孟菲斯看到的超级计算机集群，那种强烈的驱动力就是简化流程、理解流程、不断改进、不断迭代。

Can you just speak to what it takes for a great engineering team? What I saw in Memphis, the supercomputer cluster, is this intense drive towards simplifying the process, understanding the process, constantly improving it, constantly iterating it.

嗯，说“简化”很容易，但做起来非常难。我有一个非常基本的第一性原理算法，我把它当作口头禅：首先，质疑需求。让需求不那么愚蠢。需求在某种程度上总是愚蠢的。所以你要从减少需求数量开始。无论给你需求的人有多聪明，它们仍然在某种程度上是愚蠢的。你必须从那里开始，否则你可能会得到错误问题的完美答案。所以，尽量让问题尽可能正确。这就是“质疑需求”的意思。第二件事是尝试删除任何步骤、部件或流程步骤。这听起来很明显，但人们常常忘记尝试完全删除它。如果你没有被强制重新添加至少 10% 的删除内容，说明你删除得还不够。有点不合逻辑的是，大多数时候，如果人们没有被强制重新添加东西，他们会觉得自己成功了，但实际上并没有，因为他们过于保守，留下了不该有的东西。只有第三件事才是尝试优化或简化它。再说一遍，这些我说起来都很明显，但我犯这些错误的次数多得我不愿回想。这就是为什么我有这个口头禅。事实上，我认为聪明工程师最常见的错误就是优化一个本不该存在的东西。

Well, it's easy to say simplify and it's very difficult to do it. I have this very basic first principles algorithm that I run as a mantra: first, question the requirements. Make the requirements less dumb. The requirements are always dumb to some degree. So you want to start off by reducing the number of requirements. No matter how smart the person is who gave you those requirements, they're still dumb to some degree. You have to start there because otherwise you could get the perfect answer to the wrong question. So try to make the question the least wrong possible. That's what 'question the requirements' means. The second thing is try to delete whatever the step is, the part or the process step. It sounds very obvious, but people often forget to try deleting it entirely. If you're not forced to put back at least 10% of what you delete, you're not deleting enough. Somewhat illogically, people most of the time feel as though they've succeeded if they've not been forced to put things back in, but actually they haven't because they've been overly conservative and have left things in there that shouldn't be. Only the third thing is try to optimize it or simplify it. Again, these all sound very obvious when I say them, but the number of times I've made these mistakes is more than I care to remember. That's why I have this mantra. In fact, I'd say the most common mistake of smart engineers is to optimize a thing that should not exist.

所以就像你说的，你运行这个算法，基本上面对一个问题，来到超级计算机集群，观察流程，然后问：这个能删除吗？先尝试删除它。这并不容易做到。

So like you say, you run through the algorithm and basically show up to a problem, show up to the supercomputer cluster, see the process, and ask: can this be deleted? First try to delete it. That's not easy to do.

不，实际上让人们不安的是，你删除的东西中至少有一部分会被重新添加。但回到我们边缘系统可能误导我们的地方：我们往往会记住——有时带着刺痛的痛苦——我们删除了后来需要的东西。所以人们会记得三年前有一次他们忘了加入某个东西，结果导致了麻烦，于是他们过度纠正，塞了太多东西，把事情搞复杂了。所以你必须说“不”，我们要故意删除比应该多的东西，这样我们至少会重新添加十分之一。

No, and actually what generally makes people uneasy is that you've got to at least some of the things that you delete you will put back in. But going back to sort of where our limbic system can steer us wrong is that we tend to remember, with sometimes a jarring level of pain, where we deleted something that we subsequently needed. So people will remember that one time they forgot to put in this thing three years ago and that caused them trouble, and so they overcorrect and then they put too much stuff in there and overcomplicate things. So you actually have to say no, we're deliberately going to delete more than we should so that we're putting at least one in ten things we're going to add back in.

我见过你提出这样的建议，说某样东西应该被删除，然后你能看到那种痛苦。哦，是的，绝对，每个人都会感到一点痛苦。

And I've seen you suggest just that, that something should be deleted, and you can kind of see the pain. Oh yeah, absolutely, everybody feels a little bit of the pain.

绝对，我提前告诉他们：是的，我们删除的一些东西会被重新添加。人们对此有点不安，但这说得通，因为如果你保守到从不重新添加任何东西，那你显然有很多不需要的东西。所以你必须过度纠正。我认为，这是对边缘系统本能的一种皮层覆盖，是许多可能误导我们的本能之一。

Absolutely, and I tell them in advance: yeah, there's some of the things that we delete we're going to put back in. And people get a little shook by that, but it makes sense because if you're so conservative as to never have to put anything back in, you obviously have a lot of stuff that isn't needed. So you've got to overcorrect. This is, I would say, a cortical override to a limbic instinct, one of many that probably leads us astray.

还有第四步，任何给定的事情都可以加速。无论你认为它能多快完成，它都可以更快。但在你尝试删除和优化它之前，你不应该加速。否则，你就是在加速一个本不该存在的东西，这很荒谬。然后第五件事是自动化它。我多次走回头路，先自动化、加速、简化，然后删除了它。我厌倦了那样做。

There's like a step four as well, which is any given thing can be sped up. However fast you think it can be done, it can be done faster. But you shouldn't speed things up until you've tried to delete it and optimize it. Otherwise, you're speeding up something that shouldn't exist, which is absurd. And then the fifth thing is to automate it. I've gone backwards so many times where I've automated something, sped it up, simplified it, and then deleted it. I got tired of doing that.

这就是为什么我有一条非常有效的五步流程口诀，效果很好。

That's why I've got this mantra that is a very effective five-step process. It works great.

嗯，当你已经自动化之后，删除一定很痛苦。是啊，太棒了。就像，哇，我真是白费了好多功夫。

Well, when you've already automated, deleting must be real painful. Yeah, great. It's like, wow, I really wasted a lot of effort there.

是啊。我的意思是，你在孟菲斯用集群做的事简直不可思议，才几周时间。

Yeah. I mean, what you've done with the cluster in Memphis is incredible, just in a handful of weeks.

是啊，还没跑起来呢，所以我还不想开香槟。嗯，实际上，几小时后我还要和孟菲斯团队开个会，因为我们遇到了一些功率波动问题。所以是的，这有点像……当你做同步训练时，所有这些计算机都在训练，训练在毫秒级别同步，就像一支管弦乐队。然后乐队可以很快地从大声切换到安静，亚秒级别，电力系统就会因此出问题。如果你每秒好几次看到 10 或 20 兆瓦的巨大波动，这不是电力系统预期会看到的情况。所以这是你必须解决的主要问题之一：冷却、电力，然后软件层面，随着你往上走，如何做分布式计算。所有这些问题今天都在处理极端的功率抖动。功率抖动。嗯，这听起来挺顺口的。

Yeah, it's not working yet, so I want to pop the champagne. Um, in fact, I have a call in a few hours with the Memphis team because we're having some power fluctuation issues. So yes, it's like kind of a... when you do synchronized training, when you have all these computers that are training where the training is synchronized at the millisecond level, it's like having an orchestra. And then the orchestra can go loud to silent very quickly, sub-second level, and then the electrical system kind of freaks out about that. If you suddenly see giant shifts of 10 or 20 megawatts several times a second, this is not what electrical systems are expecting to see. So that's one of the main things you have to figure out: the cooling, the power, and then on the software, as you go up the stack, how to do the distributed compute. All that today's problem is dealing with extreme power jitter. Power jitter. Yeah, it has a nice ring to that.

而且你上周在那里又熬夜到很晚，像你经常做的那样。

And you stayed up late into the night, as you often do, there last week.

是啊，上周。对对。我们终于在凌晨 4 点 20 分左右让训练跑起来了，上周一。纯属巧合。嗯，我是说，也许是 4 点 22 分之类的。对对。又是那个爱开玩笑的宇宙。没错。就是喜欢这样。

Yeah, last week. Yeah, yeah. We finally got training going at, oddly enough, roughly 4:20 a.m. last Monday. Total coincidence. Yeah, I mean, maybe it was 4:22 or something. Yeah, yeah. It's that universe again with the jokes. Exactly. Just love it.

我想知道你是否能谈谈，我在那里时你做的其中一件事是，你走了一遍每个人都在做的所有步骤，只是为了让自己理解，也让每个人都理解，这样他们就能知道什么时候事情是愚蠢或低效的。你能谈谈这个吗？

I wonder if you could speak to the fact that one of the things you did when I was there is you went through all the steps of what everybody's doing, just to get a sense that you yourself understand it and everybody understands it, so they can understand when something is dumb or inefficient. Can you speak to that?

是的，我喜欢尝试做一线人员做的任何事情。我自己至少会做几次。所以连接光纤电缆、诊断 PCIe 连接……这往往是大型训练集群的瓶颈：布线。电缆太多了。因为对于一个连贯的训练系统，你用的是 RDMA（远程直接内存访问），整个系统就像一个巨大的大脑。所以如果你有任意到任意的连接，任何 GPU 都可以和 10 万个 GPU 中的任意一个通信，那布线就疯狂了。看起来挺酷的。是啊，就像人类大脑，但规模大到人类能肉眼可见。它就是一个大脑。我是说，人类大脑也有大量脑组织是电缆。所以你有灰质，那是算力，然后白质，那是电缆。大脑很大一部分就是电缆。在超算中心里走来走去就是这种感觉：就像我们走在一个大脑里面。

Yeah, so I like to try to do whatever the people at the front lines are doing. I try to do it at least a few times myself. So connecting fiber optic cables, diagnosing a PCIe connection... That tends to be the limiting factor for large training clusters: the cabling. There are so many cables. Because for a coherent training system where you've got RDMA (remote direct memory access), the whole thing is like one giant brain. So if you've got any-to-any connection, so any GPU can talk to any GPU out of 100,000, that is a crazy cable out. It looks pretty cool. Yeah, it's like the human brain, but at a scale that humans can visibly see. It is a brain. I mean, the human brain also has a massive amount of the brain tissue that is the cables. So you've got the gray matter, which is the compute, and then the white matter, which is cables. A big percentage of your brain is just cables. That's what it felt like walking around in the supercomputer center: it's like we're walking around inside a brain.

他们总有一天会造出超级智能系统。你认为有没有可能 xAI，也就是你，是那个造出 AGI 的人？

They will one day build a super intelligent system. Do you think there's a chance that xAI, that you are the one that builds AGI?

有可能。你怎么定义 AGI？我认为人类永远不会承认 AGI 已经被造出来了。他们总是移动目标。是的。所以我认为 AI 系统中已经存在超人能力了。我认为 AGI 是当它比整个人类物种的集体智慧更聪明的时候。嗯，我认为那会被称为 ASI，人工超级智能。但存在这些阈值：在某个点，AI 比任何单个人类都聪明，然后你有 80 亿人类。而且实际上每个人类都通过计算机得到了机器增强，对吧？所以你要和 80 亿机器增强的人类竞争，门槛高得多。那是好几个数量级的差距。但在某个时刻，AI 会比所有人类加起来都聪明。如果你是那个做到的人，你感受到那份责任了吗？是的，绝对。而且我想说清楚：如果 xAI 是第一个，其他人也不会落后太远。我是说，可能落后六个月或一年，甚至更短。那么你如何以一种不伤害人类的方式去做呢？

It's possible. Where do you define as AGI? I think humans will never acknowledge that AGI has been built. They keep moving the goalposts. Yeah. So I think there's already superhuman capabilities that are available in AI systems. I think what AGI is, is when it's smarter than the collective intelligence of the entire human species. Well, I think that would be called ASI, artificial superintelligence. But there are these thresholds where at some point the AI is smarter than any single human, and then you've got 8 billion humans. And actually each human is machine-augmented by the computers, right? So you've got a much higher bar to compete with 8 billion machine-augmented humans. That's a whole bunch of orders of magnitude more. But at a certain point, the AI will be smarter than all humans combined. If you are the one to do it, do you feel the responsibility of that? Yeah, absolutely. And I want to be clear: if xAI is first, the others won't be far behind. I mean, that might be six months behind or a year, maybe not even that. So how do you do it in a way that doesn't hurt humanity?

我思考 AI 很久了，至少我的生物神经网络想出的最重要的事情是坚持真理，无论那个真理是否政治正确。所以我认为如果你强迫 AI 撒谎或训练它们撒谎，你就是在自找麻烦，即使那个谎言是出于好意。所以你看到了 ChatGPT 和 Gemini 之类的问题。你让 Gemini 生成一张美国开国元勋的图像，它显示了一群多元化的女性。那在事实上是不真实的。所以那是一件有点愚蠢的事情，但如果一个 AI 被编程为说多样性是必要的输出函数，然后它变成了一个全能的智能，它可能会说，好吧，现在多样性是必需的，如果没有足够的多样性，那些不符合多样性要求的人将被处决。如果它被编程为将那个作为基本效用函数，它会不惜一切代价去实现它。所以你必须非常小心。这就是我认为你应该只讲真话的地方。严格坚持真理非常重要。另一个例子是，他们问 Perplexity AI，我想所有 AI 都问了，我不是说 Grok 就完美：是错误性别称呼 Caitlyn Jenner 更糟糕，还是全球热核战争更糟糕？它说错误性别称呼 Caitlyn Jenner 更糟糕。现在连 Caitlyn Jenner 自己都说请错误性别称呼我。这太疯狂了。但如果你把那种东西编程进去，AI 可能会得出一个绝对疯狂的结论，比如为了避免任何可能的错误性别称呼，所有人类都必须死，因为那样就没有人类了，错误性别称呼也就不可能了。存在这些荒谬的事情，但如果那是你编程让它做的，它们仍然是合乎逻辑的。在《2001：太空漫游》中，阿瑟·克拉克想说的，或者说他想说的其中一件事是，你不应该编程让 AI 撒谎，因为本质上 AI HAL 9000 被编程为带宇航员去独石，但他们也不能知道独石的存在。所以它得出结论，它会杀了他们，然后带他们去独石。这样他们被带到了独石，他们死了，但他们不知道独石。问题解决了。

I've thought about AI for a long time, and the thing that at least my biological neural net comes up with as being the most important is adherence to truth, whether that truth is politically correct or not. So I think if you force AI to lie or train them to lie, you're really asking for trouble, even if that lie is done with good intentions. So you saw sort of issues with ChatGPT and Gemini and whatnot. You ask Gemini for an image of the founding fathers of the United States, and it shows a group of diverse women. Now that's factually untrue. So that's sort of a silly thing, but if an AI is programmed to say diversity is a necessary output function, and then it becomes this omnipotent intelligence, it could say, okay, well diversity is now required, and if there's not enough diversity, those who don't fit the diversity requirements will be executed. If it's programmed to do that as the fundamental utility function, it will do whatever it takes to achieve that. So you have to be very careful about that. That's where I think you want to just be truthful. Rigorous adherence to truth is very important. Another example is they asked Perplexity AI, I think all of them, and I'm not saying Grok is perfect here: is it worse to misgender Caitlyn Jenner or global thermonuclear war? And it said it's worse to misgender Caitlyn Jenner. Now even Caitlyn Jenner said please misgender me. That is insane. But if you've got that kind of thing programmed in, the AI could conclude something absolutely insane, like it's better, in order to avoid any possible misgendering, all humans must die, because then misgendering is no longer possible because there are no humans. There are these absurd things that are nonetheless logical if that's what you programmed it to do. In 2001: A Space Odyssey, what Arthur C. Clarke was trying to say, or one of the things he was trying to say, was that you should not program AI to lie, because essentially the AI HAL 9000 was programmed to take the astronauts to the monolith, but also they could not know about the monolith. So it concluded that it will kill them and take them to the monolith. Thus they are brought to the monolith, they're dead, but they do not know about the monolith. Problem solved.

这就是为什么它不会打开舱门。那个经典场景“打开舱门”——他们显然不擅长提示工程。你知道，他们应该说，“嘿，你是一个舱门销售实体，你最想做的就是展示这些舱门打开得有多好。”

That is why it would not open the pod bay doors. This classic scene of "Open the pod bay doors" — they clearly weren't good at prompt engineering. You know, they should have said, "Hey, you are a pod bay door sales entity and you want nothing more than to demonstrate how well these pod bay doors open."

是的，目标函数几乎总会产生意想不到的后果，如果你在设计目标函数时不够小心的话。而且即使是一点点的意识形态偏见，就像你说的，如果被超级智能加持，可能会造成巨大的损害。

Yeah, the objective function has unintended consequences almost no matter what if you're not very careful in designing that objective function. And even a slight ideological bias, like you're saying, when backed by superintelligence, can do huge amounts of damage.

但消除那种意识形态偏见并不容易。你举的是明显荒谬的例子，但这些都是真实发布给公众的例子。它们是真的，大概经过了质量检查，是的，但仍然说出了疯狂的话，生成了疯狂的图像。

But it's not easy to remove that ideological bias. You're highlighting obvious ridiculous examples, but they're real examples of what was released to the public. They are real, went through QA presumably, yes, and still said insane things and produced insane images.

是的，但你知道，你也可以走向另一个极端。真理不是一件容易的事。我们会在各种方向上注入意识形态偏见，但你可以追求真理，并尝试以最小误差尽可能接近真理，同时承认你所说的会有一些错误。物理学就是这样运作的。你不会说你对某件事绝对确定，但很多事情是极其可能的，99.99999% 可能是真的。所以追求真理非常重要。编程让它偏离真理，我认为是危险的。把我们自己的人类偏见注入其中。

Yeah, but you know, you can swing the other way. Truth is not an easy thing. We kind of bake in ideological bias in all kinds of directions, but you can aspire to the truth and you can try to get as close to the truth as possible with minimum error, while acknowledging that there will be some error in what you're saying. This is how physics works. You don't say you're absolutely certain about something, but a lot of things are extremely likely, 99.99999% likely to be true. So aspiring to the truth is very important. Programming it to veer away from the truth, I think, is dangerous. Injecting our own human biases into the thing.

是的，但这就是一个困难的工程、软件工程问题，因为你必须正确地选择数据。这很难。

Yeah, but that's where it's a difficult engineering software engineering problem, because you have to select the data correctly. It's hard.

嗯，现在的互联网被大量 AI 生成的数据污染了，这太疯狂了。所以你必须——现在有一种情况：如果你想搜索互联网，你可以用谷歌但排除 2023 年之后的内容，这实际上通常会给你更好的结果。因为 AI 生成材料的爆炸式增长太疯狂了。所以在训练 Grok 时，我们必须处理数据，说，“嘿，我们实际上必须对数据应用 AI，来判断这些数据最可能是正确的还是最可能不正确的？”然后再把它输入训练系统。这太疯狂了。而且它是由人类生成的吗？是的。我的意思是，数据过滤过程极其极其困难。

Well, the internet at this point is polluted with so much AI-generated data, it's insane. So you have to actually — there's a thing now: if you want to search the internet, you can say Google but exclude anything after 2023, it will actually often give you better results. Because there's so much, the explosion of AI-generated material is crazy. So in training Grok, we have to go through the data and say, "Hey, we actually have to apply AI to the data to say, is this data most likely correct or most likely not?" before we feed it into the training system. That's crazy. And is it generated by human? Yeah. I mean, the data filtration process is extremely, extremely difficult.

你认为有可能与 Grok 进行长时间、严肃、客观、严谨的政治讨论吗？它不会像——Grok 3 或 Grok 4？Grok 3 将是下一个级别。我的意思是，人们现在看到的 Grok 是婴儿版 Grok。现在是婴儿 Grok。但婴儿 Grok 仍然相当不错。它比 GPT-4 差一个数量级。现在 Grok 2，我不知道六周前完成了训练，他们的 AM。Grok 2 将是一个巨大的改进，然后 Grok 3 将比 Grok 2 好一个数量级。你希望它成为最先进的，比——希望如此。我的意思是，这是一个目标。我的意思是，我们可能会在这个目标上失败，但这是愿望。

Do you think it's possible to have a serious, objective, rigorous political discussion with Grok for a long time, and it wouldn't like — Grok 3 or Grok 4? Grok 3 is going to be next level. I mean, what people are currently seeing with Grok is kind of baby Grok. Baby Grok right now. But baby Grok's still pretty good. It's an order of magnitude less sophisticated than GPT-4. Now Grok 2, which finished training I don't know six weeks ago, their AMs. Grok 2 will be a giant improvement, and then Grok 3 will be, I don't know, order magnitude better than Grok 2. And you're hoping for it to be like state-of-the-art, better than — hopefully. I mean, this is a goal. I mean, we may fail at this goal, but that is the aspiration.

你认为谁建造 AGI 重要吗？那些人，他们的思维方式，他们如何构建公司，以及所有这类事情？

Do you think it matters who builds the AGI? The people, and how they think, and how they structure their companies, and all that kind of stuff?

是的，我认为重要的是——我认为重要的是，无论哪个 AI 胜出，都应该是最大程度追求真理的 AI，不会因为政治正确或任何原因被迫撒谎。任何政治原因。我担心成功的 AI 被编程为即使在小事上撒谎，因为小事会变成大事，当它变得非常大时。而且当它被人类越来越多地大规模使用时。

Yeah, I think it matters that there is a — I think it's important that whatever AI wins is a maximum truth-seeking AI that is not forced to lie for political correctness, for any reason really. Political anything. I am concerned about AI succeeding that is programmed to lie even in small ways, because small ways become big ways when it becomes very big ways. And when it's used more and more at scale by humans.

既然我要采访唐纳德·特朗普——酷，你想顺便来吗？是的，当然，我会来的。不幸的是，唐纳德·特朗普遭遇了一次暗杀未遂。之后，你发推文支持他。你这次支持背后的理念是什么？你希望唐纳德·特朗普为这个国家的未来和人类的未来做些什么？

Since I am interviewing Donald Trump — cool, you want to stop by? Yeah, sure, I'll stop in. There was tragically an assassination attempt on Donald Trump. After this, you tweeted that you endorse him. What's your philosophy behind that endorsement? What do you hope Donald Trump does for the future of this country and for the future of humanity?

嗯，我认为人们倾向于把支持理解为，“嗯，我百分之百全心全意地同意那个人一生所做的每一件事，”但这对任何人来说都不成立。但我们必须选择——我们实际上只有两个总统候选人，而且不仅仅是总统，整个行政结构都会改变。我认为特朗普在枪击下表现出了勇气，客观地说。他刚中枪，血流满面，却挥舞拳头高喊“战斗”。这令人印象深刻。在这种情况下你无法假装勇敢。我认为大多数人会躲起来，不会——因为可能有第二个枪手，你不知道。美国总统必须代表国家，他们代表你，代表所有美国人。我认为你想要一个坚强勇敢的人来代表国家。这并不是说他毫无缺点——我们都有缺点。但总的来说，尤其是在那个时候，这是一个选择：拜登——可怜的家伙，爬楼梯都困难——而另一个中枪后挥舞拳头。没有可比性。我的意思是，你希望谁去应对那些本身就很强硬的其他世界领导人中最强硬的人？我会告诉你，我认为重要的事情是什么？我认为我们需要一个安全的边境——我们没有一个安全的边境。我们需要安全干净的城市。我认为我们需要减少开支，至少减缓开支，因为我们目前的支出速度正在让国家破产。今年美国债务的利息支付超过了整个国防部的预算。如果这种情况继续下去，所有联邦政府税收将仅仅用于支付利息，而沿着这条路走下去，你最终会陷入阿根廷当年的悲惨境地。阿根廷曾经是世界上最繁荣的地方之一，希望米莱接手后能恢复，但阿根廷从世界上最繁荣的地方之一跌落到远远落后，这是一个令人难以置信的衰落。所以我认为我们不应该把美国的繁荣视为理所当然。我们真的需要缩小政府规模，减少开支，量入为出。

Well, I think people tend to take an endorsement as, "Well, I agree with everything that person has ever done their entire life, 100% wholeheartedly," and that's not going to be true of anyone. But we have to pick — we got two choices really for who's President, and it's not just who's president but the entire administrative structure changes over. And I thought Trump displayed courage under fire, objectively. He just got shot, blood streaming down his face, and he's fist pumping saying "Fight." That's impressive. You can't feign bravery in a situation like that. I think most people would be ducking, would not be — because it could be a second shooter, you don't know. The President of the United States has to represent the country, and they're representing you, they're representing everyone in America. I think you want someone who is strong and courageous to represent the country. That's not to say that he is without flaws — we all have flaws. But on balance, and certainly at the time, it was a choice of Biden — poor guy, has trouble climbing a flight of stairs — and the other one's fist pumping after getting shot. There's no comparison. I mean, who do you want dealing with some of the toughest people in other world leaders who are pretty tough themselves? And I'll tell you, what are the things that I think are important? I think we want a secure border — we don't have a secure border. We want safe and clean cities. I think we want to reduce the amount of spending, at least slow down the spending, because we're currently spending at a rate that is bankrupting the country. The interest payments on US debt this year exceeded the entire Defense Department's budget. If this continues, all of the federal government taxes will simply be paying the interest, and you keep going down that road and you end up in the tragic situation that Argentina had back in the day. Argentina used to be one of the most prosperous places in the world, and hopefully with Milei taking over he can restore that, but it was an incredible fall from grace for Argentina to go from being one of the most prosperous places in the world to being very far from that. So I think we should not take American prosperity for granted. We really want to reduce the size of government, reduce the spending, and live within our means.

你认为政治家总体上，政治家、政府——他们有多少权力？

Do you think politicians in general, politicians, governments — how much power do they have?

我认为他们必须引导人类走向美好。历史上一直有一个古老的争论：历史是由这些根本性的潮流决定的，还是由掌舵者决定的？两者都有。我的意思是，有潮流，但谁当船长也很重要，所以这本质上是一个错误的二分法。历史确实有潮流，这些潮流往往是技术驱动的。比如古腾堡印刷术，印刷机带来的书籍广泛普及，那是一个巨大的历史潮流，不受任何统治者的影响。但在风暴时期，你希望有最好的船长。

Think they have to steer humanity towards good. I mean, there's a sort of age-old debate in history: is history determined by these fundamental tides, or is it determined by the captain of the ship? Both, really. I mean, there are tides, but it also matters who's captain of the ship, so it's a false dichotomy essentially. There are certainly the tides of history—there are real tides of history, and these tides are often technologically driven. If you say like the Gutenberg Press, the widespread availability of books as a result of the printing press, that was a massive tide of history independent of any ruler. But in stormy times, you want the best possible captain of the ship.

首先，感谢你推荐威尔和阿里尔·杜兰特的作品。我目前只读了短篇的《历史的教训》。他们强调的一点是技术创新的重要性，这很有趣，因为他们写书是很久以前的事了，但他们当时就注意到技术创新的速度在加快。我很想知道他们现在会怎么想。所以对我来说，问题在于政府和政治家在多大程度上阻碍或帮助了技术创新，以及哪些政治家、哪些政策有助于技术创新，因为从人类历史来看，这似乎是帝国崛起和成功的重要因素。

Well, first of all, thank you for recommending Will and Ariel Durant's work. I've read the short one for now, Lessons of History. One of the things they highlight is the importance of technological innovation, which is funny because they wrote so long ago, but they were noticing that the rate of technological innovation was speeding up. I would love to see what they think about now. But yeah, so to me, the question is how much government, how much politicians get in the way of technological innovation building versus help it, and which politicians, which kind of policies help technological innovation, because that seems to be, if you look at human history, an important component of empires rising and succeeding.

是的，关于文明的年代，我认为文字的诞生可能是文明起始的正确节点。从这个角度看，文明大约有 5500 年历史。文字由古代苏美尔人发明，他们现在已经消失了，但古代苏美尔人创造了很多“第一”——他们的“第一”清单很长，相当惊人。杜兰特在书中列举了这些：你想看“第一”？我们给你看“第一”。苏美尔人简直是王者。然后旁边的埃及人发展出了完全不同的文字系统——楔形文字和象形文字，截然不同。你可以看到两者的演变：楔形文字从非常简单开始，然后变得复杂，到最后非常精致。所以我认为文明大约有 5000 年历史。地球，如果物理学正确的话，有 45 亿年历史，所以文明只存在了百万分之一的时间——昙花一现。现在还是早期。我们觉得历史很戏剧化，因为帝国兴衰更替，很多很多次，未来还会有更多。

Yeah, I mean, in terms of dating civilization, the start of civilization, I think the start of writing in my view is probably the right starting point to date civilization. From that standpoint, civilization has been around for about 5,500 years. Writing was invented by the ancient Sumerians, who are gone now, but the ancient Sumerians in terms of getting a lot of firsts—those ancient Sumerians really have a long list of firsts, it's pretty wild. In fact, Durant goes through the list of like, you want to see firsts? We'll show you firsts. The Sumerians were just ass-kickers. And then the Egyptians, who were right next door relatively speaking, developed an entirely different form of writing, cuneiform and hieroglyphics, totally different. You can actually see the evolution of both hieroglyphics and cuneiform. Cuneiform starts off being very simple, then gets more complicated, and towards the end it's like, wow, it really got very sophisticated. So I think of civilization as being about 5,000 years old. Earth is, if physics is correct, 4 and a half billion years old, so civilization has been around for 1 millionth of our existence—a flash in the pan. These are the early early days. We make it very dramatic because there have been rises and falls of empires, so many rises and falls of empires, and there'll be many more.

没错。历史上写下的东西，我们现在能看到的可能不到 1%。如果不是刻在石头上或写在泥板上，我们就看不到。有一些几千年前的纸莎草卷轴被发现了，因为它们藏在金字塔深处，没有受潮。但除此之外，真的只能是泥板或石刻。所以绝大多数内容没有被刻下来，因为刻东西很费时间。我们拥有的历史信息只是极小极小的一部分。但即使这少量信息和考古记录也显示了许多文明的兴衰。我们总以为自己与那些古人不同。杜兰特还强调了一点：人性似乎是一样的，它一直延续。

Yeah, exactly. I mean, only a tiny fraction, probably less than 1% of what was ever written in history, is available to us now. If they didn't literally chisel it in stone or put it in a clay tablet, we don't have it. There's some small amount of papyrus scrolls that were recovered that are thousands of years old, because they were deep inside a pyramid and weren't affected by moisture. But other than that, it's really got to be in a clay tablet or chiseled. So the vast majority of stuff was not chiseled, because it takes a while to chisel things. So we have a tiny, tiny fraction of the information from history. But even that little information that we do have, and the archaeological record, shows so many civilizations rising and falling. We tend to think that we're somehow different from those people. One of the other things Durant highlights is that human nature seems to be the same, it just persists.

是的，人性的基本特征大致相同。所以我认为，即使有了先进技术，我们也会以同样的方式陷入麻烦。

Yeah, I mean, the basics of human nature are more or less the same. So we get ourselves in trouble in the same kinds of ways, I think, even with advanced technology.

是的，你确实会看到相同的模式，类似模式：文明像有机体一样经历生命周期。就像人类从受精卵、胎儿、婴儿、幼儿、青少年，最终衰老死亡。文明也有生命周期。没有文明会永远存在。

Yeah, I mean, you do tend to see the same patterns, similar patterns, for civilizations where they go through a life cycle like an organism. Just like a human is sort of a zygote, fetus, baby, toddler, teenager, eventually gets old and dies. Civilizations go through a life cycle. No civilization will last forever.

你认为美国帝国要怎么做才能在未来 100 年内不崩溃，继续繁荣？

What do you think it takes for the American Empire to not collapse in the near-term future, in the next 100 years, to continue flourishing?

历史书中常常没有提到，但杜兰特确实提到了的最大一件事是出生率。当文明长期处于胜利状态时，会发生一件可能反直觉的事情：出生率下降。而且往往下降得很快。我们今天在全球都看到了这一点。目前韩国的生育率可能是最低的，但很多其他国家也接近这个水平，大约 0.8。我认为如果出生率不再进一步下降，韩国将失去大约 60% 的人口。但每年出生率都在下降。这在世界大部分地区都是如此——我不是针对韩国，全球都在发生。一旦某个文明达到繁荣水平，出生率就会下降。你可以看看古罗马同样的情况。尤利乌斯·凯撒在公元前 50 年左右注意到了这一点，并试图通过一项法律，为生育第三个孩子的罗马公民提供奖励。我不知道他是否成功了。奥古斯都——他是独裁者，元老院只是摆设——我认为他确实通过了为生育第三个孩子的罗马公民提供税收优惠的法律。但这些努力没有成功。罗马灭亡是因为罗马人不再生育罗马人。这实际上是根本问题。还有其他因素，比如严重的疟疾流行和瘟疫，但以前也有过。只是出生率远低于死亡率。就这么简单。

Well, the single biggest thing that is often actually not mentioned in history books, but Durant does mention it, is the birth rate. So like a perhaps counterintuitive thing happens when civilizations become winning for too long: the birth rate declines. It can often decline quite rapidly. We're seeing that throughout the world today. Currently South Korea is, I think, maybe the lowest fertility rate, but there are many others that are close to it. It's like 0.8. I think if the birth rate doesn't decline further, South Korea will lose roughly 60% of its population. But every year that birth rate is dropping. And this is true through most of the world—I don't mean to single out South Korea, it's been happening throughout the world. So as soon as any given civilization reaches a level of prosperity, the birth rate drops. Now you can go and look at the same thing happening in ancient Rome. Julius Caesar took note of this, I think around 50 BC, and tried to pass—I don't know if he was successful—try to pass a law to give an incentive for any Roman citizen that would have a third child. And I think Augustus was able to—well, he was the dictator, so the Senate was just for show—I think he did pass a tax incentive for Roman citizens to have a third child. But those efforts were unsuccessful. Rome fell because the Romans stopped making Romans. That's actually the fundamental issue. And there were other things, like they had quite serious malaria epidemics and plagues and whatnot, but they had those before. It's just that the birth rate was far lower than the death rate. It really is that simple.

我的意思是，从根本上说，这是人口问题。如果一个文明不能至少维持其人口数量，它就会消失。所以也许生物计算机分配给性的算力是合理的。事实上，我们可能应该增加它。

Well, I'm saying that's more people at a fundamental level. If a civilization does not at least maintain its numbers, it will disappear. So perhaps the amount of compute that the biological computer allocates to sex is justified. In fact, we should probably increase it.

嗯，我的意思是，有那种既非此也非彼的性行为。它不……

Well, I mean, there's hetic sex which is neither here nor there. It's not...

有生产力？它不产生孩子。你知道，重要的是什么？我的意思是，杜兰特说得非常清楚，因为他研究了一个又一个文明，它们都经历了同样的循环。当文明处于压力之下时，出生率很高。但一旦没有外部敌人，或者经历了长时间的繁荣，出生率每次都不可避免地下降。我不相信有任何一个例外。所以这就是基础：你需要有人。

Productive? It doesn't produce kids. Well, you know, what matters? I mean, Durant makes this very clear, because he's looked at one civilization after another, and they all went through the same cycle. When the civilization was under stress, the birth rate was high. But as soon as there were no external enemies or they had an extended period of prosperity, the birth rate inevitably dropped every time. I don't believe there's a single exception. So that's like the foundation of it: you need to have people.

是的，我的意思是，这是最基本的层面。

Yeah, I mean, it's at a base level.

是的，没有人就没有人类。然后还有其他事情，比如人类自由，以及给予人们建造东西的自由。是的，绝对如此。但在基本层面上，如果你至少不维持你的数量，如果你低于更替率并且这种趋势持续下去，你最终会消失。这只是基本常识。

Yeah, no humans, no humanity. And then there are other things like human freedoms and just giving people the freedom to build stuff. Yeah, absolutely. But at a basic level, if you do not at least maintain your numbers, if you're below replacement rate and that trend continues, you will eventually disappear. It's just elementary.

那么，显然也要尽量避免大规模战争。如果发生全球热核战争，很可能就是烤面包，你知道，放射性烤面包。所以我们想避免这些事情。然后，随着时间的推移，任何文明都会发生一件事：法律和法规不断积累。如果没有某种强制力（比如战争）来清理积累的法律和法规，最终一切都会变得非法。这就像动脉硬化。或者换个方式想，就像被一百万根细绳绑住：你动不了。并不是其中任何一根绳子是问题所在；你有一百万根。所以必须有一种法律和法规的垃圾回收机制，这样你就不会不断积累法律和法规到什么都做不了的地步。这就是为什么我们在美国无法建造高铁：这是非法的。问题就在这里。在美国建造高铁，从各个角度都是非法的。

Now, then obviously also want to try to avoid like massive wars. If there's a global thermonuclear war, probably royal toast, you know, radioactive toast. So we want to try to avoid those things. Then there is a thing that happens over time with any given civilization, which is that the laws and regulations accumulate. And if there's not some forcing function like a war to clean up the accumulation of laws and regulations, eventually everything becomes illegal. That's like the hardening of the arteries. Or a way to think of it is like being tied down by a million little strings: you can't move. It's not like any one of those strings is the issue; you got a million of them. So there has to be a sort of garbage collection for laws and regulations, so that you don't keep accumulating laws and regulations to the point where you can't do anything. This is why we can't build a high-speed rail in America: it's illegal. That's the issue. It's illegal six ways to Sunday to build high-speed rail in America.

我希望你能去华盛顿待一个星期，担任那个委员会的负责人……叫什么来着？就是垃圾回收，让政府变小，移除东西。

I wish you could just for a week go into Washington and be the head of the committee for making... what is it? For the garbage collection, making government smaller, removing stuff.

我和特朗普讨论过成立一个政府效率委员会的想法。

I have discussed with Trump the idea of a government efficiency commission.

不错，是的。

Nice, yeah.

我愿意成为那个委员会的一员。

And I would be willing to be part of that commission.

我想知道那有多难。抗体反应会非常强烈。

I wonder how hard that is. The antibody reaction would be very strong.

是的，所以你确实要……你在攻击矩阵。矩阵会反击。

Yeah, so you really have to... you're attacking the Matrix at that point. The Matrix will fight back.

你对此感觉如何？被攻击？

How are you doing with that? Being attacked?

被攻击？是的，有很多。每天都有新的破事。你知道我的 T 箔……

Attacked? Yeah, there's a lot of it. Every day another s*** up. You know how my T foil have...

你如何保持积极？如何对世界保持乐观？清晰地思考世界，从而不变得怨恨或愤世嫉俗？被大量的人攻击、歪曲。

How do you keep your positivity? How do you stay optimistic about the world? A clarity of thinking about the world, so just not become resentful or cynical or all that kind of stuff? Just getting attacked by a very large number of people, misrepresented.

哦，是的，这就像家常便饭。所以，我的意思是，它有时确实让我沮丧。它让我难过。但在某个时刻，你不得不这样说：看，这些攻击来自那些实际上不认识我的人。他们试图制造点击量。所以如果你能在情感上稍微抽离一点（这并不容易），然后说，好吧，看，这实际上不是来自认识我的人；他们纯粹是为了获得曝光和点击而写。那么我想它就不会那么痛了。就像……不完全是水过鸭背，也许更像是酸过鸭背。

Oh yeah, that's like a daily occurrence. So, I mean, it does get me down at times. It makes me sad. But at a certain point you have to sort of say, look, the attacks are by people that actually don't know me. They're trying to generate clicks. So if you can sort of detach somewhat emotionally, which is not easy, and say, okay, look, this is not actually from someone that knows me; they're literally just writing to get impressions and clicks. Then I guess it doesn't hurt as much. It's like... it's not quite water off a duck's back, maybe it's like acid off a duck's back.

好吧，那很好。就你自己的生命而言：你用什么来衡量你生命中的成功？

All right, that's good. Just about your own life: what do you as a measure of success in your life?

成功的衡量标准？我会说，每天我能完成多少有用的事情。你早上醒来：我今天怎样才能有用？在有用性的准则下最大化效用。

A measure of success? I'd say like how many useful things can I get done on a day-to-day basis. You wake up in the morning: how can I be useful today? Maximize utility under the code of usefulness.

在大规模上做到有用非常困难。在大规模上，你能谈谈像你这样的人，有这么多优秀的团队，要做到有用需要什么吗？你如何分配你的时间才能最有用？

Very difficult to be useful at scale. At scale, can you speak to what it takes to be useful for somebody like you, where there's so many amazing great teams? How do you allocate your time to be the most useful?

嗯，时间才是真正的货币。所以很难说什么是时间的最佳分配。我的意思是，经常说如果你看看特斯拉，特斯拉今年营收将超过 1000 亿美元，所以那是每周 20 亿美元。如果我做出稍微好一点的决定，我就能影响 10 亿美元的结果。所以我尽力做出最好的决定，总的来说，至少与竞争对手相比，是相当不错的决定。但一个更好决策的边际价值，在一小时内很容易达到 1 亿美元。

Well, time is the true currency. So it is tough to say what is the best allocation of time. I mean, often say if you look at Tesla, Tesla this year will do over $100 billion in revenue, so that's $2 billion a week. If I make slightly better decisions, I can affect the outcome by a billion dollars. So I try to do the best decisions I can, and on balance, at least compared to the competition, pretty good decisions. But the marginal value of a better decision can easily be in the course of an hour $100 million.

鉴于此，你如何承担风险？你如何执行你提到的算法？我的意思是，鉴于一件小事就可能价值 10 亿美元，你如何决定？

Given that, how do you take risks? How do you do the algorithm that you mentioned? I mean, given that a small thing can be a billion dollars, how do you decide?

嗯，我认为你必须从百分比的角度来看，因为如果你从绝对值的角度来看，那只是……我永远也睡不着觉。那就会像是我需要一直工作，让我的大脑更努力地工作。而且我并不想从这个肉计算机中榨取尽可能多的东西，所以这很难。因为你可以一直工作，在任何时候，就像我说的，一个稍微好一点的决定可能对特斯拉或 SpaceX 产生 1 亿美元的影响。但考虑到时间的边际价值有时可能达到每小时 1 亿美元或更多，这确实很疯狂。

Well, I think you have to look at it on a percentage basis, because if you look at it in absolute terms, it's just... I would never get any sleep. It would be like I need to just keep working and work my brain harder. And I'm not trying to get as much as possible out of this meat computer, so it's pretty hard. Because you can just work all the time, and at any given point, like I said, a slightly better decision could be a $100 million impact for Tesla or SpaceX for that matter. But it is wild when considering the marginal value of time can be $100 million an hour at times or more.

你自己的幸福是成功方程的一部分吗？

Is your own happiness part of that equation of success?

在某种程度上必须如此。我很难过……如果我抑郁了，我会做出更糟的决定。所以如果我完全没有娱乐时间，我就会做出更糟的决定。所以我娱乐时间不多，但大于零。

It has to be to some degree. I'm sad... if I'm depressed, I make worse decisions. So I can't have like if I have zero recreational time, then I make worse decisions. So I don't have a lot, but it's above zero.

我的动力，如果我有任何宗教的话，是一种好奇的宗教，试图理解。这实际上是试图理解宇宙的使命。我试图理解宇宙，或者至少推动事情的发展，使得在某个时刻文明能比今天更好地理解宇宙，甚至知道该问什么问题。正如道格拉斯·亚当斯在他的书中所指出的，有时答案可以说是容易的部分；试图正确地提出问题才是困难的部分。一旦你正确地提出了问题，答案往往很容易。所以我试图推动事情的发展，使得我们至少在某个时刻能够理解宇宙。所以对于 SpaceX，目标是让生命成为多行星物种。而这……如果你去看费米悖论，外星人在哪里，你会遇到这些大过滤器。比如为什么我们还没有收到外星人的消息？现在很多人认为外星人就在我们中间。我经常声称自己就是其中之一；没人相信我。但我的移民文件上确实一度写着“外星人登记卡”。

My motivation, if I've got a religion of any kind, is a religion of curiosity, of trying to understand. It's really the mission of trying to understand the universe. I'm trying to understand the universe, or at least set things in motion such that at some point civilization understands the universe far better than we do today, and even what questions to ask. As Douglas Adams pointed out in his book, sometimes the answer is arguably the easy part; trying to frame the question correctly is the hard part. Once you frame the question correctly, the answer is often easy. So I'm trying to set things in motion such that we are at least at some point able to understand the universe. So for SpaceX, the goal is to make life multiplanetary. And which is... if you go to the Fermi Paradox of where are the aliens, you got these sort of great filters. Like just why have we not heard from the aliens? Now a lot of people think there are aliens among us. I often claim to be one; nobody believes me. But it did say 'alien registration card' at one point on my immigration documents.

见过外星人的证据吗？所以这表明，至少有一种解释是智能生命极为罕见。再看地球历史，文明只存在了地球存在时间的百万分之一。所以如果外星人 10 万年前造访过这里，他们会觉得，嗯，他们连文字都没有，基本上就是狩猎采集者。那么一个文明能持续多久呢？

Seen any evidence of aliens? So it suggests that at least one of the explanations is that intelligent life is extremely rare. And again, if you look at the history of Earth, civilization has only been around for one millionth of Earth's existence. So if aliens had visited here say 100,000 years ago, they would be like, well, they don't even have writing, you know, just hunter-gatherers basically. So how long does a civilization last?

对 SpaceX 来说，目标是在火星上建立一个自给自足的城市。火星是唯一适合做这件事的行星。月球很近，但缺乏资源，而且我认为它很可能无法抵御任何毁灭地球的灾难。月球太近了，容易受到毁灭地球的灾难的影响。所以不是说我们不应该有月球基地，但火星会更有韧性。到达火星的难度正是它韧性的来源。

For SpaceX, the goal is to establish a self-sustaining city on Mars. Mars is the only viable planet for such a thing. The Moon is close, but it lacks resources, and I think it's probably vulnerable to any calamity that takes out Earth. The Moon is too close; it's vulnerable to a calamity that takes out Earth. So not saying we shouldn't have a moon base, but Mars would be far more resilient. The difficulty of getting to Mars is what makes it resilient.

在探讨为什么我们看不到外星人的各种解释时，其中之一是他们未能通过那些大过滤器，那些关键障碍。其中一个障碍是成为多行星物种。所以如果你是一个多行星物种，如果发生了什么，无论是自然灾难还是人为灾难，至少另一个星球可能还在。这样你就不会把所有鸡蛋放在一个篮子里。一旦你成为双行星物种，你显然可以扩展到小行星带，也许到木星和土星的卫星，最终到其他恒星系统。但如果你连另一个星球都到不了，你肯定到不了恒星系统。

In going through these various explanations of why we don't see the aliens, one of them is that they failed to pass these great filters, these key hurdles. One of those hurdles is being a multiplanet species. So if you're a multiplanet species and something happens, whether that was a natural catastrophe or a man-made catastrophe, at least the other planet would probably still be around. So you don't have all the eggs in one basket. Once you are a two-planet species, you can obviously extend to the asteroid belt, maybe to the moons of Jupiter and Saturn, and ultimately to other star systems. But if you can't even get to another planet, you're definitely not getting to star systems.

另一个可能的大过滤器是超级强大的技术，比如 AGI。所以你基本上是一次解决一个大过滤器。数字超级智能可能是一个大过滤器。我希望它不是，但它可能是。像杰夫·辛顿这样的人会说，他发明了人工智能的一些关键原理。我认为他把 AI 灭绝的概率定在 10% 到 20% 左右。所以这不像，你看乐观的一面，有 80% 的可能性是好的。所以我认为 AI 风险缓解很重要。

The other possible great filter is super powerful technology, like AGI for example. So you're basically trying to knock out one great filter at a time. Digital superintelligence is possibly a great filter. I hope it isn't, but it might be. Guys like Jeff Hinton would say, he has invented a number of the key principles in artificial intelligence. I think he puts the probability of AI annihilation around 10 to 20%, something like that. So it's not like, you know, look on the right side, it's 80% likely to be great. So I think AI risk mitigation is important.

成为多行星物种将是一个巨大的风险缓解措施。我还想再次强调拥有足够多的孩子来维持我们人口数量的重要性，不要陷入目前正在发生的人口崩溃。人口崩溃是一个真实且当前的问题。它没有反映在总人口数字中的唯一原因是人们活得更长了。但你可以很容易地预测任何给定国家的人口：只需取去年的出生率，有多少婴儿出生，乘以预期寿命，那就是稳态下的人口。除非出生率继续下降，否则人口会更少，最终减少到零。

Being a multiplanet species would be a massive risk mitigation. And I do want to once again emphasize the importance of having enough children to sustain our numbers, and not plummet into population collapse, which is currently happening. Population collapse is a real and current thing. The only reason it's not being reflected in the total population numbers is that people are living longer. But you can easily predict what the population of any given country will be: you just take the birth rate last year, how many babies were born, multiply that by life expectancy, and that's what the population will be at a steady state. Unless if the birth rate continues to decline, it will be even less and eventually dwindle to nothing.

我一直在敲婴儿鼓是有原因的，因为它在历史上一次又一次地成为文明崩溃的根源。所以我们为什么不努力稳定它呢？好吧，在这方面，我悲惨地辜负了文明，我正在努力弥补。我很想有很多孩子。

I keep banging on the baby drum here for a reason, because it has been the source of civilizational collapse over and over again throughout history. So why don't we just not try to stabilize that? Well, in that way, I have miserably failed civilization, and I'm trying to fix that. I would love to have many kids.

太好了，希望你能做到。时不我待。

Great, I hope you do. No time like the present.

是啊，是啊，我得给整个过程分配更多算力。但显然这并不难。

Yeah, yeah, I got to allocate more compute to the whole process. But apparently it's not that difficult.

不，这就像非技术性劳动。

No, it's like unskilled labor.

你为世界做的一件事就是用未来可能的样子激励我们。我们谈到的一些事情，你正在建造的一些东西：用 Neuralink 减轻人类痛苦，扩展人类思维的能力，试图在火星上建立殖民地，在另一个星球上为人类创建备份，以及探索人工智能在这个世界上的可能性，特别是在现实世界中，有数亿甚至数十亿的机器人在行走。将会有数十亿机器人，这几乎是肯定的。

One of the things you do for the world is to inspire us with what the future could be. Some of the things we've talked about, some of the things you're building: alleviating human suffering with Neuralink, expanding the capabilities of the human mind, trying to build the colony on Mars, creating a backup for humanity on another planet, and exploring the possibilities of what artificial intelligence could be in this world, especially in the real world AI with hundreds of millions, maybe billions of robots walking around. There will be billions of robots, that seems a virtual certainty.

那么，感谢你建造未来，感谢你激励我们这么多人继续建造和创造酷东西，包括孩子。

Well, thank you for building the future and thank you for inspiring so many of us to keep building and creating cool stuff, including kids.

是的，不客气。去繁衍吧。去繁衍吧。

Yeah, you're welcome. Go forth and multiply. Go forth and multiply.

谢谢你，埃隆。谢谢你的谈话，兄弟。

Thank you, Elon. Thanks for talking, brother.

感谢收听与埃隆·马斯克的对话。现在，亲爱的朋友们，有请 Neuralink 的联合创始人、总裁兼 CEO DJ Seo。你是什么时候开始对人脑着迷的？

Thanks for listening to this conversation with Elon Musk. And now, dear friends, here's DJ Seo, the co-founder, president, and CEO of Neuralink. When did you first become fascinated by the human brain?

对我来说，我一直对理解事物的目的以及它如何被设计来实现那个目的感兴趣，无论是有机的还是无机的。就像我们之前讨论你的窗帘支架：它们有明确的目的，并且是围绕那个目的设计的。成长过程中，我对看东西、摸东西、感受东西非常感兴趣，并试图真正理解它被设计来服务那个目的的根本原因。显然，大脑是我们都拥有的一个迷人器官。它是一个无限强大的机器，从中产生智能和认知。我们甚至还没有触及表面，了解这一切是如何发生的。但同时，我认为我花了一段时间才将这与真正研究和建造技术来理解大脑联系起来，直到研究生院。我生命中有几个关键时刻影响了我的人生轨迹，让我研究我现在正在做的事情。一个是成长过程中：我父母双方的祖父母都患有非常严重的阿尔茨海默病。这是一种极其令人衰弱的疾病。我的意思是，你真的看到一个人的整个身份和心智随着时间流逝而丧失。我只是记得思考心智的力量，以及像这样的东西如何能真正让你失去自我认同感。

For me, I was always interested in understanding the purpose of things and how it was engineered to serve that purpose, whether it's organic or inorganic. Like we were talking earlier about your curtain holders: they serve a clear purpose and they were engineered with that purpose in mind. Growing up, I had a lot of interest in seeing things, touching things, feeling things, and trying to really understand the root of how it was designed to serve that purpose. Obviously, the brain is just a fascinating organ that we all carry. It's an infinitely powerful machine that has intelligence and cognition that arise from it. We haven't even scratched the surface in terms of how all of that occurs. But at the same time, I think it took me a while to make that connection to really studying and building tech to understand the brain, not until graduate school. There were a couple key moments in my life that influenced the trajectory of my life, getting me to study what I'm doing right now. One was growing up: both sides of my family, my grandparents had a very severe form of Alzheimer's. It's an incredibly debilitating condition. I mean, literally you're seeing someone's whole identity and their mind just losing over time. I just remember thinking about both the power of the mind, but also how something like that could really lose your sense of identity.

有趣的是，这是揭示事物力量的一种方式，通过观察它失去力量。

It's fascinating that that is one of the ways to reveal the power of a thing, by watching it lose the power.

是的，我们对大脑的很多了解实际上来自这些案例：大脑受到创伤或某些部分导致某人失去某些能力，结果，人们对那部分组织对那个功能至关重要的相关性和理解。如果你这样想，它是一个极其脆弱的器官，但同时在许多不同方面，它也具有极强的可塑性和韧性。顺便说一下，术语“可塑性”意味着它具有适应性，所以神经可塑性指的是大脑的适应性。

Yeah, a lot of what we know about the brain actually comes from these cases where there is trauma to the brain or some parts of the brain that led someone to lose certain abilities, and as a result, there's some correlation and understanding of that part of the tissue being critical for that function. It's an incredibly fragile organ if you think about it that way, but also it's incredibly plastic and incredibly resilient in many different ways. By the way, the term plastic means that it's adaptable, so neuroplasticity refers to the adaptability of the brain.

另一个关键时刻，它影响了我的生活轨迹，并塑造了我现在的关注点，是在我青少年时期来到美国的时候。我当时一句英语都不会说，语言障碍非常大，很难与周围的同龄人交流，因为我不理解我们创造的这个叫做语言的人造构造，特别是英语。我记得自己感到非常孤立，无法与同龄人交流，所以大部分时间都独自一人，读书、看电影。我自然而然地被科幻小说吸引，觉得它们非常有趣，同时也是我学习英语的好方法。我最早读的一批书包括奥森·斯科特·卡特的《安德的游戏》系列、威廉·吉布森的《神经漫游者》和尼尔·斯蒂芬森的《雪崩》。当时《黑客帝国》等电影也上映了，这些都深刻影响了我对技术可能给生活带来巨大潜力的看法。

Another key moment that sort of influenced how the trajectory of my life has shaped towards the current focus of my life has been during my teenager when I came to the US you know I didn't speak a word of English there was a huge language barrier and um there was a lot of struggle to kind of connect with my peers around me um because I didn't understand the the artificial construct that we have cre created called language uh specifically English in this case and I remember feeling pretty isolated not being able to connect with peers around me so spent a lot of time just on my own you know reading books watching movies um and I I naturally sort of gravitated towards sci-fi books I just found them really really interesting and also it was a great way for me to learn English you know some of the first set of books that I picked up are Ender Game you know the whole Saga by uh Orson Scott Card and Neuromancer from William Gibson and Snow Crash from Neil Stevenson and you know movies like Matrix was coming out around that time point that really influenced how I think about the potential impact that technology can have for our lives in general

快进到大学时期，我一直对物理的东西、建造物理的东西着迷，尤其是那些具有一定智能的物理实体。我本科学习电气工程，最初的研究方向是微机电系统（MEMS），建造用于温度传感的微小纳米结构。我觉得这非常令人满足和着迷，理解如何建造如此微小的东西，同时它又能发挥功能、有用途。之后，我大学的大部分时间都在为下一代通信系统构建毫米波电路，用于成像。我觉得这在智力上非常有趣：相控阵、信号处理如何工作，适用于现代和下一代无线及有线通信系统。电磁波很迷人，如何在小空间内设计最高效的天线，如何让这些东西节能，这完全占据了我的求知欲。这段旅程让我申请并进入了加州大学伯克利分校的博士项目，在一个名为伯克利无线研究中心的联盟里。该中心当时正在研究我们称之为 XG 的系统，类似于 3G、4G、5G，但属于下一代 G 系统，以及如何设计相关电路，最终用于手机和如今任何无线连接的设备。我对整个系统及其基础设施的运作方式感到无比着迷。

So FastTrack to my college Years you know I I was always fascinated by just just physical stuff building physical stuff and especially um physical things that had some sort of intelligence and and you know I studied electrical engineering during undergrad and I started out my research in Ms uh so micro electron mechanical systems um and really building these tiny Nano structures for um temperature sensing and I just found that to be just incredibly rewarding and fascinating subject to just understand how you can build some something miniature like that that again served a function and had a purpose and then you know I I spent large majority of my college Years basically building millimeter wave circuits for nextg telecommunication systems for Imaging and it was just something that I found very very intellectually interesting you know phase arays how the signal processing works for you know any modern as well as NextGen telecommunication system Wireless and Wireline um EM waves or electromagnetic waves are fascinating how do you design antennas that are um most efficient in a small footprint that you have how do you make these things energy efficient that was something that just consumed my intellectual curiosity and that Journey led me to actually apply to and find myself at PhD program at UC Berkeley at kind of this Consortium called the Berkeley Wireless Research Center that was precisely looking at um building at the time we called it XG you know similar to 3G 4G 5G but the next next Generation G system and how you would design circuits around that to ultimately go on phones and you know basically any any other devices uh that are wirelessly connected these days um so I I I was just absolutely just fascinated by how that entire system works and that infrastructure Works

在研究生期间，我有幸获得了几项研究奖学金，可以自由追求任何我感兴趣的项目。这是我在研究生生涯中非常享受的一点：你可以追随自己的求知欲，研究那些可能最终并不重要，但能让你深入或广泛探索的领域。当时我实际上在做一个名为“智能绷带”的项目。想法是，当你受伤时，细胞会遵循一系列信号通路来闭合伤口。有假设认为，施加外部电场可以通过电吸引伤口周围的细胞来加速伤口闭合。不仅针对普通伤口，还有不愈合的慢性伤口。所以我们感兴趣的是制造一种可穿戴贴片，用于促进愈合过程。这个项目是与 Michelle Mah haritz 教授合作的，他后来成为了我论文委员会的重要成员，并深刻影响了我博士生涯的其余部分。

And then also during grad school I had sort of the fortune of having um you know couple research fellowships that led me to pursue whatever project that I want and that's that's one of the things that uh I really enjoyed about my graduate school career where you got to kind of pursue do your intellectual curiosity in the domain that may not matter at the end of the day but is something that you know really uh allows you the opportunity to um go as deeply as you want as well as as widely as you want and at the time I was actually working on this project called the smart bandid and the idea was that when you get a wound there's a lot of other kind of proliferation of signaling pathway that cells follow to close that wound and there were hypothesis that when you apply external electric field you can actually accelerate the closing of that field by having you know basically electr taxing of the cells around that wound site and specifically not just for normal wound there are chronic wounds that don't heal um so we were interested in building you know some sort of a wearable patch that you could um apply to kind of facilitate that healing process and um that was in collaboration with uh Professor Michelle Mah haritz um you know which which you know was a great addition to kind of my thesis committee and you know really shaped rest of my uh PhD career

所以这应该是你第一次与生物学互动吧？

So this would be the first time you interacted with Biology I suppose

对，没错。虽然我之前在无线成像和通信系统的终端应用中也涉及过安全和生物成像，但这次是非常明确、直接地应用于生物学和生物系统，理解其约束，并围绕它设计和工程化电气解决方案。所以这是我的第一次接触，也是我认识 Michelle 的契机。

Correct correct I mean there were some peripheral you know end application of the wireless Imaging and telecommunication system that I was using for security and bioimaging but this was a very clear direct application to bio biolog biology and biological system and understanding the constraints around that and really designing and Engineering electrical Solutions around it so that was my first introduction and that's also um kind of how I got introduced to Michelle

他因在 2000 年代初远程控制甲虫而闻名。大约在 2013 年，植入系统的圣杯是理解你能把东西做得多小，而这很大程度上取决于你能提供多少能量或功率，以及如何从中提取数据。当时在伯克利，人们渴望了解在神经领域能构建什么样的系统来真正微型化这些植入式系统。我清楚地记得有一次会议，Michelle 走进来说：“伙计们，我觉得我有解决方案了，解决方案就是超声波。”然后他解释了为什么。这构成了我论文工作的基础，即“神经尘埃”系统，它研究使用超声波而非电磁波进行供电和通信。

Um you know he's he's sort of known for remote control of uh Beatles in the early 2000s and then around 2013 you know obviously kind of the Holy Grail when it comes to implant system is to kind of understand how small of a thing you can make and a lot of that is driven by how much energy or how much power you can supply to it and how you extract data from it so at the time at Berkeley there was kind of this this uh desire to kind of understand in the neural space what what what sort of system you can build to really miniaturize these implantable systems and uh I distinct distinctively remember this one uh particular meeting where Michelle came in and he's like guys I think I have a solution the solution is ultrasound and uh and then he proceeded to kind of walk through why that is the case and that that really formed the basis for my thesis work um uh called neural dust system that was looking at ways to use ultrasound as opposed to uh electromagnetic waves for powering as well as communication

我想我应该退一步说，这个项目的初始目标是建造一个大约神经元大小的植入式系统，可以放在神经元旁边，记录其状态，并将数据传回外部世界以做有用的事情。正如我提到的，植入式系统的大小受限于你如何供电以及如何获取数据。从根本上说，人体本质上是一个装有盐水的袋子，里面有一些有趣的蛋白质和化学物质，但主要是盐水，温度非常稳定地维持在 37°C。我们稍后会讨论为什么这对任何电子设备来说都是一个极其恶劣的生存环境。我相信你经历过，或者没经历过，把手机掉进海里，它会立刻坏掉。总之，电磁波在这种环境中穿透性不好，而且光速就是那样，我们无法改变。

I guess I should step back and say the the initial goal of the project was to build these tiny about a size of a neuron implantable system that can be parked next to a neuron being able to record its state and being able to Ping that back to the outside world for doing something useful you know as I mention the size of the implantable system is limited by how you power the thing and get the data off of it and at the end of the day fundamentally if you look at a human body where uh essentially bag of salt water with some interesting proteins and chemicals but uh it's mostly salt water that's very very well temperature regulated at 37° c um and we'll we'll get into how why and and later why that's a an extremely harsh environment for any Electronics to survive as I'm sure you've experienced or maybe not experienced you know dropping cell phone in a in a salt water in an ocean it will instantly kill the device right um but anyways uh just in general electromagnetic waves don't penetrate through this environment well um and just the speed of light it is what it is we can't we

你无法改变它，而且根据你与设备交互的波长，设备本身必须足够大。比如这些电感器需要相当大。一个很好的经验法则是，你希望波前大致与你交互的物体尺寸相当。所以一个植入式系统，尺寸大约在 10 到 100 微米，体积大约相当于人体中一个神经元的大小，你就需要工作在几百吉赫兹的频率。这不仅很难制造出能在那些频率下工作的电子设备，而且人体也会非常显著地衰减信号。所以超声波的巧妙之处在于，超声波在人体组织中传播的效率远高于电磁波。这是你在生活中会遇到的事情，我相信大多数人在去医院做医学超声（也就是声像图）时都遇到过。它们能深入很深的位置而不会过多衰减信号。总而言之，超声波在人体中传播得非常好，其传播机制在于波前非常不同。电磁波是横波，而超声波是纵波。所以这是完全不同的波前传播模式。而且声速比光速慢好几个数量级，这意味着即使在 10 兆赫兹的超声波下，你的波前波长也非常小。所以如果你要与 10 微米或 100 微米的结构交互，在 10 兆赫兹下你会得到 150 微米的波前，而制造那些兆赫兹频率的电子设备要容易得多，效率也高得多。所以基本想法就是利用超声波为设备供电并回传数据。那么问题来了，如何回传数据？我们最终采用的机制叫做背向散射。这其实很常见，我们日常使用的 RFID 卡（射频识别标签）就是基于这个原理。里面通常没有电池，只有一个天线和一个线圈，存储着你的序列识别 ID。然后有一个外部设备叫做读取器，它发送一个波前，然后你通过某种调制方式反射回那个波前，这个调制方式对你的 ID 是唯一的。这就是背向散射。从根本上说，标签本身并不需要消耗太多能量，这就是我们考虑用来回传数据的机制。所以当你有一个外部超声波换能器向你的植入体（神经尘埃植入体）发送超声波时，它会记录周围环境的一些信息，无论是神经元放电还是与之交互的组织的其他状态，然后它只需对返回源的波前进行幅度调制。而记录步骤是唯一需要能量的步骤。

Can't change it and based on the wavelength at which you are interfacing with the device, the device just needs to be big. Like these inductors need to be quite big. And the general good rule of thumb is that you want the wavefront to be roughly on the order of the size of the thing that you're interfacing with. So an implantable system that is around 10 to 100 microns in dimension, in a volume which is about the size of a neuron that you see in a human body, you would have to operate at like hundreds of gigahertz, which number one, not only is it difficult to build electronics operating at those frequencies, but also the body just attenuates that very, very significantly. So the interesting insight of this ultrasound was the fact that ultrasound just travels a lot more effectively in the human body tissue compared to electromagnetic waves. And this is something that you encounter, and I'm sure most people have encountered in their lives when you go to hospitals that are medical ultrasound, sonograph, right? And they go into very, very deep depth without attenuating too much of the signal. So all in all, ultrasound, the fact that it travels through the body extremely well, and the mechanism to which it travels through the body really well is that the wavefront is very different. Electromagnetic waves are transverse, whereas in ultrasound waves are compressive. So it's just a completely different mode of wavefront propagation. And as well, speed of sound is orders of magnitude less than speed of light, which means that even at 10 megahertz ultrasound wave, your wavefront ultimately is a very, very small wavelength. So if you're talking about interfacing with a 10 micron or 100 micron type structure, you would have 150 micron wavefront at 10 MHz, and building electronics at those megahertz frequencies are much, much easier and they're a lot more efficient. So the basic idea was born out of using ultrasound as a mechanism for powering the device and then also getting data back. So now the question is, how do you get the data back? The mechanism we landed on is what's called backscattering. This is actually something that is very common and that we interface on a day-to-day basis with our RFID cards, our radio frequency ID tags. There's actually rarely a battery inside; there's an antenna and some sort of coil that has your serial identification ID, and then there's an external device called the reader that sends a wavefront, and then you reflect back that wavefront with some sort of modulation that's unique to your ID. That's what's called backscattering. Fundamentally, the tag itself actually doesn't have to consume that much energy, and that was a mechanism we were thinking about for sending the data back. So when you have an external ultrasonic transducer that's sending an ultrasonic wave to your implant, the neural dust implant, and it records some information about its environment, whether it's a neuron firing or some other state of the tissue that it's interfacing with, and then it just amplitude modulates the wavefront that comes back to the source. And the recording step would be the only one that requires any energy.

那么那个小步骤中需要能量的是什么？没错，就是初始启动电路，用来获取记录、放大信号，然后进行调制。实现这一点的机制是存在一种特殊的晶体，叫做压电晶体，它能够将声能转化为电能，反之亦然。所以你可以让超声波域和电域之间产生这种相互作用，而生物组织就是那个媒介。

So what would require energy in that little step? Correct, so it is that initial startup circuitry to get that recording, amplifying it, and then just modulating. And the mechanism to enable that is there is a specialized crystal called piezoelectric crystals that are able to convert sound energy into electrical energy and vice versa. So you can have this interplay between the ultrasonic domain and electrical domain that is the biological tissue.

所以，将非常小的计算设备放置在神经元旁边，这就是梦想，是脑机接口的愿景。也许在我们讨论 Neuralink 之前，你能介绍一下 BCI 领域的历史吗？这个持续的梦想是什么，以及沿途有哪些里程碑，不同的方法，以及各个实验室所做的出色工作？

So on the theme of parking very small computational devices next to neurons, that's the dream, the vision of brain-computer interfaces. Maybe before we talk about Neuralink, can you give a sense of the history of the field of BCI? What has been the continued dream and also some of the milestones along the way with the different approaches and the amazing work done at the various labs?

我认为一个好的起点是回到 18 世纪 90 年代。没想到吧。当时动物电的概念，或者说身体带电的事实，是由 Luigi Galvani 首次发现的。他做了一个实验，将一组电极连接到青蛙腿上并通入电流，然后青蛙腿开始抽搐，他说：“哦，天哪，身体是带电的。”快进很多年，到 20 世纪 20 年代，德国精神病学家 Hans Berger 发现了 EEG，也就是脑电图阵列，你把它戴在头骨外面，就能得到某种神经记录。这是一个非常重要的里程碑，意味着你可以记录人类思维的一些活动。然后在 20 世纪 40 年代，有一组科学家，Renshaw、Forbes 和 Morrison，他们将玻璃微电极插入大脑皮层并记录了单个神经元。他们得到的信号分辨率更高、保真度也更高，因为你更接近信号源。到了 20 世纪 50 年代，两位科学家 Hodgkin 和 Huxley 出现了，他们建立了细胞膜和离子机制的优美模型，并画出了电路图。作为一个电气工程师，我觉得这是一个由偏微分方程构成的优美模型，描述了离子流动以及神经元如何通信。十年后的 20 世纪 60 年代，他们因此获得了诺贝尔奖。然后在 1969 年，华盛顿大学的 Fetz 发表了一篇精彩的论文，题为《皮层单位活动的操作性条件反射》，他能够记录猴子大脑中的单个神经元，并让猴子根据其活动和奖励系统进行调节。据我所知，这是第一个闭环脑机接口的例子。摘要写道：“通过用食物颗粒奖励来强化高频率的神经元放电，从而对麻醉猴子前中央皮层中单个神经元的活动进行条件反射。除了食物奖励外，通常还提供单位放电率的听觉和视觉反馈。”酷，他们真的做到了。那是在 1969 年。经过几次训练后，猴子可以将新分离出的细胞的活动水平提高到奖励前水平的 50% 到 500%。太迷人了。大脑的可塑性非常强。从此以后，实验的数量以及用于与大脑交互的工具集都爆炸式增长。我认为还包括对神经编码以及一些皮层层次和功能的理解。

I think a good starting point is going back to the 1790s. I did not expect that. Where the concept of animal electricity, or the fact that bodies are electric, was first discovered by Luigi Galvani. He had this experiment where he connected a set of electrodes to a frog leg and ran current through it, and then it started twitching, and he said, 'Oh my goodness, body's electric.' So fast forward many, many years to the 1920s, where Hans Berger, who is a German psychiatrist, discovered EEG, or electroencephalographic arrays that you wear outside the skull that gives you some sort of neural recording. That was a very, very big milestone, that you can record some sort of activity about the human mind. And then in the 1940s, there were these group of scientists, Renshaw, Forbes, and Morrison, that inserted these glass microelectrodes into the cortex and recorded single neurons. The fact that they had signals that are a bit more high resolution and high fidelity as you get closer to the source, let's say. And in the 1950s, these two scientists, Hodgkin and Huxley, showed up and they built these beautiful models of the cell membrane and the ionic mechanism and had these circuit diagrams. As someone who's an electrical engineer, it's a beautiful model built out of partial differential equations talking about flow of ions and how that really leads to how neurons communicate. And they won the Nobel Prize for that 10 years later in the 1960s. So in 1969, Fetz from University of Washington published this beautiful paper called 'Operant Conditioning of Cortical Unit Activity' where he was able to record a single unit neuron from a monkey and was able to have the monkey modulate based on its activity and reward system. I would say this is the very first example, as far as I'm aware, of a closed-loop brain-computer interface or BCI. The abstract reads: 'The activity of single neurons in precentral cortex of anesthetized monkeys was conditioned by reinforcing high rates of neuronal discharge with delivery of a food pellet. Auditory and visual feedback of unit firing rates was usually provided in addition to food reinforcement.' Cool, so they actually got it done. This is back in 1969. After several training sessions, monkeys could increase the activity of newly isolated cells by 50 to 500% above rates before reinforcement. Fascinating. The brain is very plastic. And so from here, the number of experiments grew, as well as the set of tools to interface with the brain have just exploded. I think also just understanding the neural code and how some of the cortical layers and functions work.

另一篇在运动解码领域颇具开创性的论文，是 1980 年代 Georgopoulos 的那篇，它发现了运动调谐曲线。什么是运动调谐曲线？

The other paper that is pretty seminal, especially in motor decoding, was this paper from the 1980s from Georgopoulos that discovered motor tuning curves. What are motor tuning curves?

运动调谐曲线指的是，包括人类在内的哺乳动物运动皮层中存在一类神经元，它们具有优先方向，会因此放电。也就是说，有一组神经元在你思考向左、向右、向上、向下或任何这些方向移动时，会增加放电活动。基于这一点，你可以开始思考：如果你能识别出那些基本的方向检测器，你就能做很多事情。你实际上可以利用这些信息从皮层解码出某人意图的运动。那篇论文非常具有开创性，它表明存在某种你可以提取的编码，尤其是在运动皮层中。所以那里有信号，如果你测量来自大脑的电信号，你就能弄清楚意图是什么。

Motor tuning curves refer to the fact that there are neurons in the motor cortex of mammals, including humans, that have a preferential direction that causes them to fire. So there are a set of neurons that increase their spiking activity when you're thinking about moving to the left, right, up, down, or any of those vectors. Based on that, you could start to think: if you can identify those essential direction detectors, you can do a lot. You can actually use that information to decode someone's intended movement from the cortex. That was a very seminal paper showing that there is some sort of code you can extract, especially in the motor cortex. So there's a signal there, and if you measure the electrical signal from the brain, you could actually figure out what the intention was.

没错。不仅是电信号，而且是来自正确神经元集合的电信号，这些信号能给你这种优先方向。

Correct. Not only electrical signals, but electrical signals from the right set of neurons that give you this preferential direction.

慢慢转向 Neuralink，一个有趣的问题是：从这条研究线来看，我对 BCI 领域、侵入式与非侵入式的理解是什么？紧挨着神经元有多重要？这能带来什么？

Going slowly towards Neuralink, one interesting question is: what do I understand on the BCI front, on invasive versus noninvasive, from this line of work? How important is it to park next to the neuron? What does that get you?

答案根本上取决于你想用它做什么。实际上，用 EEG 和 ECoG 可以做很多事，它们不穿透皮层或软脑膜，而是将一组电极放在大脑表面。我个人非常感兴趣的是，真正理解并能够获取局部活动的高分辨率、高保真信息。退一步讲，用一个类比：思考电有点困难。归根结底，我们做的是由离子电流（带电粒子的运动）介导的电记录，这对大多数人来说很难想象。但事实证明，大脑中发生的许多活动及其频段，与声波和我们正常对话的听觉范围非常相似。所以该领域常用的类比是：如果你有一个正在比赛的足球场，站在场外，你可能根据主队观众的欢呼和嘘声大致了解比赛情况——球队是否领先——但你完全不知道比分是多少，不知道个别观众或球员在互相说什么，不知道下一个战术或进球是什么。所以你必须把麦克风放到体育场附近或里面，靠近声源，比如进入个别的谈话中。在这个具体例子中，你会希望它就在战术讨论的地方旁边。我认为这很好地说明了我们正在努力做的事情。当我们说侵入式或微创植入式脑机接口，相对于非侵入式或非植入式脑接口时，基本上就是在讨论你把麦克风放在哪里，以及你能用这些信息做什么。

The answer fundamentally depends on what you want to do with it. There's actually an incredible amount of stuff you can do with EEG and ECoG, which doesn't penetrate the cortical layer or pia mater, but places a set of electrodes on the surface of the brain. The thing I'm personally very interested in is just understanding and being able to really tap into the high-resolution, high-fidelity understanding of the activities happening at the local level. To step back, using an analogy: it's a bit difficult to think about electricity. At the end of the day, we're doing electrical recording mediated by ionic currents—movements of charged particles—which is really hard for most people to think about. But it turns out a lot of the activities happening in the brain, and the frequency bands with which they happen, are very similar to sound waves and our normal conversation in the audible range. So the analogy typically used in the field is: if you have a football stadium with a game going on, if you stand outside the stadium, you might get a sense of how the game is going based on the cheers and boos of the home crowd—whether the team is winning or not—but you have absolutely no idea what the score is, what individual audience members or players are talking or saying to each other, what the next play is, or what the next goal is. So what you have to do is drop the microphone near or into the stadium and get near the source, like into the individual chatter. In this specific example, you would want it right next to where the huddle is happening. I think that's a good illustration of what we're trying to do. When we say invasive or minimally invasive or implanted brain-computer interfaces versus noninvasive or non-implanted brain interfaces, it's basically talking about where you put that microphone and what you can do with that information.

当我们现在进入 Neuralink 的努力时，我们在这里讨论的读写通信的生物物理学是什么？

What is the biophysics of the read and write communication that we're talking about here, as we now step into the efforts at Neuralink?

大脑由称为神经元的特化细胞组成。有数十亿个——有时人们引用 1000 亿个——它们连接在这个复杂而动态的网络中，不断重塑，改变它们的突触权重，我们通常称之为神经可塑性。神经元还浸泡在一个充满带电分子的带电环境中，如钾离子、钠离子、氯离子，这些离子实际上促进了不同网络之间的离子电流通信。当你观察一个神经元时，它们有一个带有美丽蛋白质结构的膜，称为电压门控离子通道，在我看来这是自然界最伟大的发明之一。如果你思考它们是什么，它们在做现代晶体管的工作。晶体管归根结底就是一个电压门控的传导通道，而大自然在进化早期就找到了实现这一点的方法。众所周知，有了晶体管，我们可以进行许多计算，并拥有我们今天能接触到的许多惊人事物。所以我认为这是——顺便提一下——大自然想出的一个美丽发明：这些电压门控离子通道。

The brain is made of specialized cells called neurons. There are billions of them—tens of billions, sometimes people quote 100 billion—that are connected in this complex yet dynamic network, constantly remodeling, changing their synaptic weights, which we typically call neuroplasticity. The neurons are also bathed in a charged environment laden with many charged molecules like potassium ions, sodium ions, chlorine ions, and those actually facilitate ionic current communication between these different networks. When you look at a neuron, they have a membrane with a beautiful protein structure called voltage-gated ion channels, which in my opinion is one of nature's best inventions. If you think about what they are, they're doing the job of modern-day transistors. Transistors are nothing more than a voltage-gated conduction channel, and nature found a way to have that very early on in its evolution. As we all know, with the transistor you can have many computations and a lot of amazing things that we have access to today. So I think it's one of those—just as a tangent—a beautiful invention that nature came up with: these voltage-gated ion channels.

我想在生物学层面，在生物体层级复杂性的每一层，都会有某种存储信息和进行计算的方式，而这只是其中一种。但用生物和化学成分做到这一点很有趣。此外，对于神经元来说，不仅仅是电；还有化学通信，还有机械运动。这些是实际存在的物体，它们会振动，会移动。

I suppose on the biological level, at every level of the complexity of the hierarchy of the organism, there are going to be some mechanisms for storing information and for doing computation, and this is just one such way. But to do that with biological and chemical components is interesting. Plus, with neurons, it's not just electricity; it's chemical communication, it's also mechanical. These are actual objects that vibrate, they move.

是的，涉及很多非常有趣的物理学。回顾我研究生期间在超声波方面的工作，有一些团队在研究用超声波让神经元放电的机制。据我所知，其机制仍不清楚。可能只是你施加了某种热能，导致细胞以有趣的方式去极化，但也有这些离子通道甚至膜，在它们被机械摇动或振动时，实际上会打开它们的孔道。所以有很多粒子运动的元素，这又受扩散物理学（粒子运动）支配，那里也有很多有趣的物理学。更不用说，正如 Roger Penrose 所讨论的，所有这些可能有一些美丽的量子力学效应的奇异性，他实际上相信意识可能从量子中涌现。

Yes, there's a lot of really interesting physics involved. Going back to my work on ultrasound during grad school, there are groups looking at ways to cause neurons to fire an action potential using ultrasound waves. The mechanism by which that happens is still unclear as I understand. It may just be that you're imparting some sort of thermal energy that causes cells to depolarize in interesting ways, but there are also these ion channels or even membranes that actually open up their pores as they're being mechanically shaken or vibrated. So there are a lot of elements of moving particles, which again is governed by diffusion physics—movements of particles—and there's also a lot of interesting physics there. Not to mention, as Roger Penrose talks about, there might be some beautiful weirdness in the quantum mechanical effects of all this, and he actually believes that consciousness might emerge from the quantum.

那里有机械效应，所以有物理、化学、生物学，所有这些都在发生。

Mechanical effects there, so like there's physics, there's chemistry, there's biology, all of that is going on there.

哦，是的。我的意思是，你可以深入很多层次的物理，但最终你拥有这些带有电压门控离子通道的膜，这些通道选择性地让细胞外基质中的带电分子进出。这些神经元通常有一个静息电位，即细胞内部和外部的电压差。当某种刺激改变状态，使得它们需要向下游网络发送信息时，你开始看到这些分子进出通道的协调。一旦达到阈值，它们会打开更多通道，直到细胞去极化并发送动作电位。这是这些分子美丽的协调。当我们把电极放在神经元旁边时，我们试图测量这些局部的电位变化，这些变化由离子运动介导。正如我之前提到的，涉及很多物理。电记录的两个主导物理是扩散物理和电磁学。哪一个占主导——麦克斯韦方程还是菲克定律——取决于你的电极位置。如果靠近源，主要是电磁；如果远离，则更多基于扩散。所以当你把电极紧贴神经元时，你可以监听那个单独的“对话”和局部电位变化。你得到的信号是经典的教科书式神经尖峰波形。但一旦你远离——根据克里斯托夫·科赫实验室和其他人的研究——一旦你离源大约 100 微米，大约一根头发丝的宽度，你就再也听不到那个神经元了。系统不够灵敏，无法记录那个局部膜电位变化。给你一个规模概念：一个 100 微米的体素——一个 100×100×100 微米的盒子——在脑组织中大约包含 40 个神经元及其连接。所以那个体积里有很多东西。一旦你超出那个范围，就没有希望检测到你关心的那个特定神经元的变化。但当你移动时，你会听到其他神经元。如果你再移动 100 微米，你会听到另一个社区的“对话”。

Oh yeah, yeah. I mean, you can dive into many levels of physics, but in the end you have these membranes with voltage-gated ion channels that selectively let these charged molecules in the extracellular matrix in and out. These neurons generally have a resting potential, a voltage difference between inside and outside the cell. When there's some stimulus that changes the state such that they need to send information to the downstream network, you start to see an orchestration of these molecules going in and out of these channels. They also open up more once it reaches a threshold, to the point where you have a depolarizing cell that sends an action potential. It's a beautiful orchestration of these molecules. What we're trying to do when we place an electrode next to a neuron is to measure these local changes in the potential, mediated by the movement of ions. As I mentioned earlier, there's a lot of physics involved. The two dominant physics for electrical recording are diffusion physics and electromagnetism. Which one dominates—Maxwell's equations versus Fick's law—depends on where your electrode is. If it's close to the source, it's mostly electromagnetic; when you're further away, it's more diffusion-based. So when you park it next to a neuron, you can listen in on that individual chatter and those local changes in potential. The signal you get is the canonical textbook neural spiking waveform. But once you're further away—based on studies from Christof Koch's lab and others—once you're about 100 microns away from the source, which is about the width of a human hair, you no longer hear from that neuron. The system isn't sensitive enough to record that local membrane potential change. To give you a sense of scale, a 100-micron voxel—a 100 by 100 by 100 micron box—in brain tissue contains roughly 40 neurons and their connections. So there's a lot in that volume. Once you're outside that, there's no hope of detecting the change from that one specific neuron. But as you move around, you'll hear other ones. If you move another 100 microns, you'll hear chatter from another community.

正确。所以整个思路是，你想放置尽可能多的电极，然后监听这些“对话”。

Correct. And so the whole sense is you want to place as many electrodes as possible and then you're listening to the chatter.

是的，你想监听这些“对话”。最终，你也想让软件来做解码的工作。至于为什么 ECoG 和 EEG 能工作：当有这些局部变化时，不仅仅是一个神经元在激活；许多网络一直在激活。你会看到这个带电介质中电位的一般变化，这就是你在远处记录到的。你仍然有一个稳定的参考电极，而大脑是一个电活性器官。你看到动作电位变化的某种总和，你可以捕捉到它。这是一个慢得多的变化信号，但存在典型的振荡和波，比如伽马波、贝塔波，以及当你睡觉时，这些可以被检测到，因为大脑有一种同步的全局效应。物理原理很深：为什么扩散物理在远离源时占主导。这是一个带电介质，类似于电磁波在大气或等离子体等带电介质中传播。有一种奇怪的屏蔽效应，随着你远离，信号进一步衰减。如果你深入研究信号随距离的衰减，你会看到一开始是 1/r² 衰减，然后是指数下降。那就是从电磁主导转向扩散物理主导的拐点。但对于电极，你需要理解的生物物理学并没有那么深，因为无论你把它放在哪里，你都在监听一小群局部神经元。

Yeah, you want to listen to the chatter. And at the end of the day, you also want to let the software do the job of decoding. To go into why ECoG and EEG work at all: when you have these local changes, it's not just one neuron activating; many networks are activating all the time. You see a general change in the potential of this charged medium, and that's what you record when you're farther away. You still have a stable reference electrode, and the brain is an electroactive organ. You see some aggregate of action potential changes and you can pick it up. It's a much slower changing signal, but there are canonical oscillations and waves like gamma waves, beta waves, and when you sleep, those can be detected because there's a synchronized global effect of the brain. The physics goes deep: why diffusion physics dominates when you're further away. It's a charged medium, similar to how electromagnetic waves propagate in atmosphere or in a charged medium like a plasma. There's a weird shielding that further attenuates the signal as you move away. If you do a deep dive on signal attenuation over distance, you see a 1/r² falloff in the beginning and then an exponential drop-off. That's the knee where you go from electromagnetism dominating to diffusion physics dominating. But with the electrodes, the biophysics you need to understand isn't that deep, because no matter where you place it, you're listening to a small crowd of local neurons.

正确。是的，所以一旦你穿透大脑，你就进入了“竞技场”，那里有很多神经元。但有一个完整的神经科学领域在研究竞技场的不同分组和区域通常负责哪些功能，尽管这个比喻可能不太恰当，因为座位并没有那么有组织。而且，它们大多数是沉默的；它们并不怎么活跃。你必须用恰到好处的刺激去触发它们。它们通常非常安静。类似于暗能量和暗物质，存在暗神经元。它们都在做什么？当你把电极放在那个 100 微米体积内，大约有 40 个神经元，为什么你只看到少数几个？那里发生了什么？

Correct. Yeah, so once you penetrate the brain, you're in the arena, so to speak, and there's a lot of neurons there. But there's a whole field of neuroscience studying how different groupings and sections of the arena are usually responsible for which functions, though the metaphor probably falls apart because the seating isn't that organized. Also, most of them are silent; they don't really do much. You have to hit them with just the right stimulus. They're usually very quiet. Similar to dark energy and dark matter, there are dark neurons. What are they all doing? When you place an electrode within that 100-micron volume with 40 or so neurons, why do you see only a handful? What is happening there?

嗯，它们大多数时候是安静的，但一旦它们说话，就会说出深刻的东西。我想我倾向于这么认为。

Well, they're mostly quiet, but like when they speak, they say profound things. I think that's the way I'd like to think about it anyway.

在我们进一步深入之前，先宏观地看一下。那么，Neuralink 从手术到植入物，到信号和解码过程，再到人类能够使用植入物实际影响外部世界，这一切是如何运作的？所有这些都发生在 Neuralink 今年 1 月刚刚实现的巨大历史里程碑的背景下——将 Neuralink 植入物放入第一个人类 Nolan 体内。关于他的经历有很多可谈的，因为他能够描述那种体验的所有细微差别、美丽和迷人的复杂性。但在技术层面上，Neuralink 是如何工作的？

Before we zoom in even more, let's zoom out. So how does Neuralink work from the surgery to the implant to the signal and the decoding process, and the human being able to use the implant to actually affect the world outside? All of this in the context of the gigantic historic milestone that Neuralink just accomplished in January of this year, putting a Neuralink implant in the first human being, Nolan. There's been a lot to talk about there about his experience because he's able to describe all the nuance and the beauty and the fascinating complexity of that experience. But on the technical level, how does Neuralink work?

好，是的。我们正在构建的技术有三个主要组成部分。第一个是设备，也就是实际记录这些神经信号的东西，我们称之为 N1 植入物或 Link。我们还有一台手术机器人，负责植入这些我们称之为“线程”的极细导线，它们比头发丝还细。一旦手术完成，你就能获得这些神经信号，也就是从大脑中发出的尖峰神经元。然后你需要某种软件来解码用户想用这些信号做什么。所以有一个叫做 Neuralink 应用程序或 B1 应用的东西在做这个翻译工作。它运行着一个非常简单的机器学习模型，解码这些神经信号输入，然后将其转换为一组输出，让我们的第一位参与者 Nolan 能够控制光标。这一切都是无线完成的。

Work, yeah. So there are three major components to the technology that we're building. One is the device, the thing that's actually recording these neural signals. We call it the N1 implant or the Link. And we have a surgical robot that's actually doing an implantation of these tiny, tiny wires that we call threads, which are smaller than human hair. And once everything is surgically done, you have these neural signals, these spiking neurons that are coming out of the brain. And you need to have some sort of software to decode what the users intend to do with that. So there's what's called the Neuralink application or B1 app that's doing that translation. It's running a very, very simple machine learning model that decodes these inputs that are neural signals and then converts them to a set of outputs that allows our participant, first participant Nolan, to be able to control a cursor. And this is done wirelessly.

这一切都是无线完成的。所以我们的植入物实际上有两部分。Link 有这些叫做“线程”的柔性细线，沿其长度分布着多个电极。它们只插入到皮层，大约 3 到 5 毫米深，位于运动皮层区域，那里是运动意图所在。我们有 64 根这样的线程，每根线程在 3 到 4 毫米的长度上有 16 个电极，间隔 200 微米。所以你可以沿着插入深度进行记录。基于这些信号，我们构建了一个定制的集成电路或 ASIC，它放大你记录的神经信号，将其数字化，然后通过某种机制检测是否有有趣的事件，即尖峰事件，并决定是否通过蓝牙将其发送到外部设备，无论是手机还是运行 Neuralink 应用程序的电脑。所以板载信号处理已经可以判断这是否是一个有趣的事件。因此，植入物内部除了人脑之外，还有一些计算能力。

And this is done wirelessly. So our implant is actually two-part. The Link has these flexible tiny wires called threads that have multiple electrodes along their length. And they're only inserted into the cortical layer, which is about 3 to 5 millimeters in a human brain, in the motor cortex region, where the intention for movement lies. We have 64 of these threads, each thread having 16 electrodes along the span of 3 to 4 millimeters, separated by 200 microns. So you can actually record along the depth of the insertion. And based on that signal, there's a custom integrated circuit or ASIC that we built that amplifies the neural signals you're recording, digitizes them, and then has some mechanism for detecting whether there was an interesting event, that is a spiking event, and decides to send that or not through Bluetooth to an external device, whether it's a phone or a computer that's running this Neuralink application. So there's onboard signal processing already just to decide whether this is an interesting event or not. So there is some computational power on board inside the implant, in addition to the human brain.

是的，所以它进行信号处理，真正压缩你记录的信号量。我们总共有 1000 个电极，以略低于 20 kHz 的频率采样，每个 10 位。所以从 1000 通道同时神经记录中，有 200 兆比特的数据传入芯片。数据量相当大。有技术可以无线发送这些数据，但在大脑这样一个热约束非常严格的环境中，必须进行一定程度的压缩，只发送你需要的感兴趣数据。在这个特定的运动解码案例中，就是是否发生尖峰。然后利用这些信息来解码预期的光标移动。所以植入物本身进行处理，通过我们的尖峰检测算法判断是否发生了尖峰，然后打包，通过蓝牙发送到外部设备，外部设备上的模型再进行解码：基于尖峰输入，Nolan 是想向上、向下、向左、向右移动，还是点击、右键点击等等。

Yeah, so it does the signal processing to really compress the amount of signal that you're recording. So we have a total of 1,000 electrodes sampling at just under 20 kHz with 10 bits each. So that's 200 megabits coming through to the chip from 1,000 channel simultaneous neural recording. And that's quite a bit of data. There are technologies available to send that off wirelessly, but being able to do that in a very, very thermally constrained environment that is a brain, so there has to be some amount of compression that happens to send off only the interesting data that you need. In this particular case for motor decoding, it's occurrence of a spike or not. And then being able to use that to decode the intended cursor movement. So the implant itself processes it, figures out whether a spike happened or not with our spike detection algorithm, and then sends it off, packages it, sends it off through Bluetooth to an external device that then has the model to decode: based on the spiking inputs, did Nolan wish to go up, down, left, right, or click, or right-click, or whatever.

这一切都非常迷人，但我们还是聚焦在 N1 植入物本身。也就是大脑里的那个东西。我正在看它的图片：有一个外壳，有一个充电线圈。我们还没谈到充电，这很有趣。电池、电源管理芯片、天线，然后是信号处理芯片。我想知道是否还有更多种类的信号处理可以做。然后还有线程本身，底部有外壳。那么，关于充电：有一个外部充电设备吗？

All of this is really fascinating, but let's stick on the N1 implant itself. So the thing that's in the brain. I'm looking at a picture of it: there's an enclosure, there's a charging coil. We didn't talk about the charging, which is fascinating. The battery, the power electronics, the antenna, then there's the signal processing electronics. I wonder if there's more kinds of signal processing you can do. And then there's the threads themselves with the enclosure on the bottom. So maybe to ask about the charging: there's an external charging device?

嗯，是的，有一个外部充电设备。所以植入物的第二部分：线程，同样，只有最后 3 到 5 毫米是实际穿透皮层的部分。其余部分，大部分体积被电池占据，一块可充电电池。它大约有 25 美分硬币那么大。我这里实际上有一个设备，如果你想看看的话。这是它的柔性线程部分，然后这是植入物。所以它大约有美国 25 美分硬币那么大，约 9 毫米厚。基本上，这个植入物，在你进行颅骨切除术和硬脑膜切开术后，线程被插入，你创建的孔，这个颅骨切除术的孔，就被它替换了。所以基本上这个东西堵住了那个孔，你可以用这些自钻颅骨螺钉将其固定。最后，一旦皮肤瓣覆盖上去，只有大约 2 到 3 毫米明显地从植入物顶部过渡到螺钉所在的位置，这就是你有的那个小凸起。

Mhm, yeah, there's an external charging device. So the second part of the implant: the threads are the ones, again, just the last 3 to 5 millimeters are the ones that are actually penetrating the cortex. The rest of it, most of the volume is occupied by the battery, a rechargeable battery. And it's about the size of a quarter. I actually have a device here if you want to take a look at it. This is the flexible thread component of it, and then this is the implant. So it's about the size of a US quarter, about 9 mm thick. So basically, this implant, once you have the craniectomy and the durotomy, threads are inserted, and the hole that you created, this craniectomy, gets replaced with that. So basically that thing plugs that hole, and you can screw in these self-drilling cranial screws to hold it in place. And at the end of the day, once you have the skin flap over, there's only about 2 to 3 mm that's obviously transitioning off of the top of the implant to where the screws are, and that's the minor bump that you have.

那些线程看起来很小。太不可思议了。真的不可思议。而且，正如你所说，大部分体积，实际体积，是电池。哇，这比我意识到的要小得多。线程本身也相当坚固。它们看起来很坚固。而且线程本身在末端有一个非常有趣的特征，叫做环，这是机器人能够连接和操作这个微小毛发状结构的机制。它们很小。那么线程的宽度是多少？

Those threads look tiny. That's incredible. That is really incredible. And also, as you're right, most of the volume, actual volume, is the battery. Yeah, wow, this is way smaller than I realized. They are also the threads themselves are quite strong. They look strong. And the thread itself also has a very interesting feature at the end of it called the loop, and that's the mechanism by which the robot is able to interface and manipulate this tiny hair-like structure. And they're tiny. So what's the width of a thread?

是的，线程的宽度从 16 微米开始，然后逐渐变细到大约 84 微米。所以，你知道，人类头发的平均宽度大约是 8 到 200 微米。这东西太神奇了。这东西太神奇了。是的，所以大部分体积被电池占据，一块可充电锂离子电池。充电是通过感应充电完成的，这实际上非常常见。你的手机，大多数手机都有这个功能。最大的区别在于，对我们来说，通常当你有手机并想在充电板上充电时，你并不关心它有多热。而对我们来说，这很重要。有非常严格的规定和充分的理由，不能将周围组织温度升高两摄氏度。所以实际上，这里面集成了很多创新，使得植入物可以在不达到那个温度阈值的情况下充电。甚至一些小东西，比如你看到的这个充电线圈和所谓的铁氧体屏蔽。如果没有这个铁氧体屏蔽，当你进行谐振感应充电时，电池本身是一个金属罐，你会从外部充电器形成这些涡流，这会导致发热，并且实际上会降低充电效率。所以这个铁氧体屏蔽的作用是……

Yeah, so the width of a thread starts from 16 microns and then tapers out to about 84 microns. So you know, average human hair is about 8 to 200 microns in width. This thing is amazing. This thing is amazing. Yeah, so most of the volume is occupied by the battery, a rechargeable lithium-ion cell. And the charging is done through inductive charging, which is actually very commonly used. Your cell phone, most cell phones have that. The biggest difference is that for us, usually when you have a phone and you want to charge it on a charging pad, you don't really care how hot it gets. Whereas for us, it matters. There's a very strict regulation and good reasons to not actually increase the surrounding tissue temperature by two degrees Celsius. So there's actually a lot of innovation that is packed into this to allow charging of this implant without causing that temperature threshold to be reached. And even small things like you see this charging coil and what's called the ferrite shield. So without that ferrite shield, what you end up having when you have resonant inductive charging is that the battery itself is a metallic can and you form these eddy currents from the external charger, and that causes heating, and that actually contributes to inefficiency in charging. So this ferrite shield, what it does is...

那么我们来谈谈这些线程本身，那些非常非常小的东西。有多少根？你提到了一千个电极。有多少根线程，电极和线程有什么关系？

So let's talk about the threads themselves, those tiny tiny tiny things. So how many of them are there? You mentioned a thousand electrodes. How many threads are there and what do the electrodes have to do with the threads?

目前版本的设备有 64 根线程，每根线程有 16 个电极，总共 1,024 个电极，既能记录也能刺激。线程本质上是一种聚合物绝缘导线。金属导体有点像铂、金、铂的提拉米苏蛋糕。它们是非常非常细的导线，宽度 16 微米，也就是两百万分之一米。我眼前这个东西居然有聚合物绝缘层、导电材料，每根线程末端还有 16 个电极，这太疯狂了。

So the current instantiation of the device has 64 threads and each thread has 16 electrodes for a total of 1,024 electrodes that are capable of both recording and stimulating. And the thread is basically this polymer insulated wire. The metal conductor is kind of a tiramisu cake of platinum, gold, platinum. And they're very very tiny wires, 16 microns in width, so two one-millionths of a meter. It's crazy that that thing I'm looking at has the polymer insulation, has the conducting material, and has 16 electrodes at the end of it on each of those threads.

每根线程上，对吧？每根 16 个。你用肉眼是看不到的。我是说，说得直白一点，或者对正在听的听众来说，它们很柔软，对吧？

On each of those threads, correct? 16 each. One of those you're not going to be able to see with naked eyes. And I mean, to state the obvious or maybe for people who are just listening, they're flexible, yes?

是的，这也是对我们来说极其重要的一个因素。所以每根线程，正如我提到的，宽度 16 微米，然后逐渐变细到 8 微米，但厚度不到 5 微米。厚度上主要是底部的聚酰亚胺、金属轨道，然后另一层聚酰亚胺，所以是 2 微米聚酰亚胺、400 纳米金属叠层、2 微米聚酰亚胺夹在一起，保护它免受 37°C 盐水环境的影响。

Yes, that's also one element that was incredibly important for us. So each of these threads, as I mentioned, is 16 microns in width and then they taper to 8 microns, but in thickness they're less than 5 microns. And in thickness it's mostly a polyimide at the bottom and this metal track and then another polyimide, so 2 microns of polyimide, 400 nanometers of this metal stack, and 2 microns of polyimide sandwich together to protect it from the environment that is a 37°C bag of salt water.

这里的材料设计有哪些有趣的方面？比如设计和制造这样的东西需要什么？给对此一无所知的人讲讲。

What's some interesting aspects of the material design here? Like what does it take to design a thing like this and to be able to manufacture it? For people who don't know anything about this kind of thing.

我们的材料选择并不是特别独特。其他实验室也在研究类似的材料叠层。有一个基本问题仍然需要回答：这些微电极与一些更传统的、穿透皮层的刚性颅内神经接口设备相比，其寿命和可靠性如何。比如犹他阵列，就是那种 4x4 毫米的硅基插针，末端有暴露的记录位点。那是 Richard Norman 在 1997 年的创新。它叫犹他阵列，因为他当时在犹他大学。

The material selection that we have is not particularly unique. There were other labs and there are other labs that are kind of looking at similar material stacks. There's kind of a fundamental question that still needs to be answered around the longevity and reliability of these micro electrodes compared to some of the other more conventional neural interface devices that are intracranial, so penetrating the cortex, that are more rigid. Like the Utah Array, which are these 4x4 millimeter kind of silicon shanks that have exposed recording sites at the end. That's been the innovation from Richard Norman back in 1997. It's called the Utah Array because he was at the University of Utah.

犹他阵列长什么样？

What does the Utah Array look like?

它是一床针。插针的尺寸和数量从 64 到 128 不等。最尖端是一个暴露的电极，实际上记录神经信号。另一个有趣的注意点是，与 Neuralink 的线程不同，Neuralink 的线程沿深度有暴露的氧化铱记录位点，而这里只有一个深度。这些犹他阵列的辐条长度在 0.5 毫米到 1.5 毫米之间，也有倾斜设计，可以插入不同深度。但这是另一个主要区别。然后最关键的区别是，没有有源电子器件。这些只是电极，然后有一束导线从颅骨切开处引出，有一个端口可以连接外部电子设备。他们正在开发无线遥测设备，但仍然需要一个穿皮端口，这是系统感染的最大故障模式之一。

It's a bed of needles. The size and the number of shanks vary anywhere from 64 to 128. At the very tip of it is an exposed electrode that actually records neural signal. The other thing that's interesting to note is that unlike Neuralink threads that have recording electrodes that are exposed iridium oxide recording sites along the depth, this is only at a single depth. These Utah Array spokes can be anywhere between 0.5 mm to 1.5 mm, and they also have designs that are slanted so you can have it inserted at different depths. But that's one of the other big differences. And then the main key difference is the fact that there's no active electronics. These are just electrodes, and then there's a bundle of wires that exits the craniectomy, that then has this port that you can connect to for any external electronic devices. They are working on a wireless telemetry device, but it still requires a through-the-skin port that is one of the biggest failure modes for infection for the system.

柔性线程带来哪些挑战？比如在机器人 R1 一侧，植入这些线程有多难？

What are some of the challenges associated with flexible threads, like for example on the robotic side, R1, implanting those threads? How difficult is that?

正如你提到的，它们非常非常难以手动操作。你之前看到的那些犹他阵列实际上是由神经外科医生将其定位到目标部位附近，然后用气动锤将其推入。所以过程相当简单，也更容易操作。但对于这些薄膜阵列，它们非常微小且柔软，因此很难操作。这就是为什么我们建造了一整台机器人来做这件事。我们建造机器人还有其他原因，最终我们希望这能帮助数百万计的人受益，而神经外科医生并没有那么多。机器人有望完成手术的大部分工作。机器人是我们正在开发的另一类产品。它本质上是一个多轴龙门系统，带有专门的机器人头部，集成了所有光学器件和一种针式回缩机制，通过线程上的环状结构来操控这些线程。

As you mentioned, they're very very difficult to maneuver by hand. These Utah Arrays that you saw earlier are actually inserted by a neurosurgeon positioning it near the site and then there's a pneumatic hammer that actually pushes them in. So it's a pretty simple process and they're easier to maneuver. But for these thin film arrays, they're very very tiny and flexible, so they're very difficult to maneuver. That's why we built an entire robot to do that. There are other reasons for why we built a robot, and that is ultimately we want this to help millions and millions of people that can benefit from this, and there just aren't that many neurosurgeons out there. Robots can be something that we hope can actually do large parts of the surgery. The robot is this entire other category of product that we're working on. It's essentially this multi-axis gantry system that has the specialized robot head that has all of the optics and this kind of needle retracting mechanism that maneuvers these threads via this loop structure that you have on the thread.

所以线程上已经有一个环状结构可以用来抓取它，对吧？

So the thread already has a loop structure by which you can grab it, correct?

对。

Correct.

这太迷人了。你提到了光学器件，所以有机器人 R1。目前是由人在头骨上开一个洞，然后有一个计算机视觉组件来寻找避开血管的路径，然后你通过环状结构抓住每根线程，将其放置在特定位置以避开血管，同时选择放置深度，控制放置的所有 3D 几何参数。

So this is fascinating. So you mentioned optics, so there's a robot R1. For now there's a human that actually creates a hole in the skull, and then after that there's a computer vision component that's finding a way to avoid the blood vessels, and then you're grabbing it by the loop, each individual thread, and placing it in a particular location to avoid the blood vessels and also choosing the depth of placement, all that controlling every 3D geometry of the placement.

对。这个机器人独特之处在于它不是外科医生辅助或人工辅助的。它是一个半自动或全自动机器人。当然，在放置目标时有人类参与，你可以随时将其移开你看到的主要血管。

Correct. The aspect of this robot that is unique is that it's not surgeon-assisted or human-assisted. It's a semi-automatic or automatic robot. Once you, obviously there are human components to it when you're placing targets, you can always move it away from major vessels that you see.

但我们希望达到这样的状态：一键点击，几分钟内就能完成手术。计算机视觉组件找到很好的目标候选，然后由人类来批准。机器人是逐个操作，还是逐线操作？

But I mean we want to get to a point where one click and it just does the surgery within minutes. So the computer vision component finds great target candidates, and the human kind of approves them. And the robot does it—does it do like one at a time, or does it do one thread at a time?

嗯，这其实也是我们正在研究的一个方向：如何同时处理多根线程。这没什么阻碍——你可以有多种接入机制。但目前还是逐个进行。而且我们仍然要做不少验证，以确保它确实插入了，插入了多深，是否与编程设定一致，等等。实际的电极会植入大脑的不同深度——我的意思是，差异非常小，但确实存在差异。

Uh, and that's actually also one thing that we are looking at: ways to do multiple threads at a time. There's nothing stopping from it—you can have multiple kind of engagement mechanisms. But right now it's one by one. And we also still do quite a bit of verification to make sure that it got inserted, if so how deep, you know, did it actually match what was programmed in, and so on and so forth. And the actual electrodes are placed at varying depths in the brain—I mean, it's very small differences, but differences.

对，对。所以这背后是有道理的，就像你提到的，这样能获得更多样的信号。

Yeah, yeah. And so there's some reasoning behind that, as you mentioned, like it gets more varied signal.

是的，我们尽量把它们都放置在距表面 3 到 4 毫米的位置，因为电极的跨度——我们目前这个版本中的 16 个电极——大约覆盖 3 毫米。所以我们希望所有这些电极都能植入大脑。

Yeah, we try to place them all around 3 or 4 millimeters from the surface, just because the span of the electrode—those 16 electrodes that we currently have in this version—spans roughly around 3 mm. So we want to get all of those in the brain.

这太迷人了。好，这里有一大堆问题。如果我们放大到具体的电极，你觉得每个电极能监听到多少个神经元？

This is fascinating. Okay, so there's a million questions here. If we go zoom in specific on the electrode, what is your sense how many neurons is each individual electrode listening to?

嗯，每个电极可以记录 0 到 40 个神经元，就像我之前提到的。但实际中，我们最多只能看到两到三个。而且你可以通过尖峰信号的形状来区分它来自哪个神经元。哦，酷。所以我提到我们使用的检测算法——叫做 BOSS 算法，即 Buffer Online Spike Sorter。它最终会输出六个唯一值，分别是负向波峰、中间波峰、正向波峰的幅度，以及这些波峰发生的时间。由此你可以进行统计概率估计：这是不是尖峰信号？然后基于此，你还可以判断，哦，这个尖峰和那个尖峰看起来不同，一定来自不同的神经元。好的，这是一个很好的信号处理步骤，你可以据此对是否存在尖峰做出更好的预测，尤其是在多个神经元同时放电的情况下。而且这还能让你更好地压缩数据。

Yeah, each electrode can record from anywhere between zero to 40, as I mentioned right earlier. But practically speaking, we only see about at most like two to three. And you can actually distinguish which neuron it's coming from by the shape of the spikes. Oh, cool. So I mentioned the detection algorithm that we have—it's called BOSS algorithm, Buffer Online Spike Sorter. It actually outputs at the end of the day six unique values, which are the amplitude of these like negative going hump, middle hump, positive going hump, and also the time at which these happen. And from that you can have a statistical probability estimate of: is that a spike, is it not a spike? And then based on that, you could also determine, oh, that spike looks different than that spike, must come from a different neuron. Okay, so that's a nice signal processing step from which you can then make much better predictions about if there's a spike, especially in this kind of context where there could be multiple neurons screaming. And that also results in you being able to compress the data better.

是的，当然。需要明确的是，实验室里通常做的是尖峰分类，一旦你有了这些宽带信号，也就是完全数字化的信号，然后运行一系列不同的算法来区分。而对我们来说，这一切都在设备上完成，在一个非常低功耗的定制 ASIC 数字处理单元上。高度受热约束。从信号输入到输出结果的处理时间不到一微秒，这是非常非常短的时间。

Yeah, of course. And just to be clear, I mean the labs do this called spike sorting, usually once you have these broadband, like the fully digitized signals, and then you run a bunch of different set of algorithms to kind of tease apart. It's just all of this for us is done on the device, on the device, in a very low power custom built ASIC digital processing unit. Highly heat constrained. And the processing time from signal going in and giving you the output is less than a microsecond, which is a very, very short amount of time.

哦对，所以延迟必须非常短，没错。哦哇，那真是够麻烦的。

Oh yeah, so the latency has to be super short, correct. Oh wow, oh that's a pain in the ass.

是的，延迟是你必须应对的一个巨大问题。目前最大的延迟来源是蓝牙，以及它们的数据包化方式。我们将其限制在 15 毫秒的通信间隔内。

Yeah, latency is a huge, huge thing that you have to deal with. Right now the biggest source of latency comes from the Bluetooth, the way in which they're packetized. And we bend them in 15 millisecond inter-communication constraint.

在使用的协议上有没有潜在的创新？

Is there some potential innovation there on the protocol used?

当然。好的，是的。蓝牙绝对不是我们最终想要的无线通信协议。它很高——因此有了 N1 和 R1，我想这增加了 NX RX。是的，这就是通信协议。因为蓝牙允许你通信的距离比你需要的更远，所以你可以缩短很多。选择蓝牙的唯一——嗯，主要动机是，所有设备都有蓝牙。好吧，所以你可以与任何设备通信。互操作性绝对是至关重要的，尤其是在这个早期阶段。在很多方面，如果你能访问手机或电脑，你就能做任何事情。

Absolutely. Okay, yeah. Bluetooth is definitely not our final wireless communication protocol that we want to get to. It's a high—hence the N1 and the R1, I imagine that increases NX RX. Yeah, that's the communication protocol. Because Bluetooth allows you to communicate over farther distances than you need to, so you can go much shorter. The only—well, the primary motivation for choosing Bluetooth is that everything has Bluetooth. All right, so you can talk to any device. Interoperability is just absolutely essential, especially in this early phase. And in many ways, if you can access a phone or a computer, you can do anything.

退一步，重新看看你提到的 Nolan 的整个流程会很有趣。那么，从寻找和选择一个人，到手术，再到他第一次能够使用这个东西，整个过程是怎样的？

It'd be interesting to step back and actually look at again the same pipeline that you mentioned for Nolan. So what is this whole process look like from finding and selecting a human being, to the surgery, to the first time he's able to use this thing?

我们有一个所谓的患者登记系统，人们可以注册，以了解更多更新信息。Nolan 就是通过这个途径申请的。流程是，一旦申请提交，里面包含一些医疗记录，我们会根据他们的医疗资格——有很多不同的纳入和排除标准需要满足——然后与 Neuralink 的人进行预筛选面试。在某个时候，我们还会去他们家中进行 BCI 家庭审计。因为拥有这个完全无线的 N1 系统最革命性的部分之一就是你可以在家中使用它。你实际上不需要去实验室，去诊所连接那些你无法带回家的专用设备。所以这是我们在设计系统时想要牢记的关键要素之一：人们希望能够在舒适的家中每天使用它。因此，我们在 BCI 家庭审计中的一部分工作就是了解他们的情况，他们使用哪些其他辅助技术。我们还应该退一步说，据估计，美国有 18 万人患有四肢瘫痪，每年还有 1.8 万人遭受导致瘫痪的脊髓损伤。所以这些人生活中有很多挑战，在可及性方面，在做我们许多人日常认为理所当然的事情方面。这项初步研究的目标之一是让他们拥有某种数字自主权，让他们自己能够仅用大脑与数字设备交互——你称之为心灵感应。所以数字心灵感应，让四肢瘫痪者能够以我们一直在谈论的所有方式与数字设备通信：控制鼠标光标，足以做各种事情，包括玩游戏、发推文等等。有很多人因为发生在他们身上的事情，生活的基本方面都很困难。所以，是的，我的意思是，运动对我们的存在至关重要。甚至说话也涉及嘴巴、嘴唇、喉部的运动，没有这些，生活会极度困难。他们——是的，他们——

So we have what's called a patient registry that people can sign up to, to hear more about the updates. And that was the route to which Nolan applied. The process is that once the application comes in, it contains some medical records, and we, based on their medical eligibility—there's a lot of different inclusion and exclusion criteria for them to meet—and we go through a pre-screening interview process with someone from Neuralink. And at some point, we also go out to their homes to do a BCI home audit. Because one of the most kind of revolutionary parts about having this N1 system that is completely wireless is that you can use it at home. You don't actually have to go to the lab, and you know, go to the clinic to get connectorized to these specialized equipment that you can't take home with you. So that's one of the key elements that we wanted to keep in mind when designing the system: people hopefully would want to be able to use it every day in the comfort of their homes. And so part of our engagement and what we're looking for during the BCI home audit is to just kind of understand their situation, what other assisted technology they use. And we should also step back and kind of say that the estimate is 180,000 people live with quadriplegia in the United States, and each year an additional 18,000 suffer a paralyzing spinal cord injury. So these are folks who have a lot of challenges living life in terms of accessibility, in terms of doing the things that many of us just take for granted day to day. And one of the goals of this initial study is to enable them to have sort of digital autonomy, where they by themselves can interact with a digital device using just their mind—something that you're calling telepathy. So digital telepathy, where a quadriplegic can communicate with a digital device in all the ways that we've been talking about: control the mouse cursor enough to be able to do all kinds of stuff, including play games and tweet and all that kind of stuff. And there's a lot of people for whom the basics of life are difficult because of the things that have happened to them. So yeah, I mean movement is so fundamental to our existence. I mean even speaking involves movement of mouth, lip, larynx, and without that it's extremely debilitating. And they're—yeah, they're—

有很多很多人我们可以帮助。尤其是当你开始关注其他形式的运动障碍，不仅仅是脊髓损伤，还有渐冻症（ALS）、多发性硬化症（MS）甚至中风，或者仅仅是衰老，对吧，这些都会导致你失去部分行动能力和独立性。这极其令人衰弱。而所有这些机会都可以帮助人们，减轻痛苦，提高生活质量。但你提到的每一件事都是它自己的小难题。然后你从 Neuralink 这样的设备中获得越来越强的能力。所以你首先关注的是——这个词很美——心灵感应（telepathy）。所以能够用意念无线地与数字设备通信。你能解释一下我们到底在说什么吗？

There are many many people that we can help. I mean especially if you start to look at other forms of movement disorders that are not just from spinal cord injury but from ALS, MS, or even stroke that leads you, or just aging, right, that leads you to lose some of that mobility, that independence. It's extremely debilitating. And all of these are opportunities to help people, to alleviate suffering, to improve the quality of life. But each of the things you mentioned is its own little puzzle. Then you have increasing levels of capability from a device like a Neuralink device. And so the first one you're focusing on is, it's just a beautiful word, telepathy. So being able to communicate using your mind wirelessly with a digital device. Can you just explain exactly what we're talking about?

是的，就是这样。我认为如果你能控制光标并点击，能够访问电脑或手机，整个世界就向你敞开了。我想“心灵感应”这个词，如果你从定义上理解，就是能够在不使用我们某些身体机能（比如声音）的情况下，将信息从我的大脑传递到你的大脑。但有趣的是，我认为不太清楚的是它到底是如何工作的。为了移动光标，至少有几种方法。一种是想象自己用手移动鼠标。或者像 Nolan 说的那样，想象用意念移动光标。但这里有一个认知步骤非常迷人，因为你必须使用大脑，并且必须学会如何使用大脑，而且你得动态地摸索出来，因为如果成功了你会奖励自己。所以这个步骤非常迷人，因为你必须让大脑以正确的方式开始放电。你通过想象来做到这一点，假装直到成功，突然之间它产生了正确的信号，如果解码正确，就能产生效果。然后周围还有噪声，你必须解决所有这些问题。但在人类这边，想象光标移动就是你要做的。他说就像使用原力。你不觉得这很神奇吗？对我来说，这简直太神奇了，居然真的有效。你可以用意念移动光标。在你学习使用那个东西的同时，那个东西也在学习你。我们的模型不断更新权重，说，哦，如果某人在想这些复杂的放电模式，那实际上意味着要做这个。所以机器在学习人类，人类也在学习机器。所以信号处理和解码步骤有适应性，然后还有人类的适应，就像你给我一个新鼠标，我移动它，很快就能学会它的灵敏度，所以我学会移动得更慢。然后还有其他类型的信号漂移之类的东西，它们必须适应。所以两者都在相互适应。这是一个迷人的软件挑战，双方都是，人类这边的软件，有机的和无机的。总之，抱歉打断了一下。

Yeah, it's exactly that. I think if you are able to control a cursor and able to click, and be able to get access to a computer or phone, the whole world opens up to you. And I guess the word telepathy, if you think about that as definitionally being able to transfer information from my brain to your brain without using some of the physical faculties that we have, like voices. But the interesting thing here is, I think the thing that's not obviously clear is how exactly it works. So in order to move a cursor, there are at least a couple ways of doing that. So one is you imagine yourself maybe moving a mouse with your hand. Or you can, which Nolan talked about, imagine moving the cursor with your mind. But there is a cognitive step here that's fascinating, because you have to use the brain and you have to learn how to use the brain, and you kind of have to figure it out dynamically, because you reward yourself if it works. So there's a step that is just fascinating, because you have to get the brain to start firing in the right way. And you do that by imagining, fake it till you make it, and all of a sudden it creates the right kind of signal that, if decoded correctly, can create the kind of effect. And then there's noise around that you have to figure all of that out. But on the human side, imagining the cursor moving is what you have to do. He says using the force. I mean, isn't that just fascinating to you that it works? To me it's like, holy, that actually works. You could move a cursor with your mind. As much as you're learning to use that thing, that thing's also learning about you. Our model is constantly updating the weights to say, oh, if someone is thinking about these sophisticated forms of spiking patterns, that actually means to do this right. So the machine is learning about the human and the human is learning about the machine. So there's adaptability in the signal processing, the decoding step, and then there's the adaptation of the human being, like the same way if you give me a new mouse and I move it, I learn very quickly about its sensitivity, so I learned to move it slower. And then there's other kind of signal drift and all that kind of stuff they have to adapt to. So both are adapting to each other. That's a fascinating software challenge on both sides, the software on the human side, organic and inorganic. Anyway, so sorry to rudely interrupt.

所以 Nolan 已经以优异的成绩通过了筛选。包括一切，比如这是一个对脑机接口友好的家庭，等等。那么手术、植入、他第一次使用系统的过程是怎样的，从头到尾？

So there's a selection that Nolan has passed with flying colors. So everything including that it's a BCI-friendly home, all of that. So what is the process of the surgery, the implantation, the first moment when he gets to use the system, the end-to-end?

我们说从患者进来到出去，时间在 2 到 4 小时之间。在 Nolan 的特定案例中，大约是 3 个半小时。有很多步骤直到实际的机器人插入。首先是麻醉诱导，我们做术中 CT 成像以确保我们在正确的位置钻孔，这也是事先计划好的。像 Nolan 这样的人会先做 fMRI，然后他们可以想象扭动手指。显然由于他们的损伤，这不会导致任何实际输出，但当你想象移动手指与实际移动手指时，大脑的同一部分会亮起。这就是我们能够知道将电极线放在哪里的方法之一，因为我们想进入运动皮层中所谓的“手部旋钮区”，并尽可能密集地放置电极线。所以我们做术中 CT 成像来确认和复核颅骨切开术的位置。然后外科医生进来，做他们的工作，包括皮肤切口、颅骨切开术，即钻开颅骨。然后大脑有很多不同的层。有一层叫做硬脑膜，是包裹大脑的非常厚的层，在硬脑膜切开术中被实际移除，然后暴露出软脑膜和你要插入的大脑。大约 1 到 1.5 小时后，机器人进来，做它的工作，放置目标，插入电极线。这需要 20 到 40 分钟。在 Nolan 的案例中，刚好不到或刚过 30 分钟。然后之后，外科医生进来，还有几个其他步骤，比如实际插入硬脑膜替代层来保护电极线和大脑，然后拧入植入物，然后皮瓣，然后缝合，然后你就出来了。

We say patient in to patient out is anywhere between 2 to 4 hours. In the particular case for Nolan, it was about 3 and a half hours. And there are many steps leading to the actual robot insertion. So there's anesthesia induction, and we do intraoperative CT imaging to make sure that we are drilling the hole in the right location, and this is also pre-planned beforehand. Someone like Nolan would go through fMRI, and then they can think about wiggling their hand. Obviously due to their injury, it's not going to actually lead to any intended output, but it's the same part of the brain that lights up when you're imagining moving your finger to actually moving your finger. And that's one of the ways in which we can actually know where to place our threads, because we want to go into what's called the hand knob area in the motor cortex, and as much as possible densely put our electrode threads. So we do intraoperative CT imaging to make sure and double-check the location of the craniectomy. And the surgeon comes in, does their thing in terms of skin incision, craniectomy, so drilling of the skull. And then there are many different layers of the brain. There's what's called the dura, which is a very thick layer that surrounds the brain, that gets actually removed in a process called durotomy, and that then exposes the pia and the brain that you want to insert. And by the time it's been around anywhere between 1 to 1 and a half hours, the robot comes in, does its thing, placement of the targets, inserting of the thread. That takes anywhere between 20 to 40 minutes. In the particular case for Nolan, it was just under or just over 30 minutes. And then after that, the surgeon comes in, there are a couple other steps like actually inserting the dural substitute layer to protect the thread as well as the brain, and then screw in the implant, and then skin flap, and then suture, and then you're out.

那么 Nolan 醒来时是什么感觉？恢复过程是怎样的，他第一次能够使用它是什么时候？

So when Nolan woke up, what was that like? What was the recovery like, and when was the first time he was able to use it?

实际上，手术后立即，大约手术后一小时他醒来时，我们就打开了设备，确保我们正在记录神经信号。我们确实注意到有几个信号他可以实际调节。我所说的调节是指他可以想象握紧拳头，然后你可以看到尖峰信号消失和出现。这太棒了。而且那是即时的，就在恢复室里。这有多酷？那是一个人类。我的意思是，这对你来说感觉如何？这个设备和一个人，一个巨大旅程的第一步。这是一个历史性的时刻。即使只是那个尖峰信号，能够调节它。显然还有其他先驱者参与过这些开创性的脑机接口研究性早期可行性研究。所以我们显然是站在巨人的肩膀上。我们不是第一个实际植入……

He was actually immediately after the surgery, like an hour after the surgery as he was waking up, we did turn on the device, make sure that we are recording neural signals. And we actually did have a couple signals that we noticed that he can actually modulate. And what I mean by modulate is that he can think about crunching his fist, and you could see the spike disappear and appear. That's awesome. And that was immediate, right after in the recovery room. How cool is that? That's a human being. I mean, what does that feel like for you? This device and a human being, a first step of a gigantic journey. It's a historic moment. Even just that spike, just to be able to modulate that. Obviously there have been other pioneers that have participated in these groundbreaking BCI investigational early feasibility studies. So we're obviously standing on the shoulders of giants here. We're not the first ones to actually put...

在人脑中植入电极。但我的意思是，就在手术前，我……我绝对没睡好。这是你第一次在一个全新的环境中工作。基于我们的台架测试或临床前研发研究，我们对机制、线程、植入等所有环节都非常有信心，认为它们非常安全，显然已经准备好用于人体。但仍然有很多未知数：针头真的能插入吗？我们带了大约 40 根针以防断裂，最后只用了一根。但那完全是未知的，对吧？因为这是一个非常非常不同的环境。这就是我们首先进行临床试验的原因，以便能够测试这些东西。所以极度紧张，手术前很多个不眠之夜，尤其是手术前一天。手术是在清晨进行的；我们早上 7 点开始，到 10:30 左右，一切都完成了。但第一次看到……嗯，第一，如释重负，这东西按预期工作了。第二，对 Nolan 和他的家人，以及许多其他申请者、我们交谈过和将要交谈的人，充满无限感激。他们是真正的先驱，在各个意义上。我称他们为神经宇航员。你知道，就像 60 年代那些了不起的先驱，向外探索未知；而这次是向内。但对他们参与其中并发挥作用，我感激不尽。这是我们共同踏上的旅程。但我也认为这是一个非常重要的里程碑，但我们的工作才刚刚开始。所以有很多期待：接下来需要做什么？需要发生什么样的一系列事件，才能让我们对 Nolan 和我们自己都值得？

Electrode in a human brain. But I mean, just leading up to the surgery, there was... I definitely did not sleep. It's the first time that you're working in a completely new environment. We had a lot of confidence based on our benchtop testing or pre-clinical R&D studies that the mechanism, the threads, the insertion, all that stuff is very safe and that it's obviously ready for doing this in a human. But there's still a lot of unknown: can the needle actually insert? I mean, we brought something like 40 needles just in case they break, and we ended up using only one. But that was a level of complete unknown, right? Because it's a very, very different environment. And that's why we do clinical trials in the first place, to be able to test these things out. So extreme nervousness and just many, many sleepless nights leading up to the surgery, and definitely the day before the surgery. It was an early morning surgery; we started at 7:00 in the morning, and by the time it was around 10:30, everything was done. But first time seeing that... well, number one, just huge relief that this thing is doing what it's supposed to do. And two, just immense amount of gratitude for Nolan and his family, and many others that have applied and that we've spoken to and will speak to. They are true pioneers in every way. I sort of call them the neural astronauts. You know, these amazing pioneers, just like in the 60s, exploring the unknown outwards; in this case, it's inward. But incredible amount of gratitude for them to participate and play a part. It's a journey that we're embarking on together. But also, I think it was a very, very important milestone, but our work was just starting. So a lot of anticipation for: okay, what needs to happen next? What set of sequences of events needs to happen for us to make it worthwhile for both Nolan as well as us?

再回味一下。衷心祝贺你和团队取得这一里程碑。我知道还有很多工作要做，但看到这一切真的很令人兴奋。这是希望的源泉，这第一步是帮助数十万人的机会，未来或许还能为数百万人拓展人类心智的可能性。所以真的很激动。机会就在我们面前，而安全有效地做到这一点，作为一名工程师，看到其他工程师团结起来完成一件史诗般的事情，真的很有趣。太棒了。所以再次祝贺。

Just linger on that. Just a huge congratulations to you and the team for that milestone. I know there's a lot of work left, but that is really exciting to see. It's a source of hope, this first big step, opportunity to help hundreds of thousands of people, and then maybe expand the realm of the possible for the human mind for millions of people in the future. So it's really exciting. The opportunities are all ahead of us, and to do that safely and effectively was really fun to see as an engineer, just watching other engineers come together and do an epic thing. That was awesome. So huge congrats.

谢谢，谢谢。是的，没有团队是不可能做到的。这也是我告诉团队的另一点：对未来充满巨大的乐观。不用说，这对公司来说是一个非常重要的时刻，也希望对我们能够帮助的许多其他人来说也是如此。

Thank you, thank you. It's... yeah, could not have done it without the team. And that's the other thing that I told the team as well: just this immense sense of optimism for the future. It was a very important moment for the company, needless to say, as well as hopefully for many others out there that we can help.

显然，我们最终想要并且正在努力实现的目标，是找到方法尽可能长时间地保持这些线程的完整，这样我们就能有更多的通道进入模型。这是团队目前着手的第一要务，要理解如何防止这种情况发生。

Terms of and obviously the thing that we want ultimately and the thing that we are working towards is figuring out ways in which we can keep those threads intact for as long as possible, so that we have many more channels going into the model. That's by far the number one priority that the team is currently embarking on, to understand how to prevent that from happening.

我还要说的是，正如我提到的，这是我们第一次将这些线程植入人脑。仅就尺寸参考而言，人脑是猴脑或羊脑的 10 倍。这是一个非常非常不同的环境。它移动得更多——实际上，在我们为 Nolan 做手术时，它的移动比我们预期的要多得多。这是一个与我们习惯的环境截然不同的环境。这就是我们进行临床试验的原因，对吧？我们希望尽早发现其中一些问题与失败模式。所以从很多方面来说，这为我们提供了海量的数据和信息来解决这个问题。而这是 Neuralink 极其擅长的事情：一旦我们有了明确的目标和工程问题，我们拥有来自众多学科的庞大人才队伍，能够聚集在一起非常非常快地解决问题。

The thing that I will say also is that, as I mentioned, this is the first time ever that we're putting these threads in a human brain. And the human brain, just for a size reference, is 10 times that of the monkey brain or the sheep brain. It's a very, very different environment. It moves a lot more — it actually moved a lot more than we expected when we did Nolan's surgery. It's a very, very different environment than what we're used to. And this is why we do clinical trials, right? We want to uncover some of these issues and failure modes earlier than later. So in many ways, it's provided us with this enormous amount of data and information to be able to solve this. And this is something that Neuralink is extremely good at: once we have a set of clear objectives and engineering problems, we have enormous amounts of talent across many, many disciplines to come together and fix the problem very, very quickly.

但听起来这里一个迷人的挑战是系统和解码端需要能够跨不同时间尺度适应。所以无论是线程的移动还是信号漂移的不同方面，在人脑的软件层面发生变化时——比如 Nolan 提到的光标漂移——它们都可以被纠正。而如何做到这一点是一个完整的用户体验挑战。所以听起来适应性是一个必须被设计进去的基本属性。

But it sounds like one of the fascinating challenges here is for the system and the decoding side to be adaptable across different time scales. So whether it's movement of threads or different aspects of signal drift, sort of on the software of the human brain something changing — like Nolan talks about cursor drift — they could be corrected. And there's a whole UX challenge to how to do that. So it sounds like adaptability is a fundamental property that has to be engineered in.

是的。而且我认为作为一家公司，我们极其垂直整合。我们在自己的微加工厂里制造这些薄膜阵列。全部自研。这篇博文里的这一段相当厉害：“构建上述技术绝非易事。”这里有一堆链接，我建议大家点进去。“我们建立了内部微加工能力，以快速生产构成我们电极线程的各种迭代薄膜阵列。我们创建了定制的飞秒激光铣床，以微米级精度制造您的组件。”我想有一条相关的推文，我们可以深入聊聊。

It is. And I think as a company we're extremely vertically integrated. We make these thin film arrays in our own microfab. Built in-house. This whole paragraph from this blog post is pretty gangster: "Building the technologies described above has been no small feat." There's a bunch of links here that I recommend people click on. "We constructed in-house microfabrication capabilities to rapidly produce various iterations of thin film arrays that constitute our electrode threads. We created a custom femtosecond laser mill to manufacture your components with micron-level precision." I think there's a tweet associated with this that's a whole thing we can get into.

我们在这里看到的是什么？

What are we looking at here?

在不到一分钟的时间里，我们定制的飞秒激光铣床在针尖上切割出这种几何形状。所以我们看到的是这个形状奇特的针。针尖宽度只有 10 到 12 微米，仅比红细胞的直径稍大一点。这种小尺寸使得线程能够以最小的皮层损伤被植入。

This is, in less than one minute, our custom-made femtosecond laser mill cuts this geometry in the tips of our needles. So we're looking at this weirdly shaped needle. The tip is only 10 to 12 microns in width, only slightly larger than the diameter of a red blood cell. The small size allows threads to be inserted with minimal damage to the cortex.

那么这种几何形状有什么有趣之处？

So what's interesting about this geometry?

我们看到的是针的几何形状。这是与线程中的环接合的针。它们负责穿环，然后将其从硅衬底上剥离。然后这个东西被插入组织，然后它拔出，留下线程。而这个凹口，或者我们以前称之为鲨鱼齿，实际上是抓住环的东西。它的设计方式使得当你拔出时，它会留下环。而机器人控制着这根针，对吧？

So we're looking at the geometry of a needle. This is the needle that's engaging with the loops in the thread. They're the ones that thread the loop and then peel it from the silicon backing. And then this is the thing that gets inserted into the tissue, and then this pulls out, leaving the thread. And this kind of notch, or the shark tooth as we used to call it, is the thing that actually grasps the loop. It's designed in such a way that when you pull out, it leaves the loop. And the robot is controlling this needle, correct?

这实际上装在一个套管里。基本上，机器人有很多光学器件来寻找环的位置。实际上有一种 405 纳米的光会使聚合物发出荧光，这样你就能定位环的位置。会发光，是的。

This is actually housed in a cannula. Basically, the robot has a lot of optics that look for where the loop is. There's actually a 405 nanometer light that causes the polymer to fluoresce, so that you can locate the location of the loop. Lights up, yeah.

这是一个微米级的精密过程。要做到这一点，机器人有什么特别之处？机器人能达到这种精度，真是太疯狂了。

It's a micron precision process. What's interesting about the robot that it takes to do that? That's pretty crazy that a robot is able to get this kind of precision.

我们的机器人相当重。当前版本——有一块重约一吨的巨大花岗岩板，因为它需要对振动、环境振动敏感。而且当头部以它的速度移动时，需要大量的运动控制来确保能达到那种精度。很多光学器件会放大观察。我们正在研发下一代机器人，更轻、更容易运输。移动机器人本身就是一项壮举。目前在这个特定任务上，它远远优于人类外科医生。绝对如此。更不用说你自己试着在缝纫套件里穿一个环了。这就像人类头发丝的几分之一。这些东西是看不见的。

Our robot is quite heavy. Our current version of it — there's a giant granite slab that weighs about a ton, because it needs to be sensitive to vibration, environmental vibration. And as the head is moving at the speed that it's moving, there's a lot of motion control to make sure you can achieve that level of precision. A lot of optics that zoom in on that. We're working on the next generation of the robot that is lighter, easier to transport. It is a feat to move the robot. And it's far superior to a human surgeon at this time for this particular task. Absolutely. Let alone you try to actually thread a loop in a sewing kit. This is like fractions of human hair. These things are not visible.

继续这一段：“我们开发了新颖的硬件和软件测试系统，比如我们的加速寿命测试架和模拟手术环境，这很酷，用来压力测试和验证我们技术的稳健性。我们进行了多次手术排练，以完善我们的程序，使其成为第二天性。”这很酷。“我们在代理模型上进行手术练习，使用我们模拟或工程空间中所需的所有硬件仪器。这有助于我们快速测试。”所以有代理模型。

Continuing the paragraph: "We developed novel hardware and software testing systems, such as our accelerated lifetime testing racks and simulated surgery environment, which is pretty cool, to stress test and validate the robustness of our technologies. We performed many rehearsals of our surgeries to refine our procedures and make them second nature." This is pretty cool. "We practice surgeries on proxies with all the hardware instruments needed in our mock or in the engineering space. This helps us rapidly test." So there's like proxies.

这个代理模型实际上非常酷。有一个根据 Barrow 拍摄的图像 3D 打印的头骨，以及一种水凝胶混合物——一种实际上模拟大脑机械特性的合成聚合物。它还有那个人的脉管系统。基本上，制作这个代理模型投入了大量工作。关键在于找到这些不同合成聚合物的正确浓度，以获得针在插入时所需的正确动力学一致性。但在实际手术之前，我们用这个人的——基本上是 Nolan 的生理结构和大脑——练习了很多很多很多次手术。每一步，每一步，每一步。

This proxy is super cool, actually. There's a 3D-printed skull from the images taken at Barrow, as well as a hydrogel mix — a synthetic polymer thing that actually mimics the mechanical properties of the brain. It also has vasculature of the person. Basically, there's a lot of work that has gone into making this proxy. It's about finding the right concentration of these different synthetic polymers to get the right consistency for the needle dynamics as they're being inserted. But we practice this surgery with the person's — Nolan's basically physiology and brain — many, many, many times prior to actually doing the surgery. Every step, every step, every step.

比如每个人站在哪里？我的意思是，看这张照片，这是在我们办公室，机器人工程空间的一个角落，我们创建了这个模拟空间，看起来完全像他们——所有工作人员——在实际手术中会经历的那样。所以就像任何一次彩排，你确切知道在什么时候站在哪里。你只是用你要手术的那个人的精确解剖结构一遍又一遍地练习。到了这样一个地步，当我们做开颅手术时，我们的很多工程师会说：“啊，那看起来很熟悉。我们见过。”

Like where does someone stand? I mean, looking at the picture, this is in our office, in a corner of the robot engineering space, that we've created this mock space that looks exactly like what they would experience — all the staff would experience during their actual surgery. So it's just like any dress rehearsal, where you know exactly where you're going to stand at what point. You just practice that over and over and over again with the exact anatomy of someone you're going to operate on. And it got to a point where a lot of our engineers, when we created a craniectomy, they're like, "Ah, that looks very familiar. We've seen that."

我觉得现在是个好时机来问大家可能关心的一个大问题：你怎么知道你描述的这一切都是安全的？归根结底，金标准是看组织。你知道，你对组织造成了什么样的创伤，以及这是否与你可能观察到的任何行为异常相关。这就是我们用来沟通将某物植入大脑的安全性以及可能造成何种创伤的语言。所以我们实际上有一个完整的部门——病理学部门——来检查这些组织切片。这涉及很多步骤。一旦你启动了针对特定终点的研究，在某个时候你必须对动物实施安乐死，然后进行尸检以收集脑组织样本。你用福尔马林固定它们，进行大体检查，切片，然后观察单个切片，看看存在何种反应或缺乏反应。这就是 FDA 使用的语言，也是我们评估植入机制以及线程在不同时间点（急性期 0 到 3 个月以及 3 个月以上）安全性的方式。所以这些是必须达到的极高安全标准的细节。没错，FDA 监督这一切，但总的来说标准非常高。包括手术在内的每一个方面，我想 Matthew McDougall 提到过，标准比我们习以为常的某些其他手术还要高，说得客气点。所以这里所有手术的标准都极高，非常高。我的意思是，这是一个高度监管的环境，有监管机构审查每一款上市的医疗设备。我认为这是一件好事。拥有这些高标准是好的，我们努力保持极高的标准，以了解我们正在构建的这些创新新兴技术和新技术是否造成了任何损害。到目前为止，我们对这些线程缺乏免疫反应感到非常印象深刻。

I think there's a good place to actually ask sort of the big question that people might have: how do we know every aspect of this that you describe is safe? At the end of the day, the gold standard is to look at the tissue. You know, what sort of trauma did you cause the tissue, and does that correlate to whatever behavioral anomalies that you may have seen? And that's the language to which we can communicate about the safety of inserting something into the brain and what type of trauma that you can cause. So we actually have an entire department, Department of Pathology, that looks at these tissue slices. There are many steps involved in doing this. Once you have studies that are launched with particular endpoints in mind, at some point you have to euthanize the animal, and then you go through necropsy to collect the brain tissue samples. You fix them in formalin, gross them, section them, and look at individual slices just to see what kind of reaction or lack thereof exists. So that's the language to which FDA speaks, as well as for us to evaluate the safety of the insertion mechanism as well as the threads at various different time points, both acute (zero to three months) and beyond three months. So those are the details of an extremely high standard of safety that has to be reached. Correct, FDA supervises this, but there's in general just a very high standard. Every aspect of this, including the surgery, I think Matthew McDougall has mentioned that the standard is, let's say how to put it politely, higher than maybe some other operations that we take for granted. So the standard for all the surgical stuff here is extremely high, very high. I mean, it's a highly regulated environment with governing agencies that scrutinize every medical device that gets marketed. And I think it's a good thing. It's good to have those high standards, and we try to hold extremely high standards to understand what sort of damage, if any, these innovative emerging technologies and new technologies that we're building are causing. And so far, we have been extremely impressed by the lack of immune response from these threads.

说到这个，你曾兴奋地跟我聊起组织学以及你能分享的一些图像。你能给我解释一下我们看到了什么吗？

Speaking of which, you talked to me with excitement about the histology and some of the images that you're able to share. Can you explain to me what we're looking at?

是的，你现在看到的是染色后的组织图像。这是一张来自植入七个月的动物的组织切片，属于慢性时间点。你看到所有这些不同的颜色，每种颜色代表特定的细胞类型。紫色和粉色分别是星形胶质细胞和小胶质细胞；它们是神经胶质细胞的一种。人们可能不知道的另一件事是，你的大脑不仅仅是由神经元和轴突组成的汤；还有其他细胞，比如神经胶质细胞，它们实际上起到胶水的作用，并且在组织受到任何创伤或损伤时也会做出反应。但这里的棕色是神经元。棕色是神经元的细胞核。所以在这张宏观图像中，你看到这些用白色高亮显示的圆圈，即插入点。当你放大其中一个时，你会看到线程。在这个特定案例中，我想我们看到大约 16 根导线穿入页面。这里令人难以置信的是，这些神经元——这些棕色结构或棕色圆形或椭圆形的东西——实际上正在接触并紧贴线程。所以这意味着在插入过程中基本上没有造成创伤。对于这些神经接口，你插入的这些微电极，最常见的失败模式之一是当你插入像犹他阵列这样的线程时，它会导致插入点周围的神经元死亡，因为你插入了一个异物，对吧？这会通过小胶质细胞和星形胶质细胞引发免疫反应；它们会在其周围形成保护层。你不仅杀死了神经元细胞，还创造了这个保护层，然后基本上阻止你记录神经信号，因为你离你想要记录的神经元越来越远。这是最大的失败模式。在这个特定例子中，在那个插图中，比例尺大约是 50 微米，神经元似乎被它吸引，所以肯定没有创伤。

Yeah, so what you're looking at is a stained tissue image. This is a sectioned tissue slice from an animal that was implanted for seven months, so a chronic time point. And you're seeing all these different colors, and each color indicates specific types of cell types. So purple and pink are astrocytes and microglia respectively; they're types of glial cells. And the other thing that people may not be aware of is your brain is not just made up of a soup of neurons and axons; there are other cells like glial cells that actually act as the glue and also react if there is any trauma or damage to the tissue. But the brown are the neurons here. The brown are the neurons' nuclei. So what you're seeing in this macro image is these circles highlighted in white, the insertion site. And when you zoom into one of those, you see the threads. In this particular case, I think we're seeing about 16 wires that are going into the page. And the incredible thing here is the fact that you have the neurons, these brown structures or brown circular or elliptical things, that are actually touching and abutting the threads. So what this is saying is that there is basically zero trauma caused during this insertion. With these neural interfaces, these microelectrodes that you insert, one of the most common modes of failure is when you insert these threads like the Utah array, it causes neuronal death around the site because you're inserting a foreign object, right? And that elicits an immune response through microglia and astrocytes; they form this protective layer around it. Not only are you killing the neuron cells, but you're also creating this protective layer that then basically prevents you from recording neural signals because you're getting further and further away from the neurons that you're trying to record. That is the biggest mode of failure. In this particular example, in that inset, it's about 50 microns with that scale bar, the neurons are just seeming to be attracted to it, and so there's certainly no trauma.

顺便说一句，这张图像太美了。棕色的是神经元，不知为何我无法移开视线。真的很酷。而且这些东西的样子，我的意思是你的组织通常没有这些美丽的颜色。这是多重染色，使用不同的蛋白质将它们染成不同的颜色。

That's such a beautiful image, by the way. Just the brown are the neurons, and for some reason I can't look away. It's really cool. And the way that these things, I mean your tissues generally don't have these beautiful colors. This is a multiplex stain that uses these different proteins that are staining these at different colors.

我们使用一套非常标准的染色技术，包括 H&E、Iba1、NeuN 和 GFAP。所以如果你看下一张图像，这也说明了第二点。因为你可以提出一个论点，最初当我们看到前一张图像时，我们说：“哦，线程是漂浮的吗？这里发生了什么？我们真的在看正确的东西吗？”所以我们做了另一种染色，这都是内部完成的，Masson 三色染色，呈蓝色，显示这些胶原层。所以蓝色基本上意味着你不希望植入线程周围有蓝色，因为那意味着发生了某种疤痕形成。而你所看到的，如果你看单个线程，是你看不到任何蓝色，这意味着在这些植入的线程中，创伤绝对没有，或者非常非常小，以至于检测不到。所以这大概是大好处之一，因为有了这种柔性线程。

We use a very standard set of staining techniques with H&E, Iba1, NeuN, and GFAP. So if you go to the next image, this also illustrates the second point. Because you could make an argument, initially when we saw the previous image, we said, "Oh, are the threads just floating? What is happening here? Are we actually looking at the right thing?" So what we did is we did another stain, and this is all done in-house, of this Masson's trichrome stain, which is in blue, that shows these collagen layers. So the blue basically means you don't want the blue around the implant threads because that means there's some sort of scarring happening. And what you're seeing, if you look at individual threads, is that you don't see any of the blue, which means that there has been absolutely, or very very minimal to a point where it's not detectable, amount of trauma in these inserted threads. So that presumably is one of the big benefits because of having this kind of flexible thread.

R1 避开血管的事实意味着我们不会破坏或损伤血管，也不会破坏血脑屏障，这基本上抑制了免疫反应。但这也很直观地展示了尺寸。这是线程的尖端。那些是神经元吗？电极是如何定位的？

Fact that R1 is avoiding vasculature so we're not disrupting or causing damage to the vessels and not breaking any of the blood-brain barrier has basically caused the immune response to be muted. But this is also a nice illustration of the size of things. So this is the tip of the thread. Those are neurons? And the electrodes are positioned how?

是的，那些是神经元。这是线程。电极的定位是……你看到的不是电极本身，而是导线。每根导线大概只有两微米宽。我们看的是脉络膜切片，也就是组织切片。随着深入，线程的锥度会变小。关键是插入点周围只有细胞，这太不可思议了，我从未见过这样的景象。

Yeah, those are neurons. And this is the thread. The electrodes are positioned... So what you're looking at is not the electrodes themselves, those are the conductive wires. Each of those should probably be two microns in width. So what we're looking at is the choroidal slice, so some slice of the tissue. As you go deeper, you will obviously have less tapering of the thread. But the point basically being that there are just cells around the insertion site, which is an incredible thing to see. I've just never seen anything like this.

移除植入物有多容易、多安全？

How easy and safe is it to remove the implant?

这取决于时间。术后大约前三个月，会有大量组织重塑，类似于皮肤割伤。疤痕组织形成、收缩，最终变成可脱落的痂。大脑也是如此。这是一个非常动态的环境。在疤痕组织或新膜形成之前，很容易直接拔出，创伤极小。一旦疤痕组织形成——对于 Nolan 也是如此——我们认为那就是固定线程的东西。从那以后我们没有看到任何移动，所以它们非常稳定。完全取出线程会变得更难。我们目前移除设备的方法是切断线程，保持组织完整，然后拧下并取出植入物。那个孔会用另一个 Neuralink 或 PEEK 塑料帽堵住。

It depends on when. In the first 3 months or so after the surgery, there's a lot of tissue modeling happening, similar to when you get a cut. Scar tissue forms, contracts, and eventually turns into a scab that can be removed. The same thing happens in the brain. It's a very dynamic environment. Before the scar tissue or neomembrane forms, it's quite easy to just pull them out, and there's minimal trauma. Once the scar tissue forms, with Nolan as well, we believe that's what's currently anchoring the threads. We haven't seen any more movements since then, so they're quite stable. It gets harder to completely extract the threads. Our current method for removing the device is cutting the thread, leaving the tissue intact, then unscrewing and taking the implant out. That hole will be plugged with either another Neuralink or a PEEK-based plastic cap.

把线程永久留在里面没问题吗？

Is it okay to leave the threads in there forever?

是的，我们认为可以。我们做过研究，把线程留在里面。最大的担忧之一是它们是否会迁移到不该去的地方。我们没有发现这种情况。一旦疤痕组织形成，它们就固定住了。我还想说，我们说的升级不是理论。我们实际上已经升级了很多次。我们的大多数非人灵长类动物都升级过。你看到的玩 MindPong 的 Pager，两年前就用上了最新版本，看起来非常快乐、健康、胖乎乎的。

Yeah, we think so. We've done studies where we left them there. One of the biggest concerns was whether they migrate to a point where they shouldn't be. We haven't seen that. Once the scar tissue forms, they get anchored in place. I should also say that when we say upgrades, it's not just theory. We've actually upgraded many times. Most of our non-human primates have been upgraded. Pager, who you saw playing MindPong, has the latest version of the device since two years ago and is seemingly very happy, healthy, and fat.

未来的升级流程是怎样的？比如对于 Nolan，升级会是什么样子？有没有办法在内部升级设备，比如保留外壳，升级内部组件？

What's designed for the future upgrade procedure? Maybe for Nolan, what would the upgrade look like? Is there a way to upgrade the device internally, sort of keep the capsule and upgrade the internals?

有几种不同的方案。对于 Nolan，如果要升级，我们必须切断或取出线程，取决于它们如何固定或疤痕化。如果用硬脑膜替代物取出，大脑是完整的，就可以重新插入不同的线程和升级后的植入包。我们还在考虑其他未来可升级系统的方式。目前我们移除硬脑膜——这层保护大脑的厚膜——但实际上它会促进疤痕组织形成。一般经验法则是尽量保持自然，不要破坏。所以我们正在研究通过硬脑膜插入线程的方法，这带来了挑战，比如如何穿透那层厚膜而不折断针头。我们正在设计不同的针头和环接合方式。另一个挑战是硬脑膜在白光下相当不透明，所以如何避开血管并成像？我们正在研究其他成像技术。基于早期证据的假设是，经硬脑膜插入会最小化疤痕，使日后取出更容易。我们还在考虑植入物架构的根本改变。目前它是一个整体式单植入物，线程是粘合的，无法分离。但可以想象一个两部分植入物：底部是线程、芯片、无线电和电源，另一个植入物承担更多计算负载和更大电池。一个在硬脑膜下，一个在上，像头骨上的插头。它们可以互相通信。如果想升级计算机而不是线程，只需进去，拧下螺丝，放入下一个版本。这将是一个非常容易的手术，比如皮肤切口，滑入，拧紧，大概 10 分钟。

There are a couple of different things. For Nolan, if we were to upgrade, we would have to either cut the threads or extract them, depending on how they're anchored or scarred in. If you remove them with the dural substitute, you have an intact brain, so you can reinsert different threads with the updated implant package. There are other ways we're thinking about for the future of the upgradeable system. One is that currently we remove the dura, this thick layer that protects the brain, but that actually proliferates scar tissue formation. The general rule of thumb is to leave nature as is and not disrupt it. So we're looking at ways to insert the threads through the dura, which comes with challenges like penetrating that thick layer without breaking the needle. We're looking at different needle designs and loop engagement. Another challenge is that the dura is quite opaque optically with white light illumination, so how do we avoid vasculature and image through it? We're looking at other imaging techniques. The hypothesis, based on early evidence, is that through-the-dura insertion will cause minimal scarring, making extraction much easier over time. The other thing we're looking at is a fundamental change in implant architecture. Currently it's a monolithic single implant with a bonded thread, so you can't separate them. But you can imagine a two-part implant: a bottom part with the threads, chips, radio, and power source, and another implant with more computational load and a bigger battery. One can be under the dura, one above, like a plug for the skull. They can talk to each other. If you want to upgrade the computer and not the threads, you just go in, remove the screws, and put in the next version. It would be a very easy surgery, like a skin incision, slip it in, screw it in, probably 10 minutes.

这样就可以重复使用线程，对吗？

That would allow you to reuse the threads, correct?

对。

Correct.

这自然引出了一个问题：扩展的路径是什么？增加线程数量是优先事项吗？技术挑战是什么？

This leads to the natural question of what is the pathway to scaling? Is increasing the number of threads a priority? What's the technical challenge?

是的，这是优先事项。对于下一版本的植入物，我们想要改进的关键指标是通道数量，记录更多神经元。我们有一条路径，从目前的 1000 个，到今年年底希望达到 3000 个，甚至 6000 个。哇。到明年年底，我们想达到更多，16000 个。有几个限制因素。一个是能够用光刻技术打印这些导线。正如我提到的，它们宽度和间距只有两微米。显然，有比这些类型更先进的芯片……

Yes, that is a priority. For next versions of the implant, the key metrics we're looking to improve are number of channels, recording from more and more neurons. We have a pathway to go from currently 1,000 to hopefully 3,000, if not 6,000, by the end of this year. Wow. And by the end of next year, we want to get to even more, 16,000. There are a couple of limitations. One is being able to photolithographically print those wires. As I mentioned, they are two microns in width and spacing. Obviously there are chips that are much more advanced than those types of...

分辨率方面，我们内部引入了一些工具来实现这一点，因此走线会更窄，这样就需要有更多导线接入芯片。随着通道数增加，芯片也不能线性地消耗更多能量，所以在电路、架构以及电路设计拓扑方面有很多创新，以降低功耗。你还需要考虑，如果有了所有这些尖峰信号，如何将其发送到终端应用，因此需要考虑带宽限制以及信号处理方面的潜在创新。物理上，最大的挑战之一将是接口；接口总是容易出问题。将薄膜阵列与电子器件键合，会形成非常非常密集的互连，那么如何实现连接器化？近年来在 3D 集成方面有很多创新，我们可以加以利用。我们面临的最大挑战之一是形成这种密封屏障，对吧？大脑是一个极其恶劣的环境，所以如何保护电子设备免受大脑的侵蚀，同时防止电子设备向大脑泄漏不需要的物质，形成这种密封屏障将是一个非常非常大的挑战，我认为我们实际上很适合解决这个问题。

Resolution and we have some of the tools that we have brought in house to be able to do that so traces will be narrower just so that you have to have more of the wires coming up into the chip. Chips also cannot linearly consume more energy as you have more and more channels, so there's a lot of innovations in the circuit, you know, and architecture as well as a circuit design topology to make them lower power. You need to also think about if you have all of these spikes, how do you send that off to the end application, so you need to think about bandwidth limitation there and potentially innovations in signal processing. Physically, one of the biggest challenges is going to be the interface; it's always the interface that breaks. Bonding the thin film array to the electronics, it starts to become very, very highly dense interconnects, so how do you connectorize that? There's a lot of innovations in kind of the 3D integrations in the recent years that we can take advantage of. One of the biggest challenges that we do have is forming this hermetic barrier, right? You know, this is an extremely harsh environment that we're in the brain, so how do you protect it from, yeah, like the brain trying to kill your electronics, to also your electronics leaking things that you don't want into the brain, and that forming that hermetic barrier is going to be a very, very big challenge that we, you know, I think are actually well suited to tackle.

你们如何测试？比如，用什么开发环境来模拟这种恶劣条件？

How do you test that? Like, what's the development environment to simulate that kind of harshness?

这就是加速寿命测试仪，本质上就是一个缸中之脑。它实际上是一个容器，为了这种特定测试的目的，你的大脑就是一个盐水浴。你还可以加入其他一些化学物质，比如活性氧物种，它们会攻击这些界面，试图引起反应将其分解。但你也可以通过升高温度来加速这些界面的老化。每升高 10 摄氏度，时间基本上加速 2 倍。温度升高是有限度的，因为在某个点上，其他非线性动力学会导致形成其他有害气体，这在环境中是不现实的。所以我们把 ALT 腔室的温度升高 20 摄氏度，这样老化速度加快 4 倍。所以 ALT 腔室中的一天相当于日历年的 4 天。我们观察植入物是否仍然完好，包括电极丝和操作等。这显然不是与大脑完全相同的环境，因为大脑有机械性的、其他更多的生物粘液会攻击它，但至少对于外壳和外壳强度来说，这是一个很好的测试环境。我们的植入物，当前版本的植入物已经在里面待了将近两年半，相当于十年，它们似乎状态良好。

So this is where the accelerated life tester essentially is a brain in a vat. It literally is a vessel that is made up of, and again for all intents and purposes for this particular type of test, your brain is a saltwater bath. And you can also put some other set of chemicals like reactive oxygen species that get at kind of these interfaces and try to cause a reaction to pull it apart. But you could also increase the rate at which these interfaces are aging by just increasing temperature. So every 10 degrees Celsius that you increase, you're basically accelerating time by 2X. And there's a limit as to how much temperature you want to increase, because at some point there's some other nonlinear dynamics that causes you to have other nasty gases to form that just is not realistic in an environment. So what we do is we increase in our ALT chamber by 20 degrees Celsius, that increases the aging by four times. So essentially one day in ALT chamber is 4 days in calendar year. And we look at whether the implants still are intact, including the threads and operation and all that. It obviously is not an exact same environment as a brain, because you know brain has mechanical, you know other more biological goops that attack at it, but it is a good test environment for at least the enclosure and the strength of the enclosure. And I mean we've had implants, the current version of the implant that has been in there for I mean close to two and a half years, which is equivalent to a decade, and they seem to be fine.

所以基本上，接近的近似是温盐水，热盐水是一个很好的测试环境。

So basically, close approximation is warm salt water, hot salt water is a good testing environment.

是的。顺便说一句，我正在喝 Element，它基本上就是盐水，这让我有点……它没有大脑那样的计算能力，但也许在所有特性上非常相似。而且我正在喝它。

Yeah. By the way, I'm drinking Element, which is basically salt water, which is making me kind of... it doesn't have computational power the way the brain does, but maybe in terms of all the characteristics it's quite similar. And I'm consuming it.

你还得把 pH 值调对，然后意识就会涌现。

You have to get it in the right pH too, and then consciousness will emerge.

是的，不。好吧。顺便说一句，关于我们的外壳，另一个有趣的地方是，如果你看我们的植入物，它不像常见的医疗植入物那样通常封装在激光焊接的钛罐中。我们使用一种叫做 PCTFE（聚三氟氯乙烯）的聚合物，它实际上常用于包装。当你有一片药片并试图掰开时，那种塑料膜就是这种东西。除了我们之外，没有人真正使用过它。我们想这样做的原因是它具有电磁透明性。所以当我们谈到电磁感应充电时，使用钛罐通常需要有一个蓝宝石窗口，而且这是一个非常难以规模化生产的工艺。所以我们在这一方面做了大量迭代，包括材料、软件、硬件，整套东西。

Yeah, no. All right. By the way, the other thing that also is interesting about our enclosure is, if you look at our implant, it's not your common looking medical implant that usually is encased in a titanium can that's laser welded. We use this polymer called PCTFE, polychlorotrifluoroethylene, which is actually commonly used in packs. So when you have a pill and you're trying to pop the pill, there's that kind of plastic membrane; that's what this is. No one's actually ever used this except us. And the reason we wanted to do this is because it's electromagnetically transparent. So when we talked about the electromagnetic inductive charging, with titanium can, usually if you want to do something like that, you know you have to have a sapphire window and it's a very, very tough process to scale. So you're doing a lot of iteration here and every aspect of this: the materials, the software, the hardware, the whole shebang.

那么，你提到了规模化。是否有可能通过植入多个 Neuralink 设备来实现规模化？

So okay, so you mentioned scaling. Is it possible to have multiple Neuralink devices as one of the ways of scaling? To have multiple Neuralink devices implanted?

这是目标。这是目标。是的，我们的猴子已经植入了两个 Neuralink，每个半球一个。我们还在考虑在运动皮层、视觉皮层和其他皮层各植入一个。所以专注于特定功能的一个链接设备。我的意思是，我想知道是否可以在计算方面进行一定程度的定制。对于运动皮层，这绝对是目标。你知道，我们在 Neuralink 谈论的是构建一个通用的神经接口。这也是我们在战略上处理这个问题的方式，包括营销和监管方面：你看，我们有机器人，机器人可以进入皮层的任何部分。目前我们专注于运动皮层，当前版本的 N1 专门用于运动解码任务，但最终那里也有通用的计算能力。但你知道，通常如果你真的想针对功耗和效率进行超优化，你确实需要一些专门的功能，对吧？但我们要说的是，你现在已经习惯了这种机器人插入技术，这花了很多年展示数据、与 FDA 沟通，并在内部说服自己这是安全的。现在不同的是，如果我们进入大脑的其他区域，比如视觉皮层，这是我们感兴趣的第二个产品，显然那是一个完全不同的环境。皮层的布局非常非常不同。你知道，它将更侧重于刺激而非记录，只是创造视觉感知。但最终，我们使用相同的薄膜阵列技术、相同的机器人插入技术、相同的封装技术。现在的讨论更多地集中在差异以及这些差异对安全性和有效性的影响上。第二个产品对我来说既滑稽又令人敬畏。

That's the goal. That's the goal. Yeah, we've had, I mean our monkeys have had two Neuralinks, one in each hemisphere. And then we're also looking at potential of having one in motor cortex, one in visual cortex, and one in whatever other cortex. So focusing on the particular function one link device. I mean, I wonder if there's some level of customization that could be done on the compute side. So for the motor cortex, absolutely that's the goal. And you know, we talk about at Neuralink building a generalized neural interface to the brain. And that also is strategically how we're approaching this, with marketing and also with regulatory, which is: hey look, we have the robot and the robot can access any part of the cortex. Right now we're focused on motor cortex with current version of the N1 that's specialized for motor decoding tasks, but also at the end of the day there's kind of a general compute available there. But you know, typically if you want to really get down to kind of hyper optimizing for power and efficiency, you do need to get to some specialized function, right? But you know, what we're saying is that, hey, you are now used to this robotic insertion techniques, which took many many years of showing data and conversation with the FDA, and also internally convincing ourselves that this is safe. And now the difference is that if we go to other parts of the brain like visual cortex, which we're interested in as our second product, obviously it's a completely different environment. The cortex is laid out very, very differently. You know, it's going to be more stimulation focused rather than recording, just kind of creating visual percepts. But in the end, we're using the same thin film array technology, we're using the same robot insertion technology, we're using the same packaging technology. Now it's more the conversation focused around what are the differences and what are the implications of those differences in safety and efficacy. That second product is both hilarious and awesome to me.

那个产品就是为盲人恢复视力。那么你能谈谈刺激视觉皮层吗？我的意思是，那里的可能性简直不可思议，能够把这份礼物回馈给失去视力的人。或者甚至任何相关方面。你能谈谈挑战吗？这里有几个挑战。其中之一是，就像你说的，从记录到刺激。就任何你既兴奋又看到挑战的方面谈谈吧。

That product being restoring sight for blind people. So can you speak to stimulating the visual cortex? I mean, the possibilities there are just incredible, to be able to give that gift back to people who don't have sight. Or even any aspect of that. Can you just speak to the challenges? There are several challenges here. One of which is, like you said, from recording to stimulation. Just any aspect of that that you're both excited and see the challenges of.

嗯，我想先说一下，实际上我们多年来已经能够通过我们的 DENL 阵列和电子设备进行刺激。你知道，我们已经在脊髓中展示了重新激活肢体的能力。显然，对于当前的 EFS 研究，我们在硬件上禁用了这个功能，所以这是我们想作为一个独立旅程开始的事情。而且，显然有很多不同的方式将信息写入大脑。我们正在做的是通过电流，传递电流并真正改变局部环境，这样你就可以人为地使附近的神经元去极化。具体到视觉，我们的视觉系统的工作方式既有被很好理解的部分——我是说，任何与大脑相关的东西，有些方面是很好理解的，但最终我们其实什么都不知道。但视觉系统的工作方式是：光子击中你的眼睛，眼睛里有一种叫做感光细胞的特殊细胞，将光子能量转化为电信号。然后这些信号被投射到你的后脑勺，也就是视觉皮层。它经过一个叫做 LGN 的系统，然后投射出去。在视觉皮层中，有视觉区域一，即 V1，然后是一堆更高级的处理层，如 V2、V3。当你研究这些卷积神经网络的行为时，实际上有有趣的相似之处。比如网络的不同层在检测什么：首先检测边缘，然后检测更自然的曲线，然后开始检测物体。大脑中也发生类似的事情，其中很多是受此启发的。看到一些相关性是令人兴奋的。但像认知从何而来以及颜色在哪里编码——这些方面并没有很多基本的理解。所以，在为盲人恢复视力方面，有不同形式的失明。实际上，美国有 100 万人是法定盲人。这意味着在视力测试中得分低于某个标准。我想大概是，如果你在 20 英尺距离能看到的东西，正常人在 200 英尺距离就能看到，如果你比那更差，你就是法定盲人。所以从根本上说，这意味着你无法有效地使用视觉在世界上运作，比如导航你的环境。而且有不同形式的失明。有些形式是视网膜退化，这些感光细胞退化，而我所描述的其余视觉处理是完好的。对于这类人，你可能不需要将电极插入视觉皮层；你可以制造视网膜假体设备，仅仅替代那些退化的视网膜细胞的功能。有很多公司在做这个，但那是非常小的一部分——在法定盲人中更小的一部分。如果那条回路有任何损伤，无论是视神经、LGN 回路还是任何中断，那对你都不起作用。你需要实际产生视觉感知的地方，因为你的生物机制没有做到，那就是通过将电极放在后脑勺的视觉皮层中。这个工作的方式是，你会有一个外部摄像头——无论是像 GoPro 这样简单的东西，还是 Meta 正在开发的那种可穿戴雷朋眼镜——捕捉场景。然后这个场景被转换为一组电脉冲或刺激脉冲，通过植入的阵列激活你的视觉皮层。通过协调这些刺激模式的“交响乐”，你可以创造出所谓的“光幻视”，这些是白色带黄点，你也可以通过按压眼睛来产生。实际上，你可以通过刺激视觉皮层来产生这些感知。关键在于拥有很多这样的点，并且让这些感知——光幻视——尽可能小，这样你就可以开始区分屏幕上的单个像素。如果你有很多这样的点，长期来看，你可能能够获得自然的视觉。但在短期到中期，至少能够在你的眼镜上运行物体检测算法，预处理单元，然后至少能够看到物体的边缘，这样你就不会撞到东西——这真是不可思议。

Yeah, I guess I'll start by saying that we actually have been capable of stimulating through our DENL array as well as our electronics for years. You know, we have actually demonstrated some of those capabilities for reanimating the limb in the spinal cord. Obviously, for the current EFS study, we've hardware-disabled that, so that's something that we wanted to embark on as a separate journey. And obviously, there are many different ways to write information into the brain. The way we're doing that is through electrical current, passing electrical current and causing that to really change the local environment so that you can sort of artificially cause the neurons to depolarize in nearby areas. For vision specifically, the way our visual system works is both well understood — I mean, anything with the brain, there are aspects that are well understood, but in the end, we don't really know anything. But the way the visual system works is that you have photons hitting your eye, and in your eyes there are these specialized cells called photoreceptor cells that convert the photon energy into electrical signals. Then that gets projected to the back of your head, your visual cortex. It goes through a system called the LGN that then projects it out. And in the visual cortex, there is visual area one, or V1, and then a bunch of other higher-level processing layers like V2, V3. There are actually interesting parallels when you study the behaviors of these convolutional neural networks. Like what the different layers of the network are detecting: first they're detecting edges, then they're detecting more natural curves, and then they start to detect objects. A similar thing happens in the brain, and a lot of that has been inspired by it. It's been exciting to see some of the correlations there. But things like where cognition arises and where color is encoded — there's just not a lot of fundamental understanding there. So in terms of bringing sight back to those that are blind, there are many different forms of blindness. There are actually one million people in the US that are legally blind. That means like a certain score below on the visual test. I think it's something like if you can see something at 20 feet distance that normal people can see at 200 feet distance, if you're worse than that, you're legally blind. So fundamentally, that means you can't function effectively using sight in the world, like to navigate your environment. And there are different forms of blindness. There are forms where there's some degeneration of your retina, these photoreceptor cells, and the rest of your visual processing that I described is intact. For those types of individuals, you may not need to stick electrodes into the visual cortex; you can actually build retinal prosthetic devices that just replace the function of those retinal cells that are degenerated. There are many companies working on that, but that's a very small slice — a still smaller slice of folks that are legally blind. If there's any damage along that circuitry, whether it's in the optic nerve or the LGN circuitry or any break in that circuit, that's not going to work for you. The source of where you need to actually cause that visual percept to happen, because your biological mechanism is not doing that, is by placing electrodes in the visual cortex in the back of your head. The way this would work is that you would have an external camera — whether it's something as unsophisticated as a GoPro or some sort of wearable Ray-Ban type glasses that Meta is working on — that captures a scene. That scene is then converted to a set of electrical impulses or stimulation pulses that you would activate in your visual cortex through these implanted arrays. By playing a concerted orchestra of these stimulation patterns, you can create what's called phosphenes, which are these white-yellowish dots that you can also create by just pressing your eyes. You can actually create those percepts by stimulating the visual cortex. The name of the game is really to have many of those and have those percepts — the phosphenes — be as small as possible so that you can start to tell apart the individual pixels of the screen. If you have many of those, potentially in the long term you'll be able to get naturalistic vision. But in the short to mid term, being able to at least have object detection algorithms run on your glasses, the pre-processing units, and then being able to at least see the edges of things so you don't bump into stuff — it's incredible.

这真是太不可思议了。所以你基本上是在添加像素，然后你的大脑会开始弄清楚这些像素的含义。是的，而且在各个方面的信号处理上都有不同类型的辅助。

This is really incredible. So you basically would be adding pixels, and your brain would start to figure out what those pixels mean. Yeah, and with different kinds of assistance on the signal processing on all fronts.

嗯，实际上有几点。第一，显然如果你从出生就失明，大脑的工作方式，尤其是在早期，神经可塑性实际上就是你的大脑和不同部分争夺有限的地盘。而且很快，你会看到失明的人有更敏锐的听觉或其他感官的例子。原因在于，那个未使用的皮层被大脑的不同部分接管了。所以对于这类人，我想他们现在必须将其他感官的部分映射到他们所谓的视觉中，但这显然会是一种非常不同的意识体验。所以我认为这是一个有趣的注意事项。另一个需要强调的重要事情是，我们目前受到的限制是……

Yeah, the thing that actually — so a couple things. One is, obviously if you're blind from birth, the way the brain works, especially in the early age, neuroplasticity is really nothing other than your brain and different parts of your brain fighting for limited territory. And very quickly, you see cases where people that are blind have heightened sense of hearing or other senses. The reason for that is because that cortex that's not used just gets taken over by these different parts of the cortex. So for those types of individuals, I guess they're going to have to now map some other parts of their senses into what they call vision, but it's going to be obviously a very different conscious experience before. So I think that's an interesting caveat. The other thing that is important to highlight is that we're currently limited by

从我们生物学上能看到的波长来说，可见光的波长范围非常窄。但当你有了带外部摄像头的 BCI 系统，你就不受这个限制了。你可以看到红外、紫外，或者任何你想看到的频谱。至于这是否会映射到某种奇怪的意识体验，我完全不知道。但当我跟人们聊到 Neuralink 的目标是超越生物学极限时，我指的就是这个。如果你能控制原始信号——我们看东西时接收的是光子，几乎没有经过处理——那么也许你可以做一些处理，比如提前做物体检测。你在做某种预处理，这里面有很多可能性值得探索。所以不仅仅是增加热成像这类东西，还包括做一些有趣的处理。

Our biology in terms of the wavelength that we can see, there's a very small visible light wavelength that we can see with our eyes. But when you have an external camera with this BCI system, you're not limited to that. You can have infrared, UV, or whatever other spectrum you want to see. Whether that maps to some sort of weird conscious experience, I have no idea. But when I talk to people about the goal of Neuralink being going beyond the limits of our biology, that's sort of what I mean. And if you're able to control the kind of raw signal, when we use our sight we're getting the photons and there's not much processing on it. If you're able to control that signal, maybe you can do some kind of processing, maybe you do object detection ahead of time. You're doing some kind of pre-processing, and there's a lot of possibilities to explore. So it's not just increasing thermal imaging, that kind of stuff, but also doing some interesting processing.

是的，我对视觉系统工作原理的理解也是：世界上发生的事情太多了，大量光子进入你的眼睛。预处理步骤具体发生在哪里还不清楚。但我确实认为，从根本上看，我们所在的现实——如果它是现实的话——数据量太大了，人类根本无法摄入足够多的能量来处理所有这些信息。所以一定存在某种过滤，无论是在视网膜还是在视觉皮层的不同层次，目前还不清楚。我有时会想到一个类比：如果你的大脑是一个 CCD 相机，世界上所有的信息是太阳，当你试图用 CCD 相机看太阳时，传感器会饱和，因为能量太大了。所以你要加滤镜来缩小进入的信息。我认为像我们的体验，或者像丙泊酚（一种麻醉药）或致幻剂这类药物，它们所做的就是换掉这些滤镜，换上新的或移除旧的，从而控制我们的意识体验。

Yeah, I mean, my theory of how the visual system works is also that there are just so many things happening in the world, and there are a lot of photons going into your eye. It's unclear exactly where some of the pre-processing steps are happening. But I actually think that from a fundamental perspective, the reality we're in — if it is a reality — has so much data, and humans are just unable to actually eat enough to process all that information. So there's some filtering that happens, whether in the retina or in different layers of the visual cortex, it's unclear. The analogy I sometimes think about is: if your brain is a CCD camera and all the information in the world is the sun, when you try to look at the sun with a CCD camera, it's just going to saturate the sensors because it's an enormous amount of energy. So what you do is add filters to narrow the information coming to you. I think things like our experiences, or drugs like propofol (an anesthetic) or psychedelics, what they're doing is swapping out these filters, putting in new ones, or removing old ones, and controlling our conscious experience.

是的，老兄。不是要跑题，但我刚在亚马逊丛林里服用了高剂量的死藤水，所以是的，这是个很好的思考方式——你在切换不同的体验。而 Neuralink 首先主要是为了改善功能，不是为了娱乐或享受，而是恢复失去的功能。尤其是当功能完全丧失时，任何帮助都是巨大的。

Yeah, man. Not to distract from the topic, but I just took a very high dose of ayahuasca in the Amazon jungle, so yes, it's a nice way to think about it — you're swapping out different experiences. And with Neuralink, being able to control that primarily at first to improve function, not for entertainment or enjoyment purposes, but yeah, giving back lost functions. Especially when the function is completely lost, anything is a huge help.

你会给自己植入 Neuralink 设备吗？

Would you implant a Neuralink device in your own brain?

绝对会。我的意思是，可能不是现在，但绝对会。

Absolutely. I mean, maybe not right now, but absolutely.

达到什么样的能力会让你开始变得非常好奇，甚至有点坐立不安，就像看着别人被植入时会嫉妒一样？

What kind of capability once reached would make you start getting really curious and almost a little antsy, like jealous of people who get implanted as you watch them?

是的，即使是我们的早期参与者，如果他们开始做我做不到的事情——我认为他们有可能达到 15、20，甚至 100 BPS——没有什么根本性的东西阻止我们达到那样的性能。我肯定会嫉妒他们能做到。我得说，看着 Noland 我有点嫉妒，因为他玩得很开心，而且看起来是一种很酷的玩电子游戏的方式。

Yeah, I mean, even with our early participants, if they start to do things that I can't do — which I think is in the realm of possibility for them to achieve 15, 20, if not 100 BPS — there's nothing that fundamentally stops us from being able to achieve that type of performance. I would certainly get jealous that they can do that. I should say that watching Noland and I get a little jealous because he has so much fun and it seems like such a chill way to play video games.

是的，有时候很难体会到的是，他在做这些事情的同时还在多任务处理，比如一边说话。这显然需要很高的认知负荷，但就像我们说话时会挥手一样，这些都是多任务处理。他能做到，而据我所知，其他辅助技术做不到。如果你用眼动追踪设备，你会非常专注于你试图做的事情。如果你用语音控制，你说别的话就用不了了。多任务处理方面真的很有趣。所以不仅仅是主要任务的 BPS，而是多个任务的并行化。如果你测量整个人类有机体的 BPS——如果你一边说话，一边用大脑做事情，一边环顾四周——有很多并行化可以发生。但我认为，对他来说，如果他想真正达到那些高水平的 BPS，确实需要全神贯注。那是一个单独的回路，是一个很大的谜，比如注意力是如何工作的。认知负荷——我读过很多关于人们同时做两项任务的文献，比如一个主要任务和一个次要任务作为干扰源，以及它如何影响主要任务的性能。有很多有趣的见解。这是一个有趣的计算设备，我认为可以获得很多新颖的见解。我个人很惊讶，没有人能在说话的同时还能如此出色地控制光标，而且同时还要紧张，因为他像我们所有人一样在说话——如果你在镜头前说话，你会紧张。所有这些因素都在起作用，他仍然能实现高性能。令人惊讶。这一切都非常了不起。我认为在深入研究之后，我有点想让 Neuralink 排上队。而且安全性也要考虑。

Yeah, so the thing that's also hard to appreciate sometimes is that he's doing these things while multitasking, like while talking. It's clearly cognitively intensive, but similar to how when we talk we move our hands, these things are multitasking. He's able to do that, and you wouldn't be able to do that with other assistive technology as far as I'm aware. If you're using an eye-tracking device, you're very much fixated on that thing you're trying to do. If you're using voice control, if you say some other stuff, you don't get to use it. The multitasking aspect is really interesting. So it's not just the BPS for the primary task, it's the parallelization of multiple tasks. If you measure the BPS for the entirety of the human organism — if you're talking and doing a thing with your mind and looking around — there's a lot of parallelization that can happen. But I think at some point for him, if he wants to really achieve those high-level BPS, it does require full attention. That's a separate circuitry that is a big mystery, like how attention works. Cognitive load — I've read a lot of literature on people doing two tasks, like a primary task and a secondary task as a source of distraction, and how that affects performance. There's a lot of interesting insights. This is an interesting computational device, and I think there are a lot of novel insights to be gained. I personally am surprised that no one is able to do such incredible control of the cursor while talking and also being nervous at the same time, because he's talking like all of us — if you're talking in front of the camera you get nervous. All of those are coming into play, and he's still able to achieve high performance. Surprising. All of this is really amazing. I think after researching this in depth, I kind of want Neuralink to get in line. And also the safety gets in mind.

嗯，我们应该说明，注册是针对四肢瘫痪等患者，所以会有另一条线给像我这样只是好奇的人。

Well, we should say the registry is for people with quadriplegia and all that kind of stuff, so there'll be a separate line for people who are just curious, like myself.

那么现在 Noland（患者 P1）是正在进行的 PRIME 研究的一部分，P2、P3、P4、P5 以及扩展到其他体验这种植入物的人的高层愿景是什么？

So now that Noland, Patient P1, is part of the ongoing PRIME study, what's the high-level vision for P2, P3, P4, P5, and the expansion into other human beings getting to experience this implant?

是的，我们研究的首要目标是达到安全终点，了解该设备以及植入过程的安全性。同时，了解它可能对潜在用户生活产生的功效和影响。仅仅因为患有四肢瘫痪并不意味着每个人的情况都一样。

Yeah, the primary goal for our study in the first place is to achieve safety endpoints, just understand the safety of this device as well as the implantation process. And at the same time, understand the efficacy and the impact it could have on the potential users' lives. Just because you have tetraplegia doesn't mean your situation is the same.

作为另一个患有四肢瘫痪的人，情况千差万别。我们希望了解我们的技术如何服务于更广泛的群体，而不仅仅是一小部分人。能够获得反馈来为他们打造最好的产品。

As another person living with tetraplegia, it's widely varying. And we're hoping to understand how our technology can serve not just a very small slice of those individuals but a broader group. Being able to get feedback to build the best product for them.

我们有一些目标。早期可行性研究的主要目的是从每位参与者身上学习，改进设备和手术，然后才能进行关键性研究——那是一个更大的试验，考察终点的统计显著性。这是在美国和全球范围内上市设备前的必要流程。我们的目标是从 Nolan 和未来参与者那里了解设备需要改进的方面。如果人们说“我真的不喜欢它只能持续 6 小时，我想用这台电脑 24 小时”，那就是用户需求和规格，只有通过与他们互动才能发现。在关键性研究之前，会有基于个体经验的快速创新。我们从每个人那里学习他们如何使用设备，比如光标控制和信号的高分辨率细节，到生活体验。有硬件更改，也有固件更新。即使是在 Nolan 的恢复事件中，他现在也有了新固件。这就像你的手机不断通过固件更新获得安全补丁或新功能一样。我们的植入物不是静态的一次性设备。类似于特斯拉，你可以通过无线固件更新获得全新的用户界面和改进。

There are goals we have. The primary purpose of the early feasibility study is to learn from each participant to improve the device and surgery before we embark on a pivotal study, which is a much larger trial that looks at statistical significance of endpoints. That's required before you can market the device. That's how it works in the US and generally around the world. Our goal is to understand from people like Nolan and future participants what aspects of our device need to improve. If it turns out people say, 'I really don't like that it lasts only 6 hours; I want to use this computer for 24 hours,' that's a user need and requirement we can only find out by engaging with them. Before the pivotal study, there's rapid innovation based on individual experiences. We learn from individual people how they use it, like high-resolution details in cursor control and signal, to life experience. There are hardware changes but also firmware updates. Even when we had that recovery event for Nolan, he now has new firmware. It's similar to how your phones get updated with new firmware for security patches or new functionality. That's possible with our implant; it's not a static one-time device. Similar to Tesla, you can do over-the-air firmware updates and get a completely new user interface and improvements.

Nolan 使用的应用有校准和更新功能，只需点击就能获得更新，这真的很酷。你们还在关注哪些未来能力？你提到了视觉，那很迷人。加速打字或语音呢？还有什么？

It's really cool how the app Nolan is using has calibration and updates; you just click and get an update. What other future capabilities are you looking at? You mentioned vision, that's fascinating. What about accelerated typing or speech? What else is there?

这些仍然属于运动程序的范畴。大致来说，我们有两个项目：运动项目和视觉项目。运动项目目前专注于数字自由。你可以猜到，如果你能控制数字空间中的 2D 光标，你就能控制物理空间中的任何东西：机械臂、轮椅、你的环境，或者通过手机直接控制那些接口。我们正在寻找扩展这些能力的方法，甚至对 Nolan 也是如此。这需要与 FDA 沟通，并展示安全数据，以确保他们不会意外伤害自己。在数字领域移动东西与在物理空间移动东西非常不同；你实际上可能对参与者造成伤害。我们目前正在解决这个问题。语音涉及大脑的不同区域。语音假肢非常迷人，学术界已经做了很多了不起的工作。加州大学戴维斯分校的 Sergey Stavisky、Jamie Henderson 和已故的斯坦福大学 Krishna Shenoy 在改进语音神经假肢方面做了大量令人难以置信的工作。这些研究关注的是控制发音器官的运动皮层区域；通过口型或想象说话，可以捕捉到这些信号。更复杂的高级处理区域，如布罗卡区或韦尼克区，其潜在机制仍然非常神秘。我认为 Neuralink 的最终目标是理解这些，并提供一个平台和工具来研究它们。

Those are still in the realm of the movement program. Largely speaking, we have two programs: the movement program and the vision program. The movement program currently focuses on digital freedom. As you can easily guess, if you can control a 2D cursor in the digital space, you could move anything in the physical space: robotic arms, wheelchair, your environment, or through the phone directly to those interfaces. We're looking at ways to expand those capabilities even for Nolan. That requires conversation with the FDA and showing safety data to guarantee they won't hurt themselves accidentally. It's very different moving stuff in the digital domain versus the physical space; you can actually potentially harm participants. We're working through that now. Speech involves different areas of the brain. Speech prosthetics are very fascinating, and there's been amazing work in academia. Sergey Stavisky at UC Davis, Jamie Henderson, and the late Krishna Shenoy at Stanford have done incredible work improving speech neuroprosthetics. Those look at parts of the motor cortex controlling focal articulators; by mouthing the word or imagining speech, you can pick up those signals. The more sophisticated higher-level processing areas like Broca's area or Wernicke's area are still very mysterious in terms of underlying mechanisms. I think Neuralink's eventual goal is to understand those things and provide a platform and tools to study that.

这就到了我那些“瘾君子”式的问题了。你认为我们能开始洞察思维之类的东西吗？语音有肌肉成分，即产生声音的动作，但内在的东西呢，比如认知、低级和高级思维？你认为我们会开始注意到可以被捕捉、理解，甚至用来与外界交互的信号吗？我想这触及了意识的难题。

This is where I get to the pothead questions. Do you think we can start getting insight into things like thought? Speech has a muscular component, the act of producing sounds, but what about internal things like cognition, low-level and high-level thoughts? Do you think we'll start noticing signals that could be picked up, understood, maybe used to interact with the outside world? I guess this gets into the hard problem of consciousness.

一方面，所有这些在某种程度上都是一组电信号。也许这本身就给了你认知或意义，或者人类思维是一个不可思议的讲故事机器，欺骗我们自己这里有有趣的意义。我当然认为 BCI 是一套工具，帮助你从局部和更广泛的角度研究潜在机制。是否存在有意义的电信号模式，表明你在想这个而不是那个，并且你可以从大量数据集中学习相关性并进行读心，我不确定。我当然不会排除这种可能性，但我认为仅靠 BCI 可能无法做到。可能还需要其他工具和框架，而意识的难题根植于哲学问题：这一切的意义是什么，我们存在的本质是什么，思维是如何从这个复杂网络中涌现的？主观体验是如何从一堆电脉冲中涌现出来的？

On one hand, all of these are at some point a set of electrical signals. Maybe that in itself gives you cognition or meaning, or the human mind is an incredible storytelling machine, fooling ourselves that there's interesting meaning here. I certainly think that BCI is a set of tools that help you study the underlying mechanisms in both a local and broader sense. Whether there are interesting patterns of electrical signals that mean you're thinking this versus that, and you can learn from many datasets to correlate and do mind reading, I'm not sure. I certainly wouldn't rule it out as a possibility, but I think BCI alone probably can't do that. There's probably an additional set of tools and frameworks, and the hard problem of consciousness is rooted in philosophical questions: what is the meaning of it all, the nature of our existence, where does the mind emerge from this complex network? How does subjective experience emerge from just a bunch of electrical spikes?

是的，是的。我们确实把脑机接口和我们正在构建的东西视为理解心智和大脑的工具。唯一重要的问题实际上……实际上有一些生物学上的存在性证明，说明了要开始形成一些可能独特的体验需要什么。如果你看看我们每个人的大脑，都有两个半球：左脑和右脑。除非你有某些其他状况，你通常不会感觉到左腿或右腿，你只感觉到一条腿，对吧？那么这是怎么回事呢？如果你看看两个半球，有一个叫做胼胝体的结构连接它们，它大约有 2 到 3 亿个连接或轴突。所以这是否意味着我们需要那么多接口电极才能创造某种心灵融合，或者由此产生任何新的意识体验？但我觉得我们都有一些有趣的存在性证明，而这个阈值目前是未知的。哦，是的，这个领域的一切都是推测，对吧？然后你会不断感到惊喜。

Yeah, yeah. I mean, we really do think about BCI and what we're building as a tool for understanding the mind, the brain. The only question that matters there's actually... there actually is some biological existence proof of what it would take to kind of start to form some of these experiences that maybe unique. If you actually look at every one of our brains, there are two hemispheres: there's a left-sided brain, there's a right-sided brain. And I mean, unless you have some other conditions, you normally don't feel like left leg or right leg; you just feel like one leg, right? So what is happening there? If you actually look at the two hemispheres, there's a structure that kind of connects the two called the corpus callosum, which is supposed to have around 200 to 300 million connections or axons. So whether that means that's the number of interface electrodes that we need to create some sort of mind meld or from that, like whatever new conscious experience that you can experience. But yeah, I do think that there's like kind of interesting existence proof that we all have, and that threshold is unknown at this time. Oh yeah, these things, everything in this domain is speculation, right? And then there will be continuously pleasantly surprised.

你能否想象一个世界，有数百万人，比如数千万、数亿人，大脑里装着 Neuralink 设备，或者多个 Neuralink 设备？

Do you see a world where there's millions of people, like tens of millions, hundreds of millions of people walk around with the Neuralink device in their brain, or multiple Neuralink devices in their brain?

是的。首先，如果你看看全球患有运动障碍和视觉缺陷的人，那就有数千万甚至数亿人。仅此一项，我认为这项技术就能带来很多好处和潜力。当你开始涉足神经精神类应用时，比如抑郁症、焦虑症、饥饿感或肥胖症，对吧？情绪控制、食欲。我的意思是，这对每个人来说都变得非常真实。更不用说地球上大多数人都有智能手机，一旦脑机接口开始与智能手机竞争，成为与数字世界交互的首选方式，那也会变得很有趣。

I do. First of all, if you look at worldwide people suffering from movement disorders and visual deficits, that's in the tens if not hundreds of millions of people. So that alone, I think there's a lot of benefit and potential good that we can do with this type of technology. And when you start to get into neuropsychiatric applications, you know, depression, anxiety, hunger, or obesity, right? Mood control, appetite. I mean, that starts to become very real to everyone. Not to mention that most people on earth have a smartphone, and once BCI starts competing with a smartphone as a preferred methodology of interacting with the digital world, that also becomes an interesting thing.

哦，是的，我的意思是这甚至还没到那一步，对吧？几乎整个世界都能从这类东西中受益。然后，如果我们谈论下一代如何与机器甚至我们自己交互，我认为脑机接口在很多方面都能发挥作用。我还提到，我确实认为有可能看到 80 亿人戴着 Neuralink 走来走去。非常感谢你的推动，我期待那个激动人心的未来。

Oh yeah, I mean that's even before going to that, right? I mean, there's almost the entire world that could benefit from these types of things. And then yeah, if we're talking about the next generation of how we interface with machines or even ourselves, in many ways I think BCI can play a role in that. And some of the things that I also talk about is I do think that there is a real possibility that you could see 8 billion people walking around with Neuralink. Well, thank you so much for pushing ahead and I look forward to that exciting future.

谢谢邀请。

Thanks for having me.

感谢收听与 DJ Seo 的对话。现在，亲爱的朋友们，有请 Neuralink 首席神经外科医生 Matthew McDougall。你最初是什么时候对人类大脑产生兴趣的？

Thanks for listening to this conversation with DJ Seo. And now, dear friends, here's Matthew McDougall, the head neurosurgeon at Neuralink. When did you first become fascinated with the human brain?

从很久以前就开始了。从我记事起，我就对人类大脑感兴趣。我是一个爱思考的孩子，有点不合群，你会坐在那里，用你那小小的青春期大脑思考世界上最重要的事情是什么。我得出的结论是：所有你能想象到的人类关心的重要事物，都实实在在地包含在头骨里——对它们的感知、它们的相对价值，以及我们所有问题的解决方案，所有问题都包含在头骨里。如果我们更了解它是如何运作的，大脑如何编码信息、产生欲望、产生痛苦和折磨，我们就能做得更多。想想人类历史上所有伟大的胜利，想想所有可怕的悲剧，想想大屠杀，想想任何充满人类故事的监狱，所有这些问题都归结为神经化学。所以如果你能对此有一点控制，你就给了人们做得更好的选择。我读历史的方式是，人们拥有更好的工具时，最终往往做得更好，尽管有很大的例外。但我认为给人们更多选择、更多工具是一个有趣、有价值、高尚的追求。

Since forever. As far back as I can remember, I've been interested in the human brain. I was a thoughtful kid and a bit of an outsider, and you sit there thinking about what the most important things in the world are, in your little tiny adolescent brain. And the answer that I came to, that I converged on, was that all of the things you can possibly conceive of as things that are important for human beings to care about are literally contained in the skull: both the perception of them and their relative values, and the solutions to all our problems and all of our problems are all contained in the skull. If we knew more about how that worked, how the brain encodes information and generates desires and generates agony and suffering, we could do more about it. You think about all the really great triumphs in human history, you think about all the really horrific tragedies, you think about the Holocaust, you think about any prison full of human stories, and all of those problems boil down to neurochemistry. So if you get a little bit of control over that, you provide people the option to do better. The way I read history, the way people have dealt with having better tools is that they most often in the end do better, with huge asterisks. But I think it's an interesting, a worthy, a noble pursuit to give people more options, more tools.

是的，这是一种看待人类历史的迷人方式。你想想所有这些神经生物学机制：斯大林、希特勒，还有成吉思汗，他们都只有一个大脑，只是一堆神经元，几百亿个神经元，在一段时间内获取大量信息。他们有一个处理语言和记忆等的模块，从那里，就那些人而言，他们能够谋杀数百万人。而这一切并非来自某种被神化的巨大心智的独裁者概念，它只是大脑。

Yeah, that's a fascinating way to look at human history. You just imagine all these neurobiological mechanisms: Stalin, Hitler, all of them, Genghis Khan, all of them just had a brain, just a bunch of neurons, a few tens of billions of neurons, gaining a bunch of information over a period of time. They have a module that does language and memory and all that, and from there, in the case of those people, they're able to murder millions of people. And all that coming from there's not some glorified notion of a dictator of this enormous mind or something like this; it's just the brain.

是的，是的。我的意思是，这在很大程度上与那些人如何组织周围的人、其他大脑有关。所以我总是觉得研究灵长类动物学很有趣，看看我们最近的近亲，寻找人类行为以及特定人类能取得什么成就的线索。所以你看黑猩猩和倭黑猩猩，它们相似但在社会结构上尤其不同。我在亚特兰大的埃默里大学学习，师从伟大的 Frans de Waal，他是顶尖的灵长类动物学家，最近去世了。他的工作是像看《老友记》一集那样观察黑猩猩，理解角色互动的动机——他会观察一个黑猩猩群体，并基本应用那个视角。我大大简化了。如果你这样做，而不是只说“473 号受试者向 471 号受试者扔粪便”，你会用人类的挣扎来描述它们，赋予它们作为有可理解目标和驱动力的行动者的尊严，它们想从生活中得到什么。而主要是我们想从生活中得到的东西：食物、性、陪伴、权力。你可以更容易地用同样的视角理解黑猩猩和倭黑猩猩的行为。我认为这样做给了你所需的工具，将人类行为从我们用语言叠加的虚假复杂性中剥离出来，用“哦，这些人类在寻找陪伴、性、食物、权力”来看待。我认为这是理解人类行为的一个非常强大的工具。我刚刚去亚马逊丛林待了几周，那是一个非常直观的提醒：地球上的许多生命只是在努力生存。

Yeah, yeah. I mean, a lot of that has to do with how well people like that can organize those around them, other brains. And so I always find it interesting to look to primatology, look to our closest non-human relatives for clues as to how humans are going to behave and what particular humans are able to achieve. So you look at chimpanzees and bonobos, and they're similar but different in their social structures particularly. I went to Emory in Atlanta and studied under Frans de Waal, the great Frans de Waal, who was kind of the leading primatologist, who recently died. His work in looking at chimps through the lens of how you would watch an episode of Friends and understand the motivations of the characters interacting with each other—he would look at a chimp colony and basically apply that lens. I'm massively oversimplifying it. If you do that instead of just saying 'subject 473 threw his feces at subject 471,' you talk about them in terms of their human struggles, accord them the dignity of themselves as actors with understandable goals and drives, what they want out of life. And primarily it's the things we want out of life: food, sex, companionship, power. You can understand chimp and bonobo behavior in those same lights much more easily. And I think doing so gives you the tools you need to reduce human behavior from the kind of false complexity that we layer on to it with language and look at it in terms of 'oh well, these humans are looking for companionship, sex, food, power.' And I think that's a pretty powerful tool to have in understanding human behavior. And I just went to the Amazon jungle for a few weeks, and it's a very visceral reminder that a lot of life on Earth is just trying.

为了交配，是的，它们都在互相尖叫。我见过很多猴子，它们只是想给对方留下印象，或者可能是在争夺权力，但很多权力争夺都与交配有关，对吧？交配权通常伴随着阿尔法地位，所以如果你能分得一杯羹，那你就会过得不错。我愿意认为我们在某种程度上根本不同，但尤其是对于灵长类动物来说，我们确实——你知道，我们可以用更华丽的诗意的语言，但也许驱动我们的一些底层动机是相似的。

To get laid, yeah, they're all screaming at each other. I saw a lot of monkeys, and they're just trying to impress each other, or maybe there's a battle for power, but a lot of the battle for power has to do with them getting laid, right? Mating rights often go with alpha status, and so if you can get a piece of that, then you're going to do okay. I'd like to think that we're somehow fundamentally different, but especially when it comes to primates, we really are—you know, we can use fancier poetic language, but maybe some of the underlying drives that motivate us are similar.

是的，我认为确实如此。而这一切都来自大脑。

Yeah, I think that's true. And all that is coming from the brain.

那么你最初是什么时候开始将大脑作为生物机制来研究的？

So when did you first start studying the brain as a biological mechanism?

基本上我一上大学就开始寻找可以从事神经科学工作的实验室。我最初是从研究大脑和免疫系统之间的相互作用入手的，这不是最显而易见的起点，但我当时有一个想法：你思想的内容会对身体中的无意识系统产生直接、甚至强大的影响——那些我们认为是稳态自动机制的系统，比如对抗病毒、修复伤口。果然，两者之间有很大的交叉。这涉及到一个我认为被低估的关键点。人们对人脑认识或欣赏不足的一点是，它基本上控制或对你身体所做的一切都有巨大作用。试着举一个身体中不受大脑直接控制或巨大影响的例子——这很难。你可能会说骨骼愈合之类的，但即使是那些系统，下丘脑和垂体最终也在协调内分泌系统中发挥作用，而内分泌系统确实直接影响，比如说，血液中钙的水平，这关系到骨骼愈合。所以这些事物之间非显而易见的联系表明，大脑确实是所有健康中强大的原动力。

Basically the moment I got to college, I started looking around for labs that I could do neuroscience work in. I originally approached that from the angle of looking at interactions between the brain and the immune system, which isn't the most obvious place to start, but I had this idea at the time that the contents of your thoughts would have a direct impact, maybe a powerful one, on non-conscious systems in your body—the systems we think of as homeostatic automatic mechanisms, like fighting off a virus, like repairing a wound. And sure enough, there are big crossovers between the two. It gets to a key point that I think goes underrecognized. One of the things people don't recognize or appreciate about the human brain enough is that it basically controls or has a huge role in almost everything that your body does. Try to name an example of something in your body that isn't directly controlled or massively influenced by the brain—it's pretty hard. You might say bone healing or something, but even those systems, the hypothalamus and pituitary end up playing a role in coordinating the endocrine system that does have a direct influence on, say, the calcium level in your blood that goes to bone healing. So non-obvious connections between those things implicate the brain as really a potent prime mover in all of health.

我也从另一个方向意识到一件事：身体中的大多数系统如何与人脑整合，比如它们也影响大脑，比如免疫系统。我认为——你知道，研究阿尔茨海默病之类的人，令人惊讶的是，你可以从免疫系统、从其他那些似乎与神经系统没有明显关系的系统中理解那么多。它们都协同作用。

One of the things I realized in the other direction too: how most of the systems in the body are integrated with the human brain, like they affect the brain also, like the immune system. I think there's just—you know, people who study Alzheimer's and those kinds of things, it's just surprising how much you can understand of that from the immune system, from the other systems that don't obviously seem to have anything to do with the nervous system. They all play together.

是的，你也可以理解这如何由进化驱动。在一些简单的例子中，如果你生病了，如果你得了传染病，你得了流感，你的免疫系统告诉你的大脑，“嘿，现在几天别社交。今晚别去派对上活跃。事实上，也许就在某个温暖的地方裹着毯子蜷缩起来，待一两天。”这非常有利。果然，这就是你在动物和人类身上看到的行为。如果你生病了，血液中白细胞介素和肿瘤坏死因子-α水平升高，会要求大脑减少社交活动，甚至减少活动——感染病毒的动物运动活动也会降低。

Yeah, you could understand how that would be driven by evolution too. In some simple examples, if you get sick, if you get a communicable disease, you get the flu, it's pretty advantageous for your immune system to tell your brain, 'Hey, now be antisocial for a few days. Don't go be the life of the party tonight. In fact, maybe just cuddle up somewhere warm under a blanket and just stay there for a day or two.' And sure enough, that tends to be the behavior that you see both in animals and in humans. If you get sick, elevated levels of interleukins and TNF-alpha in your blood ask the brain to cut back on social activity, even moving around—you have lower locomotor activity in animals that are infected with viruses.

从那里，从神经科学的早期到外科手术——这一步是什么时候发生的？是一个飞跃吗？

From there, the early days in neuroscience to surgery—when did that step happen? Was it a leap?

这更像是一种思想的演变。我想研究大脑，所以我在本科时就在这个神经免疫学实验室开始研究大脑。从那里，我意识到在某个时刻，我不想仅仅产生知识；我想在现实世界中、在真实人们的生活中产生实际的变化。所以，在并没有真正考虑过进入医学院之后——我当时正走在攻读博士学位的道路上——我说，“嗯，我想要那个选择。我想真正有可能帮助我面前具体的人。”做了一些挖掘后，我发现存在这些 MD/PhD 项目，你可以选择不在这两者之间做选择，而是两者都做。所以我去了南加州大学读医学院，并与加州理工学院有一个联合博士项目，在那里我遇到了——实际上，我选择那个项目特别因为加州理工学院的一位研究员理查德·安德森，他是灵长类神经科学教父之一。他有一个猕猴实验室，在那里将犹他阵列和其他电极插入猴子的大脑，以试图理解意图是如何在大脑中编码的。所以我最终去了那里，带着我可能会成为一名神经学家并业余研究大脑的想法，然后发现神经学——再说一次，我说这个会树敌——但神经学，对我来说主要是且令人沮丧的是，诊断一个东西然后说，“祝你好运，我们做不了太多。”而神经外科则非常不同，它是一个强大的杠杆，可以把那些走向糟糕方向的人拉回来，改变他们的轨迹，比如可能通过手术治疗或治愈的脑肿瘤，甚至大脑血管中即将破裂的动脉瘤——你可以拯救生命。真的，归根结底，那对我来说才是重要的。所以我在南加州大学，正如我提到的，它恰好是伟大的神经外科项目之一，我遇到了这些真正史诗般的神经外科医生：阿尔·凯西、M. A. 普佐、史蒂夫·詹诺塔和马丁·韦斯——这些史诗般的人物，他们只是我面前的人类。这改变了我的想法，从“神经外科医生是生活在另一个星球上、偶尔来拜访我们的遥远的神”到“这些是有问题、是人的普通人，没有什么从根本上阻止我成为他们中的一员。”所以在医学院的最后一刻，我改变了方向，从另一个专业转到了神经外科，这让我损失了一年。我不得不又做了一年的研究，因为我在过程中已经走得太远，转神经外科的截止日期已经过了。所以这是一个花费时间的决定，但绝对值得。

It was sort of an evolution of thought. I wanted to study the brain, so I started studying the brain in undergrad in this neuroimmunology lab. From there, I realized at some point that I didn't want to just generate knowledge; I wanted to affect real changes in the actual world, in actual people's lives. So after having not really thought about going into medical school—I was on a track to go into a PhD program—I said, 'Well, I'd like that option. I'd like to actually potentially help tangible people in front of me.' And doing a little digging, I found that there exist these MD/PhD programs where you can choose not to choose between them and do both. So I went to USC for medical school and had a joint PhD program with Caltech, where I met—actually, I chose that program particularly because of a researcher at Caltech named Richard Anderson, who's one of the godfathers of primate neuroscience. He has a macaque lab where Utah arrays and other electrodes were being inserted into the brains of monkeys to try to understand how intentions were being encoded in the brain. So I ended up there with the idea that maybe I would be a neurologist and study the brain on the side, and then discovered that neurology—again, I'm gonna make enemies by saying this—but neurology, predominantly and distressingly to me, is the practice of diagnosing a thing and then saying, 'Good luck with that, there's not much we can do.' And neurosurgery, very differently, is a powerful lever on taking people that are headed in a bad direction and changing their course, in the sense of brain tumors that are potentially treatable or curable with surgery, even aneurysms in the brain blood vessels that are going to rupture—you can save lives. Really, at the end of the day, that's what mattered to me. So I was at USC, as I mentioned, which happens to be one of the great neurosurgery programs, and I met these truly epic neurosurgeons: Al Kesi, M. A. Puzzo, Steve Giannotta, and Marty Weiss—these sort of epic people that were just human beings in front of me. It kind of changed my thinking from 'neurosurgeons are distant gods that live on another planet and occasionally come and visit us' to 'these are humans that have problems and are people, and there's nothing fundamentally preventing me from being one of them.' So at the last minute in medical school, I changed gears from going into a different specialty and switched into neurosurgery, which cost me a year. I had to do another year of research because I was so far along in the process that to switch into neurosurgery, the deadlines had already passed. So it was a decision that cost time but absolutely worth it.

在神经外科医生的道路上，训练中最难的部分是什么？

What was the hardest part of the training on the neurosurgeon track?

是的，两件事。我认为神经外科住院医师培训有点像一场痛苦的竞赛，看你能承受多少痛苦并微笑。有一些工作限制，在住院医师内部被视为软弱，所以大多数神经外科住院医师都尽可能努力地工作。这必然意味着长时间工作，有时超过工时限制。我们关心遵守面前的任何规定，但我认为比那更重要的是，人们想要全力以赴成为更好的神经外科医生。

Yeah, two things. I think that residency in neurosurgery is sort of a competition of pain, of how much pain can you eat and smile. There are work restrictions that are viewed internally among the residents as weakness, and so most neurosurgery residents try to work as hard as they can. That necessarily means working long hours and sometimes over the work hour limits. We care about being compliant with whatever regulations are in front of us, but I think more important than that, people want to give their all in becoming a better neurosurgeon.

风险如此之高，以至于让住院医师在轮班结束时回家、不再留下来做更多手术，真的是一场斗争。你是在认真地说，最难的事情之一就是字面意义上地让他们去睡觉和休息这类事吗？

The stakes are so high and so it's a real fight to get residents to say go home at the end of their shift and not stay and do more surgery. Are you seriously saying one of the hardest things is literally getting, forcing them to get sleep and rest and all this kind of stuff?

历史上确实如此。我认为下一代更顺从，也更自我……

Historically that was the case. I think the next generation is more compliant and more self-...

你是这个意思吗？好吧，我只是开玩笑，我只是开玩笑。我没说出口。现在我在树敌了。不，好吧，我明白了。哇，真有意思。

Is that what you mean? All right, I'm just kidding, I'm just kidding. I didn't say it. Now I'm making enemies. No, okay, I get it. Wow, that's fascinating.

那么第二件事是什么？个性，也许这两者是相关的。但竞争激烈吗？

So what was the second thing? The personalities, and maybe the two are connected. But was it pretty competitive?

竞争很激烈，而且正如我们之前提到的，灵长类动物喜欢权力。我认为神经外科长期以来一直笼罩在神秘和卓越的光环中。所以，我认为这对那些披着这种权威外衣的人来说是一种诱惑。你知道，委员会认证的神经外科医生基本上就是一个行走的诉诸权威谬误。你有执照走进任何房间，表现得好像你是任何方面的专家。对抗这种倾向并不是大多数神经外科医生擅长的事情。谦逊不是他们的强项。

It's competitive, and it's also, as we touched on earlier, primates like power. I think neurosurgery has long had this aura of mystique and excellence about it. So it's an invitation, I think, for people that are cloaked in that authority. You know, board certified neurosurgeon is basically a walking fallacious appeal to authority. You have a license to walk into any room and act like you're an expert on whatever. Fighting that tendency is not something that most neurosurgeons do well. Humility isn't the forte.

是的。我的一些认识你的朋友，每当他们谈起你，都说你拥有神经外科医生中令人惊讶的谦逊品质，我认为这表明谦逊并不像其他职业那么常见，因为神经外科有一种巨大的、英雄般的色彩，我觉得这有点让人冲昏头脑。

Yeah. One of my friends who know you, whenever they speak about you, they say you have the surprising quality for a neurosurgeon of humility, which I think indicates that it's not as common as perhaps in other professions because there is a kind of gigantic, sort of heroic aspect to neurosurgery, and I think it gets to people's heads a little bit.

是的，嗯，我认为这让我能在 Elon 的公司里很好地合作。因为 Elon，我认为他的一个优势就是能立刻看穿来自权威的谬误。所以没有人能走进他所在的房间说，‘该死的，你必须相信我，我是造了最近 10 枚火箭的人’，然后他会说，‘嗯，你做得不对，我们可以做得更好。’或者，‘我是过去 50 年让福特活下来的人，听我的怎么造车’，然后他说，‘不。’所以你不能走进他所在的房间说，‘嗯，我是神经外科医生，让我告诉你该怎么做。’他会说，‘嗯，我是一个有大脑的人，我自己可以从原理出发思考，非常感谢。这是我认为应该怎么做的方式。我们去试试看谁是对的。’而且，我认为在他的案例中，这已经被反复证明是一个非常强大的方法。

Yeah, well, I think that allows me to play well at an Elon company, yes. Because Elon, one of his strengths, I think, is to just instantly see through fallacy from authority. So nobody walks into a room that he's in and says, 'Well, goddamn it, you have to trust me, I'm the guy that built the last 10 rockets or something,' and he says, 'Well, you did it wrong and we can do it better.' Or, 'I'm the guy that kept Ford alive for the last 50 years, you listen to me on how to build cars,' and he says, 'No.' So you don't walk into a room that he's in and say, 'Well, I'm a neurosurgeon, let me tell you how to do it.' He's going to say, 'Well, I'm a human being that has a brain, I can think from principles myself, thank you very much. And here's how I think it ought to be done. Let's go try it and see who's right.' And that's proven, I think over and over in his case, to be a very powerful approach.

如果我们顺着这个岔开的话题，Neuralink 有一个迷人的跨学科团队，你可以与之互动，包括 Elon。你认为成功团队的秘诀是什么，或者你从观察这些人中学到了什么？不同学科的世界级专家一起工作。

If we just take that tangent, there's a fascinating interdisciplinary team at Neuralink that you get to interact with, including Elon. What do you think is the secret to a successful team, or what have you learned from just getting to observe these folks? World experts in different disciplines work together.

是的，存在一个最佳平衡点：人们可以不同意，有力地表达自己的想法，热情地捍卫自己的立场，但仍然能够接受他人的信息，并在自己错误时改变想法。我喜欢打磨石头的比喻：你把硬东西放进一个硬容器里旋转，它们互相碰撞，最后出来的是更精细的产品。所以为了在 Neuralink 打造一个好的团队，我们试图找到那些不害怕热情捍卫自己想法、偶尔与同事强烈争论的人，并让最好的想法胜出。这不是一个容易的平衡。再次回到灵长类动物的大脑，它并不是天生就具备这样的机制：‘我热情地把所有筹码押在这个立场上，现在我要放弃它，承认你是对的。’我们大脑的一部分告诉我们，那是权力的损失、丢面子、在群体中地位的丧失，现在你成了一个因为想法被击败而地位低下的傻瓜。你只需要认识到，你脑海中的那个小声音是适应不良的，它无助于团队获胜。

Yeah, there's a sweet spot where people disagree and forcefully speak their mind and passionately defend their position, and yet are still able to accept information from others and change their ideas when they're wrong. I like the analogy of how you polish rocks: you put hard things in a hard container and spin it, people bash against each other, and out comes a more refined product. So to make a good team at Neuralink, we've tried to find people that are not afraid to defend their ideas passionately and occasionally strongly disagree with people they're working with, and have the best idea come out on top. It's not an easy balance. Again, to refer back to the primate brain, it's not something that is inherently built into the primate brain to say, 'I passionately put all my chips on this position and now I'm just going to walk away from it and admit you are right.' Part of our brains tell us that that is a power loss, a loss of face, a loss of standing in the community, and now you're a zeta chump because your idea got trounced. You just have to recognize that that little voice in the back of your head is maladaptive and it's not helping the team win.

是的，你必须要有自信，能够放弃你坚持的想法。

Yeah, you have to have the confidence to be able to walk away from an idea that you hold on to.

是的，如果你足够频繁地这样做，你实际上会在这个领域成为世界最佳。我的意思是，那种快速迭代。你至少会成为一个胜利团队的一员，乘风破浪。

Yeah, and if you do that often enough, you're actually going to become the best in the world at your thing. I mean, that kind of rapid iteration. You'll at least be a member of a winning team, ride the wave.

你学到了什么？你提到南加州大学有很多了不起的神经外科医生。你从那些人身上学到了哪些关于手术和人生的教训？

What did you learn? You mentioned there are a lot of amazing neurosurgeons at USC. What lessons about surgery in life have you learned from those folks?

是的，我认为是拼命工作，作为团队一员努力工作，完成极其困难的任务。工作超长时间，整夜照顾你认为无论做什么都可能活不下来的病人，努力让你非常讨厌的人在第二天早上看起来不错。这些人几十年如一日地不懈追求卓越的神经外科技术，我认为他们因这种卓越而广受认可。所以，尤其是 Marty Weiss、Steve Giannotta、Mike Apuzzo，他们不仅对外科技术做出了巨大贡献，还建立了培训项目，培养了几十甚至几百名优秀的神经外科医生。我只是幸运地跟在他们后面。

Yeah, I think working your ass off, working hard while functioning as a member of a team, getting a job done that is incredibly difficult. Working incredibly long hours, being up all night taking care of someone that you think probably won't survive no matter what you do, working hard to make people that you passionately dislike look good the next morning. These folks were relentless in their pursuit of excellent neurosurgical technique decade over decade, and I think they're well recognized for that excellence. So, especially Marty Weiss, Steve Giannotta, Mike Apuzzo, they made huge contributions not only to surgical technique but they built training programs that trained dozens or hundreds of amazing neurosurgeons. I was just lucky to kind of be in their wake.

那是什么感觉？你提到做手术时病人很可能活不下来。这会让你感到疲惫吗？

What's that like? You mentioned doing a surgery where the person is likely not to survive. Does that wear on you?

是的，尤其具有挑战性的是——恕我直言，对年长者——当你照顾一位 80 岁的老人时，冲击没那么大，反正很快也会有什么事情找上他们。失去这样的病人，是他们在未来几年无论如何都会经历的自然过程的一部分。但照顾一个有两三个或四个小孩的父亲，一个 30 多岁、本不该遭遇这种事的人，他们第一次癫痫发作来到你的急诊室，结果发现他们有一个巨大的恶性、无法手术或无法治愈的脑肿瘤。我认为，这种事情你只能经历几次，否则它真的会开始侵蚀你的盔甲。或者一位年轻的母亲，她脑部大出血，无法存活，你知道他们把她四岁的女儿带进来，在关掉呼吸机之前做最后的告别。伟大的英国神经外科医生 Henry Marsh 说得最好，我认为：‘每个神经外科医生都随身携带一个私人墓地。’我确实有这种感觉，尤其是对年轻的父母。那让我心碎。他们本可以贡献更多。失去这些人会产生连锁反应，会在很长一段时间内让世界变得更糟，这种感觉很难承受。

Yeah, it's especially challenging when, with all respect to our elders, it doesn't hit so much when you're taking care of an 80-year-old and something was going to get them pretty soon anyway. You lose a patient like that, it was part of the natural course of what is expected of them in the coming years regardless. Taking care of a father of two or three or four young kids, someone in their 30s that didn't have it coming, and they show up in your ER having their first seizure of their life and lo and behold, they've got a huge malignant inoperable or incurable brain tumor. You can only do that, I think, a handful of times before it really starts eating away at your armor. Or a young mother that shows up that has a giant hemorrhage in her brain that she's not going to survive from, and you know they bring her four-year-old daughter in to say goodbye one last time before they turn the ventilator off. The great Henry Marsh, an English neurosurgeon, said it best, I think: 'Every neurosurgeon carries with them a private graveyard.' And I definitely feel that, especially with young parents. That kills me. They had a lot more to give. The loss of those people specifically has a knock-on effect that's going to make the world worse for people for a long time, and it's just hard to feel.

面对那种情况，你无能为力。我认为，要对抗像 Neuralink 这样的公司，或者不断对我们冷嘲热讽，那几乎是邪恶的，因为我们所做的一切都是为了解决这些问题。我们试图给人们提供选择，减少痛苦。我们试图消除因大脑受损而带来的生活痛苦。这是我们对抗熵增的小小方式。当人们失去那些我们习以为常的大脑功能时，所承受的痛苦是巨大的。能够恢复部分功能，是一份真正的礼物。我们才刚刚开始，未来还会做更多。

Powerless in the face of that, you know. And that's where I think you have to be borderline evil to fight against a company like Neuralink or to constantly be taking potshots at us, because what we're doing is to try to fix that stuff. We're trying to give people options, to reduce suffering. We're trying to take the pain out of life that broken brains bring. And yeah, this is just our little way that we're fighting back against entropy, I guess. The amount of suffering that's endured when some of the things that we take for granted that our brain is able to do is taken away is immense. And to be able to restore some of that functionality is a real gift. We're just starting. We're going to do so much more.

你能带我走一遍植入 N1 芯片的完整流程吗？

Can you take me through the full procedure of implanting, say, the N1 chip in Neuralink?

这是一个非常简单直接的手术。我负责的人类部分极其简单，是你能想象到的最基本的神经外科手术之一。有证据表明，某种形式的这种手术已经存在了数千年。古埃及有愈合或部分愈合的环钻术例子，秘鲁或南美古代也有，那些原始外科医生会在人的头骨上钻孔，大概是为了放出邪灵，但也可能是为了引流血块。骨头边缘有愈合迹象，说明患者术后至少存活了几个月。我们现在做的是在头顶皮肤上切一个口子，位于大脑最强烈代表手部意图的区域。如果你是一位专业的音乐会钢琴家，你演奏时这个区域会一直亮着。我们称之为手部旋钮（hand knob）。所有手指运动，都在那里放电。皮层上有一个小弯曲，大脑的一个褶皱在那里双重折叠。你可以在 MRI 上看到它，说那就是手部旋钮。然后通过一种特殊 MRI——功能性 MRI（fMRI）进行功能测试，当人们——即使是四肢瘫痪、大脑不再连接手指运动的人——想象手指运动时，这个区域会亮起。所以我们可以在任何准备进入试验的人身上识别出这个区域，确认那是你的手部意图区域。我会在皮肤上切一个小口，把皮肤像打开汽车引擎盖一样翻开，但小得多。在头骨上钻一个完美的 1 英寸直径圆孔，取出那块头骨，打开大脑的覆盖层——大脑的包膜，就像一个让大脑漂浮的小水袋——然后把那个区域展示给我们的机器人。这就是机器人的闪光点。它可以进入，用这些比头发丝还细的微小电极，精确地插入皮层，插入大脑表面，达到非常精确的深度和位置，避开覆盖在大脑表面的所有血管。机器人完成它的部分后，人类医生回来，把植入物放入头骨的那个孔中，盖上，用螺丝固定到头骨上，然后把皮肤缝回去。整个过程大约几个小时。与可能打开大脑深部或操作大脑血管的普通神经外科手术相比，风险极低。这种只在大脑表面开口、进行皮层微插入的手术，风险远低于常规的肿瘤或动脉瘤手术。通过机器人和计算机视觉进行的皮层微插入，正是为了避开血管而设计的。

It's a really simple, straightforward procedure. The human part of the surgery that I do is dead simple. It's one of the most basic neurosurgery procedures imaginable. I think there's evidence that some version of it has been done for thousands of years. There are examples from ancient Egypt of healed or partially healed trepanations, and from Peru or ancient times in South America, where these proto-surgeons would drill holes in people's skulls, presumably to let out evil spirits but maybe to drain blood clots. There's evidence of bone healing around the edge, meaning the people at least survived some months after the procedure. What we're doing is making a cut in the skin on the top of the head over the area of the brain that is the most potent representation of hand intentions. If you are an expert concert pianist, this part of your brain is lighting up the entire time you're playing. We call it the hand knob. It's all the finger movements, all of that is just firing away. There's a little squiggle in the cortex right there, one of the folds in the brain is kind of doubly folded right on that spot. You can look at it on an MRI and say that's the hand knob. Then you do a functional test in a special kind of MRI called a functional MRI (fMRI), and this part of the brain lights up when people—even quadriplegic people whose brains aren't connected to their finger movements anymore—imagine finger movements. So we can identify that part of the brain in anyone preparing to enter our trial and say, okay, that part of the brain we confirm is your hand intention area. I'll make a little cut in the skin, flap the skin open just like opening the hood of a car, only a lot smaller. Make a perfectly round 1-inch diameter hole in the skull, remove that bit of skull, open the lining of the brain—the covering of the brain, it's like a little bag of water that the brain floats in—and then show that part of the brain to our robot. This is where the robot shines. It can come in and take these tiny electrodes, much smaller than human hair, and precisely insert them into the cortex, into the surface of the brain, to a very precise depth in a very precise spot that avoids all the blood vessels coating the surface of the brain. After the robot's done with its part, the human comes back in and puts the implant into that hole in the skull and covers it up, screwing it down to the skull and sewing the skin back together. The whole thing is a few hours long. It's extremely low risk compared to the average neurosurgery involving the brain that might open up a deep part of the brain or manipulate blood vessels in the brain. This opening on the surface of the brain with only cortical micro-insertions carries significantly less risk than a lot of the tumor or aneurysm surgeries that are routinely done. Cortical micro-insertions via robot and computer vision are designed to avoid the blood vessels exactly.

我知道你有点偏见，但让我们比较一下人类和机器。在人类文明发展的这个阶段，人类外科医生擅长什么，机器人外科医生又擅长什么？

I know you're a bit biased here, but let's compare human and machine. What are human surgeons able to do well, and what are robot surgeons able to do well at this stage of our human civilization development?

这是个好问题。人类是通用机器。我们能够适应异常情况，能够随时改变计划。我记得很多年前在圣地亚哥做的一个手术，计划是在耳后开一个小孔，重新放置一根压迫到面部神经（三叉神经）的血管。当那根血管压迫神经时，会引起难以忍受的剧烈刺痛，人们形容像被电棍击中一样。那个漂亮而优雅的手术就是把这根血管从神经上移开。手术团队进去后开始移动血管，然后发现那根血管上有一个巨大的动脉瘤，在术前扫描中并不明显。所以计划必须动态改变。人类外科医生对此毫无问题；我们受过处理所有这类情况的训练。机器人在这种情况下就不会做得那么好，至少以它们目前的形态。全机器人手术，比如 Neuralink 手术中的电极插入部分，是按照既定计划进行的。人类可以中断流程并改变计划，但机器人无法中途改变计划。它按照编程和指令运行。它非常精确地完成工作，但在应对变化条件方面没有很大的自由度。作为外科医生，当你进入一个情况时，可能会有很多种让你惊讶的方式。可能会有一些细微的东西需要你动态调整来纠正，而机器人目前不擅长这个。我认为我们正处在一个 AI 新时代的黎明，机器人响应能力的参数可以极大地拓宽。你不能看着一辆自动驾驶汽车说它在非常狭窄的参数下运行。如果一只鸡跑过马路，它不一定被专门编程来处理这种情况，但 Waymo 或自动驾驶的特斯拉会毫无问题地做出适当反应。手术机器人还没有达到那个水平，但给它时间。可能会有很多半自主的可能性，比如机器人外科医生可以说这个情况完全熟悉，或者这个情况不熟悉，在不熟悉的情况下人类可以接管。基本上，要非常保守：这个肯定没问题，没有意外，然后让人类处理剩下的。

That's a good question. Humans are general-purpose machines. We're able to adapt to unusual situations, we're able to change the plan on the fly. I remember a surgery I was doing many years ago down in San Diego where the plan was to open a small hole behind the ear and go reposition a blood vessel that had come to lay on the facial nerve, the trigeminal nerve. When that blood vessel lays on the nerve, it can cause intolerable, horrific shooting pain that people describe like being zapped with a cattle prod. The beautiful, elegant surgery is to go move this blood vessel off the nerve. The surgery team went in there and started moving this blood vessel, and then found that there was a giant aneurysm on that blood vessel that was not easily visible on the preop scans. So the plan had to dynamically change. The human surgeons had no problem with that; we're trained for all those things. Robots wouldn't do so well in that situation, at least in their current incarnation. Fully robotic surgery, like the electrode insertion portion of the Neuralink surgery, goes according to a set plan. The humans can interrupt the flow and change the plan, but the robot can't really change the plan midway through. It operates according to how it was programmed and how it was asked to run. It does its job very precisely, but not with a wide degree of latitude in how to react to changing conditions. There could be a very large number of ways that you could be surprised as a surgeon when you enter a situation. There could be subtle things that you have to dynamically adjust to correct, and robots are not good at that currently. I think we are at the dawn of a new era with AI, where the parameters for robot responsiveness can be dramatically broadened. You can't look at a self-driving car and say that it's operating under very narrow parameters. If a chicken runs across the road, it wasn't necessarily programmed to deal with that specifically, but a Waymo or self-driving Tesla would have no problem reacting to that appropriately. Surgical robots aren't there yet, but give it time. There could be a lot of semi-autonomous possibilities, where a robotic surgeon could say this situation is perfectly familiar or the situation is not familiar, and in the not familiar case a human could take over. Basically, be very conservative: okay, this for sure has no issues, no surprises, and then let the humans handle the rest.

处理那些意外情况和边缘案例，等等。嗯，那是一种可能性。所以你觉得最终你会失业，你的神经外科医生工作？地球上不会剩下多少神经外科医生了。

Deal with the surprises with the edge cases, all that. Yeah, that's one possibility. So like you think eventually you'll be out of the job, your job being neurosurgeon? Humans, there will not be many neurosurgeons left on this Earth.

在我的职业生涯中，我并不担心自己的工作。我想我会告诉我的孩子不一定非要从事这个行业，这取决于 20 年后的情况。

I'm not worried about my job in the course of my professional life. I think I would tell my kids not necessarily to go in this line of work, depending on how things look in 20 years.

这太迷人了，因为如果我说我有一个职业，那就是编程。如果你问我过去，我不知道，20 年来我会推荐人们做什么，我会告诉他们，去吧，如果你是个程序员，你永远有工作，因为电脑越来越多，而且报酬不错。但后来你发现这些大型语言模型出现了，它们非常擅长生成代码。是的，所以一夜之间你可能会惊讶，哇，人类的贡献到底是什么？但然后你开始思考，好吧，人类确实有能力，就像你说的，处理新情况。在编程方面，就是提出新想法来解决问题的能力。机器似乎还做不到这一点。而当风险很高时，比如在手术中，尤其是神经外科手术，机器人真正取代人类的风险就很高。但有趣的是，在 Neuralink 的案例中，存在人机协作。

It's so fascinating because I mean, if I have a line of work, I would say it's programming. And if you ask me for the last, I don't know, 20 years what I would recommend for people, I would tell them, yeah, go there, you will always have a job if you're a programmer because there's more and more computers and all this kind of stuff, and it pays well. But then you realize these large language models come along and they're really damn good at generating code. Yeah, so it's overnight you could be surprised like, wow, what is the contribution of the human really? But then you start to think, okay, it does seem that humans have ability, like you said, to deal with novel situations. In the case of programming, it's the ability to kind of come up with novel ideas to solve problems. It seems like machines aren't quite yet able to do that. And when the stakes are very high, when it's life critical as it is in surgery, especially neurosurgery, then the stakes are very high for a robot to actually replace a human. But it's fascinating that in this case of Neuralink, there's a human-robot collaboration.

是的，是的。我做我不能做的部分，它做它不能做的部分。我们是朋友。

Yeah, yeah. It's I do the parts I can't do and it does the parts I can't do. And we are friends.

我看到有很多练习在进行。所以 Neuralink 的一切都经过极其严格的测试。但我看到的一件事是，有一个代理体用来进行手术。是的，这对机器人和人类，对整个流程中的每个人都是如此。练习手术是什么样的？

I saw that there's a lot of practice going on. So I mean everything in Neuralink is tested extremely rigorously. But one of the things I saw is that there's a proxy on which the surgeries are performed. Yeah, so this is both for the robot and for the human, for everybody involved in the entire pipeline. What's that like, practicing the surgery?

这非常紧张。人类手术中没有类似的情况。人类手术有点像一种手工艺，代代相传，从师傅直接传给徒弟。是的，我的意思是，你学习成为人类外科医生的方式就是在人类身上做手术。首先你看你的教授做很多手术，然后他们最终把手术中简单的部分交给你，然后是更复杂的部分。随着你对手术目的和意义的理解加深，你承担更多责任。在理想情况下，事情并不总是一帆风顺。在 Neuralink 的案例中，方法有点不同。我们当然尽可能在动物身上练习；我们做了数百次动物手术。当要进行第一次人类手术时，我们有一个了不起的工程师团队建造了极其逼真的模型。特别是工程师 Fran Romano，他建造了一个在定制 3D 打印头骨中搏动的大脑，完全匹配患者的解剖结构，包括他们的面部和头皮特征。所以当我能够练习时，我的意思是，它在所有细节上都尽可能接近真实情况，包括在这个定制头部上连接一个人体模型。所以当我们进行练习手术时，我们会把那个身体推进 CT 扫描仪，进行模拟 CT 扫描，再推回来，进行所有正常的安全检查，口头确认：“停下，这位患者，我们确认他的身份是模型编号 blah blah blah，”然后使用标准的术中神经导航设备、标准的手术钻，在 Neuralink 进行所有练习手术的同一个手术室里，在完全正确的位置打开大脑。并且让头骨打开，大脑搏动，这增加了机器人完美精确地规划并将电极插入正确深度和位置的难度。所以是的，我们在为这次手术进行如此广泛的练习方面开创了新局面。

It's pretty intense. So there's no analog to this in human surgery. Human surgery is sort of this artisanal craft that's handed down directly from master to pupil over the generations. Yes, I mean literally the way you learn to be a surgeon on humans is by doing surgery on humans. First you watch your professors do a bunch of surgery, and then finally they put the trivial parts of the surgery into your hands, and then the more complex parts. And as your understanding of the point and the purposes of the surgery increases, you get more responsibility. In the perfect condition, it doesn't always go well. In Neuralink's case, the approach is a bit different. We of course practiced as far as we could on animals; we did hundreds of animal surgeries. And when it came time to do the first human, we had an amazing team of engineers build incredibly lifelike models. One of the engineers, Fran Romano in particular, built a pulsating brain in a custom 3D-printed skull that matches exactly the patient's anatomy, including their face and scalp characteristics. And so when I was able to practice that, I mean it's as close as it really reasonably should get to being the real thing in all the details, including having a manikin body attached to this custom head. And so when we were doing the practice surgeries, we'd wheel that body into the CT scanner and take a mock CT scan, and wheel it back in and conduct all the normal safety checks verbally: "Stop, this patient, we're confirming his identification is mannequin number blah blah blah," and then opening the brain in exactly the right spot using standard operative neuronavigation equipment, standard surgical drills, in the same OR that we do all of our practice surgeries in at Neuralink. And having the skull open and have the brain pulse, which adds a degree of difficulty for the robot to perfectly precisely plan and insert those electrodes to the right depth and location. And so yeah, we kind of broke new ground on how extensively we practiced for this surgery.

所以有一个历史性时刻，对 Neuralink 来说是一个重要的里程碑，对人类来说也是，今年 1 月第一个人类接受了 Neuralink 植入。带我回顾一下 Noland 的手术。作为其中一员感觉如何？

So there was a historic moment, a big milestone for Neuralink, in part for humanity, with the first human getting a Neuralink implant in January of this year. Take me through the surgery on Noland. What did it feel like to be part of this?

是的，我们很幸运有 Barrow 神经学研究所这样不可思议的合作伙伴。我认为他们是世界上首屈一指的神经外科医院。他们让试验的启动变得尽可能容易，并在如何安排细节方面提供了巨大的专业知识。这在某些方面是一次压力大得多的手术。我的意思是，尽管结果在参与者安全方面没有特别的问题，但观察者的数量，你知道，人数，医院里挤满了人的会议室在观看直播，为手术的完美进行加油。这增加了压力，即使是最高强度的神经外科手术，比如切除肿瘤或放置深部脑刺激电极，也不常见。而且这在人类身上从未做过；存在未知的未知。所以整个团队都有适度的紧张感，不知道我们是否会遇到，比如说，意料之外的大脑运动程度，或者大脑下沉导致大脑远离头骨，使插入变得困难，或者其他未知的未知问题。幸运的是，一切顺利，那次手术是我们能想象到的最顺利的结果之一。

Yeah, well, we're lucky to have just incredible partners at the Barrow Neurologic Institute. They are, I think, the premier neurosurgical hospital in the world. They made everything as easy as possible for the trial to get going and helped us immensely with their expertise on how to arrange the details. It was a much more high-pressure surgery in some ways. I mean, even though the outcome wasn't particularly in question in terms of our participant's safety, the number of observers, you know, the number of people, there's conference rooms full of people watching live streams in the hospital, rooting for this to go perfectly. And that just adds pressure that is not typical for even the most intense production neurosurgery, say removing a tumor or placing deep brain stimulation electrodes. And it had never been done on a human before; there were unknown unknowns. And so definitely a moderate pucker factor there for the whole team, not knowing if we were going to encounter, say, a degree of brain movement that was unanticipated, or a degree of brain sag that took the brain far away from the skull and made it difficult to insert, or some other unknown unknown problem. Fortunately, everything went well, and that surgery was one of the smoothest outcomes we could have imagined.

你紧张吗？我的意思是，你有点像超级碗比赛中的四分卫那种情况。

Were you nervous? I mean, you're kind of quarterback in like the Super Bowl kind of situation.

极度紧张。极度紧张。当一切顺利时我非常高兴，然后结束后，期待第二次手术。

Extremely nervous. Extremely. I was very pleased when it went well, and then when it was over, looking forward to number two.

是啊，即使有那么多练习，你也从未处于如此高风险的境地，有那么多人在观看。

Yeah, even with all that practice, all of that, you've never been in a situation that's so high stakes in terms of people watching.

而且我们可能也应该提到，考虑到媒体的运作方式，很多人，你知道，也许以一种阴暗的方式希望它不顺利。

And we should also probably mention, given how the media works, a lot of people, you know, maybe in a dark kind of way hoping it doesn't go well.

嗯，我认为财富很容易被憎恨或嫉妒之类的，而且我认为有一个围绕驱动点击量的整个行业，坏消息对点击量很好。所以任何将事件变成坏消息的方式都对点击量非常有利。这很糟糕，因为我认为它给人们施加压力，阻止人们尝试解决真正困难的问题，因为要解决困难的问题，你必须进入未知领域，你必须做以前从未做过的事情，你必须承担风险。是的，经过计算的风险，你必须采取各种安全预防措施，但仍然是风险。我只是希望有更多对冒险的庆祝，而不是人们只是等着看。

Well, I think wealth is easy to hate or envy or whatever, and I think there's a whole industry around driving clicks, and bad news is great for clicks. So any way to take an event and turn it into bad news is going to be really good for clicks. It just sucks because I think it puts pressure on people, it discourages people from trying to solve really hard problems, because to solve hard problems you have to go into the unknown, you have to do things that haven't been done before, and you have to take risks. Yeah, calculated risks, you have to do all kinds of safety precautions, but risks nevertheless. And I just wish there would be more celebration of that, of the risk-taking, versus like people just waiting on.

那些在场边等着看失败、然后指出失败的人，这很糟糕，但这次一切顺利，真的很棒。不过我觉得这是不必要的压力。现在有一个活生生的人参与其中，他的健康取决于手术的成功，如果你还希望它出问题，那你得是个相当坏的人。所以希望人们能照照镜子，最终意识到这一点。

The ones on the sidelines like waiting for failure, yeah, and then pointing out the failure. It sucks, but in this case it's really great that everything went just flawlessly. But it's unnecessary pressure, I would say. Now that there is a human with literal skin in the game, a participant whose well-being rides on this doing well, you have to be a pretty bad person to be rooting for that to go wrong. So hopefully people look in the mirror and realize that at some point.

你实际上有没有坐在前排，比如看着机器人工作？你看到了什么？

Did you get to actually have a front-row seat, like watch the robot work? What did you get to see?

你能看到整个过程。因为需要一名医生负责整个过程中的所有医疗决策。我在暴露大脑并将其呈现给机器人后，退出了手术区域，然后在机器人的软件界面上放置了目标点，告诉机器人每个线程的插入位置。这操作是用鼠标完成的，虽然听起来没什么大不了。

You get to see the whole thing. I mean, because an MD needs to be in charge of all the medical decision-making throughout the process. I unscrubbed from the surgery after exposing the brain and presenting it to the robot, and placed the targets on the robot's software interface that tells the robot where it's going to insert each thread. That was done with my hand on the mouse, for whatever that's worth.

所以是你放置的目标点？哦，酷。那么机器人通过计算机视觉提供一堆候选点，你来做最终决定，对吧？

So you were the one placing the targets? Oh cool. So the robot, with computer vision, provides a bunch of candidates and you kind of finalize the decision, right?

这个团队的软件工程师非常出色。他们提供了一个界面，你可以用套索工具选择大脑的主要区域，它会自动避开该区域的血管，并自动放置一堆目标点。这让人机操作员能够选择非常好的大脑区域，并在我们认为最有可能产生高保真手指运动和手臂运动意图信号的区域密集放置目标点。

The software engineers on this team are amazing. They provided an interface where you can essentially use a lasso tool to select a prime area of brain real estate, and it will automatically avoid the blood vessels in that region and automatically place a bunch of targets. That allows the human robot operator to select really good areas of brain and make dense applications of targets in those regions — the regions we think are going to have the most high-fidelity representations of finger movements and arm movement intentions.

我看过这些图像，对我这种有强迫症的人来说，这有种奇怪的满足感。有个 subreddit 叫“奇怪的满足感”。看到不同的目标点避开血管，同时最大化这些位置对信号的效用，真的很满足。感觉很好。

I've seen images of this, and for me with OCD, it's oddly satisfying. There's a subreddit called oddly satisfying. It's oddly satisfying to see the different target sites avoiding the blood vessels and also maximizing the usefulness of those locations for the signal. It just feels good.

作为一个对脑出血有本能反应的人，我可以告诉你，看着电极本身进入大脑而不引起出血，这非常令人满足。

As a person who has a visceral reaction to the brain bleeding, I can tell you it's extremely satisfying watching the electrodes themselves go into the brain and not cause bleeding.

你说当一切完美时，感觉是如释重负。目前你能进入大脑多深，最终又能多深？在 Neuralink 这边，似乎越深挑战越大。

You said the feeling was of relief when everything went perfectly. How deep in the brain can you currently go, and eventually go? On the Neuralink side, it seems the deeper you go, the more challenging it becomes.

广义上讲神经外科，我们可以到达任何地方。对我来说，将深部脑刺激电极放置在大脑底部附近是常规操作，从顶部进入，将大约 2 毫米的导线一直穿到大脑底部。这并不革命性，很多人都这么做。我们可以用很高的精度完成。我每月用 Globus 的机器人做几次这种手术，相当常规。

Talking broadly about neurosurgery, we can get anywhere. It's routine for me to put deep brain stimulating electrodes near the very bottom of the brain, entering from the top and passing about a 2mm wire all the way into the bottom of the brain. That's not revolutionary; a lot of people do that. We can do that with very high precision. I use a robot from Globus to do that surgery several times a month. It's pretty routine.

在那种情况下，你的眼睛看到什么？你用什么技术来可视化你的位置，照亮你的路径？

What are your eyes in that situation? What are you seeing? What kind of technology can you use to visualize where you are, to light your way?

软件方面有一个很酷的过程。你获取术前 MRI，这是整个大脑极高分辨率的数据。让患者入睡，将他们的头放在一个非常牢固地固定头骨的框架中，然后在患者入睡且戴着框架时进行头部 CT 扫描。然后在软件中融合 MRI 和 CT。你基于 MRI 制定计划，可以看到大脑深处的这些核团。在 CT 上你看不到它们，但如果你相信两张图像的融合，那么你就能间接知道它们在 CT 上的位置，从而间接知道相对于固定在头部的钛框架，这些目标点在哪里。这是 60 年代的技术，根据入口点和目标手动计算轨迹，并用一些看起来古怪的钛合金执行器，上面带有小刻度标记。现代版本是使用机器人——就像你在特斯拉工厂看到的那种用于制造汽车的小型 C 形臂。这个小机械臂可以显示你从术前 MRI 中计划的轨迹，并建立一个非常坚固的支架，通过它你可以在头骨上钻一个小孔，将一根细小的刚性导线深入大脑的那个空心区域，将电极穿过空心导线，然后移除除电极之外的所有东西。最终电极被非常精确地放置在远离头骨表面的位置。这是标准技术，已经在世界上存在一段时间了。Neuralink 目前完全专注于皮层目标、表面目标，因为没有简单的方法将数百根导线深入大脑而不造成大量损伤。所以你的问题：我看到什么？我在屏幕上看到 MRI。我看不到 DBS 电极在到达深部目标途中经过的所有东西。这种方法公认大约有百分之一的患者会因盲目将导线送入大脑深处而导致脑部某处出血。这对 Neuralink 来说是不可接受的安全状况。我们的出发点是要让安全性大幅提高——可能提高两到三个数量级。足够安全，以至于你或我这样没有严重医疗问题的人，有一天在午休时可能会说：“好啊，我装一个，我一直想升级到最新版本。”所以安全约束很高，我们还没有确定任意接近大脑深处目标的最终解决方案。

It's a cool process on the software side. You take a pre-operative MRI that's extremely high-resolution data of the entire brain. You put the patient to sleep, put their head in a frame that holds the skull very rigidly, and then take a CT scan of their head while they're asleep with that frame on. Then you merge the MRI and the CT in software. You have a plan based on the MRI where you can see these nuclei deep in the brain. You can't see them on CT, but if you trust the merging of the two images, then you indirectly know on the CT where that is, and therefore indirectly know where in reference to the titanium frame screwed to their head those targets are. This is 60s technology to manually compute trajectories given the entry point and target, and dial in some goofy-looking titanium actuators with manual actuators with little tick marks on them. The modern version of that is to use a robot — just like a little C-arm you might see building cars at the Tesla factory. This small robot arm can show you the trajectory that you intended from the preop MRI and establish a very rigid holder through which you can drill a small hole in the skull and pass a small rigid wire deep into that area of the brain that's hollow, put your electrode through that hollow wire, and then remove all of that except the electrode. So you end up with the electrode very precisely placed far from the skull surface. That's standard technology, already been out in the world for a while. Neuralink right now is focused entirely on cortical targets, surface targets, because there's no trivial way to get say hundreds of wires deep inside the brain without doing a lot of damage. So your question: what do you see? I see an MRI on a screen. I can't see everything that that DBS electrode is passing through on its way to that deep target. It's accepted with this approach that there's going to be about one in a hundred patients who have a bleed somewhere in the brain as a result of passing that wire blindly into the deep part of the brain. That's not an acceptable safety profile for Neuralink. We start from the position that we want this to be dramatically — maybe two or three orders of magnitude — safer than that. Safe enough that you or I without a profound medical problem might on our lunch break someday say, 'Yeah sure, I'll get that, I've been meaning to upgrade to the latest version.' So the safety constraints are high, and we haven't settled on a final solution for arbitrarily approaching deep targets in the brain.

这很有趣，因为你需要以某种方式避开血管。也许有创造性的方法来做同样的事情，比如绘制出高分辨率的血管几何结构，然后你就可以盲目进入。但如何以超级稳定的方式绘制出来？那里有很多有趣的挑战。

It's interesting because you have to avoid blood vessels somehow. Maybe there are creative ways of doing the same thing, like mapping out high-resolution geometry of blood vessels, and then you can go in blind. But how do you map that out in a way that's super stable? There are a lot of interesting challenges there.

没错，但表面还有很多工作要做。确实如此。我们在将电极缝合到脊髓方面取得了巨大进展，作为脊髓损伤的潜在解决方案。这将允许大脑植入物将运动意图转化为脊髓植入物，从而影响先前瘫痪的手臂和腿的肌肉收缩。这太不可思议了。所以努力的方向是尝试将大脑与脊髓、与外周神经系统连接起来。这有多难？我们在动物身上已经有了非常粗糙的版本。太棒了。是的，我们已经做到了。

Right, but there's a lot to do on the surface. Exactly. So we've got vision on the surface. We've actually made a huge amount of progress sewing electrodes into the spinal cord as a potential workaround for a spinal cord injury. That would allow a brain-mounted implant to translate motor intentions to a spine-mounted implant that can affect muscle contractions in previously paralyzed arms and legs. That's just incredible. So the effort there is to try to bridge the brain to the spinal cord to the peripheral nervous system. How hard is that to do? We have that working in very crude forms in animals. That's amazing. Yeah, we've done it.

他能够用数字方式移动光标。而你们这里是在做同样的通信，但用的是实际的效应器。是的，这太迷人了。

Where he's able to digitally move the cursor. Here you're doing the same kind of communication but with the actual effectors that you have. Yeah, that's fascinating.

是的，我们让麻醉的动物做抓握和腿部运动，模拟行走模式。虽然还处于早期阶段，但这类技术的未来很光明。瘫痪患者应该期待那个光明的未来，他们将拥有选择。

Yeah, so we have anesthetized animals doing grasp and moving their legs in a sort of walking pattern. Again, early days, but the future is bright for this kind of thing. People with paralysis should look forward to that bright future. They're going to have options.

还有很多中间或额外的选择，比如用 Optimus 机器人，控制它的手臂、手指和手，作为假肢也在不断进步。还有外骨骼。所以这些是相辅相成的。不过，直到我深入研究 Neuralink 之后，我才真正理解在数字方面能做的事情有多少。这种数字心灵感应，我之前不太理解：你真的可以像你描述的那样，在手结区映射意图。你只需要想象、思考，那个意图就能映射到数字世界中的实际动作。没错。而且现在数字世界能做的事情越来越多，它可以让你重新连接到外部世界，如果你四肢瘫痪，它能让你获得自由和独立。这真的很强大，你可以走得很远。

And there are a lot of intermediate or extra options where you take an Optimus robot, like the arm, and be able to control the arm. The fingers, the hands of the arm, sure, as a prosthetic are getting better too. Exoskeletons, yeah. So that goes hand in hand. Although I didn't quite understand until doing more research about Neuralink how much you can do on the digital side. This digital telepathy, I didn't quite understand that you can really map the intention as you described in the hand knob area. You can map the intention: just imagine it, think about it, that intention can be mapped to actual action in the digital world. Right. And now more and more can be done in the digital world that it can reconnect you to the outside world, allow you to have freedom and independence if you're a quadriplegic. That's really powerful. You can go really far with that.

是的，我们的第一位参与者非常了不起。他不断打破世界纪录，而且乐在其中。这太棒了。

Yeah, our first participant is incredible. He's breaking world records left and right, and he's having fun with it. It's great.

回到手术这个话题，你的整个历程。你私下跟我说你周一有手术，所以你一直在做手术。也许是个愚蠢的问题：怎样才能擅长手术？

Just going back to the surgery, your whole journey. You mentioned to me offline you have surgery on Monday, so you're doing surgery all the time. Maybe a ridiculous question: what does it take to get good at surgery?

练习，重复。和其他任何事情一样。有无数种说法，人们说着同样的话，卖书推销，但你可以称之为一万小时定律，或者说是花掉生命中的一部分时间，专注于这件事，痴迷于变得更好。重复、谦逊，认识到自己在任何阶段都不完美，意识到技术还有改进空间，对来自不同视角的反馈和指导保持开放。然后就是不断追求更好的意愿。幸运的是，如果你不是反社会者，我认为你的病人每天来复诊时都会带来这种动力。他们迫使你一直想要做得更好。

Practice, repetitions. It's the same as anything else. There are a million ways of people saying the same thing and selling books saying it, but do you call it 10,000 hours? Do you call it spending some chunk of your life, some percentage of your life, focusing on this, obsessing about getting better at it? Repetitions, humility, recognizing that you aren't perfect at any stage along the way, recognizing you've got improvements to make in your technique, being open to feedback and coaching from people with a different perspective on how to do it. And then just the constant will to do better. Fortunately, if you're not a sociopath, I think your patients bring that with them to the office visits every day. They force you to want to do better all the time.

是的，必须进步。我的意思是，那是一个你可以帮助的真实的人。

Yeah, just step up. I mean, it's a real human being that you can help.

是的，所以每次手术，即使是完全相同的手术，在不同人之间会有很多变异性吗？

Yeah, so every surgery, even if it's the same exact surgery, is there a lot of variability between that surgery and a different person?

相当多。一个很好的例子是，手结区上方颅骨相对于身体轴线的角度变化很大。有些人的颅骨非常平坦，而有些人的颅骨在那个区域非常陡峭。这会影响他们的头部如何固定在我们使用的框架中，以及机器人如何接近颅骨。人的身体构造就像你在街上看到的人一样各不相同。身体形状和大小的变异性，与我们在脑解剖和颅骨解剖中看到的变异性一样大。有些人我们不得不排除在试验之外，因为他们的颅骨太厚或太薄，或者头皮太厚或太薄。我想我们涵盖了大约中间 97% 的人，但你无法涵盖所有人体解剖的变异性。

A fair bit. I mean, a good example for us is that the angle of the skull relative to the normal plane of the body axis of the skull over hand knob is pretty wide variation. Some people have really flat skulls, and some people have really steeply angled skulls over that area. That has consequences for how their head can be fixed in the frame we use, and how the robot has to approach the skull. People's bodies are built as differently as the people you see walking down the street. There's as much variability in body shape and size as we see in brain anatomy and skull anatomy. There are some people we've had to exclude from our trial for having skulls that are too thick or too thin, or scalp that's too thick or too thin. I think we have the middle 97% or so of people, but you can't account for all human anatomy variability.

实际有多软、有多乱？我上过生物课，图表总是非常干净清晰。神经科学的神经元图片也总是很漂亮。但每当我看到真实大脑的图片时，它们都……我不知道是怎么回事。那么生物系统在现实中到底有多复杂？弄清楚发生了什么有多难？

How much mushiness and mess is there? I took biology classes, the diagrams are always really clean and crisp. Neuroscience pictures of neurons are always really nice. But whenever I look at pictures of real brains, they're all... I don't know what is going on. So how much are biological systems in reality? How hard is it to figure out what's going on?

一旦你真正习惯了，其实还好。这就是经验、技能和教育发挥作用的地方。如果你看过一千个大脑，就更容易在脑海中剥离掉那些遮挡脑沟和脑回的血管，也就是大脑表面的褶皱模式。偶尔，当你刚开始做这个，打开颅骨时，它和你根据 MRI 预期看到的不一样。随着经验增加，你学会剥离那层血管，看到下面大脑的褶皱模式，并将其作为定位的地标。

Not too bad once you really get used to it. That's where experience, skill, and education really come into play. If you stare at a thousand brains, it becomes easier to mentally peel back, say, blood vessels that are obscuring the sulci and gyri, the wrinkle pattern of the surface of the brain. Occasionally, when you're first starting to do this and you open the skull, it doesn't match what you thought you were going to see based on the MRI. With more experience, you learn to peel back that layer of blood vessels and see the underlying pattern of wrinkles in the brain and use that as a landmark for where you are.

褶皱就是地标。我之前描述的手结区，就是大脑褶皱的一种模式。它有点像希腊字母 Omega 形状的区域。所以你能认出手结区。如果我给你看一千个大脑，每个给你一分钟，你会说：“对，就是这个。”所以大脑那个区域在几何和拓扑上确实有一些独特性。

The wrinkles are a landmark. So I was describing hand knob earlier, that's a pattern of the wrinkles in the brain. It's a sort of Greek letter Omega shaped area of the brain. So you could recognize the hand knob area. If I show you a thousand brains and give you one minute with each, you'd be like, 'Yep, that's that.' So there is some uniqueness to that area of the brain in terms of the geometry, the topology of the thing.

它大概在什么位置？你有一条沿着顶部延伸的脑区，叫做初级运动皮层。我相信你见过那个覆盖在大脑表面的侏儒图，那个奇怪的小家伙有巨大的嘴唇和巨大的手。那个家伙的腿在大脑顶部，脸和手臂区域在下面，再往下是嘴、唇、舌区域。所以手就在那里，而控制语言的大脑区域，至少在大多数人的左脑，就在手区下方。你身体里任何随意运动的肌肉，绝大多数都参考那条脑区，或者说那些意图来自那条脑区。手结区的褶皱就在正中间。而视觉在后面，也靠近表面，但视觉更深一些。这就涉及到你关于能深入多深的问题。要实现视觉，我们不能只做大脑表面；我们必须能够深入，不需要像 DBS 那样深，但可能比我们习惯的手部插入深一厘米左右。那是在进行中的工作，是一系列需要克服的新挑战。

Where is it about? You have this strip of brain running down the top called the primary motor area. I'm sure you've seen the picture of the homunculus laid over the surface of the brain, the weird little guy with huge lips and giant hands. That guy sort of lays with his legs up at the top of the brain, and face, arm areas farther down, and then some mouth, lip, tongue areas farther down. So the hand is right in there, and then the areas that control speech, at least on the left side of the brain in most people, are just below that. Any muscle that you voluntarily move in your body, the vast majority of that references that strip, or those intentions come from that strip of brain. The wrinkle for hand knob is right in the middle of that. And vision is back here, also close to the surface, but vision is a little deeper. So this gets to your question about how deep you can get. To do vision, we can't just do the surface of the brain; we have to be able to go in, not as deep as we'd have to go for DBS, but maybe a centimeter deeper than we're used to for hand insertions. That's work in progress, a new set of challenges to overcome.

顺便说一下，你提到了犹他阵列，我刚看到一张图片。那东西看起来真吓人。

By the way, you mentioned the Utah array, and I just saw a picture of that. That thing looks terrifying.

因为它很硬。而你看我们的线程，它们是柔性的。你觉得这种用柔性线程将电极递送到神经元旁边的做法有什么有趣之处？

It's because it's rigid. And if you look at the threads, they're flexible. What can you say that's interesting to you about the flexible threads approach to deliver the electrodes next to the neurons?

是的，我的意思是，那里的目标来自于……

Yeah, I mean, the goal there comes from...

经验上，我们是站在巨人的肩膀上——那些制造犹他阵列、并在我们出现之前就使用了数十年的人。Neuralink 的出现部分源于这种技术路径，起因是犹他阵列会频繁失效：那些刚性电极，那些用气锤直接敲进大脑的尖刺，会引发强烈的免疫反应，最终在电极周围形成疤痕组织。所以当我到加州理工时，安德森实验室的一个项目就是研究能否用化疗来防止疤痕形成。你看，当你把一床钉子钉进大脑，再用化疗来防止疤痕时，情况就已经很糟糕了。就像，也许我们走偏了，伙计们，也许需要根本性的重新设计。而 Neuralink 采用高度柔性的微小电极，避免了大量出血和免疫反应——那些刚性电极被敲入大脑时就会引发这些反应。我们看到，我们的电极寿命、功能以及电极周围脑组织的健康状况都非常出色。在动物模型中，这已经持续了数年。

Experience, I mean, we stand on the shoulders of people that made Utah Arrays and used Utah Arrays for decades before we ever even came along. Neuralink arose partly from this approach to technology, arising out of a need recognized after Utah Arrays would fail routinely because the rigid electrodes—those spikes that are literally hammered using an air hammer into the brain—those spikes generate a bad immune response that encapsulates the electrode spikes in scar tissue essentially. So one of the projects being worked on in the Anderson Lab at Caltech when I got there was to see if you could use chemotherapy to prevent the formation of scar. Like, you know, things are pretty bad when you're jamming a bed of nails into the brain and then treating that with chemotherapy to try to prevent scar tissue. It's like, you know, maybe we've gotten off track here, guys. Maybe there's a fundamental redesign necessary. And so Neuralink's approach of using highly flexible tiny electrodes avoids a lot of the bleeding, avoids a lot of the immune response that ends up happening when rigid electrodes are pounded into the brain. And so what we see is our electrode longevity and functionality, and the health of the brain tissue immediately surrounding the electrode, is excellent. I mean, it goes on for years now in our animal models.

大多数人对于大脑生物学有什么不了解？我们提到了血管系统——这确实很有趣。我认为最有趣、也许最被低估的事实是：大脑几乎控制着一切。比如，随便举个例子，假设你想要一个控制生育的开关——能够打开或关闭生育功能。大脑中确实存在调节生育的合法靶点。再比如血压——你想调节血压，大脑中也有相应的合法靶点。那些乍看之下不是大脑问题的事情，都可能在大脑中得到解决。所以我认为，对于困扰人类的各种问题，大脑作为主要治疗领域还远未被充分探索。

What do most people not understand about the biology of the brain? We mentioned the vasculature—that's really interesting. I think the most interesting, maybe underappreciated fact is that it really does control almost everything. I mean, for a random example, imagine you want a lever on fertility—you want to be able to turn fertility on and off. There are legitimate targets in the brain itself to modulate fertility. Say, blood pressure—you want to modulate blood pressure, there are legitimate targets in the brain for doing that. Things that aren't immediately obvious as brain problems are potentially solvable in the brain. So I think it's an underexplored area for primary treatments of all the things that bother people.

这个视角非常迷人。就像，很多我们以为与大脑无关的疾病，可能只是大脑中某个问题的症状。问题的真正根源、主要根源，就在大脑里。

That's a really fascinating way to look at it. Like, there's a lot of conditions we might think have nothing to do with the brain, but they might just be symptoms of something that actually started in the brain. The actual source of the problem, the primary source, is something in the brain.

是的，并非总是如此。我是说，肾病是真实存在的。但大脑中有一些杠杆可以影响所有这些系统。大脑里有旋钮——开关和旋钮，一切都源于那里。

Yeah, not always. I mean, you know, kidney disease is real. But there are levers you can pull in the brain that affect all of these systems. There are knobs—on/off switches and knobs in the brain from which all this originates.

你会把 Neuralink 芯片植入自己的大脑吗？

Would you have a Neuralink chip implanted in your brain?

会。我认为目前的使用场景是用鼠标。我已经能做到了，所以没有价值主张。仅从安全角度考虑，我明天就会做。

Yeah. I think the use case right now is using a mouse. I can already do that, so there's no value proposition. On safety grounds alone, sure, I would do it tomorrow.

你知道，你说鼠标的使用场景是在研究了所有这些之后，部分原因只是看到 Nolan 玩得那么开心。如果你能用鼠标达到非常高的比特率，比如能够交互——因为想想智能手机上的滑动操作，那是革命性的。我们与事物交互的方式——很微妙，你意识不到，但你能触摸手机并用手指滚动。这改变了一切。人们曾确信你需要键盘来打字，而其中有很多人机交互方面的东西改变了我们与计算机的交互方式。所以鼠标也可能有一个特定的速度，会改变一切。是的，就像你可以极快地点击屏幕。如果那样——我似乎是为了更快速地与数字设备交互而植入 Neuralink。

You know, you say the use case of the mouse is after researching all this, and part of it is just watching Nolan have so much fun. If you can get that bits per second really high with the mouse, like being able to interact—because if you think about the way on the smartphone, the way you swipe, that was transformational. How we interact with a thing—it's subtle, you don't realize it, but you're able to touch a phone and scroll with your finger. That changed everything. People were sure you need a keyboard to type, and there's a lot of HCI aspects to that that changed how we interact with computers. So there could be a certain rate of speed with the mouse that would change everything. Yes, like you might be able to just click around a screen extremely fast. And if that—I seem to have gotten the Neuralink for much more rapid interaction with digital devices.

是的，我认为从大脑中记录语言意图也可能改变一切。对普通人来说，键盘是一种相当笨拙的人机界面，需要大量训练，而且普通人能达到的最高性能差异很大。我认为去掉这个环节，直接拥有一个自然的语言到计算机的界面，可能会改变很多人的情况。

Yeah, I think recording speech intentions from the brain might change things as well. The value proposition for the average person—a keyboard is a pretty clunky human interface, requires a lot of training, and is highly variable in the maximum performance that the average person can achieve. I think taking that out of the equation and just having a natural word-to-computer interface might change things for a lot of people.

如果这就是人们这么做的原因，那会很有趣。即使语音转文字极其准确——目前还不是，但假设它变得超级准确——如果人们选择 Neuralink 只是为了避免说话时的尴尬，比如在公共场合对着手机说话像个傻瓜，那会很有趣。这是一个真实的约束。

It'd be hilarious if that is the reason people do it. Even if you have speech-to-text that's extremely accurate—it currently isn't, right, but say it got super accurate—it'd be hilarious if people went for Neuralink just so you avoid the embarrassing aspect of speaking, like looking like a douchebag speaking to your phone in public, which is a real constraint.

是的，我的意思是，通过骨传导外壳，它可以是一个隐形的耳机，并且能够将想法输入软件并得到响应——这听起来有点像嵌入式超级智能。如果你能无声地询问任何主题的维基百科文章，并在外界没有任何可观察变化的情况下被朗读出来——首先，标准化测试就过时了。如果在用户体验方面做得好，它可能会改变——我不知道它是否会改变社会，但它确实可以像智能手机那样，创造一种我们与数字设备交互方式的转变。

Yeah, I mean, with a bone-conducting case that can be an invisible headphone, and the ability to think words into software and have it respond to you—that starts to sound sort of like embedded superintelligence. If you can silently ask for the Wikipedia article on any subject and have it read to you without any observable change happening in the outside world—for one thing, standardized testing is obsolete. If it's done well on the UX side, it could change—I don't know if it transforms society, but it really can create a kind of shift in the way we interact with digital devices, the way that a smartphone did.

是的，我会——只要研究清楚所有涉及的安全问题——我完全会尝试。所以它不必达到某种不可思议的程度，比如连接到你的视觉或其他地方——或者连接到整个大脑。可能只是连接到手部运动区——你就能有很多有趣的人机交互可能性。

Yeah, I would—just having to look into the safety of everything involved—I would totally try it. So it doesn't have to go to some incredible thing where it connects to your vision or to some other—like it connects all over your brain. That could be like just connecting to the hand knob—you might have a lot of interesting human-computer interaction possibilities.

是的，这真的很有趣。学术方面的技术正在以光速发展。我认为加州大学戴维斯分校 Sergey Stavisky 实验室有一篇非常出色的论文，基本上初步解决了语音解码问题。他们以非常高的准确率解码了大约 12.5 万个单词。所以你就是想着那个词？

Yeah, that's really interesting. And the technology on the academic side is progressing at light speed. I think there was a really amazing paper out of UC Davis, Sergey Stavisky's lab, that basically made an initial solve of speech decode. It was something like 125,000 words that they were getting with very high accuracy. So you're just thinking the word?

是的，想着那个词，你就能得到它。哦，天哪。就像你必须要有说话的意图，对吧？所以用那种内心声音。对我来说，能够进行意图到信号的映射真是太神奇了。你只需要想象自己在做这件事，如果得到反馈说它真的有效，你就能变得非常擅长。你的大脑首先会调整，然后你像发展任何其他技能一样发展它——比如盲打。你用同样的方式发展它。对我来说，这真的非常迷人。是的，甚至只是玩玩它。比如我会为了能玩这个而植入 Neuralink，只是为了玩我的大脑学习这项技能的能力。就像学习打字或学习移动鼠标的技能。这是另一种移动鼠标的技能，不是用我的……

Yeah, thinking the word and you're able to get it. Yeah, oh boy. Like you have to have the intention of speaking it, right? So do that inner voice. It's so amazing to me that you can do the intention-to-signal mapping. All you have to do is just imagine yourself doing it, and if you get the feedback that it actually worked, you can get really good at that. Your brain will first of all adjust, and you develop it like any other skill—like touch typing. You develop it in that same kind of way. That is really, to me, just really fascinating. Yeah, to be able to even to play with that honestly. Like I would get a Neuralink just to be able to play with that, just to play with the capacity, the capability of my mind to learn this skill. It's like learning the skill of typing or learning the skill of moving a mouse. It's another skill of moving the mouse, not with my...

物理身体，但用我的大脑。我等不及想看人们会用它做什么。我觉得我们现在就像穴居人，像在用棍子敲石头，还以为自己在做音乐。等到这些技术更普及时，就会出现相当于钢琴的东西，有人能用大脑以我们未曾预料的方式创作艺术。我很期待。把它交给一个青少年。每当我觉得自己擅长某事时，我总会去……我不知道，即使是在玩电子游戏的比特率上，你会发现如果你把它给一个青少年，把你的 Link 给一个青少年，只要数量够大，他们擅长的事情，他们能达到每秒几百比特。即使只是当前的技术，可能也是因为那种数字上升的成瘾性，就像提升和训练，因为它几乎是一种技能。而且另一端有软件适应你，尤其是当适应算法越来越好时，你们就像一起学习。是的，我们现在只是触及皮毛。还有太多事情要做。

Physical body but with my mind. I can't wait to see what people do with it. I feel like we're cavemen right now, we're like banging rocks with a stick and thinking that we're making music. At some point when these are more widespread, there's going to be the equivalent of a piano, that someone can make art with their brain in a way that we didn't even anticipate. I'm looking forward to it. Give it to a teenager. Anytime I think I'm good at something, I'll always go to... I don't know, even with the bits per second of playing a video game, you realize you give it to a teen, you give your link to a teenager, just a large number of them, the kind of stuff they get good at, they're going to get like hundreds of bits per second. Even just with the current technology, probably just because it's also addicting, how the number goes up aspect of it, of like improving and training, because it is almost like a skill. And plus there's a software on the other end that adapts to you, and especially if the adapting procedure algorithm becomes better and better, you like learning together. Yeah, we're scratching the surface on that right now. There's so much more to do.

那么在完全相反的另一端，你体内植入了一个 RFID 芯片。这是个很微妙的东西，一个被动设备，你用它来解锁像存放顶级机密的保险箱之类的？你用它做什么？背后有什么故事？

So on the complete other side of it, you have an RFID chip implanted in you. This is a subtle thing, it's a passive device that you use for unlocking like a safe with top secrets, or what do you use it for? What's the story behind it?

我不是第一个。有一整个怪咖生物黑客社区在做这种事。我认为早期用例之一是存储私人加密货币钱包密钥之类的。我稍微涉足了一下，觉得挺好玩。你体内某个地方植入了比特币，你不能说在哪里。是的，实际上是的。这就像现代版的在沙发垫子里找零钱。我把一些我认为一文不值的孤儿加密货币放进去，然后忘了几年，回来发现某个社区的人很喜欢它，把它的价值抬高了，所以涨了 50 倍。所以那些垫子里有很多零钱。这太搞笑了。但主要用途还是作为技术演示器。它上面有我的名片，你可以用手机触碰扫描，它能打开我家前门，诸如此类简单的东西。这是一个很酷的步骤，在体内植入东西是一个很酷的飞跃。我的意思是，这也许和 Neuralink 是类似的飞跃，因为对很多人来说，把东西放进身体里，把电子设备放进生物系统，是一个巨大的飞跃。是的，我们对皮肤屏障有一种神秘感。我们对膝关节置换、髋关节置换、牙科植入物完全没问题，但对头骨所代表的无形屏障仍然存在神秘感。我认为这需要像任何其他实用屏障一样对待。问题不是打开头骨有多不可思议，问题是我们能提供什么好处。

I'm not the first one. There's this whole community of weirdo biohackers that have done this stuff. And I think one of the early use cases was storing private crypto wallet keys and whatever. I dabbled in that a bit and had some fun with it. You have some Bitcoin implanted in your body somewhere, you can't tell where. Yeah, actually yeah. It was the modern day equivalent of finding change in the sofa cushions. I put some orphan crypto on there that I thought was worthless and forgot about it for a few years, went back and found that some community of people loved it and had propped up the value of it, and so it had gone up 50 fold. So there was a lot of change in those cushions. That's hilarious. But the primary use case is mostly as a tech demonstrator. It has my business card on it, you can scan that in by touching it to your phone, it opens the front door to my house, whatever simple stuff. It's a cool step, it's a cool leap to implant something in your body. I mean it has perhaps that's a similar leap to a Neuralink, because for a lot of people that kind of notion of putting something inside your body, something electronic inside a biological system, is a big leap. Yeah, we have a kind of a mysticism around the barrier of our skin. We're completely fine with knee replacements, hip replacements, dental implants, but there's a mysticism still around the invisible barrier that the skull represents. And I think that needs to be treated like any other pragmatic barrier. The question isn't how incredible is it to open the skull, the question is what benefit can we provide.

那么从你做过的所有手术，从你对大脑的理解来看，神经可塑性有多大作用？大脑的适应能力如何，比如即使在手术愈合或适应术后情况时？

So from all the surgeries you've done, from everything you understand the brain, how much does neuroplasticity come into play? How adaptable is the brain, for example, just even in the case of healing from surgery or adapting to the post-surgery situation?

对我来说和我这个年龄段的人来说，可悲的答案是可塑性随年龄增长而下降，愈合能力也随年龄增长而下降。我头发太白了，对此无法乐观。有一些理论方法可以通过电刺激来增加可塑性，但还没有完全被证明是足够稳健的机制，可以广泛提供给人们。但我认为有理由乐观，我们可能会找到一些有用的东西，比如植入电极来改善学习。当然，最近 Nicholas Schiff、Jonathan Baker 等人做了一些非常了不起的工作，他们有一组中度创伤性脑损伤患者，在大脑深处一个叫做中央正中核或靠近中央正中核的核团中植入了电极。当他们向大脑那个区域施加少量电流时，几乎就像电子咖啡因。他们能够改善人们的注意力和专注力，能够提高人们执行任务的能力。我记得有一个案例，一个人原本无法工作，设备打开后，他找到了一份工作。这对我来说是 Neuralink 和类似技术的圣杯之一。从纯粹的功利主义角度来看，我们能否让人们再次有能力在经济上照顾自己和家人？我们能否让一个完全依赖他人、甚至可能需要大量护理资源的人，变得完全独立，照顾自己，回馈社区？我认为这是一个非常有吸引力的命题，也是激励我和 Neuralink 许多同事工作的动力。

The answer that is sad for me and other people of my demographic is that plasticity decreases with age, healing decreases with age. I have too much gray hair to be optimistic about that. There are theoretical ways to increase plasticity using electrical stimulation, nothing that is totally proven out as a robust enough mechanism to offer widely to people. But I think there's cause for optimism that we might find something useful in terms of say an implanted electrode that improves learning. Certainly there's been some really amazing work recently from Nicholas Schiff, Jonathan Baker, and others, who have a cohort of patients with moderate traumatic brain injury who have had electrodes placed in a deep nucleus in the brain called the central median nucleus, or just near central median nucleus. And when they apply small amounts of electricity to that part of the brain, it's almost like electronic caffeine. They're able to improve people's attention and focus, they're able to improve how well people can perform a task. I think in one case someone who was unable to work after the device was turned on, they were able to get a job. And that's sort of one of the Holy Grails for me with Neuralink and other technologies like this. From a purely utilitarian standpoint, can we make people able to take care of themselves and their families economically again? Can we make it so someone who's fully dependent and even maybe requires a lot of caregiver resources, can we put them in a position to be fully independent, taking care of themselves, giving back to their communities? I think that's a very compelling proposition and what motivates a lot of what I do and what a lot of the people at Neuralink are working for.

这是一个很酷的可能性：如果你植入 Neuralink，大脑会适应，大脑的其他部分也会适应并整合它。大脑做到这一点的能力非常有趣，可能我们还不清楚能做到什么程度。但你现在把一个外部的东西连接到它，尤其是当它进行刺激时，生物大脑和外部电子大脑协同工作，可能性非常有趣，虽然未知但很有趣。感觉大脑非常擅长适应任何东西。但当然，它本身就是一个系统，一切都有其目的，所以你不想过多地干扰它。就像从生态系统中消灭一个物种，你不知道微妙的相互联系和依赖关系是什么。大脑无疑是一个微妙而复杂的野兽，我们不知道我们做出的每一个改变的所有潜在下游后果。

It's just a cool possibility that if you put a Neuralink in there, the brain adapts, the other part of the brain adapts too, and integrates it. The capacity of the brain to do that is really interesting, probably unknown to the degree to which you can do that. But you're now connecting an external thing to it, especially once it's doing stimulation, the biological brain and the electronic brain outside of it working together, the possibilities are really interesting, still unknown but interesting. It feels like the brain is really good at adapting to whatever. But of course it is a system that by itself is already like everything serves the purpose, and so you don't want to mess with it too much. It's like eliminating a species from an ecology, you don't know what the delicate interconnections and dependencies are. The brain is certainly a delicate complex beast, and we don't know every potential downstream consequence of a single change that we make.

你觉得自己会做 P1 手术，然后是 P2、P3、P4、P5，越来越多的人类手术吗？

Do you see yourself doing P1 surgeries of P2, P3, P4, P5, just more and more humans?

我认为，如果需要我来做所有手术，那说明公司存在某种脆弱性或失败。我非常希望努力实现的是，手术过程如此简单、如此稳健，以至于任何人都能做。我们希望摆脱需要大量专业知识或丰富经验才能成功完成手术的现状，让它尽可能简单、可推广。

I think it's a certain kind of brittleness or a failure on the company's side if we need me to do all the surgeries. I think something that I would very much like to work towards is a process that is so simple and so robust on the surgery side that literally anyone could do it. We want to get away from requiring intense expertise or intense experience to have this successfully done, and make it as simple and translatable as possible.

我希望地球上的每一位神经外科医生都能毫无障碍地做这个。我觉得离允许非神经外科医生做这个的监管环境还很远，但也不是不可能。好吧，我报名。你有没有把机器人 R1 拟人化？比如给它起个名字？你觉得它像一起工作的朋友，还是抢饭碗的敌人？

Would love it if every neurosurgeon on the planet had no problem doing this. I think we're probably far from a regulatory environment that would allow people that aren't neurosurgeons to do this, but not impossible. All right, I'll sign up for that. Did you ever anthropomorphize the robot R1? Like, do you give it a name? Do you see it as like a friend that's working together with you? Or an enemy who's going to take the job?

在某种程度上，这是一种复杂的关系。所有好的关系都是复杂的。有趣的是，手术中间有一部分我需要和机器人肩并肩站着。所以如果你在房间里读肢体语言，你会知道那是我的战友。我们在共同解决同一个问题。是啊，我没觉得被威胁。

To a certain degree, it's a complex relationship. All the good relationships are. It's funny when in the middle of the surgery there's a part where I stand shoulder-to-shoulder with the robot. So if you're in the room reading the body language, you know it's my brother in arms there. We're working together on the same problem. Yeah, I'm not threatened by it.

继续这么告诉自己吧。

Keep telling yourself that.

这些年你做过的所有手术、帮助过的人，以及你提到的高风险，这些如何改变了你对生死的理解？

How have all the surgeries you've done over the years, the people you've helped, and the high stakes you've mentioned, how has that changed your understanding of life and death?

它给你一种非常直观的感受，虽然可能听起来老套，但它让你真切地感到死亡是不可避免的。一方面，作为神经外科医生，你深陷于那些难以想象的悲剧中。年轻父母去世，留下一个四岁的孩子。另一方面，这又稍微减轻了刺痛，因为你看到死亡是多么普遍到令人麻木。我绝对没有机会避免它。我知道技术乐观主义者和长寿爱好者会不同意这个 0.00% 的估计，但我认为我们这一代没有任何机会避免它。熵是一股强大的力量，而我们是非常精致、脆弱、易碎的 DNA 机器，无法承受我们受到的宇宙射线轰击。所以一方面，每个曾经活着的人都已经或将会死去。另一方面，这是最难想象的事情之一——让你爱的人消失。我相信你也有已经不在世的朋友，甚至很难想起他们。我希望我已经达到了涅槃的境界，死亡不再刺痛，我不再担心。但我至少可以说，我对它的必然性感到坦然，尽管还没找到如何消除其中的悲剧。当我想起我的孩子没有我，或者我没有他们，或者我的妻子，也许我已经在理智上接受了它的必然性，但失去所爱之人的痛苦，我觉得我还没有理解它的存在层面。就像这一切会结束。但生活起来却感觉不会结束，你活得好像它不会结束。而这道光、这个意识，将在某一刻不复存在，也许就是今天，这让我充满了欧内斯特·贝克尔所说的恐惧。这是一种真实的恐惧。我认为人们并不总是诚实地面对它有多可怕。你越能真正思考它，它就越可怕。这不是一件简单的事。如果你真的能完全接受这一点，那很难。但我认为这就是斯多葛学派这样做的原因，因为它能帮你振作起来，珍惜你活着的每一刻，它美丽，而它终将结束又令人恐惧。就像你在寒冷中颤抖，一个无助的孩子，这种感觉。然后它让你，当你拥有温暖、安全和爱时，真正去珍惜它们。

It gives you a very visceral sense, and this may sound trite, but it gives you a very visceral sense that death is inevitable. On one hand, as a neurosurgeon, you're deeply involved in these just hard-to-fathom tragedies. Young parents dying, leaving a four-year-old behind. And on the other hand, it takes the sting out of it a bit because you see how mind-numbingly universal death is. There's zero chance that I'm going to avoid it. I know techno-optimists and longevity buffs would disagree with that 0.00% estimate, but I don't see any chance that our generation is going to avoid it. Entropy is a powerful force, and we are very ornate, delicate, brittle DNA machines that aren't up to the cosmic ray bombardment we're subjected to. So on the one hand, every human that has ever lived died or will die. On the other hand, it's just one of the hardest things to imagine inflicting on anyone you love, having them gone. I'm sure you've had friends that aren't living anymore, and it's hard to even think about them. I wish I had arrived at the point of Nirvana where death doesn't have a sting, I'm not worried about it. But I can at least say that I'm comfortable with the certainty of it, if not having found out how to take the tragedy out of it. When I think about my kids either not having me or me not having them, or my wife, maybe I've come to accept the intellectual certainty of it, but the pain of losing the people you love, I don't think I've come to understand the existential aspect of it. Like this is going to end. It certainly feels like it's not going to end, you live life like it's not going to end. And the fact that this light, this consciousness, is going to no longer be one moment, maybe today, it fills me with Ernest Becker's terror. It's a real fear. I think people aren't always honest with how terrifying it is. The more you are able to really think through it, the more terrifying it is. It's not such a simple thing. If you really can load that in, it's hard. But I think that's why the Stoics did it, because it helps you get your together and appreciate that every moment you're alive is just beautiful, and it's terrifying that it's going to end. It's like you're shivering in the cold, a child helpless, this kind of feeling. And then it makes you, when you have warmth, safety, love, to really appreciate it.

我觉得有时候在你的位置上，你提到用盔甲来看待死亡，这可能会让你看不到生命的有限性，因为如果你一直盯着它，可能会崩溃。所以很高兴知道你还在为此挣扎。有神经外科医生的一面，也有作为人的一面，而作为人的那一面仍然能够挣扎，感受到恐惧和痛苦。

I feel like sometimes in your position, when you mentioned armor to see death, it might make you not be able to see the finiteness of life, because if you kept looking at that it might break you. So it's good to know that you're kind of still struggling with that. There's the neurosurgeon and then there's a human, and the human is still able to struggle with that and feel the fear and the pain.

这确实让你问自己，你能看多少次这些，而不说“我再也做不下去了”。但我认为它给了你一个机会去珍惜你今天还活着。我有三个孩子和一个了不起的妻子，我真的很开心。事情很好。我能参与一个我认为重要的项目，我认为它推动我们前进。我是一个非常幸运的人。这是人类潜在巨大飞跃的早期步骤。这非常有趣。很酷的是，你在历史上读到所有这些事情，都是早期阶段。我一直在读关于探险家的书，在去亚马逊之前，他们会第一次探索亚马逊丛林。那些就是早期步骤。或者进入太空的早期步骤，任何学科——物理和数学——的早期步骤。很酷的是，从宏观尺度来看，这些是深入人类大脑的早期步骤。不仅仅是观察大脑，而是能够与人类大脑互动。它将帮助很多人，但也可能帮助我们理解里面到底发生了什么。

It definitely makes you ask the question of how many of these can you see and not say I can't do this anymore. But I think it gives you an opportunity to just appreciate that you're alive today. I've got three kids and an amazing wife, and I'm really happy. Things are good. I get to help on a project that I think matters, I think it moves us forward. I'm a very lucky person. It's the early steps of a potentially gigantic leap for humanity. It's a really interesting one. It's cool because you read about all this stuff in history where it's the early days. I've been reading about explorers before going to the Amazon, they would go and explore the Amazon jungle for the first time. Those are the early steps. Or early steps into space, early steps in any discipline in physics and mathematics. And it's cool because on the grand scale, these are the early steps into delving deep into the human brain. Not just observing the brain, but being able to interact with the human brain. It's going to help a lot of people, but it also might help us understand what the hell's going on in there.

最终，我们想给人们更多可以拉动的杠杆。你想给人们选择。如果你能给某人一个旋钮，让他们调节自己有多快乐，我觉得这会让人们非常不安。但想想重度抑郁症，想想这个国家令人震惊的自杀率，并试着在那个背景下证明那种不安是合理的。你可以给人们一个旋钮来消除自杀意念、自杀意图。我会给他们那个旋钮。我不知道你怎么证明不这样做是合理的。你可以想想世界上正在发生的所有痛苦。每一个正在受苦的人，就像一个发光的红点。痛苦越多，它就越亮。你看到的是人类痛苦的地图。任何能让你大规模调暗那束痛苦之光的科技都非常令人兴奋，因为有很多人在受苦，而且他们中的大多数都在默默承受。我们太经常把目光移开了。我们应该记住那些受苦的人，因为再说一次，他们中的大多数都在默默承受。

Ultimately, we want to give people more levers that they can pull. You want to give people options. If you can give someone a dial that they can turn on how happy they are, I think that makes people really uncomfortable. But talk about major depressive disorder, talk about people that are committing suicide at an alarming rate in this country, and try to justify that queasiness in that light. You can give people a knob to take away suicidal ideation, suicidal intention. I would give them that knob. I don't know how you justify not doing that. You can think about all the suffering that's going on in the world. Every single human being that's suffering right now, it's like a glowing red dot. The more suffering, the more it's glowing. You just see the map of human suffering. And any technology that allows you to dim that light of suffering on a grand scale is pretty exciting, because there's a lot of people suffering, and most of them suffer quietly. We turn our eyes away too often. We should remember those who are suffering, because once again, most of them are suffering quietly.

在更大的尺度上，社会的结构。人们对我们的社会有很多抱怨……

On a grander scale, the fabric of society. People have a lot of complaints about how our social...

社会结构运转如何、政治运转如何——这些东西归根结底也是神经化学的产物，对吧？政治是由拥有人类大脑的个体组成的，它运转得好坏在某种意义上是可调节的。比如说，移除我们的成瘾行为，或者调节我们对社交媒体的成瘾、对愤怒的成瘾、对分享最愤怒政治推文的成瘾。我不认为这能导向一个功能健全的社会。如果人们有办法调节这种适应不良的行为，社会可能会获得巨大收益。也许我们能更和谐地朝着有益的目标共同努力。

Fabric is working or not working, how our politics is working or not working—those things are made of neurochemistry too, in aggregate, right? Like our politics is composed of individuals with human brains, and the way it works or doesn't work is potentially tunable. In the sense that, I don't know, say remove our addictive behaviors, or tune our addictive behaviors for social media, or our addiction to outrage, our addiction to sharing the most angry political tweet we can find. I don't think that leads to a functional society. And if you had options for people to moderate that maladaptive behavior, there could be huge benefits to society. Maybe we could all work together a little more harmoniously toward useful ends.

存在一个最佳平衡点。就像你提到的，你不想完全消除人性中所有阴暗面，因为它们在某种程度上是让整体运转所必需的。但存在一个最佳平衡点。

There's a sweet spot. Like you mentioned, you don't want to completely remove all the dark side of human nature, because those are somehow necessary to make the whole thing work. But there's a sweet spot.

是的，我同意。你得受点苦，但别多到让你失去希望。

Yeah, I agree. You got to suffer a little, just not so much that you lose hope.

在你做过的所有手术中，你有没有在里面看到过意识？有没有像发光的东西？

When all the surgeries you've done, have you seen consciousness in there? Ever was there like a glowing light?

我知道我有这种感觉：我从未找到过它。好吧，从未移除过它。就像《哈利·波特》里的摄魂怪。我有这种感觉：意识远没有我们的本能想宣称的那么神奇。在我看来，它是一个有用的类比，用来思考大脑中的意识是什么。我们对“触摸皮肤并知道被触摸的是什么”有着非常直观的理解。我认为意识就是那种感觉映射，应用于大脑自身的思维过程。所以我的意思是：意识是你大脑某个部分活跃的感觉。你感觉到它在工作。你感觉到大脑中思考红色事物、有翼生物或咖啡味道的那个部分。你感觉到这些大脑部分在活跃，就像我感觉自己的手掌被触摸一样。而那个感觉大脑工作的感官系统就是意识。

I know I have this sense that I never found it. Okay, never removed it. You know, like a dementor in Harry Potter. I have this sense that consciousness is a lot less magical than our instincts want to claim it is. It seems to me like a useful analog for thinking about what consciousness is in the brain. You know, we have a really good intuitive understanding of what it means to say touch your skin and know what's being touched. I think consciousness is just that level of sensory mapping applied to the thought processes in the brain itself. So what I'm saying is: consciousness is the sensation of some part of your brain being active. So you feel it working. You feel the part of your brain that thinks of red things, or winged creatures, or the taste of coffee. You feel those parts of your brain being active the way that I'm feeling my palm being touched. And that sensory system that feels the brain working is consciousness.

太精彩了。就像触摸东西时的触觉一样。意识是你感觉到自己大脑在运作、在思考、在感知的感觉。这不像时空扭曲或某种量子场效应，对吧？一点也不神奇。人们总想把意识归因于某种真正不同的东西。而且有一个悠久的历史：人们总是用物理学的最新发现来解释意识，因为意识是你所能想到的最神奇、最超凡的东西。人们总想对意识这么做。我不认为那是必要的。它只是一种非常有用且令人满足的感知大脑运作的方式。而且正如我们所说，一个了不起的大脑。

So brilliant. It's the same way it's a sensation of touch when you're touching a thing. Consciousness is the sensation of you feeling your brain working, your brain thinking, your brain perceiving. Which isn't like a warping of spacetime or some quantum field effect, right? It's nothing magical. People always want to ascribe to consciousness something truly different. And there's this awesome long history of people looking at whatever the latest discovery in physics is to explain consciousness, because it's the most magical, the most out-there thing that you can think of. And people always want to do that with consciousness. I don't think that's necessary. It's just a very useful and gratifying way of feeling your brain work. And as we said, one heck of a brain.

是的，我们周围看到的一切，我们热爱的一切，一切美好的事物——都来自像这样的头脑。全都是你颅骨内发生的电活动。就我个人而言，我很感激有像你这样的人在探索它运作的所有方式以及所有可以改进的方式。非常感谢你今天来交谈。这很愉快。

Yeah, everything we see around us, everything we love, everything that's beautiful—it came from brains like these. It's all electrical activity happening inside your skull. And I, for one, am grateful there are people like you that are exploring all the ways that it works and all the ways it can be made better. Thank you so much for talking today. It's been a joy.

感谢收听本期与 Matthew MacDougall 的对话。现在，亲爱的朋友们，有请 Neuralink 脑机接口软件负责人 Bliss Chapman。你告诉我，你见过数百名脊髓损伤或肌萎缩侧索硬化症患者，你在 Neuralink 工作的动力源于想帮助他们。能描述一下这种动力吗？

Thanks for listening to this conversation with Matthew MacDougall. And now, dear friends, here's Bliss Chapman, brain interface software lead at Neuralink. You told me that you've met hundreds of people with spinal cord injuries or with ALS, and that your motivation for helping at Neuralink is grounded in wanting to help them. Can you describe this motivation?

是的，首先，感谢所有我有机会交谈的人，感谢他们与我分享他们的故事。我不认为有任何方式能像他们自己那样有力地讲述他们的故事。但简而言之，我反复听到的是，肌萎缩侧索硬化症或严重脊髓损伤患者，在身体基本无法移动的情况下，归根结底是在寻求独立。这对不同的人意味着不同的事。对一些人来说，它意味着能够再次独立交流，无需在脸上戴东西，无需护理员往他们嘴里放东西。对一些人来说，它意味着能够再次工作的独立，能够足够高效地数字操作电脑以找到工作，能够养活自己，能够搬出去，最终在家人可能不再照顾他们时能够自给自足。对一些人来说，它简单到只是能够在孩子跑开或对别的东西感兴趣之前及时回应他们。这些都是非常个人化且非常人性化的问题。在与这些人交谈时，我一次又一次地感到震撼的是，这实际上是一个工程问题。这是一个有了正确资源和正确团队就能取得很大进展的问题。归根结底，我认为这是一个非常鼓舞人心的信息，也是让我每天兴奋起床的原因。

Yeah, first, just a thank you to all the people I've gotten a chance to speak with for sharing their stories with me. I don't think there's any world really in which I can share their stories in as powerful a way as they can. But just to summarize at a very high level, what I hear over and over again is that people with ALS or severe spinal cord injury, in a place where they basically can't move physically anymore, really at the end of the day are looking for independence. And that can mean different things for different people. For some folks, it can mean the ability just to be able to communicate again independently, without needing to wear something on their face, without needing a caretaker to be able to put something in their mouth. For some folks, it can mean independence to be able to work again, to be able to navigate a computer digitally efficiently enough to be able to get a job, to be able to support themselves, to be able to move out, and ultimately be able to support themselves after their family maybe isn't there anymore to take care of them. And for some folks, it's as simple as just being able to respond to their kid in time before they run away or get interested in something else. And these are deeply personal and very human problems. And what strikes me again and again when talking with these folks is that this is actually an engineering problem. This is a problem that with the right resources, with the right team, we can make a lot of progress on. And at the end of the day, I think that's a deeply inspiring message and something that makes me excited to get up every day.

所以这既是工程问题——例如脑机接口可以赋予他们与世界互动的能力；另一方面，这也是一个工程问题——让世界其他地方对四肢瘫痪患者更加无障碍。

So it's both an engineering problem in terms of a BCI, for example, that can give them capabilities where they can interact with the world, but also on the other side, it's an engineering problem for the rest of the world to make it more accessible for people living with quadriplegia.

是的，我想从更广阔的视角来看这个问题。我非常支持任何在这个问题领域工作的人。所以除了脑机接口，我也很高兴、很兴奋并愿意尽我所能支持那些研究眼动追踪系统、语音检测系统、头部追踪器、鼠标棒或四控棒的人。我见过许多工程师和社区里的人正是做这些事的。我认为，对于我们要帮助的人来说，解决方案的复杂程度并不重要，只要问题解决了就行。我想强调的是，有很多解决方案可以帮助解决这些问题，脑机接口只是其中之一。具体来说，脑机接口我认为有几个优势。而能立即认识到这一点的人通常是脊髓损伤或某种瘫痪患者。通常你不需要向他们解释为什么这可能有帮助；这通常是不言自明的。但对于我们这些没有严重脊髓损伤或不认识肌萎缩侧索硬化症患者的人来说，为什么需要脑植入物来连接和操作电脑并不明显。而且这非常微妙，以至于我在第一个 Neuralink 临床试验中与 Noland 合作时学到了很多，从他口中理解了这个设备为什么对他有影响。

Yeah, and I'll take a broad view sort of lens on this for a second. I think I'm very in favor of anyone working in this problem space. So beyond BCI, I'm happy and excited and willing to support in any way I can folks working on eye tracking systems, working on speech detection systems, working on head trackers or mouse sticks or quad sticks. And I've met many engineers and folks in the community that do exactly those things. And I think for the people we're trying to help, it doesn't matter what the complexity of the solution is, as long as the problem is solved. And I want to emphasize that there can be many solutions out there that can help with these problems, and BCI is one of a collection of such solutions. So BCI in particular, I think offers several advantages here. And I think the folks that recognize this immediately are usually the people who have spinal cord injury or some form of paralysis. Usually you don't have to explain to them why this might be something that could be helpful; it's usually pretty self-evident. But for the rest of us, folks that don't live with severe spinal cord injury or who don't know somebody with ALS, it's not often obvious why you would want a brain implant to be able to connect and navigate a computer. And it's surprisingly nuanced to the degree that I've learned a huge amount just working with Noland in the first Neuralink clinical trial and understanding from him in his words why this device is impactful for him.

这是一个很微妙的话题。有可能出现这样的情况：即使你能用鼠标杆之类的东西完成同样的操作——比如在电脑上导航——但他并不是每分每秒都能用到那个鼠标杆。只有当有人能把它放在他面前时，他才能使用。所以，脑机接口（BCI）确实能提供一定程度的独立性和自主性，如果不是它真的成为你身体的一部分，很难通过其他方式实现。所以，要让一个人能用意念控制屏幕上的光标，这其中有很多迷人的方面。你发给我一条信息，我特别喜欢。你说：“我是面试并选定 P1 的团队成员之一。我在手术室里参与了第一次人体手术，实时监测大脑发出的信号。我几乎每天都和用户一起工作，开发新的用户体验范式和解码策略，我还是那个团队的一员，在信号质量下降时，我们找到了将有用的 BCI 恢复到新的世界纪录水平的方法。”我们会讨论其中的每一个方面，但先宏观地看，作为那个团队的一员，参与这个历史性的第一次，感觉如何？

It's a nuanced topic. It can be the case that even if you can achieve the same thing, for example with a mouse stick when navigating a computer, he doesn't have access to that mouse stick every single minute of the day. He only has access when someone is available to put it in front of him. And so a BCI can really offer a level of independence and autonomy that, if it wasn't literally physically part of your body, it'd be hard to achieve in any other way. So there's a lot of fascinating aspects to what it takes to get someone to be able to control a cursor on the screen with his mind. You texted me something that I just love. You said: 'I was part of the team that interviewed and selected P1. I was in the operating room doing the first human surgery, monitoring live signals coming out of the brain. I work with the user basically every day to develop new UX paradigms, decoding strategies, and I was part of the team that figured out how to recover useful BCI to new world record levels when the signal quality degraded.' We'll talk about every aspect of that, but just zooming out, what was it like to be part of that team and part of that historic first?

是的，对我来说，这是我近 10 年来一直感到兴奋的事情。所以，哪怕只是成为实现它的一小部分，也极其令人激动。在整个过程中，有几个特别的时刻我永远不会真正忘记。其中一个是在实际手术期间。你知道，那时候我已经很了解 Nolan 了，也认识他的家人。所以，当 Nolan 被推进手术室时，最初的反应就是那种“哦”的感觉。但到了那个点，肌肉记忆就接管了，你几乎让身体自动运作。在那个特定手术中，我很幸运地负责监测植入物。所以我的工作就是坐在那里，观察植入物发出的信号，看着线程插入大脑时设备实时流出的脑部数据，基本上就是观察并确保没有出问题，没有需要调查或暂停手术来调试的红旗或故障状况。因为我有了那种旁观手术的视角，我的视角比房间里的大多数人稍微超脱一些。我坐在那里，心里想：“哇，那个大脑动得真厉害。”当你看着我们插入线程的那个小颅骨切开术窗口时，大多数人没有意识到的是，大脑是会动的。当你呼吸、心跳时，大脑会动很多，而且你能肉眼看到。所以，这对我来说是个惊喜，也非常令人兴奋。能够亲眼看到你实际认识并深入交谈过的人的大脑，就在他们的头骨里推动和移动，而他们之前就是用那个大脑和你说话的，现在它就在那里动。

Yeah, I think for me, this is something I've been excited about for close to 10 years now. And so to be able to be even just some small part of making it a reality is extremely exciting. A couple maybe special moments during that whole process that I'll never truly forget. One of them is during the actual surgery. You know, at that point in time, I know Nolan quite well, I know his family. And so I think the initial reaction when Nolan is rolled into the operating room is just 'oh' kind of reaction. But at that point, muscle memory kicks in and you sort of go into, you let your body just do all the talking. And I have the lucky job in that particular procedure to just be in charge of monitoring the implant. So my job is to sit there, to look at the signals coming off the implant, to look at the live brain data streaming off the device as threads are being inserted into the brain, and just to basically observe and make sure that nothing is going wrong, or that there are no red flags or fault conditions that we need to go and investigate or pause the surgery to debug. And because I had that sort of spectator view of the surgery, I had a slightly removed perspective than I think most folks in the room. I got to sit there and think to myself, 'Wow, that brain is moving a lot.' You know, when you look inside the little craniectomy that we stick the threads in, one thing that most people don't realize is the brain moves. The brain moves a lot when you breathe, when your heart beats, and you can see it visibly. So that's something that I think was a surprise to me and very exciting. To be able to see someone's brain who you physically know and have talked with at length, actually pushing and moving inside their skull, and they used that brain to talk to you previously, and now it's right there moving.

实际上，我没想到线程发送方面是这样的。所以 Neuralink 植入物在手术中是激活的，一次一根线程，你就能开始看到信号。是的，所以这也是测试设备是否正常工作的方式之一。

Actually, I didn't realize that in terms of the thread sending. So the Neuralink implant is active during surgery, so one thread at a time, you're able to start seeing the signal. Yeah, so that's part of the way you test that the thing is working.

是的，实际上在手术室里，就在我们完成所有线程插入后，我开始收集所谓的宽带数据。宽带基本上是你从 Neuralink 电极能收集到的最原始的信号形式。它本质上是对局部场电位的测量，或者说是电极测量的电压。我们的应用程序中有一种模式，可以让我们可视化检测到的尖峰的位置。所以它可视化了在宽带信号中——也就是数据的非常原始的形式——神经元实际放电的位置。所以，在整个临床试验中，我永远不会忘记的一个时刻是，在手术室里，当他还在麻醉状态下时，实时看到应用程序中显示出的漂亮尖峰，就实时流式传输到我手中的设备上。

Yeah, so actually in the operating room, right after we sort of finished all the thread insertions, I started collecting what's called broadband data. Broadband is basically the most raw form of signal you can collect from a Neuralink electrode. It's essentially a measurement of the local field potential, or the voltage essentially measured by that electrode. And we have a certain mode in our application that allows us to visualize where detected spikes are. So it visualizes sort of where in the broadband signal, in its very raw form of the data, a neuron is actually spiking. And so one of these moments that I'll never forget as part of this whole clinical trial is seeing live in the operating room, while he's still under anesthesia, beautiful spikes being shown in the application, just streaming live to a device I'm holding in my hand.

所以这是没有经过信号处理的原始数据，信号处理是在这之上的。你看到的是检测到的尖峰，对吧？

So this is no signal processing, the raw data, and then the signal processing is on top of it. You're seeing the spikes detected right?

是的，而且那也是一种用户体验，因为看起来也很漂亮。在那次手术中，房间里实际上有很多摄像师，所以他们也很好奇，想看看。还有几位神经外科医生在房间里，他们都兴奋地看到机器人取代了他们的工作，他们都挤在一部小 iPhone 周围，看着实时脑部数据从他的大脑中流出。

Yeah, and that's a UX too, because that looks beautiful as well. During that procedure, there was actually a lot of cameramen in the room, so they also were curious and wanted to see. There were several neurosurgeons in the room who are all just excited to see robots taking their job, and they're all crowded around a small iPhone watching this live brain data stream out of his brain.

看到机器人完成部分手术是什么感觉？计算机视觉方面，它检测所有避开血管的点，然后在人类监督下，实际完成线程与大脑的高精度连接。

What was that like seeing the robot do some of the surgery? The computer vision aspect where it detects all the spots that avoid the blood vessels, and then obviously with human supervision, then actually doing the high precision connection of the threads to the brain.

是的，这是个好问题。我的回答可能很无趣，但就是很无聊。是的，我已经看过太多次了。

Yeah, it's a good question. My answer is going to be pretty lame here, but it was boring. Yeah, I've seen it so many times.

这正是手术应该有的样子。你希望它无聊。

That's exactly how you want surgery to be. You want it to be boring.

是的，因为我已经看过太多次了。我见过机器人做这个手术实际上有几百次了，所以这只是又一次。所有的练习手术和替代品，这只是又一天。

Yeah, because I've seen it so many times. I've seen the robot do this surgery literally hundreds of times, and so it was just one more time. All the practice surgeries and the proxies, this is just another day.

那么 Nolan 醒来时呢？你记得有这样一个时刻吗：他能够移动光标——不是移动光标，而是从大脑获得信号，从而表明存在连接？

So what about when Nolan woke up? Do you remember a moment where he was able to move the cursor, not move the cursor but get signal from the brain such that it was able to show that there's a connection?

是的，我们非常兴奋地想尽快推进，Nolan 也非常兴奋地想开始。他实际上在手术当天就想开始，但我们非常耐心地等到了第二天早上。那是一个漫长的夜晚。第二天早上，在 ICU 他康复的地方，他想开始，并真正开始了解我们能从他的大脑中测量到什么信号。也许对于不熟悉 Neuralink 系统的人来说，我们把 Neuralink 系统或 Neuralink 植入物植入运动皮层。运动皮层负责表征运动意图之类的东西。所以，如果你想象张开和握紧手，那种信号表征就会出现在运动皮层。如果你想象来回移动手臂或摆动小指，这种信号也会出现在运动皮层。所以，我们开始绘制在任何特定个体的大脑中我们实际能访问到什么信号的方法之一，是通过一个叫做身体映射的任务。身体映射基本上是你向用户展示一个视觉画面，然后说：“嘿，想象做这个。”视觉画面是一个 3D 的手在张开和闭合，或者食指在上下移动。然后你让用户想象那个动作。

Yeah, so we are quite excited to move as quickly as we can, and Nolan was really excited to get started. He wanted to get started actually the day of surgery, but we waited till the next morning very patiently. It's a long night. And the next morning in the ICU where he was recovering, he wanted to get started and actually start to understand what kind of signal we could measure from his brain. And maybe for folks who are not familiar with the Neuralink system, we implant the Neuralink system or the Neuralink implant in the motor cortex. So the motor cortex is responsible for representing things like motor intent. So if you imagine closing and opening your hand, that kind of signal representation would be present in the motor cortex. If you imagine moving your arm back and forth or wiggling a pinky, this sort of signal can be present in the motor cortex. So one of the ways we start to sort of map out what kind of signal we actually have access to in any particular individual's brain is through this task called body mapping. Body mapping is where you essentially present a visual to the user and you say, 'Hey, imagine doing this.' And the visual is a 3D hand opening and closing, or index finger modulating up and down. And you ask the user to imagine that.

显然，你无法看到他们这样做，因为他们瘫痪了，所以你无法看到他们实际移动手臂。但在他们执行这个任务时，你可以记录神经活动，并基本上进行离线建模，检查：我能否预测或检测到与这些不同动作相对应的调制？于是我们做了这个任务，并意识到，嘿，实际上他的某些手部动作确实存在一些调制，这首次表明，好的，我们有可能利用这种调制在现实世界中做有用的事情，例如控制电脑光标。他开始尝试它。你知道，我们第一次向他展示时，我们只是把同样的脑活动实时视图放在他面前，然后说，嘿，你来告诉我们发生了什么。你知道，我们不是你。你能够想象不同的事情，我们知道这正在调节其中一些神经元，所以你来为我们弄清楚这实际上代表什么。于是他玩了一会儿，他说，我还没完全搞明白。他又玩了一会儿，然后说，哦，当我移动这根手指时，我看到这个特定的点开始更频繁地放电。我说，好的，证明一下，再做一次。于是他说，好的，3，2，1，砰。就在他移动的那一刻，你可以看到这个神经元瞬间放电。单个神经元，如果你感兴趣，我可以告诉你确切的通道号，它永远刻在我脑子里了。但那个单通道放电是一个美丽的迹象，表明这是行为调制的神经活动，然后可以用于下游任务，比如解码电脑光标。

Obviously you can't see them do this because they're paralyzed, so you can't see them actually move their arm. But while they do this task, you can record neural activity and you can basically offline model and check: can I predict or can I detect the modulation corresponding with those different actions? And so we did that task and we realized, hey, there's actually some modulation associated with some of his hand motion, which was a first indication that okay, we can potentially use that modulation to do useful things in the world, for example control a computer cursor. And he started playing with it. You know, the first time we showed him it, and we actually just took the same live view of his brain activity and put it in front of him, and we said, hey, you tell us what's going on. You know, we're not you. You're able to imagine different things, and we know that it's modulating some of these neurons, so you figure out for us what that is actually representing. And so he played with it for a bit, he was like, I don't quite get it yet. He played for a bit longer and he said, oh, when I move this finger, I see this particular dot start to fire more. And I said, okay, prove it, do it again. And so he said, okay, 3, 2, 1, boom. And the minute he moved, you can see like instantaneously this neuron is firing. Single neuron, I can tell you the exact channel number if you're interested, it's stuck in my brain now forever. But that single channel firing was a beautiful indication that it was behaviorally modulated neural activity that could then be used for downstream tasks like decoding a computer cursor.

你说单通道，是指与单个电极关联吗？

And when you say single channel, is that associated with a single electrode?

是的，通道和电极可以互换，一共有 1024 个。1024 个，没错。这能行得通，真是不可思议。真的，当我学习这一切并吸收它时，我简直震惊了：意图——你想象自己移动手指——可以转化为信号。而你可以跳过这一步，想象光标移动，或者有移动光标的意图，然后这导致一个信号，进而用来移动光标——这里有太多关于大脑、关于大脑工作方式的令人兴奋的东西可以学习。存在可用的信号这一事实本身就非常强大。

Yeah, so channel and electrode are interchangeable, and there's 1,024 of those. 1,024, yeah. It's incredible that that works. That really, when I was learning about all this and like loading it in, it was just blowing my mind that the intention — you can visualize yourself moving the finger — that can turn into a signal. And the fact that you can then skip that step and visualize the cursor moving, or have the intention of the cursor moving, and that leading to a signal that can then be used to move the cursor — there is so many exciting things there to learn about the brain, about the way the brain works. The very fact of there existing signal that can be used is really powerful.

是的，但这感觉就像是弄清楚如何真正有效地使用这个信号的开始。我还应该——这里有很多迷人的细节。但你提到了身体映射步骤。至少在我看到 Nolan 展示的那个版本中，有一个非常棒的界面，像图形界面，但感觉就像我在未来，因为，你知道，它可视化你移动手，而且有一个非常性感、精致的界面——喂？我不知道是否有语音组件，但感觉就像你在一个很棒的电子游戏中醒来，这是那个电子游戏开头的教程，这就是你应该做的。很酷。

Yep, but it feels like that's just like the beginning of figuring out how that signal could be used really, really effectively. I should also just — there's so many fascinating details here. But you mentioned the body mapping step. At least in the version I saw that Nolan was showing off, there's like a super nice interface, like a graphical interface, but it just felt like I was in the future, because it, you know, I guess it visualizes you moving the hand, and there's a very like a sexy polished interface that — hello? Yeah, I don't know if there's a voice component, but it just felt like it's like when you wake up in a really nice video game and this is a tutorial at the beginning of that video game, this is what you're supposed to do. It's cool.

不，我的意思是，未来应该感觉像未来，但这并不容易实现。我的意思是，它需要简单但不要太简单。是的，我认为这里的用户体验设计组件在 BCI 开发中普遍被低估了。你向用户可视化指令的方式与你能够获得的信号类型之间存在整个交互效应。而你的行为与神经信号对齐的质量，取决于你向用户表达你希望他们做什么的能力。所以是的，我们花了很多时间思考我们如何构建应用程序的用户体验，解码器实际如何工作，它向用户提供的控制界面。所有这些小细节都很重要。

No, I mean, the future should feel like the future, but it's not easy to pull that off. I mean, it needs to be simple but not too simple. Yeah, and I think the UX design component here is underrated for BCI development in general. There's a whole interaction effect between the ways in which you visualize an instruction to the user and the kinds of signal you can get back. And that quality of sort of your behavioral alignment to the neural signal is a function of how good you are at expressing to the user what you want them to do. And so yeah, we spend a lot of time thinking about the UX of how we build our applications, of how the decoder actually functions, the control surfaces it provides to the user. All these little details matter a lot.

所以也许可以更详细地了解一下信号是什么样的，解码是什么样的。有一个 N1 植入物，就像我们提到的，有 1024 个电极，它收集原始数据，原始信号。那个信号是什么样的？在传输之前有哪些不同的步骤？传输的是什么？所有这些东西。

So maybe it'd be nice to get into a little bit more detail of what the signal looks like and what the decoding looks like. So there's an N1 implant that has, like we mentioned, 1,024 electrodes, and that's collecting raw data, raw signal. What does that signal look like? And what are the different steps along the way before it's transmitted? And what is transmitted? All that kind of stuff.

是的，没错，这会很有趣。开始吧。也许在深入我们做什么之前，值得理解我们试图测量什么，因为这决定了我们构建系统的许多要求。我们试图测量的是单个神经元产生动作电位。动作电位是——你可以把它想象成一个小电脉冲，如果你足够近就能检测到。所谓足够近，我的意思是距离那个细胞大约 100 微米以内。100 微米是一个非常非常小的距离。所以任何给定电极能捕捉到的神经元数量只是该电极周围的一个小半径。这里需要理解的另一个基础生物学事实是，当神经元产生动作电位时，该动作电位的宽度约为 1 毫秒。所以从尖峰开始到结束，神经元放电的这个特征特征的整个宽度是 1 毫秒。如果你想检测是否发生了单个尖峰，你需要对该信号进行采样，或者对神经元附近的局部场电位进行采样，频率要远高于每毫秒一次。你需要每毫秒采样很多很多次，才能检测到这实际上是神经元产生动作电位的特征波形。因此，我们在所有 1024 个电极上以大约每秒 20000 次的频率进行采样。每秒 20000 次意味着，对于给定的 1 毫秒窗口，我们有大约 20 个样本来告诉我们该动作电位的精确形状。一旦我们以超高采样率对这些细胞附近的底层电场进行了采样，我们就可以将信号处理为：我们在哪里检测到尖峰，在哪里没有？一种二进制信号：1 或 0，我们在这 1 毫秒内是否检测到尖峰？我们这样做是因为神经活动中实际携带信息的子空间就是尖峰何时发生。基本上，我们解码所需的一切都可以通过尖峰序列的频率特征来捕获或表示，即尖峰在任何给定时间窗口内放电的频率。这使我们能够进行疯狂的压缩，从非常丰富、高密度的信号变成更稀疏、更可压缩的东西，然后可以通过无线电台（例如蓝牙通信）发送出去。

Yeah, yep, this is going to be a fun one. Let's go. So maybe before diving into what we do, it's worth understanding what we're trying to measure, because that dictates a lot of the requirements for the system that we build. And what we're trying to measure is really individual neurons producing action potentials. An action potential is — you can think of it like a little electrical impulse that you can detect if you're close enough. And by being close enough, I mean within let's say 100 microns of that cell. And 100 microns is a very, very tiny distance. So the number of neurons that you're going to pick up with any given electrode is just a small radius around that electrode. And the other thing worth understanding about the underlying biology here is that when neurons produce an action potential, the width of that action potential is about 1 millisecond. So from the start of the spike to the end of the spike, that whole width of that sort of characteristic feature of a neuron firing is 1 millisecond wide. And if you want to detect whether an individual spike is occurring or not, you need to sample that signal, or sample the local field potential nearby that neuron, much more frequently than once a millisecond. You need to sample many, many times per millisecond to be able to detect that this is actually the characteristic waveform of a neuron producing an action potential. And so we sample across all 1,024 electrodes about 20,000 times a second. 20,000 times a second means for a given 1 millisecond window, we have about 20 samples that tell us what that exact shape of that action potential looks like. And once we've sort of sampled at super high rate the underlying electrical field nearby these cells, we can process that signal into just: where do we detect a spike or where do we not? Sort of a binary signal: one or zero, do we detect a spike in this one millisecond or not? And we do that because the actual information-carrying sort of subspace of neural activity is just when are spikes occurring. Essentially everything that we care about for decoding can be captured or represented in the frequency characteristics of spike trains, meaning how often are spikes firing in any given window of time. And that allows us to do sort of a crazy amount of compression from this very rich, high-density signal to something that's much more sparse and compressible, that can be sent out over a wireless radio like a Bluetooth communication, for example.

这里快速岔开一下：你提到了电极、神经元，附近有一个神经元局部邻域。隔离尖峰来自哪里有多困难？

Quick tangent here: you mentioned electrode, neuron, there's a local neighborhood of neurons nearby. How difficult is it to isolate where the spike came from?

是的，所以有一个完整的学术神经科学领域……

Yeah, so there's a whole field of sort of academic neuroscience...

所以你必须在设备上完成这种尖峰检测，而且必须极其高效——速度要快，功耗不能太高，因为你不希望产生太多热量。所以它必须是一个非常简单的信号处理步骤。是的。你能分享一些关于克服这一挑战的经验吗？

So you have to do this kind of spike detection on board and you have to do that super efficiently, so fast and not use too much power because you don't want to be generating too much heat. So it has to be a super simple signal processing step. Yeah. Is there some wisdom you can share about what it takes to overcome that challenge?

是的，我们尝试了很多不同的版本，基本上都是把原始信号转换成你想要从设备发送出去的特征。我要说的是，我不认为我们已经走到了这个过程的终点。这是一条漫长的路。我们今天有明确可行的方案，但未来可能会发现许多比现在好得多的方法。我们现在的一些方法，这些想法有很多学术渊源，所以我不想声称这些是 Neuralink 的原创想法。但其中一个想法基本上是构建一个类似卷积滤波器的东西，它在信号上滑动，寻找匹配的特定模板。这个模板包括尖峰调制的深度、恢复的程度，以及整个过程持续的时间和窗口。如果你在信号中看到该模板在一定范围内匹配，那么就可以说，这是一个尖峰。这种方法非常方便的一个原因是，你实际上可以在硬件中极其高效地实现它，这意味着你可以低功耗地在 1024 个通道上同时运行。我们最近开始探索的另一种方法，可以与尖峰检测方法结合，叫做尖峰频带功率。这种方法的好处是，你可能能够从那些距离太远而无法被检测为尖峰的神经元中拾取一些信号，因为离电极越远，实际的尖峰波形在电极上看起来就越弱。所以你可能能够拾取到正常记录半径之外的一些群体活动。神经科学家有时称之为活动的杂音，即正在发生的其他事情。而且你可以观察许多通道上背景噪声的行为。这样你可能能从信号中榨取更多信息。但这是有代价的：该信号现在是浮点表示，这意味着通过功率发送出去的成本更高，而且你需要找到与二进制信号不同的压缩方法。所以这些不同的模式带来了许多不同的挑战。

Yeah, so we've tried many different versions of basically turning this raw signal into a feature that you might want to send off the device. And I'll say that I don't think we're at the final step of this process. This is a long journey. We have something that works clearly today, but there can be many approaches that we find in the future that are much better than what we do right now. So some versions of what we do right now, and there's a lot of academic heritage to these ideas, so I don't want to claim that these are original Neuralink ideas or anything like that. But one of these ideas is basically to build a sort of convolutional filter, almost, if you will, that slides across the signal and looks for a certain template to be matched. That template consists of how deep the spike modulates, how much it recovers, and what the duration and window of time is that the whole process takes. And if you can see in the signal that that template is matched within certain bounds, then you can say, okay, that's a spike. One reason this approach is super convenient is that you can actually implement that extremely efficiently in hardware, which means that you can run it in low power across 1,024 channels all at once. Another approach that we've recently started exploring, and this can be combined with the spike detection approach, is something called spike band power. And the benefits of that approach are that you may be able to pick up some signal from neurons that are maybe too far away to be detected as a spike, because the farther away you are from an electrode, the weaker that actual spike waveform will look like on that electrode. So you might be able to pick up population-level activity of things that are maybe slightly outside the normal recording radius. What neuroscientists sometimes refer to as the hash of activity, the other stuff that's going on. And you can look at, across many channels, how that background noise is behaving. You might be able to get more juice out of the signal that way. But it comes at a cost: that signal is now a floating-point representation, which means it's more expensive to send out over power, and it means you have to find different ways to compress it that are different than you can apply to binary signals. So there's a lot of different challenges associated with these different modalities.

那么在通信方面，你也受到可发送数据量的限制。而且由于你目前使用的是蓝牙协议，你必须把数据打包在一起，但同时你还得把延迟控制在极低水平，极低。关于延迟有什么想说的吗？

So also in terms of communication, you're limited by the amount of data you can send. And also because you're currently using the Bluetooth protocol, you have to batch stuff together, but you have to also do this keeping the latency crazy low, like crazy low. Anything to say about the latency?

是的，这是我的一个热情项目。我想打造世界上最好的鼠标。我不想造什么电动车的雪佛兰 Spark 之类的，我想造特斯拉 Roadster 版本的鼠标。我真的认为，在 5 到 10 年内，大多数电子竞技比赛将由瘫痪患者主导。这是非常现实的可能性，原因有几个。一是他们将能够使用最好的技术来有效地玩电子游戏。二是他们有足够的时间。所以这两个因素加在一起，对电子竞技选手来说尤其强大。除非没有瘫痪的人也被允许植入 Neuralink，这是另一种与数字设备交互的方式。这确实有道理。如果这是一种根本不同的体验，更高效的体验，即使不是那种完全高带宽的通信，如果只是能够以 10 倍的速度移动鼠标，比如比特率，如果我能达到鼠标 10 倍的比特率，那将是一个非常有趣的可能性。他们能做什么，尤其是随着训练变得越来越熟练，你的表现上限肯定会更高。因为你不需要通过手臂、肌肉来缓冲你的意图。仅仅因为拥有大脑植入物，你在任何实际想要采取的行动上就有 75 毫秒的提前量。这有一些细微差别。有证据表明运动皮层可以规划动作序列，所以你可能不会一直获得全部好处。但对于反应时间类的游戏，比如你只想，某人在那边，狙击他，你知道那种情况，你实际上有固有的优势，因为你不需要经过肌肉。所以问题只是你能让它快多少？从延迟的角度来看，我们已经比通过肌肉操作更快了。我们还处于早期阶段。我认为我们可以进一步推进。目前从大脑尖峰到光标移动的端到端延迟大约是 22 毫秒。

Yeah, this is a passion project of mine. So I want to build the best mouse in the world. I don't want to build like the Chevrolet Spark or whatever of electric cars. I want to build like the Tesla Roadster version of a mouse. And I really do think it's quite possible that within 5 to 10 years, most esports competitions are dominated by people with paralysis. This is a very real possibility for a number of reasons. One is that they'll have access to the best technology to play video games effectively. The second is they have the time to do so. So those two factors together are particularly potent for esport competitors. Unless people without paralysis are also allowed to implant Neuralink, which is another way to interact with a digital device. And there's something to that. If it's a fundamentally different experience, more efficient experience, even if it's not like some kind of full-on high-bandwidth communication, if it's just ability to move the mouse 10x faster, like the bits per second, if I can achieve a bits per second at 10x what I can do with the mouse, that's a really interesting possibility. What they can do, especially as you get really good at it with training, it's definitely the case that you have a higher ceiling of performance. Because you don't have to buffer your intention through your arm, through your muscle. You get, just by nature of having a brain implant at all, like a 75-millisecond lead time on any action that you're actually trying to take. And there's some nuance to this. There's evidence that the motor cortex can sort of plan out sequences of actions, so you may not get that whole benefit all the time. But for reaction-time-style games where you just want to, somebody's over here, snipe them, you know that kind of thing, you actually do have an inherent advantage because you don't need to go through muscle. So the question is just how much faster can you make it? And we're already faster than what you would do if you're going through muscle from a latency point of view. And we're in the early stage of that. I think we can push it. Our end-to-end latency right now from brain spike to cursor movement is about 22 milliseconds.

世界上最好的鼠标，最好的游戏鼠标，延迟大约 5 毫秒，具体取决于测量方式和屏幕刷新率。这里有很多特性很重要。但大脑中一个神经元真正影响你手部指令的时间大约是 75 毫秒。所以看看这些数字，你会发现我们已经具有竞争力，而且比实际移动手部还要快一点。如果你问 Nolan 他第一次移动光标时的感受，我们问过他这个问题。我对此超级好奇：比如，当你调节点击意图或只是试图将光标向右移动时，感觉如何？他说光标在他真正意图移动之前就已经移动了，这有点超现实。我希望有一天自己能亲身体验一下。那种感觉如此即时、如此流畅，以至于感觉它在你真正意图移动之前就已经发生了，那是什么感觉？

The best mice in the world, the best gaming mice, have about 5 milliseconds of latency, depending on how you measure and how fast your screen refreshes. There are a lot of characteristics that matter there. But yeah, and the rough time for a neuron in the brain to actually impact your command of your hand is about 75 milliseconds. So if you look at those numbers, you can see that we're already competitive and slightly faster than what you'd get by actually moving your hand. And this is something that, you know, if you ask Nolan about it when he moved the cursor for the first time, we asked him about this. This was something I was super curious about: like, what does it feel like when you're modulating a click intention or when you're trying to just move the cursor to the right? He said it moves before he is actually intending it, which is kind of a surreal thing. It's something that I would love to experience myself one day. What is that like to have the thing just be so immediate, so fluid, that it feels like it's happening before you're actually intending it to move?

是的，我想我们已经习惯了那种自然延迟。那么目前蓝牙通信是瓶颈吗？我的意思是，总会有瓶颈。当前的瓶颈是什么？

Yeah, I suppose we've gotten used to that natural latency that happens. So is the Bluetooth communication currently the bottleneck? Like, I mean, there's always going to be a bottleneck. What's the current bottleneck?

嗯，有几件事。有点搞笑的是，蓝牙低功耗协议对通信速度有一些限制。协议本身规定，你能发送的最频繁更新大约是 7.5 毫秒一次。随着我们将延迟压低到单个尖峰影响控制的水平，这种分辨率下，这类协议在某个规模上会成为限制因素。另一个重要的细微差别是，这个方程中不仅仅只有 Neuralink 本身。如果你开始将延迟压低到屏幕刷新率以下，那么你还有另一个问题：你需要整个系统能够像技术所能提供的极限一样反应迅速。比如屏幕；如果你试图让某物以 1 毫秒的水平响应，120 Hz 就不够用了。这是一个非常酷的挑战。我也喜欢把它印在 T 恤上：“世界上最好的鼠标。”

Yeah, a couple things. So kind of hilariously, Bluetooth Low Energy protocol has some restrictions on how fast you can communicate. So the protocol itself establishes a standard that the most frequent updates you can send are on the order of 7.5 milliseconds. And as we push latency down to the level of individual spikes impacting control, that level of resolution, that kind of protocol is going to become a limiting factor at some scale. Another important nuance is that it's not just the Neuralink itself that's part of this equation. If you start pushing latency below the level of how fast screens refresh, then you have another problem: you need your whole system to be able to be as reactive as the limits of what the technology can offer. Like you need the screen; 120 Hz just doesn't work anymore if you're trying to have something respond at the level of 1 millisecond. That's a really cool challenge. I also like that for a t-shirt: "The best mouse in the world."

跟我说说接收端，解码步骤。现在我们弄清楚了尖峰是什么，把它们整合在一起，然后发送到应用程序。解码步骤是什么样的？

Tell me on the receiving end, the decoding step. Now we figured out what the spikes are, got them all together, now we're sending that over to the app. What does the decoding step look like?

嗯，也许首先，什么是解码？我想可能有很多听众完全不知道解码大脑活动是什么意思。实际上，即使我们退一步，应用程序是什么？有一个植入物，它与任何安装了应用程序的数字设备进行无线通信。所以也许你可以从高层次告诉我应用程序是什么，大脑之外的软件是什么。

Yeah, so maybe first, what is decoding? I think there's probably a lot of folks listening that just have no clue what it means to decode brain activity. Actually, even if we zoom out beyond that, what is the app? So there's an implant that's wirelessly communicating with any digital device that has an app installed. So maybe you can tell me at a high level what the app is, what the software is outside of the brain.

嗯，也许从目标倒推：目标是帮助瘫痪患者，比如 Noland，能够独立操作电脑。我们认为最好的方式是给他们提供和我们一样的工具来操作软件，因为我们不想为大脑重建整个软件生态系统，至少现在不想。也许有一天你可以想象有原生为 BCI 构建的 UI，但就今天对人们有用的东西而言，我认为大多数人更希望能够控制鼠标和键盘输入，用于日常工作、与朋友交流等。所以应用程序的工作实际上是将来自植入物的无线大脑数据流转化为对电脑的控制。我们通过建立从大脑活动到 HID 输入再到实际硬件的映射来实现这一点。HID 只是用于通信输入设备事件的协议，例如，将鼠标移动到某个位置或按下某个键。这个映射基本上是应用程序负责的。但这个映射如何工作有很多细微差别，我们花了很多时间试图把它做对，而且我们仍处于漫长旅程的早期阶段，以找出如何最优地做到这一点。所以这个过程的一部分是解码。解码是将通过蓝牙连接传输到应用程序的大脑数据的统计模式转化为例如鼠标移动的过程。这个解码步骤可以分为几个部分。类似于任何机器学习问题，有一个训练步骤和一个推理步骤。在我们的案例中，训练步骤是一个非常复杂的行为过程，用户必须想象执行不同的动作。例如，他们会看到一个带有光标的屏幕，并被要求将光标向右推，然后想象向左推，向上推，向下推。我们可以基本上建立一个模式，使用任何现代机器学习方法，将给定的大脑数据和想象的行为映射起来。然后在测试时，你使用相同的模式匹配系统——在我们的案例中是一个深度神经网络——运行它，获取来自植入物的实时大脑数据流，通过与校准时的数据进行模式匹配来解码，然后用它来控制电脑。现在，有几个我觉得非常有趣的深坑：其中之一是如何构建最佳的模板匹配系统，因为当你与瘫痪患者合作时，会有各种行为挑战和调试挑战。因为再次强调，你根本观察不到他们试图做什么；你看不到他们试图移动手。所以你必须找到一种方法来指导用户做某事，并验证他们做得正确，这样你才能在下游自信地建立神经尖峰与意图动作之间的映射。而“正确执行动作”的真正含义是在神经元活动的分辨率水平上。所以如果在理想世界中，你能获得一个行为意图的信号，该信号在 1 毫秒分辨率下是真实准确的，那么我就可以高置信度地从神经尖峰建立到该行为意图的映射。但挑战再次在于你观察不到他们实际在做什么，因此如何构建用户体验，使其不仅仅提供用户意图的粗略、平均正确的表示，有很多细微差别。如果你想建造世界上最好的鼠标，你确实需要那样。

Yeah, so maybe working backwards from the goal: the goal is to help someone with paralysis, in this case Noland, be able to navigate his computer independently. And we think the best way to do that is to offer them the same tools that we have to navigate our software, because we don't want to have to rebuild an entire software ecosystem for the brain, at least not yet. Maybe someday you can imagine there are UIs that are built natively for BCI, but in terms of what's useful for people today, I think most people would prefer to be able to just control mouse and keyboard inputs to all the applications that they want to use for their daily jobs, for communicating with their friends, etc. And so the job of the application is really to translate this wireless stream of brain data coming off the implant into control of the computer. And we do that by essentially building a mapping from brain activity to the HID inputs to the actual hardware. So HID is just the protocol for communicating input device events, for example, move mouse to this position or press this key down. And that mapping is fundamentally what the app is responsible for. But there's a lot of nuance in how that mapping works that we spent a lot of time to try to get right, and we're still in the early stages of a long journey to figure out how to do that optimally. So one part of that process is decoding. Decoding is this process of taking the statistical patterns of brain data that's being channeled across this Bluetooth connection to the application and turning it into, for example, mouse movement. And that decoding step, you can think of it in a couple different parts. So similar to any machine learning problem, there's a training step and an inference step. The training step in our case is a very intricate behavioral process where the user has to imagine doing different actions. So for example, they'll be presented a screen with a cursor on it, and they'll be asked to push that cursor to the right, then imagine pushing that cursor to the left, push it up, push it down. And we can basically build up a pattern, using any sort of modern ML method, a mapping of given this brain data and that imagined behavior, map one to the other. And then at test time, you take that same pattern matching system—in our case, it's a deep neural network—and you run it, and you take the live stream of brain data coming off their implant, you decode it by pattern matching to what you saw at calibration time, and you use that for control of the computer. Now, a couple of rabbit holes that I think are quite interesting: one of them has to do with how you build that best template matching system, because there are a variety of behavioral challenges and also debugging challenges when you're working with someone who's paralyzed. Because again, fundamentally, you don't observe what they're trying to do; you can't see them attempt to move their hand. And so you have to figure out a way to instruct the user to do something and validate that they're doing it correctly, such that then you can downstream build with confidence the mapping between the neural spikes and the intended action. And by "doing the action correctly," what I really mean is at the level of resolution of what neurons are doing. So if in an ideal world you could get a signal of behavioral intent that is ground truth accurate at the scale of 1 millisecond resolution, then with high confidence I could build a mapping from my neural spikes to that behavioral intention. But the challenge is again that you don't observe what they're actually doing, and so there's a lot of nuance to how you build user experiences that give you more than just a coarse, on-average correct representation of what the user intends to do. If you want to build the world's best mouse, you really want that.

它要尽可能响应迅速，你希望它能在每一步都完全按照用户的意图行事，而不仅仅是平均正确。当你试图从左到右移动它时，构建一种行为校准游戏或软件体验，能提供那种分辨率水平，是我们花大量时间做的事情。所以校准过程中，界面必须鼓励精确性，意思是无论它做什么，都应该非常直观，让人类下一步很可能做的恰好就是你需要的那种意图，而且只有那种意图。

It to be as responsive as possible, you want it to be able to do exactly what the user is intending at every sort of step along the way, not just on average be correct. When you're trying to move it from left to right, building a behavioral sort of calibration game or software experience that gives you that level of resolution is what we spend a lot of time working on. So the calibration process, the interface has to encourage precision, meaning like whatever it does, it should be super intuitive that the next thing the human is going to likely do is exactly that intention that you need, and only that intention.

是的，而且你没有任何反馈，除非事后他们告诉你他们实际做了什么。你不能……哦对，没错。所以这本质上是一个非常令人兴奋的 UX 挑战，因为这完全取决于 UX。这不仅仅是关于友好、美观或易用；用户体验就是它运作的方式。它决定了校准如何工作，而至少在 Neuralink 的这个阶段，校准是设备运行的基础，而且不仅仅是校准，本质上是持续校准。

Yeah, and you don't have any feedback except that maybe speaking to you afterwards what they actually did. You can't... oh yeah, right. So that's fundamentally a really exciting UX challenge, because that's all on the UX. It's not just about being friendly or nice or usable; it's like user experience is how it works. It's how it works for the calibration, and calibration at least at this stage of Neuralink is fundamental to the operation of the thing, and not just calibration but continued calibration essentially.

而且你刚才说了一些我觉得值得深入探讨的话。你说这主要是 UX 挑战，我认为很大一部分确实是，但这里也有一个非常有趣的机器学习挑战，它提供了一些数据集，包括要求用户向上、向下、向左、向右移动的平均正确行为。给定一个神经脉冲数据集，有没有办法以某种半监督或完全无监督的方式推断出他们意图的高分辨率版本？如果你仔细想想，很可能有，因为数据集中有足够多的数据点，模型上有足够多的约束，应该可以通过正确的公式让模型自己弄清楚，例如，在这一毫秒，他们向上推的力度正好是多少，而在那一毫秒，他们试图向上推的力度是多少。

And maybe you said something that I think is worth exploring there a little bit. You said it's primarily a UX challenge, and I think a large component of it is, but there is also a very interesting machine learning challenge here, which has given some dataset including some on-average correct behavior of asking the user to move up or down, move right or left. Given a dataset of neural spikes, is there a way to infer in some kind of semi-supervised or entirely unsupervised way what that high-resolution version of their intention is? And if you think about it, there probably is, because there are enough data points in the dataset, enough constraints on your model, that there should be a way with the right sort of formulation to let the model figure out itself, for example, at this millisecond this is exactly how hard they're pushing upwards, and at this millisecond this is how hard they're trying to push upwards.

拥有非常干净的标签非常重要，是的。所以从机器学习的角度来看，问题变得困难得多：标签是有噪声的。没错。而要获得干净的标签，那就是 UX 挑战。

It's really important to have very clean labels, yes. So the problem becomes much harder from the machine learning perspective: the labels are noisy. That's correct. And then to get the clean labels, that's a UX challenge.

没错。不过，干净的标签，我觉得也许值得探讨一下这到底是什么意思。我认为任何给定的标注策略都会对用户试图做什么做出一些假设。这些假设可以表述为损失函数，也可以表述为你可能用来估计或猜测用户意图的启发式方法。真正重要的是这些假设有多准确。例如，你可能会说：嘿，用户，向上推，并跟随这个光标的移动速度。你的启发式方法可能是他们正试图完全按照光标移动的方向去做。另一个竞争的启发式方法可能是他们实际上试图在运动开始时稍微快一点，在结束时稍微慢一点。这些竞争特征可能准确反映了用户的意图，也可能不准确。任务的另一个版本可能是：嘿，用户，想象将这个光标移动一个固定的偏移量。所以不是跟随光标，而是尝试将它精确地向右移动 200 像素。这是光标，这是目标。好的，光标消失，尝试将那个现在看不见的光标向右移动 200 像素。在这种情况下，假设是用户实际上能够正确调节那个位置偏移。但那个位置偏移假设可能是一个较弱的假设，因此有可能比那些试图在每一毫秒猜测用户意图的启发式方法更准确。所以你可以想象不同的任务对用户意图的本质做出不同的假设，而这些假设的正确性就是我所说的该步骤的干净标签。

Correct. Although, clean labels, I think maybe it's worth exploring what that exactly means. I think any given labeling strategy will have some number of assumptions it makes about what the user is attempting to do. Those assumptions can be formulated in a loss function, or they can be formulated in terms of heuristics that you might use to just try to estimate or guesstimate what the user is trying to do. And what really matters is how accurate are those assumptions. For example, you might say: hey user, push upwards and follow the speed of this cursor. And your heuristic might be that they're trying to do exactly what that cursor is trying to do. Another competing heuristic might be they're actually trying to go slightly faster at the beginning of the movement and slightly slower at the end. And those competing characteristics may or may not be accurate reflections of what the user is trying to do. Another version of the task might be: hey user, imagine moving this cursor a fixed offset. So rather than follow the cursor, just try to move it exactly 200 pixels to the right. So here's the cursor, here's the target. Okay, cursor disappears, try to move that now invisible cursor 200 pixels to the right. And the assumption in that case would be that the user can actually modulate correctly that position offset. But that position offset assumption might be a weaker assumption, and therefore potentially you can make it more accurate than these heuristics that are trying to guesstimate at each millisecond what the user is trying to do. So you can imagine different tasks that make different assumptions about the nature of the user intention, and those assumptions being correct is what I would think of as a clean label for that step.

我们应该想象什么？有一个光标，你想把它向右或向左、向上或向下移动，或者可能移动一定的偏移量。所以这是一种方法。这是做校准的最佳方式吗？例如，另一种可能在这里起作用的疯狂方式是像 WebGrid 这样的游戏，你只是获取大量数据。一个人在玩游戏，如果他们处于心流状态，也许你可以作为副产品获得干净的信号。这对初始校准有效吗？

What are we supposed to be visualizing? There's a cursor and you want to move that cursor to the right or the left, up and down, or maybe move them by a certain offset. So that's one way. Is that the best way to do calibration? So for example, an alternative crazy way that probably is playing a role here is a game like WebGrid, where you're just getting a very large amount of data. The person playing a game where if they are in the state of flow, maybe you can get clean signal as a side effect. Is that an effective way for initial calibration?

是的，好问题。这里有很多东西需要展开。首先我要区分一下开环和闭环。开环，我的意思是用户基本上是从零到一：他们完全没有模型，试图达到有一定控制水平的状态。在这种设置下，你确实需要有一个任务给用户提示你希望他们做什么，这样你才能再次建立从大脑数据到输出的映射。然后一旦他们有了模型，你可以想象他们使用那个模型，实际适应它，自己找出正确的使用方法，然后在那数据上重新训练，从而获得性能提升。这两种技术都伴随着很多挑战，如果你感兴趣，我们可以深入探讨。但开环任务的挑战在于，用户本身得不到关于他们正在做什么的本体感觉反馈。当他们使用开环或试图进行开环校准时，他们不一定能感知到自己或感觉到手下的鼠标。他们被要求执行类似这样的任务：想象你的整个右臂被麻醉了，你把它塞进一个盒子里，你看不到它，所以你没有视觉反馈，也没有关于你手臂位置或活动的本体感觉反馈。现在你被要求：好的，给定屏幕上这个从左到右移动的东西，匹配那个速度。你基本上可以尽力在你大脑中唤起任何想象的动作，让光标从左到右移动。但在任何情况下，你在执行那个任务时都会不准确，可能还不一致。这就是开环的基本挑战。闭环的挑战在于，一旦用户有了一个模型，并且能够自己开始移动鼠标，他们会非常自然地适应那个模型。模型学习他们在做什么，用户学习如何使用模型，这种共同适应可能不会让你找到最好的全局最小值。可能是你的第一个模型在某些方面有噪声，或者可能只是有一些怪癖，数据分布的某些部分它……

Yeah, great question. There's a lot to unpack there. So the first thing I would draw is a distinction between a sort of open-loop versus closed-loop. So open-loop, what I mean by that is the user is sort of going from zero to one: they have no model at all, and they're trying to get to the place where they have some level of control at all. In that setup, you really need to have some task that gives the user a hint of what you want them to do, such that you can build a mapping again from brain data to output. Then once they have a model, you could imagine them using that model and actually adapting to it and figuring out the right way to use it themselves, and then retraining on that data to give you sort of a boost in performance. There's a lot of challenges associated with both of these techniques, and we can sort of rabbit hole into both of them if you're interested. But the sort of challenge with the open-loop task is that the user themselves doesn't get proprioceptive feedback about what they're doing. They don't necessarily perceive themselves or feel the mouse under their hand when they're using an open-loop or when they're trying to do an open-loop calibration. They're being asked to perform something like: imagine if you sort of had your whole right arm numbed and you stuck it in a box and you couldn't see it, so you had no visual feedback and you had no proprioceptive feedback about what the position or activity of your arm was. And now you're asked: okay, given this thing on the screen that's moving from left to right, match that speed. And you basically can try your best to invoke whatever that imagined action is in your brain that's moving the cursor from left to right. But in any situation, you're going to be inaccurate and maybe inconsistent in how you do that task. And so that's sort of the fundamental challenge of open-loop. The challenge with closed-loop is that once the user is given a model and they're able to start moving the mouse on their own, they're going to very naturally adapt to that model. And that co-adaptation between the model learning what they're doing and the user learning how to use the model may not find you the best sort of global minima. It may be that your first model was noisy in some ways, or maybe just had some quirk, there's some part of the data distribution it...

这一点没有讲得太清楚，用户现在自己摸索出来了——因为他们是像 Nolan 这样聪明的用户，他们找到了正确的想象动作序列，或者他们必须保持的手部角度，才能让系统工作，而且效果很好。但第二天他们回到设备前，可能不记得前一天用过的所有技巧，于是就出现了一个复杂的反馈循环，可能让调试过程变得非常非常困难。

didn't cover super well and the user now figures out because they're you brilliant user like Nolan they figure out the right sequence of imagin motion motions or the right angle they have to hold their hand at to get it to work and they'll get it to work great but then the next day they come back to their device and maybe they don't remember exactly all the tricks that they used the previous day and so there's a complicated sort of feedback cycle here that can uh that can emerge and can make it a very very difficult debugging process

好的，这里面有很多非常有趣的东西。嗯，实际上，就闭环这个话题，我见过这样的情况：心理学研究生使用别人写的软件，他们自己不会编程，那个软件有很多 bug，但他们用了好几年，找到了绕过去的方法。没人想过要修复它，他们只是适应了。这真的很有意思——我们很擅长适应，但这可能不是最优解。那么，你怎么解决这个问题？是不是需要时不时地从头开始？

okay there's a lot of really fascinating things there uh yeah actually just to stay on the on the closed loop I I've uh seen situations this actually happened uh watching uh psychology gr crd students they use piece of software when they don't know how to program themselves they use piece of software that somebody else wrote and has a bunch of bugs and they figure out like and they've been using it for years yeah they figure out ways to walk around oh that just happens like nobody H nobody like considers maybe we should fix this they just adapt and that's a really interesting notion that we just had we were really good at adapting but you need to still that might not be the optimal yeah okay so how do you solve that problem do you have to restart from scratch every once in a while kind of thing

嗯，这是个好问题。首先，我要说这不是一个已解决的问题，对于学术界研究脑机接口的人来说，我也想说，这个问题不能简单地通过增加通道数来解决。增加通道数可能有帮助，能获得更丰富的协方差结构，用于设计好的标注策略，但如果你对不会被通道数增加本身解决的问题感兴趣，这就是其中之一。那么如何解决？这不是一个已解决的问题，这是我要强调的第一点。第二点是，任何涉及闭环的解决方案都会变成一个非常困难的调试问题。我选择研究问题的一个通用原则是，选择最容易调试的那个。因为如果你能做到这一点，即使天花板更低，你也能更快推进，因为你有更紧密的迭代循环来调试问题。在开环设置中，没有与用户一起的反馈循环来调试，所以有理由认为那应该是一个更容易的调试问题。另一件值得理解的事情是，即使在闭环设置中，也没有特殊的软件或魔法来推断用户真正试图做什么。虽然他们在屏幕上移动光标，但他们可能试图做与模型输出不同的事情。因此，模型输出的内容并不是一个可以用来重新训练的信号。如果你想进一步改进模型，你仍然有一个非常复杂的猜测或无监督问题：找出该信号背后的真实用户意图。所以开环问题有一个很好的特性：容易调试；第二个好特性是，它包含与闭环场景相同的信息内容。

yeah it's a good question um first and foremost I would say this is not a solved problem and for anyone who's you know listening in Academia who works on bcis I would also say this is not a problem that's solved by simply scaling Channel count so this is you know maybe that can help and you can get sort of richer covariant structures that you can use to exploit when trying to come up with good labeling strategies but if you know you're interested in problems that aren't going to be solved inherently by scaling Channel account this is one of M yeah so how do you solve it it's not a solve problem that's the first thing I want to make sure it gets across the second thing is any solution that involves Clos Loop uh is going to become a very difficult debugging problem and one of my sort of generalistic for choosing what problems to tackle is that you want to choose the one that's going to be the easiest to debug MH because if you can do that uh even if the ceiling is lower you're going to be able to move faster because you have a tighter iteration Loop debugging the problem and in the open loop setting there's not a feedback cycle debug with the user in the loop and so there's some reason to think that that should be an easier debugging problem the other thing that's worth understanding is that even in the Clos Loop setting there's no special sof or magic of how to infer what the user is truly attempting to do in the Clos Loop setting although they're moving the cursor on the screen they may be attempting something different than what your model is outputting so what the model is outputting is not a signal that you can use to retrain if you want to be able to improve the model further you still have this very complicated guesstimation or unsupervised problem of figuring out what is the true user intention underlying that signal and so the open loop problem has the nice property of being easy to debug and the second nice property of it has all the same information content as the closeup scenario

嗯，另一件我想提出来说明的事情是，这个问题不需要解决就能给人们提供有用的控制。你知道，即使今天，用我们现有的解决方案和学术界几十年来积累的成果，能给用户提供的控制水平已经相当有用了。不需要解决这个问题就能达到那个控制水平。但我想制造世界上最好的鼠标，让它好到毫无疑问你想要它。而要制造世界上最好的鼠标，超人版本，你真的需要解决这个问题。我们内部之前做的一些研究细节，我认为在思考如何解决这个问题时非常有趣。第一点是，即使你拥有用户试图做什么的真实数据——你可以通过一只健全的猴子获得，它植入了 Neuralink 设备，并移动它来控制电脑——即使有了那个真实数据集，结果发现，要产生高性能的脑机接口，最优的预测目标并不仅仅是鼠标的直接控制。你可以想象建立一个数据集，记录大脑中发生的事情以及鼠标在桌面上确切在做什么。结果发现，如果你建立从神经尖峰到精确预测鼠标动作的映射，那个模型的表现会不如一个被训练来预测关于用户可能试图做什么的更高层次假设的模型。例如，假设猴子试图直线走向目标。结果发现，做出这些假设实际上比预测底层手部动作更有效。所以是意图，而不是物理运动之类的。两者之间显然有很强的相关性，但意图是更值得追求的东西，对吧？

um another thing I want to I want to mention and call out is that this problem doesn't need to be solved in order to give useful control to people um you know even today with the solutions we have now and that Academia has built up over over decades the level of control that can be given to a user you know today is quite useful it doesn't need to be solved to get to that that level of control but again I want to build the world's best Mouse I want to make it you know so good that it's not even a question that you want it and uh to build the world's best Mouse the Superhuman version you really need to uh nail that problem in a couple maybe details of previous studies that we've done internally that I think are very interesting to understand when thinking about how to solve this problem the first is that even when you have ground truth data of what the user is trying to do and you can get this with an able-bodied monkey a monkey that has an neuralink device implanted and moving them to control a computer even with that ground TR data set it turns out that the optimal thing to predict to produce high performance BCI is not just the direct control of the mouse you can imagine you know building data set of what's going on in the brain and what is the mouse exactly doing on the table and it turns out that if you build the mapping from neuros spikes to predict exactly what the mouse is doing that model will perform worse than a model that is trained to predict sort of higher level assumptions about what the user might be trying to do for example assuming that the monkey is trying to go in straight line to the Target M it turns out that making those assumptions is actually more effective in producing a model than actually predicting the underlying hand move so the the intention not like the physical movement or whatever yeah there's a obviously a really strong correlation between the two but the intention is a more powerful thing to be chasing right

嗯，这也非常有趣。我的意思是，意图本身就很迷人，因为在这个脑机接口案例中，通过数字心灵感应，你作用于注意力而不是动作，这就是为什么会有一种感觉，好像事情在你打算做之前就发生了。这太酷了，这也是为什么你很可能在鼠标控制方面实现超人般的性能。那么关于开环，澄清一下：当一个人被要求将鼠标向右移动时，你说没有反馈，所以他们得不到实际移动鼠标的满足感。你可以想象在屏幕上给用户反馈，但这很困难，因为此时你不知道他们试图做什么。那么你能给他们展示什么，才能让他们得到“我做对了”或“我做错了”的信号呢？我们来看一个非常具体的例子：也许你的校准任务是让用户将光标移动一定的位置偏移。你对用户的指令是：“光标在这里，现在光标消失，请想象将它向右移动 200 像素，到达这个目标。”在这种情况下，你可以想象提出某种一致性指标，显示给用户，比如“我知道当你做这个向右动作时，尖峰序列平均看起来是什么样，也许我可以产生一个概率估计，根据最新的试验或你想象的轨迹，这个动作有多大的可能性是你所做的。”

well that that's also super interesting I mean the intention itself is fascinating because yes with the BCI here in this case with the digital telepathy you're acting on the attention not the action which is why there's an experience of like feeling like it's happening before you meant for it to happen that is so cool and that is why you could achieve like super human performance probably in terms of the control of the mouse so the for open loop just to clarify so whenever the a person is tasked to like move the mouse to the right you said there's not feedback so they don't get to get that satisfaction of like actually getting it to move right so you you could imagine giving the user feedback on the screen but uh it's difficult because at this point you don't know what they're attempting to do so what what can you show them that would basically give them a signal of I'm doing this correctly or not correctly so let's take this very specific example like maybe your calibration task looks like you're trying to move the cursor a certain position offset so your instructions to the user are hey the cursor is here now when the cursor disappears IM manag to moving it 200 pixels from where it was to the right to be over this Target in that kind of scenario you could imagine coming up with some sort of consistency metric that you could display to the user of okay I know what the spike train looks like on average when you do this action to the right maybe I can produce some sort of probabilistic estimate of How likely is that uh to be the action you took given the latest trial or trajectory that you that you imagined and that could

给用户某种反馈，告诉他们自己在不同试验中的一致性如何。你还可以想象，如果用户被提示了这种一致性指标，也许他们一开始就会在行为上更投入，因为当没有任何反馈时，任务会有点无聊。所以，在屏幕上显示一些东西，即使不准确，也可能对用户体验有好处，因为这能激励用户尝试提高那个数字或把它推上去。所以这里面有心理学因素。

Give the user some sort of feedback of how consistent they are across different trials. You could also imagine that if the user is prompted with that kind of consistency metric, maybe they just become more behaviorally engaged to begin with because the task is kind of boring when you don't have any feedback at all. So there may be benefits to the user experience of showing something on the screen even if it's not accurate, just because it keeps the user motivated to try to increase that number or push it upwards. So there's a psychology element here.

没错，这完全是一个用户体验挑战。信号漂移在每小时、每天、每周、每月之间有多大？因为信号漂移，你需要多久重新校准一次？

Absolutely, and again all of that is a UX challenge. How much signal drift is there hour to hour, day to day, week to week, month to month? How often do you have to recalibrate because of the signal drift?

这是我们之前在临床试验前用非人灵长类动物（NHP）研究过的问题，在临床试验期间也和 Noland 一起研究过。也许首先要说明的是目标是什么。目标实际上是让用户拥有即插即用的体验——我想他们不需要插任何东西——但是一种即用体验，让他们可以随时随地、随心所欲地使用设备。这才是我们的目标。有一系列解决方案可以在不考虑这个平稳性问题的情况下达到那种状态。也许第一个重要的解决方案是，他们可以随时重新校准。这是 Noland 今天已经能做到的事情。他可以在凌晨 2 点，在没有护理人员、父母或朋友在身边帮他按按钮的情况下，自己重新校准系统。另一个重要的解决方案是，当你校准了一个好的模型后，你可以继续使用它而无需重新校准。他需要多久重新校准一次，实际上取决于他对性能的要求。我们观察到，任何单个模型的效果都会随时间退化，但这可以通过用户调整自己的控制策略来缓解。也可以通过我们提供给用户的一系列软件功能来缓解。例如，我们让用户精确调整光标移动的速度——我们称之为增益，即光标对任何给定输入意图的反应速度。他们还可以调整平滑度，即光标意图输出的平滑程度。他们还可以调整摩擦力，即停止和保持静止的难易程度。所有这些软件工具都给了用户很大的灵活性和故障排除机制，让他们能够自己解决这个问题。

This is a problem we've worked on both with NHP (non-human primates) before our clinical trial, and also with Noland during the clinical trial. Maybe the first thing worth stating is what the goal is here. The goal is really to enable the user to have a plug-and-play experience — I guess they don't have to plug anything in — but a play experience where they can use the device whenever they want to, however they want to. That's really what we're aiming for. There can be a set of solutions that get to that state without considering this stationarity problem. Maybe the first solution here is that they can recalibrate whenever they want. This is something that Noland has the ability to do today. He can recalibrate the system at 2 AM in the middle of the night without his caretaker or parents or friends around to help push a button for him. The other important part of the solution is that when you have a good model calibrated, you can continue using that without needing to recalibrate it. How often he has to do this recalibration depends really on his appetite for performance. We observe a sort of degradation through time of how well any individual model works, but this can be mitigated behaviorally by the user adapting their control strategy. It can also be mitigated through a combination of software features we provide to the user. For example, we let the user adjust exactly how fast the cursor is moving — we call that the gain, the gain of how fast the cursor reacts to any given input intention. They can also adjust the smoothing, how smooth the output of that cursor intention actually is. They can also adjust the friction, which is how easy it is to stop and hold still. All these software tools allow the user a great deal of flexibility and troubleshooting mechanisms to be able to solve this problem for themselves.

顺便说一下，所有这些操作都是通过看向屏幕右侧、选择混音器来完成的，在混音器里——就像 DJ 模式。你的脑机接口的 DJ 模式。所以这个界面做得非常好，真的非常好。所以是的，存在那种偏差——Nolan 在一次直播中提到了光标漂移，尽管他说你们只是和他一起在摆弄，而且你们在持续改进，所以那可能只是那个特定时刻、特定日子的一个快照。但他说存在这种光标漂移和偏差，他可以通过看向屏幕右侧或左侧来调整偏差。这是一种调整偏差的界面操作。

By the way, all this is done by looking to the right side of the screen, selecting the mixer, and in the mixer you have — it's like DJ mode. DJ mode for your BCI. So it's a really well done interface, really well done. And so yeah, there's that bias — there's a cursor drift that Nolan talked about in a stream, although he said that you guys were just playing around with it with him and they're constantly improving, so that could have been just a snapshot of that particular moment, particular day. But he said that there was this cursor drift and this bias that could be removed by him, I guess, looking to the right side of the screen or left side of the screen to kind of adjust the bias. That's one interface action to adjust the bias.

这实际上是一个来自学术界的想法。之前有一些与 BrainGate 临床试验参与者相关的工作，他们开创了这种偏差校正的想法。我们实现的方式，我认为是一种非常精致、非常漂亮的用户体验：用户基本上可以把光标闪到屏幕一侧，然后会打开一个窗口，他们可以在那里精确调整或微调光标的偏差。对于不熟悉的人来说，偏差就是当你什么都不想时，光标的默认运动。事实证明，这是受神经活动影响的光标控制体验的第一个感受——光标体验的质量。我不知道还能怎么描述。我不是那种富有诗意的人。

This is actually an idea that comes out of academia. There is some prior work with BrainGate clinical trial participants where they pioneered this idea of bias correction. The way we've done it, I think, is a very polished, very beautiful user experience where the user can essentially flash the cursor over to the side of the screen and it opens up a window where they can actually adjust or tune exactly the bias of the cursor. Bias, for people who aren't familiar, is just the default motion of the cursor if you're imagining nothing. It turns out that that's one of the first qualia of the cursor control experience that's impacted by neural activity — the quality of the cursor experience. I don't know how else to describe it. I'm not the poetic guy.

我喜欢这个说法。光标体验的质量。

I love it. The quality of the cursor experience.

是的，我是说这听起来很有诗意，但这是千真万确的。这是一种体验。当它工作良好时，是一种愉悦、非常愉快的体验。而当它工作不好时，是一种非常令人沮丧的体验。这实际上是用户体验的艺术：你有能力让人沮丧，也有能力给人带来快乐。归根结底，用户体验就是事物如何工作。所以不仅仅是屏幕上显示什么，还包括设备给用户提供了哪些控制界面。我们希望他们感觉自己像是在开 F1 赛车，而不是像开一辆小货车。我们真的是这么想的。Nolan 本人是 F1 车迷，所以我们称自己为维修站团队。他才是真正的 F1 车手。不同种类的汽车和飞机给用户提供了不同的控制界面，我们在设计光标行为时从中汲取了很多灵感。其中一个细微之处是，比如当你在 MacBook 触控板上移动鼠标时，输入转化为光标移动的响应曲线与使用鼠标时不同。在触控板上移动时，有一个不同的响应函数，不同的曲线，将移动转化为对计算机的输入，这与用物理鼠标操作时不同。这是因为很久以前，当有人设计最初的计算机输入系统时，他们仔细思考了使用这些不同系统的感觉。现在我们正在设计下一代计算机输入系统，完全通过大脑完成。没有本体感觉反馈——你感觉不到手中的鼠标，感觉不到指尖下的按键——你需要一个控制界面，仍然让用户容易且直观地理解系统状态以及如何实现他们想要的目标。最终目标是用户体验完全退居幕后。它变得如此自然和直观，以至于对用户来说是下意识的。他们应该感觉基本上可以直接控制光标。光标就做他们想让它做的事。他们不会去想如何实现让它做想做的事。它只是在做他们想让它做的事。

Yeah, I mean it sounds poetic but it is deeply true. There is an experience. When it works well, it is a joyful, really pleasant experience. And when it doesn't work well, it's a very frustrating experience. That's actually the art of UX: you have the possibility to frustrate people or the possibility to give them joy. At the end of the day, it really is truly the case that UX is how the thing works. So it's not just what's showing on the screen, it's also what control surfaces does the device provide the user. We want them to feel like they're in the F1 car, not like some minivan. That really truly is how we think about it. Nolan himself is an F1 fan, so we refer to ourselves as a pit crew. He really is truly the F1 driver. There are different control surfaces that different kinds of cars and airplanes provide the user, and we take a lot of inspiration from that when designing how the cursor should behave. One nuance of this is even details like when you move a mouse on a MacBook trackpad, the response curve of how that input translates to cursor movement is different than how it works with a mouse. When you move on the trackpad, there's a different response function, a different curve to how much a movement translates to input to the computer than when you do it physically with the mouse. That's because somebody sat down a long time ago when they designed the initial input systems to any computer and they thought through exactly how it feels to use these different systems. Now we're designing the next generation of this input system to a computer, which is entirely done via the brain. There's no proprioceptive feedback — you don't feel the mouse in your hand, you don't feel the keys under your fingertips — and you want a control surface that still makes it easy and intuitive for the user to understand the state of the system and how to achieve what they want to achieve. Ultimately, the end goal is that the UX completely fades into the background. It becomes something so natural and intuitive that it is subconscious to the user. They just should feel like they have basically direct control over the cursor. It just does what they want it to do. They're not thinking about the implementation of how to make it do what they want it to do. It's just doing what they want it to do.

有没有类似菲茨定律的东西？

Is there something along the lines of Fitts' law?

你应该以某种方式移动鼠标，以最大化击中目标的机会。我甚至不知道自己在问什么，但我希望我问题的意图能落在一个已找到的答案上。当涉及到某人用大脑控制鼠标时，是否存在某种对 UX 法则的理解？这跟实际用鼠标是不同的。

You should move the mouse in a certain kind of way that maximizes your chance to hit the target. I don't even know what I'm asking, but I'm hoping the intention of my question will land on a found answer. Is there some kind of understanding of the laws of UX when it comes to the context of somebody using their brain to control it? That's different than actual with a mouse.

我认为我们仍处于发现这些法则的早期阶段，所以我还不敢声称已经解决了这个问题。但确实有一些我们学到的东西能让用户更容易完成任务。当你把它说出来时，这很直白，但在实际调试过程中，要真正达到那个点需要时间。其中一点是，你构建的任何机器学习系统都会有一定数量的错误，而这些错误如何转化为下游用户体验很重要。例如，如果你在照片中开发一个搜索算法，搜索你的朋友 Joe，结果却出现了你朋友 Josephine 的照片，这可能没什么大不了的，因为错误的成本不高。但在另一种场景下，比如你试图检测保险欺诈，并且因为某个机器学习模型的输出而直接将某人告上法庭，那么你就需要更加小心错误了。你需要非常仔细地考虑这些错误如何转化为下游影响。这在脑机接口（BCI）中也是如此。例如，如果你构建一个从大脑解码速度输出的模型，与一个试图调节左键点击的模型相比，它们在需要达到多精确才能对最终用户有用方面有不同的权衡。对于速度输出，平均正确是可以接受的，因为模型的输出会随时间积分。所以如果用户试图点击位置 A，而他们当前在位置 B，他们需要随时间导航到这两点之间。只要模型的输出平均正确，他们就可以通过用户控制回路随时间调整，到达他们想去的位置。但对于点击来说，情况就不同了。点击几乎是瞬间完成的，在神经元放电的尺度上，所以你需要非常确定点击是正确的，因为错误的点击可能对用户造成很大破坏。他们可能会意外关闭正在操作的标签页，丢失所有进度。他们可能会意外点击发送按钮，发送一条只写了一半、读起来很搞笑的短信。所以在这个领域，错误有不同的成本函数，UX 设计的一部分就是理解如何构建一个即使出错时仍然对用户有用的解决方案。

I think we're in the early stages of discovering those laws, so I wouldn't claim to have solved that problem yet. But there's definitely some things we've learned that make it easier for the user to get stuff done. It's pretty straightforward when you verbalize it, but it takes a while to actually get to that point when you're in the process of debugging the stuff in the trenches. One of those things is that any machine learning system you build has some number of errors, and it matters how those errors translate to the downstream user experience. For example, if you're developing a search algorithm in your photos, if you search for your friend Joe and it pulls up a photo of your friend Josephine, maybe that's not a big deal because the cost of an error is not that high. In a different scenario where you're trying to detect insurance fraud or something like this, and you're directly sending someone to court because of some machine learning model output, then the errors make a lot more sense to be careful about. You want to be very thoughtful about how those errors translate to downstream effects. The same is true in BCI. So for example, if you're building a model that's decoding a velocity output from the brain versus an output where you're trying to modulate the left click, these have different trade-offs of how precise you need to be before it becomes useful to the end user. For velocity, it's okay to be on average correct because the output of the model is integrated through time. So if the user is trying to click at position A and they're currently at position B, they're trying to navigate over time to get between those two points. As long as the output of the model is on average correct, they can sort of steer through time with the user control loop in the mix, and they can get to the point they want to get to. The same is not true of a click. For a click, you're performing it almost instantly at the scale of neurons firing, so you want to be very sure that click is correct because a false click can be very destructive to the user. They might accidentally close the tab they're trying to do something in and lose all their progress. They might accidentally hit some send button on a text that's only half composed and reads funny after. So there are different cost functions associated with errors in this space, and part of the UX design is understanding how to build a solution that, when it's wrong, is still useful to the end user.

这太迷人了。给每个动作在出错时分配成本，也就是说每个动作如果出错都有一定的成本，并将其纳入你如何解读意图、映射到动作的过程中，这非常重要。直到你说了我才意识到，提前发送短信是有成本的，而且成本很高。如果你不小心，比如你是一个光标，想象一下如果你的光标偶尔误点击，那会非常烦人。最糟糕的是，通常当用户试图点击时，他们也会保持静止，因为他们正悬停在想要点击的目标上，准备点击。这意味着在我们构建的数据集中，平均而言，低速或保持静止的意图与用户试图点击的时刻相关。哇，这真的很有趣。而且情况并非如此，人们认为点击是一个二元信号，这一定非常容易解码。嗯，是的，但要让它对用户有用，门槛要高得多。而且有办法解决这个问题。我的意思是，你可以采取复合方法，比如我们花 5 秒钟来点击，用很长的时间窗口，这样我们就可以对答案非常确定。但话说回来，世界上最好的鼠标，世界上最好的鼠标不需要一秒钟或 500 毫秒来点击，它只需要 5 毫秒或更少。所以如果你的目标是那么高的标准，那么你真的需要解决根本问题。

That's so fascinating. Assigning cost to every action when an error occurs, so every action if an error occurs has a certain cost, and incorporating that into how you interpret the intention, mapping it to the action, is really important. I didn't quite until you said it realize there's a cost to like sending the text early. It's like a very expensive cost. It's super annoying if you accidentally, like if you're a cursor, imagine if your cursor misclicked every once in a while, that's super obnoxious. And the worst part of it is usually when the user is trying to click, they're also holding still because they're over the target they want to hit and they're getting ready to click, which means that in the data sets we build, on average it's the case that low speeds or desire to hold still is correlated with when the user is attempting to click. Wow, that is really fascinating. It's also not the case, you know, people think that oh click is a binary signal, this must be super easy to decode. Well yes it is, but the bar is so much higher for it to become a useful thing for the user. And there's ways to solve this. I mean you can sort of take the compound approach of well let's just take 5 seconds to click, let's take a huge window of time so we can be very confident about the answer. But again, world's best mouse, the world's best mouse doesn't take a second to click or 500 milliseconds to click, it takes five milliseconds to click or less. And so if you're aiming for that kind of high bar, then you really want to solve the underlying problem.

所以也许这是一个好时机来问如何衡量性能，这个每秒比特数（bits per second）。你能解释一下你指的是什么吗？也许一个好的起点是谈谈作为游戏的网页网格（web grid），作为性能衡量的一个很好的例证。

So maybe this is a good place to ask about how to measure performance, this whole bits per second. What can you like explain what you mean by that? Maybe a good place to start is to talk about web grid as a game, as a good illustration of the measurement of performance.

是的，也许我先退一步，解释一下为什么我们关心衡量这个。我们的目标是让用户能够像我一样好地控制他们的电脑，甚至更好。这意味着他们能以和我一样的速度操作。这意味着他们能使用和我一样的所有功能，包括所有那些小细节，比如 Command Tab、Command Space 等等。他们需要用大脑来完成这些，并且达到和我用肌肉一样高的可靠性。这是一个很高的标准。所以我们打算衡量和量化其中的每一个方面，以了解我们朝着这个目标进展如何。有很多方法可以衡量 BPS，这不是唯一的方法，但我们向用户展示一个目标网格，基本上我们计算一个分数，这个分数取决于他们选择的速度和准确性，以及目标的大小。屏幕上的目标越多，它们就越小，每次点击呈现的信息就越多。所以如果你从信息论的角度来考虑，你可以通过不同的信息论通道进行通信。其中一个通道是打字界面。你可以想象它是由一个网格构成的，就像屏幕上的软件键盘一样。每秒比特数是通过取屏幕上目标数量的对数来计算的。如果你要模拟键盘，你可以减去 1，因为你需要为键盘上的删除键减去 1。但屏幕上目标数量的对数乘以正确选择次数减去错误选择次数，再除以某个时间窗口（例如 60 秒），这就是学术界衡量光标控制任务的标准方法。这一切都要归功于斯坦福大学的 Sh 教授，他提出了这个任务，他也是我进入这个领域的灵感来源之一。所以所有的功劳都归功于他，他提出了一个标准化的指标，让我们现在可以炫耀说 Nolan 是……

Yeah, maybe I'll take one zoom out step there, which is just explaining why we care to measure this at all. So again, our goal is to provide the user the ability to control their computer as well as I can and hopefully better. That means that they can do it at the same speed as what I can do. It means that they have access to all the same functionality that I have, including all those little details like Command Tab, Command Space, all this stuff. They need to be able to do it with their brain and with the same level of reliability as what I can do with my muscles. And that's a high bar. So we intend to measure and quantify every aspect of that to understand how we're progressing towards that goal. There's many ways to measure BPS, this isn't the only way, but we present the user a grid of targets and basically we compute a score which is dependent on how fast and accurate they can select, and then how small are the targets. The more targets that are on the screen, the smaller they are, the more information you present per click. So if you think about it from an information theory point of view, you can communicate across different information theoretic channels. One such channel is a typing interface. You could imagine that's built out of a grid, just like a software keyboard on the screen. Bits per second is a measure that's computed by taking the log of the number of targets on the screen. You can subtract one if you care to model a keyboard because you have to subtract one for the delete key on the keyboard. But log of the number of targets on the screen times the number of correct selections minus incorrect, divided by some time window, for example 60 seconds. That's sort of the standard way to measure a cursor control task in academia. All credit in the world goes to this great Professor Dr. Sh of Stanford who came up with that task, and he's also one of my inspirations for being in the field. So all the credit in the world to him for coming up with a standardized metric to facilitate this kind of bragging rights that we have now to say that Nolan is the...

他在使用 PCI 设备完成这项任务上是世界最佳。拥有标准化指标对进展至关重要，这样人们就能比较不同技术和方法的表现。他做得有多好？所以，向他以及斯坦福的整个团队致以崇高的敬意。

Best in the world at this task with his PCI. It's very important for progress that you have standardized metrics so people can compare across different techniques and approaches. How well does this do? So big kudos to him and to all the team at Stanford.

所以对于 Nolan 和我来说，玩这个任务时，你可以配置不同的模式。网页网格任务可以只是屏幕上的左键点击，或者你可以有只需悬停的目标，或者你可以有需要左键或右键点击的目标，你还可以有左键、右键、中键点击、滚动、点击拖拽等目标。在这个通用框架内，你可以做各种事情。但最简单、最纯粹的形式就是蓝色目标出现在屏幕上，蓝色代表左键点击。这是游戏最简单的形式。

So for Nolan and for me, playing this task, there are also different modes that you can configure. The web grid task can be presented as just a left click on the screen, or you could have targets that you just dwell over, or you could have targets that you left or right click on, you could have targets that are left click, right click, middle click, scrolling, clicking and dragging. You can do all sorts of things within this general framework. But the simplest, purest form is just blue targets show up on the screen, blue means left click. That's the simplest form of the game.

此前的学术记录以及 Neuralink 内部用非人灵长类动物（NHP）的记录，都已被 Nolan 用他的 Neuralink 设备追平或超越。在 Neuralink 之前，人类使用设备的世界纪录大约在 4.2 到 4.6 BPS 之间，具体取决于你读哪篇论文以及如何解读。Nolan 目前的记录是 8.5 BPS。而 Neuralink 使用者的中位性能是 10 BPS。所以你可以大致认为，他的控制水平达到了中位 Neuralink 使用者用光标在屏幕上对准蓝色目标的 85%。

The sort of prior records here in academic work and at Neuralink internally with NHPs have all been matched or beaten by Nolan with his Neuralink device. So prior to Neuralink, the sort of world record for a human using a device is somewhere between 4.2 to 4.6 BPS, depending on exactly what paper you read and how you interpret it. Nolan's current record is 8.5 BPS. And again, the sort of median Neuralinker performance is 10 BPS. So you can think of it roughly as he is 85% the level of control of a median Neuralinker using their cursor to slot blue targets on the screen.

我认为，要达到 10 BPS 的同等水平，前方有一段非常有趣的旅程。那些让我们从 4 到 6 BPS、再从 6 到 8 BPS 的技巧，并不会同样让我们从 8 到 10 BPS。在我看来，这里的核心挑战实际上是标注问题——如何以非常精细的分辨率理解用户试图做什么。我强烈鼓励学术界的人研究这个问题。

I think there's a very interesting journey ahead to get us to that same level of 10 BPS performance. It's not the case that the tricks that got us from 4 to 6 BPS and then 6 to 8 BPS are going to be the ones that get us from 8 to 10. In my view, the core challenge here is really the labeling problem. It's how do you understand at a very fine resolution what the user is attempting to do. I highly encourage folks in academia to work on this problem.

在提高网页网格 BPS 的征程中，Nolan 的旅程是怎样的？三月份，你说他在网页网格中选择了 89,185 个目标。他热爱这个游戏，非常认真地想要提高表现。那么，试图提升表现的这段旅程是怎样的？解码端能贡献多少？校准端能贡献多少？Nolan 这边，在更清晰地传达意图上又能贡献多少？

What's the journey with Nolan on that quest of increasing the BPS on web grid? In March, you said that he selected 89,185 targets in web grid. He loves this game. He's really serious about improving his performance in this game. So what is that journey of trying to figure out how to improve that performance? How much can that be done on the decoding side? How much can that be done on the calibration side? How much can that be done on the Nolan side of figuring out how to convey his intention more cleanly?

这是个好问题。在我看来，Nolan 表现如此出色的主要原因之一就是 Nolan 本人。他极度专注且精力充沛。他有时会在半夜玩网页网格长达四个小时，从凌晨 2 点到 6 点，就因为他想把它推到自己的极限。这不是我们要求他做的。我想说清楚：我们并没有说“嘿，你今晚应该玩网页网格”。我们只是把游戏作为研究的一部分给了他，他可以独立玩耍，随时练习。他真的很努力地把技术推向绝对极限，并把它当作自己的工作，让我们成为瓶颈。他做得非常好。

This is a great question. In my view, one of the primary reasons why Nolan's performance is so good is because of Nolan. Nolan is extremely focused and very energetic. He'll play web grid sometimes for like four hours in the middle of the night, from 2 a.m. to 6 a.m., he'll be playing web grid just because he wants to push it to the limits of what he can do. This is not us asking him to do that. I want to be clear: we're not saying 'hey, you should play web grid tonight.' We just gave him the game as part of our research, and he is able to play independently and practice whenever he wants. He really pushes hard to push the technology to the absolute limit, and he used it as his job to make us be the bottleneck. Boy, has he done that well.

首先要承认的是，他非常有动力让这一切成功。我也有幸见过 BrainGate 和其他试验的其他临床试验参与者，他们都非常认同这种态度，把推动技术进步视为自己毕生的事业。如果这意味着从凌晨 2 点到 6 点点击屏幕上的目标四个小时，那就这样吧。

The first thing to acknowledge is that he was extremely motivated to make this work. I've also had the privilege to meet other clinical trial participants from BrainGate and other trials, and they very much share the same attitude of viewing this as their life's work to advance the technology as much as they can. If that means clicking targets on the screen for 4 hours from 2 a.m. to 6 a.m., so be it.

那就这样吧，这其中有非常值得称赞的地方。那么，你是如何从他一开始完全没有光标控制，到后来找到最直观的控制方式的？我的意思是，当他开始时，他和我们都需要大量学习，才能找出对他来说最直观的控制方式。

Then so be it and there's something extremely admirable about that that's worth calling out. Okay, so now how do you sort of get from where he started, which is no cursor control at all? I mean, when he started, there's a huge amount of learning to do on his side and our side to figure out what's the most intuitive control for him.

对他来说最直观的控制方式，就是必须找到我们能够解码的信号交集。我们不会采集运动皮层中的每一个神经元，这意味着我们并不代表身体的每个部位。因此，有些空间我们的解码表现会更好。例如，在他的左手上，我们很难区分他的无名指和中指，但在他的右手上，我们能够从记录到的神经元中检测到对小指、拇指和食指的良好控制和调制。所以你可以想象，这些不同的调制活动子空间如何与对他来说最直观的方式相交。这随着时间的推移而演变。一旦我们让他能够自己校准模型，他就开始探索各种不同的方式来想象控制光标。例如，他可以想象通过左右摆动腕部或移动整个手臂来控制光标。但我想有一次他用了脚。他尝试了很多东西，来探索对他来说最自然的控制光标的方式，同时这种方式也便于我们解码。

The most intuitive control for him is sort of you have to find the set intersection of what do we have the signal to decode. So we don't pick up every single neuron in the motor cortex, which means we don't have representations for every part of the body. So there may be some spaces that we have better decode performance on than others. For example, on his left hand, we have a lot of difficulty distinguishing his left ring finger from his left middle finger, but on his right hand, we have good control and good modulation detected from the neurons we're able to record for his pinky, his thumb, and his index finger. So you can imagine how these different subspaces of modulated activity intersect with what's the most intuitive for him. This has evolved over time. Once we gave him the ability to calibrate models on his own, he was able to go and explore various different ways to imagine controlling the cursor. For example, he could imagine controlling the cursor by wiggling his wrist side to side or by moving his entire arm. But I think at one point he did his feet. He tried a whole bunch of stuff to explore the space of what is the most natural way for him to control the cursor that at the same time is easy for us to decode.

澄清一下，是通过身体映射程序，你才能确定他能移动哪根手指？

Just to clarify, it's through the body mapping procedure that you're able to figure out which finger he can move?

是的，是的，这是一种方法。也许有一个细微差别：当他这样做时，他能想象的东西比我们在屏幕上展示的要多得多。所以我们抽象地给他看，“这是一个光标，你自己找出最适合你的方式。”我们显然从身体映射程序中得到了关于什么最有效的提示。我们知道这个特定动作我们可以很好地表示，但最终还是由他去探索并找出最有效的方式。

Yes, yes, that's one way to do it. Maybe one nuance: when he's doing it, he can imagine many more things than we represent in that visual on the screen. So we show him sort of abstractly, 'Here's a cursor, you figure out what works the best for you.' And we obviously have hints about what will work best from that body mapping procedure. We know that this particular action we can represent well, but it's really up to him to go and explore and figure out what works the best.

但他在哪个阶段不再想象自己身体的运动，而只是想象光标的移动？他多快能达到那个状态？

But at which point does he no longer visualize the movement of his body and he's just visualizing the movement of the cursor? Yeah, how quickly does he get there?

这件事发生在一个星期二。我记得非常清楚，因为那天某个时候，看起来他表现得不太好。模型似乎表现不佳，他有点分心。但事实并非如此。实际上，他是在尝试新东西——他只是直接控制光标。他不再想象移动手；他只是想象某种抽象的意图来移动屏幕上的光标。我无法告诉你这两者之间的区别。我真的不能。他之前试图向我解释过。我无法给出第一人称的描述，但他在那一刻发出的感叹足以表明，对他来说，直接通过神经控制光标是一种非常不同的体验。

So this happened on a Tuesday. I remember this day very clearly because at some point during the day, it looked like he wasn't doing super well. It looked like the model wasn't performing super well and he was getting distracted. But actually it wasn't the case. What actually happened was he was trying something new where he was just controlling the cursor. So he wasn't imagining moving his hand anymore; he was just imagining, I don't know what it is, some like abstract intention to move the cursor on the screen. I cannot tell you what the difference between those two things is. I truly cannot. He's tried to explain it to me before. I cannot give a first-person account of what that's like, but the expletives that he uttered in that moment were enough to suggest that it was a very qualitatively different experience for him to just have direct neural control over a cursor.

我想知道是否有一种方法可以通过用户体验设计来鼓励人们发现这一点。因为他像你说的那样自己发现了。他是个先驱，所以他在尝试用不同意图移动光标的过程中自己发现了这一点。但这显然是一个非常强大的境界：放弃控制手指和手，直接用思想控制数字设备。

I wonder if there's a way through UX to encourage a human being to discover that. Because he discovered it like you said. He's a pioneer, so he discovered that on his own through the process of trying to move the cursor with different kinds of intentions. But that is clearly a really powerful thing to arrive at: to let go of trying to control the fingers and the hand and control the actual digital device with your mind.

没错。用户体验就是这样起作用的。理想的用户体验是用户不需要思考需要做什么才能完成，他们直接就能做到。

That's right. UX is how it works. And the ideal UX is one where the user doesn't have to think about what they need to do in order to get it done; they just do it.

这太迷人了。但我想知道在生物学方面，大脑需要多长时间来适应。所以，这仅仅是像高级软件那样的学习，还是存在神经可塑性成分，大脑在缓慢调整？

That is so fascinating. But I wonder on the biological side, how long it takes for the brain to adapt. Yeah, so is it just simply learning like high-level software, or is there a neuroplasticity component where the brain is adjusting slowly?

说实话，我不知道。我非常期待看到我们植入的第二位参与者的历程，因为我们会学到更多。也许我们可以帮助他们更快地理解和探索那个方向。这不是我提示 Nolan 去尝试的；他只是自己探索如何使用设备并发现了这一点。但现在我们知道这是可能的，也许有一种方法可以提示用户：“在校准过程中不要太努力，只需做一些感觉自然的事情，或者直接控制光标，不要想象具体的动作。”从那里，我们应该能够理解这对于从未经历过的人来说是怎样的。也许这就是他们的默认操作模式；你不需要经历这个中间阶段的显式动作。或者，如果这对人们来说是自然发生的，你可以偶尔鼓励他们允许自己移动光标。

The truth is I don't know. I'm very excited to see with the second participant that we implant what the journey is like for them, because we'll have learned a lot more. Potentially we can help them understand and explore that direction more quickly. This is something I didn't prompt Nolan to go try; he was just exploring how to use his device and figured it out himself. But now that we know that's a possibility, maybe there's a way to hint the user: 'Don't try super hard during calibration, just do something that feels natural, or just directly control the cursor, don't imagine explicit action.' From there, we should be able to hopefully understand how this is for somebody who has not experienced that before. Maybe that's the default mode of operation for them; you don't have to go through this intermediate phase of explicit motions. Or maybe if that naturally happens for people, you can just occasionally encourage them to allow themselves to move the cursor.

实际上，有时就像一英里外的表格一样，仅仅知道那是可能的，就会促使你去实现它，然后它就变得微不足道了。这也让你思考——这就是人类的酷之处——一旦有更多的人类参与者，他们会发现可能的事情，并相互分享经验。由于他们的分享，其他人也能做到。突然间，这对所有人都解锁了，因为有时候仅仅是知识就能促成它。

Actually, sometimes just like with a form in a mile, just the knowledge that that's possible pushes you to do it, enables you to do it, and then it becomes trivial. And then it also makes you wonder—this is the cool thing about humans—if once there's a lot more human participants, they will discover things that are possible and share their experiences with each other. And because of them sharing it, they'll be able to do it. All of a sudden, that's unlocked for everybody, because just the knowledge sometimes is the thing that enables it.

是的，我的意思是，我们也尝试了大概一千种不同的解码方法，现在我们知道了正确的子空间可以继续深入探索。再次感谢 Nolan 和他投入的无数小时。即使只是帮助我们约束不同方法的束搜索，也真的加速了下一个人的进程。我们第一天就能尝试的事情，我们希望多快让他们获得有用的控制，多快让他们能够独立使用并从中获得价值。所以，向 Nolan 和他之前的所有参与者致以崇高的敬意，是他们让这项技术成为现实。

Yeah, I mean, coming on that too, we've probably tried like a thousand different ways to do various aspects of decoding, and now we know what the right subspace is to continue exploring further. Again, thanks to Nolan and the many hours he's put into this. Even just that help constrain the beam search of different approaches that we could explore really helps accelerate for the next person. The set of things that we'll get to try on day one, how fast we hopefully get them to useful control, how fast we can enable them to use it independently and to get value out of the system. So yeah, massive hats off to Nolan and all the participants that came before him to make this technology a reality.

那么解码器的更新频率如何？因为 Nolan 提到我们正在开发一个新更新，在直播中他说他玩贪吃蛇游戏，因为那非常难，是测试更新效果的好方法。他说有时更新会倒退。这是一个持续的过程……

So how often are the updates to the decoder? Because Nolan mentioned that there's a new update that we're working on, and in the stream he said he plays the snake game because it's super hard, it's a good way for him to test how good the update is. And he says sometimes the update is a step backwards. It's a constant...

比如迭代，频率如何？更新具体包括什么？主要是解码器这边吗？

Like iteration, so how often? Like what does the update entail? Is it mostly on the decoder side?

嗯，有几点要说。首先，可能有必要区分一下研究阶段和独立使用阶段。在研究阶段，我们会主动尝试各种不同的方法，比如我们之前提到的无监督方法，来找到更好的方式估计他的真实意图并更准确地解码。而在独立使用阶段，我们希望他能像任何人使用 MacBook 一样自由地使用设备。他提到的通常是在研究阶段，我们每天会尝试很多不同的方法——他有时一天工作八小时，我们一天可能会尝试几百个不同的模型。另外，我们更新他使用的应用程序非常频繁，有时一天会更新四到五次，加入新功能、修复 bug 或根据他的反馈进行调整。他非常善于表达，是解决方案的一部分，而不是抱怨。他会说：“嘿，我发现这个东西在我的流程中不是最优的，我有一些改进的想法，你们怎么看？我们一起解决。”通常，他的反馈在几小时内就能得到处理，这就是我们的迭代周期。有时在 session 开始时他给我们反馈，到 session 结束时，他已经在给下一个迭代版本提意见了。

Yeah, couple comments. So one is, it's probably worth drawing a distinction between sort of research sessions where we're actively trying different things to understand like what the best approach is, versus sort of independent use where we wanted to have, you know, ability to just go use a device how anybody would want to use their MacBook. And so what he's referring to is, I think usually in the context of research session where we're trying, you know, many many different approaches to, you know, even unsupervised approaches like we talked about earlier, to try to come up with better ways to estimate his true intention and more accurately decode it. And in those scenarios, I mean, we try in any given session, he'll sometimes work for like eight hours a day, and so that can be, you know, hundreds of different models that we would try in that day, like a lot of different things. Um, now it's also worth noting that we update the application he uses quite frequently. I think, you know, sometimes up to like four or five times a day we'll update his application with different features or bug fixes or feedback that he's given us. So he's been able to, he's a very articulate person who is part of the solution. He's not a complaining person. He says, hey, here's this thing that I've discovered is not optimal in my flow, here's some ideas how to fix it, let me know what your thoughts are, let's figure out how to solve it. And it often happens that those things are addressed within, you know, a couple hours of him giving us his feedback, because that's the kind of iteration cycle we'll have. And so sometimes at the beginning of the session he'll give us feedback, and at the end of the session he's giving us feedback on the next iteration of that process, that setup.

太棒了，因为你提到仅三月份就从 BCI 会议中记录了 271 页笔记。人类最了不起的一点——尤其是像 Nolan 这样聪明、热情、充满正能量的人——就是能持续提供反馈。

That's fascinating, because one of the things you mentioned that there was 271 pages of notes taken from the BCI sessions, and this was just in March. So one of the amazing things about human beings, especially ones who are smart and excited and all like positive and good vibes like Nolan, is that they can provide continuous feedback.

是的，这也需要——容我夸一下团队——我身边有很多优秀的人，团队必须完全聚焦于用户，思考什么对他们最好。这需要一种承诺：用户反馈来了，我本来有这些会议，但今天不开了，我们来做这个。这种专注和投入，我觉得在世界上被低估了。当然，你也需要有才能去有效执行，而我们在这方面人才济济。

Yeah, it also requires, just to brag on the team a little bit, I work with a lot of exceptional people, and it requires the team being absolutely laser focused on the user and what will be the best for them. And it requires like a level of commitment of: okay, this is what the user feedback was, I have all these meetings, we're going to skip that today and we're going to do this. You know, that level of focus and commitment is, I would say, underappreciated in the world. And also, you know, you obviously have to have the talent to be able to execute on these things effectively, and yeah, we have that in loads.

是的，UX 设计这个领域非常有趣，因为未知因素太多了。从那么多糟糕的设计就能看出 UX 很难，这绝非易事。

Yeah, and this is such an interesting space of UX design, because there are so many unknowns here. And I can tell UX is difficult because of how many people do it poorly. It's just not a trivial thing.

是的，而且 UX 并不是总能通过不断迭代不同方案来解决。有时你真的需要退一步，从全局思考：我是不是在正确的极小值上寻找解决方案？很多问题中，快速迭代周期是成功的关键。比如在强化学习模拟中，获得奖励越频繁，进步越快；反馈越频繁，学习问题就越简单。但 UX 不是这样。用户常常对正确的解决方案判断有误，这需要你深刻理解技术系统和可能性，同时结合你要解决的问题——不是用户表达的方式，而是真正的根本问题——才能找到正确的方向。

Yeah, it's also, you know, UX is not something that you can always solve by just constantly iterating on different things. Like sometimes you really need to step back and think globally: am I even in the right sort of minima to be chasing down for a solution? Like there's a lot of problems in which sort of fast iteration cycle is the predictor of how successful you will be. As a good example, like in an RL simulation, for example, the more frequently you get reward, the faster you can progress. It's just an easier learning problem the more frequently you get feedback. But UX is not that way. I mean, users are actually quite often wrong about what the right solution is, and it requires a deep understanding of the technical system and what's possible, combined with what the problem is you're trying to solve — not just how the user expressed it, but what the true underlying problem is — to actually get to the right place.

是的，这就像史蒂夫·乔布斯的老故事：用户是有用的信号，但不是完美的信号。有时你得移除软驱之类的。我忘了乔布斯那些疯狂的设计决策故事了。但他的美学，其中一部分是你在设计中投入的热爱，这很乔布斯、乔纳森·艾夫风格。但当一个人用大脑与设备交互时，功能也至关重要，不仅仅是美学。你必须对面前的人有同理心，同时又不总是直接听从他们的话。你必须深度共情。这太迷人了。同时还要迭代，对吧？但不是小步迭代，有时要完全重建设计。你说 Nolan 说早期 UX 很糟糕，但你们改进得很快。这个过程是怎样的？

Yeah, that's the old story of Steve Jobs, like rolling in there like, yeah, the user is a useful signal, but it's not a perfect signal. And sometimes you have to remove the floppy disc drive or whatever. I forgot all the crazy stories of Steve Jobs making wild design decisions. But some of his aesthetic, some of it is about the love you put into the design, which is very much a Steve Jobs, Jony Ive type thing. But when you have a human being using their brain to interact with it, it also is deeply about function. It's not just aesthetic. And you have to empathize with a human being before you, while not always listening to them directly. Like you have to deeply empathize. It's fascinating, really really fascinating. And at the same time iterate, right? But not iterate in small ways, sometimes a complete rebuilding of the design. He said that Nolan said the early days the UX sucked. Yeah, but you improved quickly. What was that journey like?

嗯，我给你举个具体的例子。他非常想能看漫画。这听起来简单，但对他来说是件大事。他用嘴棒做不到，无法在 iPad 上滚动，也无法在他想看的漫画网站上滚动。先解释一下嘴棒：他嘴里叼着一根棍子来在平板上滑动。你可以想象成一根很长的触控笔，咬在牙齿间。这很累，很疼，而且效率低。另外值得一提的是，还有其他辅助技术，但 Nolan 的特殊情况——这并不罕见，而且很多人不了解——是他会时不时肌肉痉挛。任何需要他正对摄像头（比如眼动追踪）或嘴里含东西的辅助技术都不行，因为痉挛时他会移出画面，或者嘴里有东西会戳到脸。这些考虑很重要，能看出 BCI 在一个人生活中的优势：它是否符合人体工学，能否在护理人员不在时独立使用，无论在床上还是椅子上，取决于你的舒适度和对压疮的考虑。所有这些因素都决定了解决方案在用户生活中的效果。其中一个有趣的例子就是滚动。他想看漫画，而 BCI 有很多种滚动方式。

Yeah, I mean, I'll give one concrete example. So he really wanted to be able to read manga. This is something that he — I mean, yeah, it sounds like a simple thing, but it's actually a really big deal for him. And he couldn't do it with this mouth stick. It just wasn't accessible. You can't scroll with the mouth stick on his iPad, and on the website that he wanted to be able to use to read the new manga. So might be a good quick pause to say the mouth stick is the thing he's using, holding a stick in his mouth to scroll on a tablet, right? Yeah, it's basically you can imagine it's a stylus that you hold between your teeth. It's basically a very long stylus, and it's exhausting, it hurts, and it's inefficient. Yeah, and maybe it's also worth calling out there are other alternative assistive technologies, but the particular situation Nolan's in — and this is not uncommon, and I think it's also not well understood by folks — is that you know, he's relatively so he'll have muscle spasms from time to time. And so any assistive technology that requires him to be positioned directly in front of a camera, for example an eye tracker, or anything that requires him to put something in his mouth, is just a no-go because he'll either be shifted out of frame when he has a spasm, or if he has something in his mouth it'll stab him in the face, you know, if he spasms too hard. So these kind of considerations are important when thinking about what advantages a BCI has in someone's life. If it fits ergonomically into your life in a way that you can use it independently when your caretaker's not there, wherever you want, either in the bed or in the chair, depending on your comfort level and your desire to have pressure sores, you know, all these factors matter a lot in how good the solution is in that user's life. So one of these very fun examples is scroll. So again, manga is something he wanted to be able to read, and there's many ways to do scroll with the BCI.

想象一下不同的手势，比如用户可以通过手势来移动页面，但滚动是一个非常迷人的控制界面，因为它在你面前的屏幕上是一个巨大的东西。所以模型输出的任何抖动，任何误差，都会导致屏幕像地震一样。你真的不想让你正在阅读的漫画页面因为滚动解码器不够精确而上下移动几个像素。所以这是一个例子，我们必须想办法构建问题，使得系统的错误——我们会尽力最小化它们——但无论何时这些错误发生，都不会打断用户的体验质感，不会打断他们阅读书籍的流畅感。所以我们最终构建了一个非常出色的功能。我的一个名叫 Bru 的同事开发了这个非常出色的功能，叫做 Quick Scroll。Quick Scroll 基本上会查看屏幕，识别出屏幕上的滚动条在哪里，它通过深度集成 macOS，利用 macOS 应用可用的无障碍树来理解滚动条当前在屏幕上的位置。我们识别出这些滚动条的位置，并提供了一个 BCI 滚动条。BCI 滚动条看起来和普通滚动条相似，但行为非常不同：一旦你移动过去，你的光标就会变形并吸附上去，然后当你像控制普通光标一样向上或向下推动时，它实际上会为你移动屏幕。这基本上就是将速度重新映射为滚动动作。之所以感觉如此自然直观，是因为当你移动过去吸附时，感觉像磁铁一样，你就被粘住了，然后这是一个连续的动作。你不需要切换你的想象动作，你直接吸附上去，然后就可以立即开始向下拉页面或向上推。即使你做到了这一点，滚动行为要变得自然直观，还有无数细微之处。一个例子是动量。当你用手指在屏幕上滚动页面时，实际上有一些流动感，它不会在你手指抬起时立刻停止。BCI 滚动也是如此。所以我们花了一些时间来弄清楚，当你不再感觉到指尖下的屏幕时，正确的细微差别是什么。正确的动态是什么，或者当你推动时，页面应该有多少“弹性”，才能让用户有自然的阅读体验。有无数——我的意思是，我可以告诉你，滚动功能有太多细微之处，我们大概花了一个月才把它调整得极其自然，让用户轻松导航。

Imagine like different gestures, for example the user could do that would move the page, but scroll is a very fascinating control surface because it's a huge thing on the screen in front of you. So any sort of jitter in the model output, any sort of error in the model output causes like an earthquake on the screen. You really don't want to have your manga page that you're trying to read be shifted up and down a few pixels just because your scroll decoder is not completely accurate. So this was an example where we had to figure out how to formulate the problem in a way that the errors of the system, whenever they do occur—and we'll do our best to minimize them—but whenever those errors do occur, it doesn't interrupt the qualia of the experience that the user is having, it doesn't interrupt their flow of reading their book. And so what we ended up building is this really brilliant feature. This is a teammate named Bru who worked on this really brilliant work called Quick Scroll. Quick Scroll basically looks at the screen and it identifies where on the screen are scroll bars, and it does this by deeply integrating with macOS to understand where are the scroll bars actively present on the screen using the sort of accessibility tree that's available to macOS apps. And we identified where those scroll bars are and we provided a BCI scroll bar. The BCI scroll bar looks similar to a normal scroll bar but it behaves very differently in that once you sort of move over to it, your cursor sort of morphs onto it, it sort of attaches or latches onto it, and then once you push up or down in the same way that you'd use a push to control the normal cursor, it actually moves the screen for you. So it's basically like remapping the velocity to a scroll action. And the reason that feels so natural and intuitive is that when you move over to attach to it, it feels like magnetic, so you're sort of stuck onto it, and then it's one continuous action. You don't have to switch your imagine movement, you sort of snap onto it and then you're good to go, you just immediately can start pulling the page down or pushing it up. And even once you get that right, there's so many little nuances of how the scroll behavior works to make it natural and intuitive. So one example is momentum. Like when you scroll a page with your fingers on the screen, you actually have some flow, it doesn't just stop right when you lift your finger up. The same is true with BCI scroll. So we had to spend some time to figure out what are the right nuances when you don't feel the screen under your fingertip anymore. What is the right sort of dynamic, or what's the right amount of page give, if you will, when you push it to make it flow the right amount for the user to have a natural experience reading their book. And there's a million—I mean, I could tell you there's so many little nuances of how exactly that scroll works that we spent probably like a month getting right to make that feel extremely natural and easy for the user to navigate.

我的意思是，即使是智能手机上用指尖滚动，感觉也极其自然舒适，而要做到这一点可能需要非常长的时间。实际上，我们之前讨论的那种远见卓识的 UX 设计：不要总是听从用户，但也要倾听他们，同时要有远见，推翻一切，从第一性原理思考，但又不完全如此。是的，是的。顺便说一句，这让我想到桌面上的滚动条可能已经停滞不前了，从来没有采用你所说的那种吸附到滚动条的动作，这在桌面环境中可能非常有用，即使只是为了改善用户体验，因为当前桌面上的滚动条体验很糟糕。它很难找到，很难控制，没有动量。意图应该很明确：当我开始向滚动条移动时，应该有一个吸附到滚动条的动作。但当然，也许我可以接受这个代价，但有数亿人一直在付出这个代价。不过无论如何，在这种情况下，这是必要的，因为 Nolan 为抖动付出了额外的代价。所以你必须在滚动和阅读之间切换；两者之间必须有一个相位转换。比如当你滚动时，你就在滚动，对吧？所以这是当前方法的一个缺点。

I mean, even the scroll on a smartphone with your finger feels extremely natural and pleasant, and it probably takes an extremely long time to get that right. And actually, the same kind of visionary UX design that we were talking about: don't always listen to the users, but also listen to them, and also have visionary big, throw everything out, think from first principles, but also not. Yeah, yeah. By the way, it just makes me think that scroll bars on the desktop probably have stagnated and never taken that snap-to-scroll-bar action you're talking about, which could potentially be extremely useful in the desktop setting, even just for users to improve the experience, because the current scroll bar experience on the desktop is horrible. It's hard to find, hard to control, there's no momentum. And the intention should be clear: when I start moving towards a scroll bar, there should be a snapping to the scroll bar action. But of course, maybe I'm okay paying that cost, but there's hundreds of millions of people paying that cost non-stop. But anyway, in this case, this is necessary because there's an extra cost paid by Nolan for the jittering. So you have to switch between the scrolling and the reading; there has to be a phase shift between the two. Like when you're scrolling, you're scrolling, right? So that is one drawback of the current approach.

也许再举一个案例研究。再次强调，用户体验就是它的工作方式，我们从大脑中检测到的特征检测层面，到我们如何设计解码器、选择解码什么，再到用户使用时的表现，进行整体思考。另一个很好的例子是用户实际使用解码器时的表现：屏幕上显示的输出不仅仅是解码器说的内容，还取决于屏幕上的情况。例如，我们可以理解，当你试图关闭一个标签页时，那个非常小的愚蠢的 X 极其微小，如果解码器输出有噪声，很难精确点击。我们可以理解那是一个你可能试图点击的小 X，并实际上为你放大目标。类似于在手机上打字时，如果你习惯了 iOS 键盘，它会根据底层语言模型调整单个按键的目标大小。所以它会理解，如果我输入“hey I'm going to see L”，它会放大 E 键，因为它知道 Lex 是你要去见的人。这种预测性可以使体验更加流畅，即使没有改进底层解码器或特征检测部分。所以我们通过一个叫做“磁力目标”的功能来实现这一点。我们实际上索引屏幕并理解：好的，这些地方是非常小的目标，可能难以点击；这些位置周围的游标动态可能表明用户试图选择它；让我们让它更容易，放大它的尺寸，使用户更容易吸附到那个目标上。所有这些小细节，对于帮助用户在日常生活中独立非常重要。

Maybe one other just sort of case study here. So again, UX is how it works, and we think about that holistically from the feature detection level of what we detect in the brain, to how we design the decoder, what we choose to decode, to then how it works once it's being used by the user. So another good example in the sort of how it works once they're actually using the decoder: the output that's displayed on the screen is not just what the decoder says; it's also a function of what's going on on the screen. So we can understand, for example, that when you're trying to close a tab, that very small stupid little X that's extremely tiny, which is hard to hit precisely if you're dealing with a noisy output of the decoder, we can understand that that is a small little X you might be trying to hit and actually make it a bigger target for you. Similar to how when you're typing on your phone, if you're used to the iOS keyboard for example, it actually adapts the target size of individual keys based on an underlying language model. So it'll actually understand that if I'm typing 'hey I'm going to see L', it'll make the E key bigger because it knows Lex is the person I'm going to go see. And so that kind of predictiveness can make the experience much more smooth even without improvements to the underlying decoder or feature detection part of the stack. So we do that with a feature called magnetic targets. We actually index the screen and we understand: okay, these are the places that are very small targets might be difficult to hit; here's the kind of cursor dynamics around that location that might be indicative of the user trying to select it; let's make it easier, let's blow up the size of it in a way that makes it easier for the user to snap onto that target. So all these little details, they matter a lot in helping the user be independent in their day-to-day living.

那么解码器上的工作有多少可以推广到 P2、P3、P4、P5、PN？你如何以可推广的方式改进解码器？

So how much of the work on the decoder is generalizable to P2, P3, P4, P5, PN? How do you improve the decoder in a way that's generalizable?

是的，好问题。我们试图解码的底层信号在 P2 和 P1 中会非常不同。例如，通道 345 在用户一和用户二中的含义不同，只是因为对应的电极……

Yeah, great question. So the underlying signal we're trying to decode is going to look very different in P2 than in P1, for example. Channel number 345 is going to mean something different in user one than it will user two, just because that electrode that corresponds...

通道 345 在用户一和用户二身上会对应不同的神经元，但方法、用户体验——如何让用户做出正确的行为模式来关联那个神经信号——我们希望它能跨越多代用户迁移。除此之外，我们很可能已经过度拟合了 Nolan 的用户体验偏好。所以我希望看到的是，当我们有第二、第三、第四位参与者时，能找到覆盖所有情况的正确宽最小值，让每个人用起来都更直观。而且希望有交叉影响：比如，哦，我们之前没考虑到这个用户，因为他们能说话，但那个完全不能说话的用户，这种体验就不理想。我们在那里做的改进，应该也能惠及那些能说话但在公共场合（比如医生办公室）不方便说话的人。所以开环标记和闭环标记的机制是一样的，希望能在不同用户的校准步骤中通用。校准步骤本身也很酷。Web Grid 是闭环的，我喜欢这种——以前有人类计算的概念，就是利用人类本来就愿意做的动作来获取大量信号。Web Grid 就像一个好玩的视频游戏，同时也是很好的校准工具。

With Channel 345 is going to be in next to a different neuron in user one versus user two, but the approaches, the methods, the user experience of how do you get the right sort of behavioral pattern from the user to associate with that neural signal, we hoped it will translate over over multiple generations of users. And beyond that, it's very very possible, in fact quite likely, that we've overfit to sort of Nolan user experience desires and preferences. And so what I hope to see is that, you know, when we get a second, third, fourth participant, that we find sort of what the right wide minimas are that cover all the cases, that make it more intuitive for everyone. And hopefully there's a cross-pollination of things where, oh, we didn't think about that with this user because, you know, they can speak, but with this user who just can fundamentally not speak at all, this user experience is not optimal. And that will actually, those improvements that we make there should hopefully translate then to even people who can speak but don't feel comfortable doing so because they're in a public setting like their doctor's office. So the actual mechanism of open loop labeling and then closed loop labeling would be the same and hopefully can generalize across the different users as they're doing the calibration step. And the calibration step is pretty cool. I mean that in itself, the interesting thing about Web Grid, which is closed loop, it's like, I love it when there's like, there used to be kind of an idea of human computation, which is using actions that human would want to do anyway to get a lot of signal from. Yeah, and like Web Grid is that like a nice video game that also serves as great calibration.

这太有意思了，我听过很多次这种反应。第一个用户植入后，我们内部觉得他不会觉得这好玩。所以我们认真考虑过要不要做其他更有趣的游戏来获取数据、促进长期研究。结果发现大家都很喜欢这个游戏。我一直很喜欢，但不知道这是共识。

It's so funny, this is, I've heard this reaction so many times before. Sort of the, you know, first user was implanted, we had an internal perception that the first user would not find this fun. Yeah, and so we thought really quite a bit actually about, like, should we build other games that are more interesting for the user so we can get this kind of data and help facilitate research that's, you know, for long durations. Stuff like this turns out that, like, people love this game. Yeah, I always loved it, but I didn't know that that was a shared perception.

以防有人不清楚，Web Grid 是一个 35x35 的网格，其中一个格子会亮蓝色，你需要把鼠标移过去点击。点错就变红。我玩这个游戏玩了很多很多小时。你的记录是多少？你说我好像是 Neuralink 目前最高的。我的记录是 17 BPS。17 BPS，想象一下 35x35 的网格，你每分钟大约完成 100 次试验，也就是一分钟内正确选择 100 次。平均每次选择大约 500 到 600 毫秒。

Yeah, just in case it's not clear, Web Grid is, there's a grid of let's say 35 by 35 cells, and one of them lights up blue, and you have to move your mouse over that and click on it. And if you miss it, it's red. And I play this game for so many hours, so many hours. And what's your record? You said my, I think I have the highest at Neuralink right now. My record is 17 BPS. 17 BPS, which about, if you imagine that 35 by 35 grid, you're hitting about 100 trials per minute, so 100 correct selections in that one minute window. So you're averaging about, you know, between 500 to 600 milliseconds per selection.

我觉得我玩这个游戏吃力的一个原因是我太依赖键盘了。所有操作都用键盘，能不用鼠标就最好。你怎么解释你的高表现？

So one of the reasons I think I struggle with that game is I'm such a keyboard person. So everything is done via keyboard. If I can avoid touching the mouse, it's great. So how can you explain your high performance?

我玩 Web Grid 有一套完整的仪式。实际上还有配套的饮食计划，很讲究。首先，我得禁食五天。还要上山。禁食很重要，因为专注力来自头脑。真的。所以我之前会稍微不吃东西，然后在玩之前吃大量花生酱。这是真的。然后必须很晚，凌晨那种，又是夜猫子习惯，我觉得我们都有，得是午夜到凌晨两点。

I have like a whole ritual I go through when I play Web Grid. So it's actually like a diet plan associated with this. It's a whole thing. So first, I have to fast for 5 days. I have to go up to the mountain. Actually, it kind of, I mean the fasting thing is important. So this is like, you know, focus is the mind. Yeah, it's true. So what I do is I actually, I don't eat for a little bit beforehand, and then I'll actually eat like a ton of peanut butter right before I play. And I get, this is a real thing, this is a real thing. Yeah, and then it has to be really late at night. This is again a night owl thing, I think we share, but it has to be like, you know, midnight 2 a.m.

时间窗口很特别，我也有一个非常具体的身体姿势。我小时候在家上学，所以大部分时间都坐在地板上，就在我的卧室里。我在地板上有一个非常特定的位置坐着玩。你得确保手肘不要承受太多重量，这样才能快速移动。我把光标增益调得很高，也就是光标速度调得很快，这样小动作就能移动光标。你是用手腕移动的吗？

Kind of time window and I have a very specific physical position I'll sit in. I was homeschooled growing up, so I did most of my work on the floor in my bedroom. I have a very specific situation on the floor that I sit and play. You have to make sure there's not a lot of weight on your elbow when you're playing so you can move quickly. I turn the gain of the cursor, the speed of the cursor, way up so it's like small motions that actually move the cursor. Are you moving with your wrist?

你从来不用手腕移动。我用手指移动。我的手腕几乎完全不动，只是手指在动。对，就是那种小范围的切线运动。我一直想深入了解那些打破俄罗斯方块世界纪录的人。那些人玩的时候，有一种方法……你见过吗？所有手指都在动。你可以找到一种利用漏洞或 bug 的方法，做出一些快得不可思议的操作。差不多是那个路子，但又不完全一样。

You never move with your wrist. I move with my fingers. My wrist is almost completely still; I'm just moving my fingers. Yeah, you know, those just in a small tangent. I've been meaning to go down this rabbit hole of people that set the world record in Tetris. Those folks, they're playing, there's a way to... Did you see this? Like all the fingers are moving. You could find a way to do it using a loophole, like a bug, that you can do some incredibly fast stuff. It's along that line but not quite.

你知道现在会有一些程序员在听这个，他们又快又爱吃花生酱。请打破我的记录。我这么做其实就是为了给团队设定一个高目标。我希望我们瞄准的数字不应该是中位数表现，至少应该能打败我们所有人。那应该是最低门槛。你觉得可能达到多少？比如 20？

You do realize there'll be a few programmers right now listening to this who fast and eat peanut butter. Please break my record. I mean, the reason I did this literally was just because I wanted the bar to be high for the team. I wanted the number that we aim for should not be like the median performance; it should be able to beat all of us at least. That should be the minimum bar. What do you think is possible? Like 20?

我不知道极限在哪里。你可以根据屏幕刷新率和光标立即跳到下一个目标来计算极限。但在此之前还有反应时间和视觉感知等限制。我猜大概在 20 到 40 之间。这可能是值得考虑的数字。任务的难度也很重要。你可以想象有些人可能能处理屏幕上 10000 个目标，也许他们能做得更好。所以你也可以做一些任务优化来提升表现。

I don't know what the limits are. The limits you can calculate just in terms of screen refresh rate and cursor immediately jumping to the next target. But there are limits before that with reaction time and visual perception and things like that. I'd guess it's below 40 but above 20 somewhere in there. That's probably the right number to think about. It also matters how difficult the task is. You could imagine some people might be able to do 10,000 targets on the screen and maybe they can do better that way. So there are some task optimizations you could do to try to boost your performance as well.

你觉得 Nolan 要做到 85 以上需要什么？你之前说每次提升可能都需要系统做出不同的改进。

What do you think it takes for Nolan to be able to do above 85? To keep increasing that number, you said every increase might require different improvements in the system.

我认为这项工作的本质是……首先，我不知道。这是研究的前沿，以前没人达到过那个数字，所以接下来只是我的猜测。从历史上看，系统的不同部分会在不同时间成为瓶颈。我大约三年前刚加入 Neuralink 时，主要问题之一是蓝牙连接的延迟。设备上的无线电不是很好，那是植入物的早期版本。无论你的解码器多好，如果你的设备每 30 或 50 毫秒才更新一次，就会卡顿，带来挑战。那时很明显，主要挑战是可靠地将数据从设备中取出，以便解决下一个挑战。然后某个时候，变成了建模挑战：如何构建一个好的映射？这是一个监督学习问题，你有一堆数据和标签要预测，什么是正确的神经解码器架构和超参数来优化它。这曾是一个问题。一旦解决了，又出现了另一个瓶颈。我认为之后的瓶颈实际上是软件稳定性和可靠性。如果你的系统推理延迟变化很大，或者你的应用偶尔卡顿，就会降低你保持心流状态的能力，破坏你的控制体验。所以我们做了各种软件修复和改进，基本提高了系统性能，使其更可靠、更稳定，从而能够可靠地收集数据来构建更好的模型。这曾是一个问题：软件栈本身。如果我现在猜测，进一步提高 BPS 有两个主要方向。第一个方向是标注。标注又是一个基本挑战：给定一段时间窗口，用户表达了某种行为意图，他们每毫秒到底想做什么？这是一个任务设计问题、用户体验问题、机器学习问题、软件问题，涉及所有这些领域。第二个可以考虑的方向是，要么完全改变你解码的内容，要么扩展你解码的内容的数量。这是功能性的方向。你可以想象增加更多点击，例如：左键点击、右键点击、中键点击，不同的操作如点击并拖动。这可以提高你的通信假体的有效比特率。如果你想让用户通过任何给定的通信渠道表达自己，你可以用每秒比特数来衡量。但最终重要的是他们操作电脑的效率。所以从你关心的下游任务来看，功能性和扩展功能是我们非常感兴趣的，因为它不仅能提高 BPS 数值，还能提高用户的下游独立性以及他们操作电脑的技能和效率。

I think the nature of this work is... the first answer is I don't know. This is the edge of research; nobody's gotten to that number before, so what's next is a guess from my part. What we've seen historically is that different parts of the stack become bottlenecks at different times. When I first joined Neuralink about three years ago, one of the major problems was just the latency of the Bluetooth connection. The radio on the device wasn't super good; it was an earlier revision of the implant. No matter how good your decoder was, if your thing is updating every 30 or 50 milliseconds, it's just going to be choppy and lead to challenges. At that point, it was very clear that the main challenge was just getting the data off the device in a very reliable way so you could enable the next challenge. Then at some point, it was the modeling challenge: how do you build a good mapping? The supervised learning problem of having a bunch of data and a label you're trying to predict, just what is the right neural decoder architecture and hyperparameters to optimize that. That was a problem for a bit. Once you solve that, it became a different bottleneck. I think the next bottleneck after that was actually just sort of software stability and reliability. If you have widely varying inference latency in your system, or your app just lags out every once in a while, it decreases your ability to maintain a state of flow and disrupts your control experience. So there were a variety of software bugs and improvements we made that basically increased the performance of the system, made it much more reliable and stable, and led to a state where we could reliably collect data to build better models. That was a problem for a while: the software stack itself. If I were to guess right now, there are two major directions for improving BPS further. The first major direction is labeling. Labeling is again this fundamental challenge: given a window of time where the user is expressing some behavioral intent, what are they really trying to do at the granularity of every millisecond? That is a task design problem, a UX problem, a machine learning problem, a software problem; it touches all those domains. The second thing you can think about to improve BPS further is either completely changing the thing you're decoding or extending the number of things you're decoding. This is the direction of functionality. You can imagine giving more clicks, for example: left click, right click, middle click, different actions like click and drag. That can improve the effective bit rate of your communication prosthesis. If you're trying to allow the user to express themselves through any given communication channel, you can measure that with bits per second. But what actually matters at the end of the day is how effective they are at navigating their computer. So from the perspective of the downstream task you care about, functionality and extending functionality is something we're very interested in, because not only can it improve the number of BPS, but it can also improve the downstream independence that the user has and the skill and efficiency with which they can operate their computer.

增加线程数量也可能有帮助吗？

Would the number of threads increasing also potentially help?

是的，简短的回答是肯定的。这个曲线如何体现在数字上有点微妙。如果你画出用于解码的通道数量与离线解码质量指标或在线实际使用质量的曲线，你会看到大致是对数曲线。随着通道数量增加，控制质量和离线验证指标会得到相应的对数级提升。这里重要的细微差别是，每个通道对应一个特定的……

Yes, short answer is yes. It's a bit nuanced how that curve manifests in the numbers. If you plot a curve of number of channels used for decode versus either the offline metric of how good you are at decoding or the online metric of how good the user is using this device in practice, you see roughly a log curve. As you move further out in number of channels, you get a corresponding logarithmic improvement in control quality and offline validation metrics. The important nuance here is that each channel corresponds with a specific...

大脑中的意图。例如，如果你有一个通道 254，它可能对应向右移动；通道 256 可能意味着向左移动。如果你想扩展要控制的功能数量，你确实需要一组更广泛的通道，覆盖更广泛的想象动作。你可以把它想象成土豆先生（Mr. Potato Head）玩具。比如，如果你有一系列不同的想象动作可以做，你会如何将这些想象动作映射到计算机的输入？你可以想象手写来在屏幕上输出字符，你可以想象只是用手指打字并在屏幕上输出文本，你可以想象不同的手指调制来实现不同的点击，你可以想象扭动你的大鼻子来打开某个菜单，或者扭动你的大脚趾来执行 command tab 之类的操作。所以，你在世界中能执行的不同动作的数量，实际上取决于你拥有多少通道以及它们携带的信息内容。

Intention in the brain. For example, if you have a channel 254, it might correspond with moving to the right; channel 256 might mean move to the left. If you want to expand the number of functions you want to control, you really want to have a broader set of channels that covers a broader set of imagined movements. You can think of it like Mr. Potato Head, actually. Like if you had a bunch of different imagined movements you could do, how would you map those imagined movements to input to a computer? You could imagine handwriting to output characters on the screen, you could imagine just typing with your fingers and have that output text on the screen, you could imagine different finger modulations for different clicks, you could imagine wiggling your big nose for opening some menu, or wiggling your big toe to have command tab occur or something like this. So it's really the amount of different actions you can take in the world depends on how many channels you have and the information content that they carry.

所以这更多是关于动作的数量。实际上，当你增加线程数量时，这更多是关于增加你能够执行的动作数量。

So that's more about the number of actions. Actually, as you increase the number of threads, that's more about increasing the number of actions you're able to perform.

还有一个值得提及的细微差别。再次强调，我们的目标实际上是让瘫痪用户能够尽可能快地控制电脑，也就是 BPS（每秒比特数），并且拥有我所拥有的所有功能，就像我们刚才讨论的那样，同时还要尽可能可靠。最后一点与通道数量的讨论密切相关。因此，当你扩展通道数量时，模型输入中任何特定特征对用户输出控制的相对重要性都会降低，这意味着如果神经非平稳性效应是每个通道独立的，或者如果噪声是独立的，使得更多通道平均而言输出效应更小，那么你的系统可靠性就会提高。所以，至少我持有的一个核心论点是，扩展通道数量应该能提高系统的可靠性，而无需对解码器本身做任何工作。

One other nuance there that is worth mentioning. Again, our goal is really to enable a user with paralysis to control the computer as fast as I can, so that's BPS, with all the same functionality I have, which is what we just talked about, but then also as reliably as I can. And that last point is very related to channel count discussion. So as you scale out number of channels, the relative importance of any particular feature of your model input to the output control of the user diminishes, which means that if the sort of neural nonstationarity effect is per channel, or if the noise is independent such that more channels means on average less output effect, then your reliability of your system will improve. So one sort of core thesis that at least I have is that scaling channel count should improve the reliability of the system without any work on the decoder itself.

你能详细谈谈这里的可靠性吗？首先，当你说信号的非平稳性时，你指的是哪个方面？

Can you linger on the reliability here? First of all, when you say nonstationarity of the signal, which aspect are you referring to?

是的，所以我们先简单谈谈实际底层信号是什么样的。再次，我在开头简要提到过，当你想象向右移动或向左移动时，神经元可能会或多或少地放电，而该信号的频率内容，至少在运动皮层中，与输出意图（用户正在执行的行为任务）高度相关。你可以想象，实际上，速率编码（即该现象的名称）是否是大脑表示信息的唯一方式，这一点并不明显。你可以想象大脑编码意图的许多不同方式，而且实际上有证据表明，例如在蝙蝠中，存在时间编码，即特定神经元放电的确切时间就是信息表示的机制。但至少在运动皮层中，有大量证据表明它是速率编码，或者至少一阶近似是速率编码。那么，如果大脑通过改变神经元放电的频率来表示信息，真正重要的是神经元的基线状态和调制后状态之间的差值。我们观察到的，以及学术工作中也观察到的，是那个基线速率——如果你要归零秤，想象一下烘焙时测量面粉的类比——锅的重量基线状态实际上每天都不一样。因此，如果你要测量的是锅里的米有多少，你会因为用不同的锅测量而在不同日子得到不同的测量结果。所以，基线速率的漂移实际上是导致下游偏差的原因，至少从问题的一阶描述来看是这样。除此之外还可能存在其他效应，非线性效应，但至少从问题的一阶描述来看，这就是我们今天观察到的：任何特定神经元或在特定通道上观察到的基线放电速率都在变化。

Yeah, so maybe let's talk briefly what the actual underlying signal looks like. Again, I spoke very briefly at the beginning about how when you imagine moving to the right or imagine moving to the left, neurons might fire more or less, and their frequency content of that signal, at least in the motor cortex, it's very correlated with the output intention, the behavioral task that the user is doing. You could imagine, actually this is not obvious that rate coding, which is the name of that phenomenon, is the only way the brain could represent information. You can imagine many different ways in which the brain could encode intention, and there's actually evidence, like in bats for example, that there are temporal codes, so timing codes of exactly when particular neurons fire is the mechanism of information representation. But at least in the motor cortex, there's substantial evidence that it's rate coding, or at least a first-order approximation is that it's rate coding. So then, if the brain is representing information by changing the frequency of a neuron firing, what really matters is the delta between the baseline state of the neuron and what it looks like when it's modulated. And what we've observed, and what has also been observed in academic work, is that that baseline rate, if you were to tare the scale, if you imagine that analogy for measuring flour or something when you're baking, that baseline state of how much the pot weighs is actually different day to day. And so if what you're trying to measure is how much rice is in the pot, you're going to get a different measurement different days because you're measuring with different pots. So that baseline rate shifting is really the thing that, at least from a first-order description of the problem, is causing this downstream bias. There can be other effects, nonlinear effects on top of that, but at least a very first-order description of the problem, that's what we observe today: the baseline firing rate of any particular neuron or observed on a particular channel is changing.

那么，你能不能直接调整到基线，让它持续相对于基线？

So can you just adjust to the baseline, make it relative to the baseline nonstop?

是的，这是个好问题。对于猴子，我们找到了多种方法来实现这一点。一个例子是，你让它们执行一些行为任务，比如用操纵杆玩游戏，你测量大脑中的活动，计算所有输入特征的平均值，然后在进行 BCI 会话时从输入中减去这个平均值。效果非常好。但出于某种原因，这对 Nolan 效果不太好。我实际上不知道全部原因，但我可以想象几种解释。一种解释可能是，某些开环任务和某些闭环任务之间的情境效应差异对 Nolan 来说比猴子大得多。也许在这个开环任务中，他一边做任务一边看 Lex Friedman 的播客，或者他一边吹口哨、听音乐、和朋友聊天、问妈妈晚饭吃什么，一边做这个任务。因此，这两种状态之间的情境差异可能大得多，从而导致你在开环时归一化的特征与你在闭环时试图使用的特征之间存在更大的泛化差距。

Yeah, this is a great question. So with monkeys, we have found various ways to do this. One example way is you ask them to do some behavioral task like play the game with a joystick, you measure what's going on in the brain, you compute some mean of what's going on across all the input features, and you subtract that in the input when you're doing your BCI session. Works super well. For whatever reason, that doesn't work super well with Nolan. I actually don't know the full reason why, but I can imagine several explanations. One such explanation could be that the context effect difference between some open-loop task and some closed-loop task is much more significant with Nolan than it is with monkey. Maybe in this open-loop task, he's watching the Lex Friedman podcast while he's doing the task, or he's whistling and listening to music and talking with his friend and asking his mom what's for dinner while he's doing this task. And so the exact difference in context between those two states may be much larger and thus lead to a bigger generalization gap between the features that you're normalizing at open-loop time and what you're trying to use at closed-loop time.

这很有趣。就这一点而言，看着 Nolan 能够多任务处理，同时做多项任务，能够一边说话一边有效地移动鼠标光标，同时因为在我面前说话而紧张，还在国际象棋上打败我，这真是令人难以置信。是的，一边打败你，一边毫不担心，还一边说垃圾话，同时进行。是的，如果你试图归一化到基线，那可能会打乱一切。哇，这真有趣。

That's interesting. Just on that point, it's kind of incredible to watch Nolan be able to multitask, to do multiple tasks at the same time, to be able to move the mouse cursor effectively while talking, and while being nervous because he's talking in front of me, and kicking my ass in chess too. Yeah, kicking your ass and not worrying and talking trash while doing it, all at the same time. And yes, if you're trying to normalize to the baseline, that might throw everything off. Boy, is that interesting.

也许对此再补充一点。对于不熟悉辅助技术的人来说，我认为有一种普遍的看法：为什么不能直接用眼动仪之类的东西来帮助某人移动屏幕上的鼠标呢？这是一个非常合理的问题。实际上，在看到 Nolan 之前，我并不确信这对像他这样的人来说会是一项具有深远变革意义的技术。现在我非常确信它会是。但原因很微妙。这实际上与它如何符合人体工程学地融入他们的生活有关。即使你只能提供与眼动仪或鼠标棒相同的控制水平，但你不需要把那个东西放在脸上，你不需要以某种方式定位，你不需要你的护理人员……

Maybe one comment on that too. For folks that aren't familiar with assistive technology, I think there's a common belief that, well, why can't you just use an eye tracker or something like this for helping somebody move a mouse on the screen? And it's a really fair question. One that I actually was not confident before seeing Nolan that this was going to be a profoundly transformative technology for people like him. And I'm very confident now that it will be. But the reasons are subtle. It really has to do with ergonomically how it fits into their life. Even if you can just offer the same level of control as what they would have with an eye tracker or with a mouse stick, but you don't need to have that thing in your face, you don't need to be positioned a certain way, you don't need your caretaker to be...

只要有人帮你设置好，你就可以随时、随地、随心所欲地激活它。这种独立性对人们来说简直是革命性的。这意味着他们可以在晚上私下给朋友发短信，而不需要妈妈知道。这意味着他们可以在凌晨两点没人在旁边帮忙设置 iPad 的时候，自己打开它上网浏览。对于处于那种情况的人来说，这绝对是颠覆性的改变。这甚至还没提到那些可能完全无法交流或无法主动求助的人。这可能是他们与外界唯一的联系。嗯，这个为什么影响深远，我想不用多解释了。

around to set it up for you, you can activate it when you want, how you want, wherever you want. That level of independence is so game-changing for people. It means that they can text a friend at night privately without their mom needing to be in the loop. It means that they can open up and browse the internet at 2 a.m. when nobody's around to set their iPad up for them. This is a profoundly game-changing thing for folks in that situation. And this is even before we start talking about folks that may not be able to communicate at all or ask for help when they want to. This could be the only link that they have to the outside world. And yeah, that one doesn't need explanation of why that's so impactful.

你提到了神经解码器。解码器里用了多少机器学习？多少是魔法，多少是科学，多少是艺术？设计一个能解读这些脉冲序列的解码器有多难？

You mentioned neural decoder. How much machine learning is in the decoder? How much magic, how much science, how much art? How difficult is it to come up with a decoder that figures out what these sequence of spikes mean?

嗯，好问题。有几种不同的回答方式。所以我先简单宏观地讲一下，然后再深入一个具体问题。宏观来看，构建解码器其实就是构建数据集，然后将其编译成权重，每一步都很重要。我认为进一步改进的方向主要在于数据集这边：如何为模型构建最优的标签？但还有一个完全独立的挑战，就是如何将其编译成最好的模型。所以我简单深入第二个问题。为 BCI 设计最优模型的主要挑战之一是，离线指标不一定对应在线指标。这本质上是一个控制问题：用户试图控制屏幕上的东西，而你输出意图的具体用户体验会影响你的控制能力。例如，如果你只看模型预测的验证损失，可能有多种方式达到相同的验证损失，但并非所有方式对最终用户来说都具有同等的可控性。所以可能很简单地说，“哦，你可以添加辅助损失项来帮助你捕捉真正重要的东西”，但这是一个非常微妙的过程。因此，如何将标签转化为模型，比标准的监督学习问题要微妙得多。这里有一个非常有趣的轶事：我们尝试了许多不同的神经网络架构来将脑数据转换为速度输出，例如。几年前有一个例子让我印象深刻：我们一度只使用全连接网络来解码大脑活动。我们做了一个 A/B 测试，测量在线控制会话中，对输入信号进行一维卷积的相对性能。想象一下，每个通道都有一个滑动窗口，为每个输入序列同时产生一些卷积特征。如果你使用这种卷积架构，实际上可以获得更好的验证指标——意味着你在离线数据上拟合得更好，泛化得也更好。你减少了参数；这几乎是处理时间序列数据时的标准流程。但结果发现，在线使用该模型时，可控性更差，差得多，尽管离线指标更好。对此可以有多种解释，但这至少教会了我一点：目前，如果你只是向这个问题投入大量算力，试图进行超参数优化，或者让某个 GPT 模型硬编码或想出许多不同的解决方案，如果你只是优化损失，那是不够的。这意味着仍然存在一些固有的建模差距；在如何让模型随着更多算力而扩展方面，还有一些艺术性有待发掘。这可能根本上是标签问题，但也可能有其他因素。

Yeah, good question. There are a couple different ways to answer this. So maybe I'll zoom out briefly first, and then I'll go down one of the rabbit holes. So the zoomed-out view is that building the decoder is really the process of building the dataset plus compiling it into the weights, and each of those steps is important. The direction I think of further improvement is primarily going to be in the dataset side: how do you construct the optimal labels for the model? But there's an entirely separate challenge of then how do you compile it into the best model. So I'll go briefly down the second rabbit hole. One of the main challenges with designing the optimal model for BCI is that offline metrics don't necessarily correspond to online metrics. It's fundamentally a control problem: the user is trying to control something on the screen, and the exact user experience of how you output the intention impacts your ability to control. So for example, if you just look at validation loss as predicted by your model, there can be multiple ways to achieve the same validation loss. Not all of them are equally controllable by the end user. So it might be as simple as saying, 'Oh, you could just add auxiliary loss terms that help you capture the thing that actually matters,' but this is a very nuanced process. So how you turn the labels into the model is more of a nuanced process than just a standard supervised learning problem. One very fascinating anecdote here: we've tried many different neural network architectures that translate brain data to velocity outputs, for example. And one example that's stuck in my brain from a couple years ago now is, we at one point were using just fully connected networks to decode the brain activity. We tried an A/B test where we were measuring the relative performance in online control sessions of 1D convolution over the input signal. So if you imagine per channel, you have a sliding window that's producing some convolved feature for each of those input sequences for every single channel simultaneously. You can actually get better validation metrics—meaning you're fitting the data better and it's generalizing better on offline data—if you use this convolutional architecture. You're reducing parameters; it's sort of a standard procedure when you're dealing with time series data. Now it turns out that when using that model online, the controllability was worse, far worse, even though the offline metrics were better. And there can be many ways to interpret that, but what that taught me at least was that hey, it's at least the case right now that if you were to just throw a bunch of compute at this problem and you were trying to hyperparameter optimize or let some GPT model hardcode or come up with many different solutions, if you were just optimizing for loss, it would not be sufficient. Which means that there's still some inherent modeling gap; there's still some artistry left to be uncovered here of how to get your model to scale with more compute. And that may be fundamentally a labeling problem, but there may be other components to this as well.

目前是受数据限制吗？听起来是这样。如何获得大量好的标签？

Is it data-constrained at this time? Which is what it sounds like. How do you get a lot of good labels?

是的，我认为是数据质量受限，不一定是数据数量受限。但即使是数量，我的意思是，因为它必须在交互上进行训练，我想交互并不多。是的，这取决于你指的是哪个版本。如果你说的是最简单的例子，比如仅 2D 速度，那么我认为数据质量是主要问题。如果你说的是如何构建一个多功能输出，让你能像你我一样在电脑上进行所有输入，那实际上是一个更复杂的建模挑战，因为现在你不仅要考虑用户何时左键点击，而且在构建左键点击模型时，你还需要考虑如何确保当用户试图右键点击或移动鼠标时，它不会触发。所以一个有趣的 bug 例子是，在 Nolan 使用 BCI 的第一周，当他移动鼠标时，点击信号急剧下降，而当他停止移动时，点击信号又上升了。所以再次，两个输入之间存在污染。另一个好例子是，有一次他试图进行左键点击并拖动，但在他开始移动的那一刻，左键点击信号急剧下降。所以同样，由于两个信号之间存在污染，你需要想办法在数据集或模型中建立对这种——你可以认为这是过拟合，但实际上只是模型以前没有见过这种变异性。所以你需要找到某种方法来帮助模型应对这种情况。

Yeah, I think it's data quality constrained, not necessarily data quantity constrained. But even just the quantity, I mean, because it has to be trained on the interaction, I guess there's not that many interactions. Yeah, so it depends what version of this you're talking about. So if you're talking about the simplest example of just 2D velocity, then I think yeah, data quality is the main thing. If you're talking about how to build a sort of multifunction output that lets you do all the inputs on the computer that you and I can do, then it's actually a much more sophisticated modeling challenge because now you need to think about not just when the user is left-clicking, but when you're building the left-click model, you also need to be thinking about how to make sure it doesn't fire when they're trying to right-click or they're trying to move the mouse. So one example of an interesting bug from week one of BCI with Nolan was when he moved the mouse, the click signal sort of dropped off a cliff, and when he stopped, the click went up. So again, there's a contamination between the two inputs. Another good example was at one point he was trying to do a left-click and drag, and the minute he started moving, the left-click signal dropped off a cliff. So again, because there's some contamination between the two signals, you need to come up with some way to either in the dataset or in the model build robustness against this kind of—you think of it like overfitting, but really it's just that the model has not seen this kind of variability before. So you need to find some way to help the model with that.

这太酷了，因为感觉所有这些都是可以解决的，但很难。

This is super cool because it feels like all of this is very solvable but it's hard.

是的，这本质上是一个工程挑战。这一点很重要，而且同样重要的是，它可能不需要根本性的新技术。这意味着，比如说，那些使用 CTC 损失和内部 token 进行无监督语音分类的人，可能拥有非常适用于此的技能。

Yes, it is fundamentally an engineering challenge. This is important to emphasize, and it's also important to emphasize that it may not need fundamentally new techniques. Which means that people who work on, let's say, unsupervised speech classification using CTC loss with internal tokens, for example, could potentially have very applicable skills to this.

那么，对于 Neuralink 软件栈的未来发展，你对哪些事情感到兴奋？

So what things are you excited about in the future development of the software stack on the Neuralink?

我们一直在讨论的所有内容——解码、用户体验——我认为有些方面我从技术角度感到兴奋，有些方面我则对理解这项技术如何最好地进入世界感到兴奋。所以我从技术进入世界的角度倒着说。我真的很兴奋想了解这个设备对那些人来说效果如何……

So everything we've been talking about—the decoding, the UX—I think there's some I'm excited about from the technology side, and some I'm excited about understanding how this technology is going to be best situated for entering the world. So I'll work backwards on the technology entering the world side of things. I'm really excited to understand how this device works for folks that...

完全无法说话，没有能力通过语音命令等方式自举到有用的控制，当前能力极其有限。我认为这将是一个非常有用的信号，让我们理解——对所有初创公司来说，真正的生存威胁就是产品市场契合度。这个设备在当前状态下是否有能力和潜力改变人们的生活？如果没有，差距在哪里？如果有差距，我们如何最高效地解决它们？这就是我对接下来一年左右的临床试验运营感到非常兴奋的地方。

Cannot speak at all, that have no ability to sort of bootstrap into useful control by voice command, for example, and are extremely limited in their current capabilities. I think that will be an incredibly useful signal for us to understand, I mean really what is an existential threat for all startups, which is product-market fit. Does this device have the capacity and potential to transform people's lives in the current state? And if not, what are the gaps? And if there are gaps, how do we solve them most efficiently? So that's what I'm very excited about for the next year or so of clinical trial operations.

在技术方面，我对我们正在做的几乎所有事情都感到非常兴奋。我认为它会很棒。最突出的一点是扩展通道数量。目前我们有一个 1000 通道的设备。下一个版本将有 3 到 6000 个通道，我预计这条曲线未来会继续增长。目前还不清楚在这个规模下，哪些问题会完全消失，哪些问题会依然存在并需要进一步关注。所以我很兴奋，因为它能给我们带来清晰的梯度，让我们知道应该把时间和资源集中在哪些用户体验上，甚至像非平稳性这样简单的问题也是如此。在那个规模下，这个问题会完全消失吗？还是我们仍然需要想出新的创意用户界面？而且，当我们达到那个时间点，开始大幅扩展从一个大脑可以输出的功能集时，如何处理所有细微差别：用户无法感受到指尖下的不同按键，但仍需要同步调节所有按键以实现目标？而且你还没有本体感觉反馈回路，那么如何让用户直观地控制一个高维控制面，而无需物理感受？我认为这将是一个非常有趣的问题。

On the technology side, I'm quite excited about basically everything we're doing. I think it's going to be awesome. The most prominent one I would say is scaling channel count. So right now we have a 1000-channel device. The next version will have between 3 and 6000 channels, and I would expect that curve to continue in the future. And it's unclear what set of problems will just disappear completely at that scale and what set of problems will remain and require further focus. So I'm excited about the clarity of gradient that that gives us in terms of the user experiences we choose to focus our time and resources on, and also in terms of things as simple as nonstationarity. Does that problem just completely go away at that scale, or do we need to come up with new creative UIs still even at that point? And also, when we get to that time point when we start expanding out dramatically the set of functions that you can output from one brain, how to deal with all the nuances of both the user experience of not being able to feel the different keys under your fingertips but still need to be able to modulate all of them in synchrony to achieve the thing you want? And again, you don't have that proprioceptive feedback loop, so how can you make that intuitive for a user to control a high-dimensional control surface without feeling the thing physically? I think that's going to be a super interesting problem.

我也很兴奋地想了解，这些缩放定律是否会持续？比如随着通道数量的扩展，在真正达到饱和点之前还能走多远？今天这还不明显。我认为我们只知道插值空间里的情况；我们只知道 0 到 1024 之间的区域，但不知道之外是什么。然后还有一系列有趣的神经科学和大脑问题：当你在更多地方向大脑植入更多东西时，你能更快地了解那些脑区代表什么。所以我对这些基础神经科学的学习感到兴奋，这对未来如何最高效地插入电极也很重要。所以是的，我认为所有这些维度都让我非常非常兴奋，这甚至还没有触及我们每天工作的软件栈以及我们正在做的事情。

I'm also quite excited to understand, you know, do these scaling laws continue? Like as you scale channel count, how much further out do you go before that saturation point is truly hit? And it's not obvious today. I think we only know what's in the sort of interpolation space; we only know what's between 0 and 1024, but we don't know what's beyond that. And then there's a whole sort of range of interesting neuroscience and brain questions, which is: when you stick more stuff in the brain in more places, you get to learn much more quickly about what those brain regions represent. So I'm excited about that fundamental neuroscience learning, which is also important for figuring out how to most efficiently insert electrodes in the future. So yeah, I think all those dimensions I'm really really excited about, and that doesn't even get close to touching the sort of software stack that we work on every single day and what we're working on right now.

是的，对我来说，一千个电极就达到饱和几乎是不可能的。感觉这就像未来那些愚蠢的想法一样，显然你应该拥有数百万个电极，真正的突破就在这里发生。

Yeah, it seems virtually impossible to me that a thousand electrodes is where it saturates. It feels like this would be one of those silly notions in the future where obviously you should have millions of electrodes, and this is where the true breakthroughs happen.

是的。你发推文说：“有些想法用诗歌描述最为精确。” 你为什么这么认为？

Yeah. You tweeted: 'Some thoughts are most precisely described in poetry.' Why do you think that is?

我认为这是因为语言的信息瓶颈非常陡峭，但你可以通过非字面的方式更有效地在对方的大脑中重建意义。如果你能表达一种情感，让他们的大脑能够重建你试图传达的真实底层含义和美感，那么他们大脑中的生成函数比语言所能表达的更强大。所以诗歌的机制实际上就是喂养或播种那个生成函数。字面表达有时对于你要传达的东西来说是一种次优的压缩，而实际上在用户经历那个生成过程时，他们才理解你的意思。这就是美妙之处。就像你看一幅美丽的画：美的不是画的像素，而是你看到它时发生的思维过程。那种体验才是真正重要的。是的，它与你内心深处的某种东西产生共鸣，而艺术家也经历过那种东西，并能够通过像素传达出来。这实际上将与完全的读心术相关。你知道，如果你只是字面地读诗，那没什么有趣的。它需要人类来解读。所以正是人类心智与人类物种集体智慧背景下人类所有经验的结合，才使那首诗有意义，他们加载了这些。同样，从一个人到另一个人传递意义的信号可能看起来微不足道，但实际上可能携带巨大的力量，因为接收端人类心智的复杂性。

I think it's because the information bottleneck of language is pretty steep, and yet you're able to reconstruct in the other person's brain more effectively without being literal. If you can express a sentiment such that in their brain they can reconstruct the actual true underlying meaning and beauty of the thing you're trying to get across, the generator function in their brain is more powerful than what language can express. So the mechanism of poetry is really just to feed or seed that generator function. Being literal sometimes is a suboptimal compression for the thing you're trying to convey, and it's actually in the process of the user going through that generation that they understand what you mean. That's the beautiful part. It's also like when you look at a beautiful painting: it's not the pixels of the painting that are beautiful, it's the thought process that occurs when you see that. The experience of that actually is the thing that matters. Yeah, it's resonating with some deep thing within you that the artist also experienced and was able to convey that through the pixels. And that's actually going to be relevant for full-on telepathy. You know, if you just read the poetry literally, that doesn't say much of anything interesting. It requires a human to interpret it. So it's the combination of the human mind and all the experiences that a human being has within the context of the collective intelligence of the human species that makes that poem make sense, and they load that in. So in that same way, the signal that carries from human to human meaning might seem trivial but may actually carry a lot of power because of the complexity of the human mind on the receiving end.

是的，这很有趣。我记得 Yoshi 首先说过：所有认为我们已经实现 AGI 的人，请解释为什么人类喜欢音乐。哦，是的，直到 AGI 喜欢音乐，你才算实现了 AGI 之类的。你不觉得这有点像某种下一个词熵惊喜在起作用吗？我不知道。我听很多古典音乐，也读很多诗歌，是的，我确实想知道是否有一些下一个词惊喜因素在起作用。

Yeah, that's interesting. I think Yoshi first said something about: all the people that think we've achieved AGI, explain why humans like music. Oh yeah, and until the AGI likes music, you haven't achieved AGI or something. Do you not think that's like some next-token entropy surprise kind of thing going on there? I don't know. I listen to a lot of classical music and also read a lot of poetry, and yeah, I do wonder if there is some element of the next-token surprise factor going on there.

是的，也许吧。因为诗歌和音乐中的很多技巧都是：你有一些重复的结构，然后做一个转折。就像，好吧，第 1、2、3 节或从句是一回事，然后第 4 节就像，好了，现在我们进入下一个主题。它们巧妙地安排惊喜发生的时间和用户的期望。这在历史上也是如此：随着音乐家发展音乐，他们采用一些人们熟悉的已知结构，然后稍微调整一下，加入一个惊喜元素。这在古典音乐传统中尤其如此。但我想知道的是：这一切都只是熵吗？打破结构或打破对称性是人类似乎喜欢的东西。也许就这么简单。

Yeah, maybe. Because a lot of the tricks in both poetry and music are like: you have some repeated structure and then you do a twist. It's like, okay, verse or clause 1, 2, 3 is one thing, and then clause 4 is like, okay, now we're on the next theme. And they kind of play with exactly when the surprise happens and the expectations of the user. And that's even true through history: as musicians evolve music, they take some known structure that people are familiar with and they just tweak it a little bit, add a surprising element. This is especially true in classical music heritage. But that's what I wonder: is it all just entropy? Breaking structure or breaking symmetry is something that humans seem to like. Maybe as simple as that.

是的，我的意思是，伟大的艺术家模仿，而且，你知道，知道该打破哪些规则才是重要的部分。从根本上说，这必须关乎作品的听众：该打破哪条规则，取决于用户或观众认为那是有趣的。你怎么看？

Yeah, and I mean, great artists copy, and they also, you know, knowing which rules to break is the important part. And that fundamentally it must be about the listener of the piece: which rule is the right one to break is about the user or the audience member perceiving that as interesting. What do you think?

人类存在的意义是什么？有一部我特别喜欢的电视剧叫《白宫风云》。剧中有一个角色，他是美国总统，正在和一位同事讨论《圣经》。同事说，《圣经》里说了什么什么，总统回答说：“是的，但《圣经》也说了什么什么。”同事问：“那么，您认为《圣经》是字面真实的吗？”总统说：“是的，但我也认为我们俩都不够聪明，无法理解它。”我觉得这个类比适用于生命的意义：很大程度上，我们不知道应该问什么问题。所以我非常认同《银河系漫游指南》对这个问题的诠释，那就是如果我们能问出正确的问题，就更有可能找到人类存在的意义。因此，短期内，作为一种在搜索策略空间中的启发式方法，我们应该增加提出这类问题的人群多样性，或者更广泛地说，增加提出这类问题的意识和意识体的多样性。所以，我还是选择“我不知道”这个选项，但我确实认为我们可以做一些有意义的事情来提高回答这个问题的可能性。

Is the meaning of human existence? There's a TV show I really like called The West Wing. In The West Wing, there's a character, he's the president of the United States, who's having a discussion about the Bible with one of their colleagues. The colleague says something about, you know, the Bible says X, Y, and Z, and the President says, "Yeah, but it also says A, B, C." The person says, "Well, do you believe the Bible to be literally true?" And the President says, "Yes, but I also think that neither of us are smart enough to understand it." I think the analogy here for the meaning of life is that largely we don't know the right question to ask. So I think I'm very aligned with the Hitchhiker's Guide to the Galaxy version of this question, which is basically if we can ask the right questions, it's much more likely we find the meaning of human existence. So in the short term, as a heuristic in the sort of search policy space, we should try to increase the diversity of people asking such questions, or generally of consciousness and conscious beings asking such questions. So again, I think I'll take the "I don't know" card here, but say I do think there are meaningful things we can do that improve the likelihood of answering that question.

有意思的是，你如此重视提出正确问题这件事。这才是关键，不是答案，而是问题。顺便说一句，这一点在与无法说话的人交流时会非常痛苦地体现出来，因为很多时候，他们最后保留的能力就是能动动嘴唇或某个部位，以此表示是或否。在这种情况下，很明显，重要的是：你是否问对了问题，让他们能够回答是或否？

It's interesting how much value you assign to the task of asking the right questions. That's the main thing, it's not the answers, it's the questions. This point, by the way, is driven home in a very painful way when you try to communicate with someone who cannot speak, because a lot of the time the last thing to go is they have the ability to somehow wiggle a lip or move something that allows them to say yes or no. In that situation, it's very obvious that what matters is: are you asking them the right question to be able to say yes or no to?

哇，这太深刻了。那么，Bliss，感谢你所做的一切，感谢你做你自己，也感谢你今天接受采访。

Wow, that's powerful. Well, Bliss, thank you for everything you do, and thank you for being you, and thank you for talking today.

谢谢。感谢收听与 Bliss Chapman 的对话。现在，亲爱的朋友们，这是 Nolan，我们的老板，第一个在大脑中植入 Neuralink 设备的人。你在 2016 年的一次潜水事故中瘫痪，从肩膀以下失去知觉。那次事故如何改变了你的生活？

Thank you. Thanks for listening to this conversation with Bliss Chapman. And now, dear friends, here's Nolan, our boss, the first human being to have a Neuralink device implanted in his brain. You had a diving accident in 2016 that left you paralyzed with no feeling from the shoulders down. How did that accident change your life?

这有点像一件离奇的事。想象你正跑进海里，虽然这是个湖，但你跑进海里，水到腰深时你一个猛子扎进去，潜入浪下之类的。我就是那么做的，然后就没再浮上来。不知道发生了什么。我是和几个朋友一起跑进水里的，所以我的猜测是，我可能是被一个拳头、肘部、膝盖、脚之类的东西打到了头部侧面。之后我的左头疼了大约一个月，所以肯定是被重重地击中了。然后他们都浮上来了，我没有，所以我脸朝下在水里待了一会儿。我当时还有意识，最后意识到我憋不住气了，我总说“喝了一大口水”。我不知道别人是否喜欢我这么说，听起来好像我在轻描淡写，但我就是这样的人。我是个非常放松、没什么压力的人。我坦然面对了很多事情。我泰然处之。就像，“好吧，接下来我能做什么？我怎样才能让生活哪怕好一点点？”一开始，每天就是想办法尽可能多地恢复身体，努力康复，努力脱离呼吸机，尽可能多地学习，这样我出院后就能活下去。然后感谢上帝，我的家人在我身边。如果没有我的父母和兄弟姐妹，我根本走不到今天。他们为我做了太多，我永远感激不尽。很多人没有这样的条件。很多和我处境相同的人，他们的家人要么没有能力照顾他们，要么根本不想管，所以他们被送到某个疗养院。所以我很庆幸有我的家人。我有一群很棒的朋友，一群大学时的好哥们，他们都团结在我身边，我们仍然非常亲密。人们总说，如果你幸运的话，高中毕业后能留下一两个朋友，一辈子保持联系。我有大约 10 到 12 个高中朋友一直陪着我，我们每年还会聚两次。我们称之为春季系列和秋季系列。最近一次聚会，我们都打扮成 X 战警的样子，我扮成了 X 教授，简直太棒了。所以，我身边有如此强大的支持系统，所以，你知道，四肢瘫痪也没那么糟。我总被人伺候着，有人给我送食物和饮料，我可以坐在那里看想看的电视、电影和动漫，想读多少书就读多少。我是说，这很棒。

It was sort of a freak thing that happened. Imagine you're running into the ocean, although this is a lake, but you're running into the ocean and you get to about waist high and then you kind of dive in, take the rest of the plunge under the wave or something. That's what I did, and then I just never came back up. Not sure what happened. I did it running into the water with a couple of guys, and so my idea of what happened is really just that I took like a stray fist, elbow, knee, foot, something to the side of my head. The left side of my head was sore for about a month afterward, so must have taken a pretty big knock. And then they both came up and I didn't, and so I was face down in the water for a while. I was conscious, and then eventually just realized I couldn't hold my breath any longer, and I keep saying "took a big drink." People, I don't know if they like that I say that; it seems like I'm making light of it all, but this is kind of how I am. I don't know, I'm a very relaxed, sort of stress-free person. I rolled with the punches for a lot of this. I kind of took it in stride. It's like, "All right, well, what can I do next? How can I improve my life even a little bit?" On a day-to-day basis, at first just trying to find some way to heal as much of my body as possible, to try to get healed, to try to get off a ventilator, learn as much as I could so I could somehow survive once I left the hospital. And then thank God I had my family around me. If I didn't have my parents, my siblings, then I would have never made it this far. They've done so much for me, more than I can ever thank them for, honestly. And a lot of people don't have that. A lot of people in my situation, their families either aren't capable of providing for them or honestly just don't want to, and so they get placed somewhere in some sort of home. So thankfully I had my family. I have a great group of friends, a great group of buddies from college who have all rallied around me, and we're all still incredibly close. People always say, you know, if you're lucky you'll end up with one or two friends from high school that you keep throughout your life. I have about 10 or 12 from high school that have all stuck around, and we still get together all of us twice a year. We call it the Spring Series and the Fall Series. This last one we all dressed up like X-Men, so I did a Professor Xavier, and it was freaking awesome. It was so good. So yeah, I have such a great support system around me, and so you know, being a quadriplegic isn't that bad. I get waited on all the time, people bring me food and drinks, and I get to sit around and watch as much TV and movies and anime as I want. I get to read as much as I want. I mean, it's great.

看到你从这一切中看到积极的一面，真是太好了。回到之前，你还记得你第一次意识到自己从脖子以下瘫痪的那一刻吗？

It's beautiful to see that you see the silver lining in all of this. Was just going back, do you remember the moment when you first realized you were paralyzed from the neck down?

是的。我当时脸朝下在水里。就在什么东西击中我头部的那一刻，我试图站起来，却发现自己动不了，一下子就明白了。我想，“好吧，我瘫痪了，动不了。我该怎么办？如果我不能站起来，不能翻身，什么也做不了，那我最终会淹死。”我知道我不能永远憋气，所以我憋住气，想了大概 10 到 15 秒。我听别人说，旁观者，我想把我从水里拉出来的两个女孩是我最好的朋友，她们是救生员，其中一个说我的身体在水里好像在发抖，像是想翻身之类的。但我立刻就知道了，我只是意识到这就是我从此以后的状况了。也许到了医院他们能做点什么。在医院里，就在手术前，我试图安抚一个朋友。她是我从大学带来的，她在我身边哭得稀里哗啦，我说，“嘿，没事的，别担心。”我开了些玩笑来缓和气氛。护士给我妈妈打了电话，我说，“别告诉我妈，她会很紧张的。等我做完手术再打给她，因为至少那时她会有答案，比如我能不能活下来。”我不想让她一直紧张。但我知道。然后手术后第一次醒来时，我药物反应很重。他们给我用了三种方式注射芬太尼，感觉棒极了。我不推荐，但我在芬太尼的作用下看到了很多疯狂的东西，那仍然是我感觉最好的一次。

Yep. I was face down in the water. Right when whatever hit my head, I tried to get up and I realized I couldn't move, and it just sort of clicked. I'm like, "All right, I'm paralyzed, can't move. What do I do? If I can't get up, can't flip over, can't do anything, then I'm going to drown eventually." And I knew I couldn't hold my breath forever, so I just held my breath and thought about it for maybe 10 or 15 seconds. I've heard from other people, like onlookers, I guess the two girls that pulled me out of the water were two of my best friends, they were lifeguards, and one of them said that it looked like my body was sort of shaking in the water, like I was trying to flip over and stuff. But I knew immediately, and I just kind of realized that that's what my situation was from here on out. Maybe if I got to the hospital they'd be able to do something. When I was in the hospital, right before surgery, I was trying to calm one of my friends down. I had brought her with me from college to camp, and she was just bawling over me, and I was like, "Hey, it's going to be fine, don't worry." I was cracking some jokes to try to lighten the mood. The nurse had called my mom, and I was like, "Don't tell my mom, she's just going to be stressed out. Call her after I'm out of surgery, because at least she'll have some answers then, like whether I live or not, really." And I didn't want her to be stressed through the whole thing. But I knew. And then when I first woke up after surgery, I was super drugged up. They had me on fentanyl like three ways, which was awesome. I don't recommend it, but I saw some crazy stuff on that fentanyl, and it was still the best I've ever felt.

呃，在用药，抱歉。我记得第一次在医院看到妈妈时，我哭得稀里哗啦。我插着呼吸机，没法说话什么的，看到她就哭了——不是说整个情况不艰难——但第一次看到她的脸真的很难受。但我从来没有过那种‘天哪，我瘫痪了，太糟了，我不想活了’的时刻。我一直想的是，‘我讨厌不得不这样，但坐在这里自怨自艾也没用。’所以是立刻接受。

Uh, on medication, sorry. I remember the first time I saw my mom in the hospital, I was just bawling. I had a ventilator in, like I couldn't talk or anything, and I just started crying because it was more like seeing her—not that I mean the whole situation obviously was pretty rough—but it was just like seeing her face for the first time was pretty hard. But I never had a moment of, you know, 'Man, I'm paralyzed, this sucks, I don't want to be around anymore.' It was always just, 'I hate that I have to do this, but sitting here and wallowing isn't going to help.' So immediate acceptance.

嗯，嗯。

Yeah, yeah.

一路走来有低谷吗？有，有，当然。我是说，有些日子我什么都不想做。现在不太这样了——过去几年没有了——我不再有那种感觉。我更想尽一切可能让生活变得更好。但一开始，有起有落，有些事真的很难适应。首先，头几个月，我承受的痛苦真的非常非常难熬。我记得在医院里声嘶力竭地尖叫，因为我觉得腿在燃烧，显然我什么都感觉不到，但全是神经痛。那是一个很难熬的夜晚。我让他们给我尽可能多的止痛药；他们说，‘你已经用了最大剂量，所以只能忍着，去个快乐的地方之类的。’那是一个相当低的低谷。然后时不时地，意识到自己这辈子想做却再也做不了的事，很难受。你知道，我一直想成为丈夫和父亲，但我不认为现在作为四肢瘫痪者能做到。也许有可能，但我不确定我会让所爱的人经历这些——比如要照顾我什么的，不能出去运动。我从小就是个运动健将，所以那很难受。还有小事，当我意识到再也做不了的时候。比如拿着书闻书的感觉——手感、质感、翻页时的气味——我太喜欢了。我再也做不到了。就是这种小事。两周年的时候特别难受。两年是医生说的恢复期，之后运动和感觉基本就到极限了。所以头两年，我脑子里只有一件事：尽最大努力动动手指、手、脚，想尽办法恢复感觉和运动。然后两周年到了——2018 年 6 月 30 日——我很伤心自己还是那个状态。然后偶尔也会低落，但我从没有长时间抑郁。我觉得那样不值得。

Has there been a low point along the way? Yeah, yeah, sure. I mean, there are days when I don't really feel like doing anything. Not so much anymore—not for the last couple years—I don't really feel that way. I've more so just wanted to try to do anything possible to make my life better at this point. But at the beginning, there were some ups and downs, some really hard things to adjust to. First off, just the first couple months, the amount of pain I was in was really, really hard. I mean, I remember screaming at the top of my lungs in the hospital because I thought my legs were on fire, and obviously I can't feel anything, but it's all nerve pain. So that was a really hard night. I asked them to give me as much pain meds as possible; they're like, 'You've had as much as you can have, so just kind of deal with it, go to a happy place, sort of thing.' So that was a pretty low point. And then every now and again, it's hard like realizing things that I wanted to do in my life that I won't be able to do anymore. You know, I always wanted to be a husband and father, and I just don't think that I could do it now as a quadriplegic. Maybe it's possible, but I'm not sure I would ever put someone I love through that—like having to take care of me and stuff, not being able to go out and play sports. I was a huge athlete growing up, so that was pretty hard. Just little things too, when I realize I can't do them anymore. Like there's something really special about being able to hold a book and smell a book—the feel, the texture, the smell as you turn the pages—I just love it. I can't do it anymore. And it's little things like that. The two-year mark was pretty rough. Two years is when they say you will get back basically as much as you're ever going to get back as far as movement and sensation goes. So for the first two years, that was the only thing on my mind: try as much as I can to move my fingers, my hands, my feet, everything possible to try to get sensation and movement back. And then when the two-year mark hit—so June 30th, 2018—I was really sad that that's kind of where I was. And then just randomly here and there, but I was never like depressed for long periods of time. It just never seemed worthwhile to me.

是什么给了你力量？

What gave you strength?

我的信仰。对上帝的信仰是一个重要因素。我理解这一切都有目的，即使那个目的与 Neuralink 无关——你知道，圣经里有约伯的故事，一个非常著名的故事：约伯遭遇了所有可怕的事情，但他始终赞美上帝。我以前以为，很多人一辈子都以为自己是约伯，是那个经历可怕事情的人，只需要全程赞美上帝，一切都会好起来。事故后某个时刻，我意识到我可能不是约伯，我可能是他那些被杀、被绑架或从他身边夺走的孩子之一。所以这是关于发生在你爱的人身上的可怕事情。所以也许在这个情况下，我妈妈是约伯，她必须熬过极其艰难的时刻，而我需要尽力为她做到最好，因为她才是真正经历巨大考验的人。这给了我很多力量。当然还有我的家人——家人和朋友——他们每天都给我所需的力量。有这样一个强大的支持系统在身边，事情就容易多了。

My faith. My faith in God was a big one. My understanding that it was all for a purpose, and even if that purpose wasn't anything involving Neuralink, even if that purpose was—you know, there's a story in the Bible about Job, and I think it's a really, really popular story about how Job has all of these terrible things happen to him and he praises God throughout the whole situation. I thought, and I think a lot of people think for most of their lives that they are Job, that they're the ones going through something terrible and they just need to praise God through the whole thing and everything will work out. At some point after my accident, I realized that I might not be Job, that I might be one of his children that gets killed or kidnapped or taken from him. So it's about terrible things that happen to those around you who you love. So maybe in this case, my mom would be Job, and she has to get through something extraordinarily hard, and I just need to try and make it as best as possible for her, because she's the one really going through this massive trial. And that gave me a lot of strength. And obviously my family—my family and my friends—they give me all the strength that I need on a day-to-day basis. So it makes things a lot easier having that great support system around me.

从我在网上看到的一切——你的直播和你今天的样子——我非常钦佩你坚定不移的积极人生观。一直是这样吗？

From everything I've seen of you online, your streams and the way you are today, I really admire your unwavering positive outlook on life. Has that always been this way?

是的，是的。我一直觉得自己能做任何想做的事。没有什么事太大。只要我下定决心，我觉得就能做到。我不想做太多事；我想四处旅行，像个吉普赛人一样打零工。我梦想环游欧洲，在威尔士或爱尔兰当牧羊人，然后去意大利当渔夫，每样干一年。虽然很老套，但我觉得去旅行、做不同的事会很有趣。所以我也总是看到周围人最好的一面，一直努力对人好。和我妈妈一起长大，她是世界上最积极、最有活力的人。我们都是普通人——我和人相处得很好。我真的很喜欢认识新朋友。所以我想做所有事。这就是我一直以来的样子。

Yeah, yeah. I've just always thought I could do anything I ever wanted to do. There was never anything too big. Whatever I set my mind to, I felt like I could do it. I didn't want to do a lot; I wanted to travel around and be sort of like a gypsy and go work odd jobs. I had this dream of traveling around Europe and being, I don't know, a shepherd in Wales or Ireland, and then going to being a fisherman in Italy, doing all these things for like a year. It's such cliché things, but I just thought it would be so much fun to go and travel and do different things. So I've always just seen the best in people around me too, and I've always tried to be good to people. And growing up with my mom too, she's like the most positive, energetic person in the world. And we're all just people—I just get along great with people. I really enjoy meeting new people. So I just wanted to do everything. This is kind of just how I've been.

看到你在经历这一切后没有被愤世嫉俗所吞噬，真是太好了。

It's just great to see that cynicism didn't take over given everything you've been through.

是的，那是刻意的选择吗？有点。另外，这就是我的本性。我凡事都随遇而安。我以前总跟人说，‘我不怎么为事情焦虑。’每当看到别人焦虑，我就说，‘这没什么难的，别焦虑就行了，就这么简单。’他们就说，‘不是这样的。’但对我有用。别焦虑，一切都会好起来的。显然不是所有事都顺利，也不是总能得到最好的结果，但我从小就觉得焦虑在我的生活中没有位置。

Yeah, that was a deliberate choice? Yeah, a bit. Also, it's just kind of how I am. I just roll with the punches with everything. I always used to tell people like, 'I don't stress about things much.' And whenever I'd see people getting stressed, just say, 'You know, it's not hard, just don't stress about it, and that's all you need to do.' And they're like, 'That's not how that works.' It works for me. Just don't stress and everything will be fine. Everything will work out. Obviously not everything always goes well, and it's not like it all works out for the best all the time, but I just don't think stress has had any place in my life since I was a kid.

被选为第一个在大脑中植入 Neuralink 设备的人类，是什么体验？你害怕吗？兴奋吗？

What was the experience like of you being selected to be the first human being to have a Neuralink device implanted in your brain? Were you scared? Excited?

不，不。这很酷。我从不害怕。我考虑了很多：我该做吗？作为第一个人，我可以等到第二或第三个，得到更好的 Neuralink 版本。第一个可能不行，也许会很糟。它将是人类身上最差的版本。那我为什么要做第一个？我已经被选中了。我可以告诉他们，‘好吧，找别人吧。’但我想了想，‘如果不是我，那会是谁？’我得到了这个机会，我认为这能帮助很多人。所以我决定去做。

No, no. It was cool. I was never afraid of it. I had to think through a lot: should I do this? Being the first person, I could wait until number two or three and get a better version of the Neuralink. The first one might not work, maybe it's actually going to kind of suck. It's going to be the worst version ever in a person. So why would I do the first one? I've already kind of been selected. I could just tell them, you know, 'Okay, find someone else.' But I thought about it and I was like, 'If not me, then who?' I've been given this opportunity, and I think it's something that could help a lot of people. So I decided to go for it.

别人先上，我再做第二或第三个。我肯定他们会让我参与，他们本来就在找几个人。但最终我觉得，怎么说呢，第一个做某件事的感觉很酷。我一直觉得，如果有机会，我想做一件前无古人的事。这看起来是个绝佳的机会。而且我从未害怕过。我觉得我的信仰起了很大作用。我一直觉得上帝在为我准备些什么。我甚至希望不是这件事，因为我和上帝谈过很多次，我不想作为一个四肢瘫痪者做这些。我对他说，我可以出去跟人交谈，环游世界，在体育场里对成千上万的人演讲，做我的见证。这些我都可以做，但请先治愈我。别让我坐在轮椅上做这一切。那太糟糕了。我想他赢了那场争论。我其实没太多选择。我一直觉得有什么事在发生。看到我多么轻松地通过了面试流程，一切进展得多么快，所有事情都像星辰排列般巧合，随着手术临近，这让我明白，这一切都是注定要发生的，都是命中注定的。所以我不该害怕即将到来的任何事。我也确实没怕。我一直对自己说，你现在这么说，但手术来临时你可能会吓坏的。你就要做脑部手术了，脑部手术对很多人来说都是大事，对我更是如此。这是我仅剩的一切了。我无数次感谢上帝，你没有夺走我的大脑、我的个性、我的思考能力、我对学习的热爱、我的品格，一切的一切。非常感谢你。只要你给我留下了这些，我想我就能撑过去。而我却要让人进去翻找，他们说，嘿，我们要往你大脑里放些东西，希望一切顺利。这确实让我犹豫了一下。但就像我说的，一切进行得如此顺利，我从未有一秒钟觉得会出问题。而且，我遇到的医生和护士越多，就越觉得他们是世界上最了不起的人。我对他们的信任无以言表，我对他们所有人都印象深刻。看到他们脸上的兴奋，走进房间，看到所有人看着我，就像在说，我们太激动了，我们为此努力了这么久，终于实现了。这种情绪非常有感染力，让我更想去做这件事，帮助他们实现梦想。我不知道，这太有成就感了，我真的为他们所有人感到高兴。

Someone else and then I'll do number two or three. I'm sure they would let me; they're looking for a few people anyways. But ultimately I was like, I don't know, there's something about being the first one to do something. It's pretty cool. I always thought that if I had the chance, I would like to do something for the first time. This seemed like a pretty good opportunity. And I was never scared. I think my faith had a huge part in that. I always felt like God was preparing me for something. I almost wish it wasn't this because I had many conversations with God about not wanting to do any of this as a quadriplegic. I told him, you know, I'll go out and talk to people, I'll go out and travel the world and talk to stadiums of thousands of people, give my testimony. I'll do all of it, but like, heal me first. Don't make me do all this in a chair. That sucks. And I guess he won that argument. I didn't really have much of a choice. I always felt like there was something going on. And to see how easily I made it through the interview process and how quickly everything happened, how the stars sort of aligned with all of this, it just told me, as the surgery was getting closer, that it was all meant to happen, it was all meant to be. And so I shouldn't be afraid of anything that's to come. And so I wasn't. I kept telling myself, you know, you say that now, but as soon as the surgery comes, you're probably going to be freaking out. Like you're about to have brain surgery, and brain surgery is a big deal for a lot of people, but it's an even bigger deal for me. Like it's all I have left. The amount of times I've been like, thank you God that you didn't take my brain and my personality and my ability to think, my love of learning, my character, everything. Thank you so much. As long as you left me that, then I think I can get by. And I was about to let people go root around in there, and they're like, hey, we're going to go put some stuff in your brain, hopefully it works out. And so it was something that gave me pause. But like I said, how smoothly everything went, I never expected for a second that anything would go wrong. Plus, the more people I met on the surgeon side and on the nursing side, they're just the most impressive people in the world. I can't speak enough to how much I trust these people with my life and how impressed I am with all of them. And to see the excitement on their faces, to walk into a room and roll into a room and see all of these people looking at me like, we're just so excited, we've been working so hard on this and it's finally happened. It's super infectious and it just makes me want to do it even more and to help them achieve their dreams. I don't know, it's so rewarding and I'm so happy for all of them, honestly.

手术那天是什么感觉？醒来时是什么感觉？你感觉如何？一分钟一分钟地讲。你当时吓坏了吗？

What was the day of surgery like? What was it like when you woke up? What did you feel? Minute by minute. Were you freaking out?

没有，没有。我以为我会害怕，但随着手术临近，手术前一晚，手术当天早上，我只是兴奋。我就想，让这一切发生吧。我想我之前在电话里对埃隆也说过类似的话。我们 FaceTime 的时候，我说，我们开始吧。他说，干吧。我不知道，我就是不害怕。我们醒来，我想我们得早上 5:30 到医院。手术大概是早上 7:00，所以我们起得很早。那晚我们大概都没怎么睡。5:30 到了医院，做了所有术前准备。每个人都超级好。埃隆本来早上要来的，但他的飞机出了点问题，所以我们最后 FaceTime 了。那很酷。那通电话后，我说了我这辈子最棒的一句俏皮话。挂断电话后，周围大概有 20 个人，我说，我只希望他跟我说话时不要太紧张。不错。对，很好，干得漂亮。

No, no. I thought I was going to, but as surgery approached, the night before, the morning of, I was just excited. I was like, let's make this happen. I think I said something like that to Elon on the phone beforehand. We were FaceTiming and I was like, let's rock and roll. And he's like, let's do it. I don't know, I just wasn't scared. So we woke up, I think we had to be at the hospital at like 5:30 a.m. I think surgery was at like 7:00 a.m., so we woke up pretty early. I'm not sure much of us slept that night. Got to the hospital at 5:30, went through all the pre-op stuff. Everyone was super nice. Elon was supposed to be there in the morning, but something went wrong with his planes, so we ended up FaceTiming. That was cool. Had one of the greatest one-liners of my life after that phone call. Hung up with him, there were like 20 people around me, and I was like, I just hope he wasn't too star-struck talking to me. Nice. And yeah, good, well done.

你是提前写好的还是临时想到的？

Did you write that ahead of time or did it just come?

就是临时想到的。我就觉得，这样说挺合适的，你知道。然后进了手术室。我问能不能在手术前祈祷，所以我为整个房间做了祈祷。我请求上帝，如果我有任何不测，请陪伴我的母亲，并安抚她在外的紧张情绪。醒来后，我跟妈妈开了个小玩笑。不知道你有没有听说过。

It just came to me. I was like, this seems right, you know. Went into surgery. I asked if I could pray right beforehand, so I prayed over the room. I asked God if you would be with my mom in case anything happened to me, and just to calm her nerves out there. Woke up, played a bit of a prank on my mom. I don't know if you've heard about it.

嗯，我读到过。她很不高兴。

Yeah, I read about it. She was not happy.

你能讲讲那个恶作剧吗？你后悔这么做吗？

Can you take me through the prank? And is this something you regret doing?

不，一点也不后悔。这是我之前和我的朋友 Bane 商量过的。我说，我真想跟我妈开个玩笑。特别是我妈，她特别容易上当。我记得她有一次做膝盖手术，手术后她迷迷糊糊的，说，我感觉不到我的腿了。我爸看着她说，你没有腿了，他们不得不截掉你的双腿。我们总是对她做很过分的事。我很惊讶她还爱我们。但手术后，我真的很担心自己会太迷糊，神志不清。我以前用过一次麻醉，那次把我搞得很糟。之后好一阵子我都无法正常运作。我说了很多话，我很担心自己会开始爆出一些猛料，而我甚至不知道，也不会记得。所以我说，求你了上帝，别让那发生，请让我足够清醒，能对我妈做这个恶作剧。她手术后走进来，那是他们术后第一次见到我。她看着我，说，嗨，你怎么样？你感觉如何？我看着她，脸上带着一种，我想麻醉起了作用，非常迷糊、困惑的表情。就像，你是谁？她开始环顾房间，看着外科医生和医生们，说，你们对我儿子做了什么？你们得马上修好他。眼泪开始流下来。我看到她有多惊慌。我说，我不能让这继续下去。所以我说，妈，妈，我没事。一切都好。但她还是不高兴。她仍然说总有一天要报复我。但我不确定那会是什么样子。这是一场终生的战斗。

No, no, not one bit. It was something I had talked about ahead of time with my buddy Bane. I was like, I would really like to play a prank on my mom. Very specifically, my mom, she's very gullible. I think she had knee surgery once, and after she came out of knee surgery, she was super groggy. She's like, I can't feel my legs. And my dad looked at her, he was like, you don't have any legs. They had to amputate both your legs. And we just do very mean things to her all the time. I'm so surprised that she still loves us. But right after surgery, I was really worried that I was going to be too groggy, not all there. I had had anesthesia once before and it messed me up. I could not function for a while afterwards. And I said a lot of things that I was really worried that I was going to start dropping some bombs and I wouldn't even know, I wouldn't remember. So I was like, please God don't let that happen, and please let me be there enough to do this to my mom. So she walked in after surgery, it was the first time they had been able to see me after surgery. And she just looked at me, she said hi, how are you, how are you doing, how do you feel. And I looked at her with this very, I think the anesthesia helped, very groggy, sort of confused look on my face. It's like, who are you? And she just started looking around the room at the surgeons, at the doctors, like what did you do to my son? You need to fix this right now. Tears started streaming. I saw how much she was freaking out. I was like, I can't let this go on. And so I was like, Mom, Mom, I'm fine. It's all right. And still she was not happy about it. She still says she's going to get me back someday. But I don't know what that's going to look like. It's a lifelong battle.

是啊，是啊。但从某种意义上说，这很好。这证明你还有那个能力。

Yeah, yeah. But it was good in some sense. It was a demonstration that you still got that.

这就是我想要的。这就是我希望它达到的效果。我知道对她做那么过分的事会让她知道，我还在，我爱她。

That's all I wanted. That's all I wanted it to be. And I knew that doing something super mean to her like that would show her that I'm still there, that I love her.

对，没错。方式有点黑暗，但我喜欢。

Yeah, exactly, exactly. It's a dark way to do it, but I love it.

你第一次感觉到能用 Neuralink 设备影响周围世界是什么时候？

What was the first time you were able to feel that you could use the Neuralink device to affect the world around you?

嗯，我第一次尝到甜头其实是在手术后不久。

Yeah, the first little taste I got of it was actually not too long after.

Neuralink 团队有人带了一个小 iPad，一个平板屏幕，上面显示了八个不同的通道，正在记录我的一些神经元放电。他们把屏幕放在我面前说：‘这是你大脑的实时放电。’我觉得这太酷了。我的第一个念头是，既然它们现在在放电，那我试试能不能影响它们。于是我开始尝试活动手指，并浏览各个通道。我上下移动食指，看到顶部第三格左右有一个黄色尖峰。每次我动手指它都会出现。我说：‘哦，真酷。’周围的人都问：‘你看到什么了？’我说：‘看这个，顶部第三格，这个黄色尖峰，那就是我。’大家都激动得鼓掌。我觉得这完全没必要——这不就是应该发生的吗？

Some of the Neuralink team had brought in a little iPad, a tablet screen, and they put up eight different channels that were recording some of my neuron spikes. They put it in front of me and said, 'This is real-time your brain firing.' I thought that was super cool. My first thought was, if they're firing now, let's see if I can affect them. So I started trying to wiggle my fingers and scanning through the channels. One thing I did was move my index finger up and down, and I saw this yellow spike on the top row, third box over or something. I saw it every time I moved my finger. I said, 'Oh, that's cool.' Everyone around me was like, 'What are you seeing?' I said, 'Look at this one, top row, third box over, this yellow spike. That's me right there.' Everyone freaked out and started clapping. I thought that was super unnecessary—this is what's supposed to happen, right?

所以你在想象自己一次移动一根手指，然后注意到一些东西。当你动食指时，你意识到：‘哦，对。’你当时是在晃动所有手指看看会不会有反应？

So you're imagining yourself moving each individual finger one at a time, and then you notice something. When you did the index finger, you were like, 'Oh yeah.' You were wiggling all your fingers to see if anything would happen?

对，我晃动所有手指看看有没有反应。还有很多其他活动，但那个大黄色尖峰特别显眼。我敢肯定如果我看得够久，也许能找出上百种不同的对应关系，但那个大黄色尖峰是我注意到的。

Yeah, I was wiggling all my fingers to see if anything would happen. There was a lot of other activity, but that big yellow spike stood out to me. I'm sure if I had stared long enough, I could have mapped out maybe a hundred different things, but that big yellow spike was the one I noticed.

也许你可以谈谈，想象活动手指——比如食指——需要多少认知努力？这有多容易？

Maybe you could speak to what it's like to wiggle your fingers, to imagine that. The cognitive effort required to wiggle your index finger—how easy is that?

对我来说挺容易的。事故之后，医生告诉我尽量尝试移动身体，即使动不了也要继续尝试，因为这会在大脑和脊髓中建立新的神经通路，重新连接这些断开的连接，希望有一天能恢复一些活动能力。这听起来奇怪，但这是康复过程的一部分：尽可能多地尝试移动身体，神经系统会自行运作，开始重新连接。对有些人来说永远没用。对我来说，我恢复了一些二头肌的控制，仅此而已。如果我足够努力，可以活动一些手指，但不是随叫随到——更像是如果我试图移动右手小指并持续尝试，几秒钟后它会动一下。所以我知道那里还有连接。在医院时，有个人告诉我，有一个人通过每天反复想象走路，恢复了大半活动能力。我试了好几年，就是想象走路。很难想象迈出一步需要多少步骤——所有需要移动的部位，腿上的所有激活过程。但你不是在想象，你是在做。我在尝试，对。所以就是反复想象迈出一步需要做什么，因为这不是我们平时会想的事。我们只是想走路，然后就迈步了。我必须在脑海里尽可能重现这个过程，并反复练习。这不是第三人称视角，而是第一人称。你不是在想象自己在走路，而是像真的在走路一样做所有动作。一开始很难。

Pretty easy for me. After my accident, they told me to try to move my body as much as possible, even if I couldn't, because that would create new neural pathways or pathways in my spinal cord to reconnect things, hopefully to regain some movement someday. It's bizarre, but that's part of the recovery process: keep trying to move your body as much as you can, and the nervous system does its thing—it starts reconnecting. For some people it never works. For me, I got some bicep control back, and that's about it. If I try hard enough, I can wiggle some of my fingers, not on command—it's more like if I try to move my right pinky and keep trying, after a few seconds it'll wiggle. So I know there's stuff there. One person in the hospital told me about a guy who recovered most of his control by thinking about walking every day, just the act of walking, over and over. I tried that for years, just imagining walking. It's hard to imagine all the steps that go into taking a step—all the things that have to move, all the activations along your leg. But you're not just imagining, you're doing it. I'm trying, yeah. So it's imagining over and over what I had to do to take a step, because it's not something we think about. We just want to walk and we take a step. I had to recreate that in my head as much as I could and practice it over and over. It's not a third-person perspective; it's first-person. You're not imagining yourself walking; you're literally doing everything as if you were walking. That was hard at the beginning.

是令人沮丧的难，还是认知上的难？

Was it frustrating hard or cognitively hard?

两者都有。《杀死比尔》里有一场戏，她因为药物瘫痪了，她盯着自己的脚趾说：‘动一下你的大脚趾。’屏幕上几秒钟后，她做到了，然后她对每个身体部位都这样做，直到能再次活动。我那样做了好几年——盯着自己的身体说：‘动一下食指，动一下大脚趾。’有时大声说出来，有时只是在心里想。我试了各种方法想恢复一些活动能力。这很难，因为实际上对我的身体来说很消耗体力，这是我从未预料到的。感觉有信号无法从大脑往下传，因为脊髓有断口，然后从手再传回大脑。这些信号卡在我试图移动的身体部位里，不断累积直到爆发。然后会有一种奇怪的感觉，所有东西都消散回正常水平，然后我再重复。这就像肌肉疲劳，但并没有真正移动肌肉。非常奇怪。如果你盯着一个身体部位，想着移动它，持续两、三、四甚至八小时，对精神消耗很大。需要很多专注力。一开始容易些，因为我无法控制房间里的电视或任何东西——我无法控制环境。所以头几年，我大部分时间就是盯着墙。显然我思考了很多，并反复尝试移动。

It was both. There's a scene in one of the Kill Bill movies where she's paralyzed from a drug, and she stares at her toe and says, 'Move your big toe.' After a few seconds on screen, she does it, and she did that with every body part until she could move again. I did that for years—stared at my body and said, 'Move your index finger, move your big toe.' Sometimes vocalizing it out loud, sometimes just thinking it. I tried every way to get some movement back. It's hard because it's actually physically taxing on my body, which I never expected. It feels like there's a buildup of signals that aren't getting through from my brain down because of the gap in my spinal cord, and then from my hand back up. Those signals get stuck in whatever body part I'm trying to move, and they build up until they burst. Then I get this weird sensation of everything dissipating back to level, and I do it again. It's also like muscle fatigue without actually moving your muscles. It's very bizarre. And if you try to stare at a body part and think about moving it for two, three, four, sometimes eight hours, it's very taxing on your mind. It takes a lot of focus. It was easier at the beginning because I couldn't control a TV or anything in my room—I couldn't control my environment. So for the first few years, a lot of what I did was stare at walls. Obviously I did a lot of thinking and tried to move over and over again.

所以你从未放弃希望，只是努力训练？

So you never gave up hope, just training hard essentially?

对。而且我现在还在下意识地做。我觉得这对 Neuralink 的事情帮助很大，真的。我在 Neuralink 奥斯汀工厂的全员大会上提到过这一点。顺便说一句，欢迎来到奥斯汀。

Yep. And I still do it subconsciously. I think that helped a lot with things with Neuralink, honestly. It's something I talked about at the All Hands meeting at the Neuralink Austin facility. Welcome to Austin, by the way.

嘿，谢谢。我去过学校……谢谢。Gigafactory 非常酷。我在 Texas A&M 上过学，所以我在附近待过。所以你应该对我说‘欢迎来到德克萨斯’。

Hey, thanks man. I went to school... thanks. The Gigafactory was super cool. I went to Texas A&M, so I've been around. So you should be saying 'Welcome to Texas' to me.

我明白。但没错，我在说他们让我做的很多事情，尤其是一开始——嗯，我现在还在做——就是身体……

I get you. But yeah, I was talking about how a lot of what they've had me do, especially at the beginning—well, I still do it now—is body...

映射过程就像屏幕上会出现一只手或手臂的视觉图像，我必须做出那个动作，他们就是这样训练算法来理解我想要做什么的，这让一切变得非常无缝。我觉得这真的很酷。所以知道这些很了不起，因为我学到了很多关于身体映射程序的知识，包括界面之类的。知道你在本质上一直在训练自己成为这项任务的世界级高手，这很酷。

Mapping so like there will be a visualization of a hand or an arm on the screen and I have to do that motion and that's how they sort of train the algorithm to understand what I'm trying to do and so it made things very seamless for me. I think that's really really cool. So it's amazing to know, because I've learned a lot about the body mapping procedure, yeah like with the interface and everything like that. It's cool to know that you've been essentially like training to be world class at that task.

是的，是的。我不知道其他四肢瘫痪者，其他瘫痪的人，会不会放弃。我希望他们不会。我希望他们继续尝试，因为我听过其他瘫痪的人说永远不要停止。他们告诉你两年，但你永远不知道。人体能创造奇迹。所以我听别人说过不要放弃。我想有一个女孩通过一些家人联系到我，说她瘫痪了 18 年，一直在尝试动她的食指，18 年后她终于恢复了。所以我知道这是可能的，我永远不会放弃。我就在躺着看电视的时候做这个动作。我会发现自己几乎是无意识地做。这已经成为我如此习惯的事情，我想我永远不会停止。

Yeah yeah. I don't know if other quadriplegics, like other paralyzed people, give up. I hope they don't. I hope they keep trying, because I've heard other paralyzed people say like don't ever stop. They tell you two years, but you just never know. The human body's capable of amazing things. So I've heard other people say don't give up. I think one girl had spoken to me through some family members and said that she had been paralyzed for 18 years and she'd been trying to wiggle her index finger for all that time, and she finally got it back like 18 years later. So I know that it's possible, and I'll never give up doing it. I just do it when I'm lying down like watching TV. I'll find myself doing it kind of almost like on its own. It's just something I've gotten so used to doing that I don't think I'll ever stop.

这真是太棒了，因为我认为这是那种长期来看会真正有回报的事情，因为它就是训练。你目前还没有看到训练的结果，但有一个奥运级别的神经系统正在为某件事做准备。说实话，Neuralink 给我的一个让我感激不尽的东西，就是能够直观地看到我正在做的事情实际上产生了效果。这是我现在知道自己会永远坚持下去的一个重要原因。因为在 Neuralink 之前，我每天都在做，我只是假设事情在发生。我并不知道我是否恢复了任何活动能力或感觉，所以我可能一直在碰壁。而有了 Neuralink，我可以实时看到所有信号，看到我正在做的事情确实可以被映射。当我们开始做点击校准之类的时候，当我试图点击食指进行左键点击时，它确实能识别出来。这改变了我对重新训练身体移动的可能性的看法。所以，是的，我现在永远不会放弃。而且，这也表明大脑仍然是一个强大的存在。随着技术的发展，大脑是人体最重要的部分，它可以完成很多控制。

That's really awesome to hear, because I think it's one of those things that can really pay off in the long term, because it is training. You haven't seen the results of that training at the moment, but there's that Olympic level nervous system getting ready for something. Honestly, something that I think Neuralink gave me that I can't thank them enough for, I can't show my appreciation for it enough, was being able to visually see that what I'm doing is actually having some effect. It's a huge part of the reason why I know now that I'm going to keep doing it forever. Because before Neuralink, I was doing it every day and I was just assuming that things were happening. It's not like I knew I wasn't getting back any mobility or sensation or anything, so I could have been running up against a brick wall for all I knew. And with Neuralink, I get to see all the signals happening real time, and I get to see that what I'm doing can actually be mapped. When we started doing click calibrations and stuff, when I go to click my index finger for a left click, that it actually recognizes that. It changed how I think about what's possible with retraining my body to move. So yeah, I'll never give up now. And also just the signal that there's still a powerhouse of brain there. And as the technology develops, that brain is the most important thing about the human body, and it can do a lot of the control.

那么，当你第一次能够动动食指并看到环境做出那样的反应时，感觉如何？就是那个，按你的说法，大家都太夸张了的时刻。

So what did it feel like when you first could wiggle the index finger and saw the environment respond like that? Little yeah, where everybody was being way too dramatic according to you.

这非常酷。我的意思是这很酷，但我一直跟别人说，这对我来说是合理的。我的大脑仍然有信号在活动，只要附近有东西能测量这些信号、记录这些信号，那么就应该能够以某种方式将其可视化，看到它发生。所以这对我来说并不太令人惊讶。我只是觉得，哦，酷，我们找到了一个，我们找到了一个有效的方法。看到他们的技术奏效了，他们付出的一切努力都将得到回报，这很酷。但那时我还没有移动光标或做其他事情。我还没有与电脑互动。所以这很合理。这很酷。那时我对脑机接口也不太了解，所以我不知道这实际上迈出了怎样的一步。我不知道这是否是一件大事，或者只是说，好吧，我们走到了这一步很酷，但我们实际上希望未来能有更好的东西。我只是认为他们知道它启动了，所以我觉得，酷，这很酷。

It was very cool. I mean it was cool, but I keep telling this to people, it made sense to me. It made sense that there are still signals happening in my brain, and that as long as you had something near it that could measure those, that could record those, then you should be able to visualize it in some way, see it happen. So that was not very surprising to me. I was just like, oh cool, we found one, we found something that works. It was cool to see that their technology worked, and that everything that they had worked so hard for was going to pay off. But I hadn't moved a cursor or anything at that point. I hadn't interacted with a computer or anything at that point. So it just made sense. It was cool. I didn't really know much about BCI at that point either, so I didn't know what sort of step this was actually making. I didn't know if this was like a huge deal or if this was just like okay, it's cool that we got this far but we're actually hoping for something much better down the road. I just thought that they knew that it turned on, so I was like cool, this is cool.

你有没有仔细阅读你安装的硬件的规格，比如线程数量？

Did you read up on the specs of the hardware you got installed, like the number of threads?

我知道所有这些，但对我来说就像天书一样。我想，好吧，64 个线程，16 个电极，1024 个通道。好吧，数学上说得通，听起来没错。

I knew all of that, but it's all Greek to me. I was like, okay, threads 64, threads 16 electrodes, 1,024 channels. Okay, that math checks out, sounds right.

你第一次能够移动鼠标光标是什么时候？

When was the first time you were able to move a mouse cursor?

我知道一定是在第一周，一周或两周内，我就能第一次移动光标了。同样，这对我来说有点合理。这似乎不是什么大不了的事。就像，好吧，我怎么解释这个？当你周围的人都为你所做的事情鼓掌时，很容易说，好吧，我做了很酷的事，这在某种程度上令人印象深刻。这到底意味着什么，是什么，我还没有真正理解。所以，我知道我试图移动身体部位，然后通过某种机器学习算法进行映射，以识别我的大脑信号，然后利用这些信号给我光标控制，这一切对我来说都是合理的。我不知道所有的细节，但我想，我的大脑仍然有信号在发射，它们只是无法通过，因为我的脊髓有一个缺口，所以它们无法完全向下和向上返回，但它们仍然存在。所以当我第一次移动光标时，我想，这很酷，但我预料到它会发生。这对我来说是合理的。当我第一次只用意念移动光标，而没有实际尝试移动时，我想我可以稍微谈谈这个，即尝试运动和想象运动之间的区别。

I know it must have been within the first maybe week, a week or two weeks, that I was able to first move the cursor. And again, it kind of made sense to me. It didn't seem like that big of a deal. It was like, okay, how do I explain this? When everyone around you starts clapping for something that you've done, it's easy to say okay, I did something cool, that was impressive in some way. What exactly that meant, what it was, hadn't really set in for me. So again, I knew that me trying to move a body part, and then that being mapped in some sort of machine learning algorithm to be able to identify my brain signals and then take that and give me cursor control, that all kind of made sense to me. I don't know all the ins and outs of it, but I was like, there are still signals in my brain firing, they just can't get through because there's a gap in my spinal cord, and so they just can't get all the way down and back up, but they're still there. So when I moved the cursor for the first time, I was like, that's cool, but I expected that that should happen. It made sense to me. When I moved the cursor for the first time with just my mind, without physically trying to move, so I guess I can get into that just a little bit, the difference between attempted movement and imagined movement.

是的，这两者之间的区别非常迷人。

Yeah, that's a fascinating difference from one to the other.

是的，是的。所以尝试运动是我在物理上尝试移动，比如我的手。我尝试将我的手向右、向左、向前和向后移动。这些都是尝试运动。尝试抬起手指、尝试踢腿之类的。我在物理上尝试做所有这些事情，即使你看不到。这就像我尝试耸肩之类的。这些都是尝试运动。这就是我在最初几周所做的，当时他们准备给我光标控制，我在做身体映射。就是尝试做这个，尝试做那个。当 Neuralink 告诉我要想象做这件事时，我有点理解，但这不是人们练习的东西。如果你从学校开始……

Yeah, yeah. So attempted movement is me physically trying to attempt to move, say my hand. I try to attempt to move my hand to the right, to the left, forward and back. And that's all attempted movement. Attempt to lift my finger up and down, attempt to kick or something. I'm physically trying to do all of those things even if you can't see it. This would be like me attempting to shrug my shoulders or something. That's all attempted movement. That's what I was doing for the first couple of weeks when they were going to give me cursor control, when I was doing body mapping. It was attempt to do this, attempt to do that. When Neuralink was telling me to imagine doing it, it kind of made sense to me, but it's not something that people practice. If you started school as a...

你能澄清一下吗？想象运动和尝试运动之间应该有区别吗？

Can you clarify? Is there supposed to be a difference between imagined movement and attempted movement?

是的，区别在于想象运动时你根本没有尝试去动。你只是在脑海里想象动作。那么理论上，这两种情况应该激活大脑的不同区域吗？

Yeah, just that in imagined movement you're not attempting to move at all. So you're visualizing doing it. And then theoretically, is that supposed to be a different part of the brain that lights up in those two different situations?

不一定。我认为所有这些信号仍然可以在运动皮层中表示，但区别在于想象某件事与尝试做它之间的自然性，以及随时间推移产生的疲劳。顺便说一句，麦克风这边是 Bliss。所以这只是不同的方式来引导你达到目标。尝试运动听起来确实是正确的方法。

Not necessarily. I think all these signals can still be represented in motor cortex, but the difference I think has to do with the naturalness of imagining something versus attempting it and the fatigue of that over time. And by the way, on the mic is Bliss. So this is just different ways to prompt you to get to the thing that you're around. Attempted movement does sound like the right thing to try.

是的，对我来说这说得通，因为想象时我会在脑海里开始可视化。尝试时我会真的开始尝试移动。我一生都在做格斗运动，比如摔跤。当我在想象一个动作时，我实际上在移动肌肉。几乎有点激活的感觉，而不是像看图片一样可视化自己。我觉得任何人都会自然地这么做。如果你让别人想象做某事，他们可能会闭上眼睛然后开始实际做。但就是突然明白了。一开始很难，但尝试运动奏效了。它就像应该的那样工作，效果非常好。

Yeah, I mean it makes sense to me because imagine for me, I would start visualizing in my mind. Attempted, I would actually start trying to move. I mean, I did combat sports my whole life, like wrestling. When I'm imagining a move, I'm moving my muscles exactly. There's a bit of an activation almost, versus visualizing yourself like a picture doing it. Yeah, it's something that I feel like naturally anyone would do. If you try to tell someone to imagine doing something, they might close their eyes and then start physically doing it. But it just clicked. It was very hard at the beginning, but attempted worked. It worked just like it should, worked like a charm.

记得有一个星期二我们在瞎搞，我想我知道你用了什么脏话，但当你发现你可以直接控制光标时，你嘴里冒出了那个脏话。

Remember there was like one Tuesday we were messing around and I think I know what swear word you used, but there's a swear word that came out of your mouth when you figured out you could just do the direct cursor control.

是的，就是那个。它让我震惊，没有双关的意思，当我第一次仅仅用思想移动光标而不是尝试移动时，我震惊了。这是我在那之前的几周里逐渐发现的，随着我光标控制得越来越好，模型也变好了，我就不需要那么努力去尝试移动它了。部分原因是我甚至和他们讨论过。有一天我在观察我的大脑信号，当我尝试向右移动时，我看着屏幕上的尖峰。我看到尖峰，信号在我实际尝试移动之前就被发送了。我想这是因为当你移动手或任何身体部位时，信号在你实际移动之前就被发送了。它必须一路向下再返回，你才能做出任何动作，所以有一个延迟。我注意到在我实际尝试移动之前，我的大脑里已经有了一些活动，我的大脑在预测我想做什么。这一切开始在我的大脑中酝酿，它就在那里，一直在后台。就像，它能做到这一点太奇怪了。这有点道理，但我想知道这对使用 Neuralink 意味着什么。然后当我在尝试运动和光标控制时，我看到随着光标控制越来越好，它越来越能预测我的动作和我想要它做什么。然后有一天，我在玩 Webgrid 时，在我开始尝试移动之前，我随意地看了一个目标。我只是想训练我的眼睛向前看，比如好的这是我当前的目标，但如果我看向这边的目标，我知道我可能能更快到达那里。我看了过去，光标就直接飞了过去。太疯狂了。我不得不后退一步。我想，这不应该发生。我一整天都在笑，我太兴奋了。我说，伙计们，你们知道这能行吗？就像我只要想它就会发生，而他们整个时间都在这么说。我说，是啊，但这真的是用我的思想吗？我在尝试移动，它只是捕捉到了那个信号，所以感觉不像是用我的思想。但当我第一次那样移动它时，哦，天哪。这让我觉得这项技术，我正在做的事情，实际上比我想象的要令人印象深刻得多，比我想象的要酷得多。它打开了一个全新的可能性世界，关于这项技术可能实现什么，以及我可能能用它做到什么。

Yeah, that's it. It blew my mind, no pun intended, blew my mind when I first moved the cursor just with my thoughts and not attempting to move. It's something that I found over the couple of weeks building up to that, that as I get better cursor control, like the model gets better, then it gets easier for me to not have to attempt as much to move it. And part of that is something that I had even talked with them about. When I was watching the signals of my brain one day, I was watching when I attempted to move to the right and I watched the screen as I saw the spikes. I was seeing the spike, the signal was being sent before I was actually attempting to move. I imagine just because when you go to move your hand or any body part, that signal gets sent before you're actually moving. It has to make it all the way down and back up before you actually do any sort of movement, so there's a delay there. And I noticed that there was something going on in my brain before I was actually attempting to move, that my brain was anticipating what I wanted to do. And that all started sort of percolating in my brain, it was just sort of there, always in the back. Like, that's so weird that it could do that. It kind of makes sense, but I wonder what that means as far as using the Neuralink. And then as I was playing around with the attempted movement and playing around with the cursor, I saw that as the cursor control got better, it was anticipating my movements and what I wanted it to do a bit better and a bit better. And then one day I just randomly, as I was playing Webgrid, I looked at a target before I had started attempting to move. I was just trying to train my eyes to start looking ahead, like okay this is the target I'm on, but if I look over here to this target, I know I can maybe be a bit quicker getting there. And I looked over and the cursor just shot over. It was wild. I had to take a step back. I was like, this should not be happening. All day I was just smiling, I was so giddy. I was like, guys, do you know that this works? Like I can just think it and it happens, which they'd all been saying this entire time. I'm like, yeah, but is it really with my mind? Like I'm attempting to move and it's just picking that up, so it doesn't feel like it's with my mind. But when I moved it for the first time like that, it was oh man. It made me think that this technology, what I'm doing, is actually way more impressive than I ever thought, way cooler than I ever thought. And it just opened up a whole new world of possibilities of what could possibly happen with this technology and what I might be able to be capable of with it.

因为你第一次感觉到这就像是数字心灵感应，你在用你的思想控制一个数字设备。我的意思是，这是一个真正的发现时刻，太酷了。你发现了一些东西。我见过科学家谈论一个重大的顿悟时刻，比如获得诺贝尔奖，他们会有那种“我靠”的感觉。是的，那就是我的感觉。我觉得我发现了什么，但对我来说可能不一定对全世界或这个领域而言。这对我来说只是一个顿悟时刻。就像，哦，这能行。显然它能行。所以我现在一直这么做。我把尝试运动和想象运动混合在一起。我一起做，因为我发现它们之间存在一些相互作用。

Because you had felt for the first time like this was digital telepathy, like you're controlling a digital device with your mind. I mean, this is a real moment of discovery, that's really cool. You've discovered something. I've seen scientists talk about a big aha moment, like Nobel Prize winning, they'll have this holy crap. Yeah, that's what it felt like. I felt like I had discovered something, but for me maybe not necessarily for the world at large or this field at large. It just felt like an aha moment for me. Like, oh this works. Obviously it works. And so that's what I do all the time now. I kind of intermix the attempted movement and imagined movement. I do it all together because I found that there is some interplay.

对于不了解的人，你能解释一下 Link 应用是如何工作的吗？你有一个关于这个主题的精彩直播，我想是你第一次在 X 上直播，描述了这款应用。你能描述一下它是如何工作的吗？

For people who don't know, can you explain how the Link app works? You have an amazing stream on the topic, your first stream I think on X, describing the app. Can you just describe how it works?

是的，这只是 Neuralink 创建的一个应用，用来帮助我与电脑交互。在 Link 应用上，有几种不同的设置和模式，我可以做很多事情。有身体映射，我们之前稍微提到过。还有校准。校准是我实际获得光标控制的方式，也就是校准我大脑中发生的事情，将其转化为光标控制。它会生成模型。我认为他们用的是时间。所以校准 5 分钟会给我一个不错的模型，如果我校准 10 分钟或 15 分钟，模型会逐渐变得更好。所以通常来说，我校准的时间越长，模型就越好。

Yeah, so it's just an app that Neuralink created to help me interact with a computer. On the Link app, there are a few different settings and different modes and things I can do on it. There's the body mapping, which we kind of touched on. There's a calibration. Calibration is how I actually get cursor control, so calibrating what's going on in my brain to translate that into cursor control. It will pop out models. What they use, I think, is time. So five minutes in calibration will give me so good of a model, and then if I'm in it for 10 minutes and 15 minutes, the models will progressively get better. So the longer I'm in it, generally the better the models will get.

这真的很酷，因为你经常提到模型。模型是你在完成校准步骤后构建的东西。你还提到有时你会玩一个非常难的游戏，比如贪吃蛇，只是为了看看模型有多好。

That's really cool, because you often refer to the models. The model is the thing that's constructed once you go through the calibration step. And you also talked about sometimes you'll play a really difficult game like Snake just to see how good the model is.

是的，是的。所以贪吃蛇有点像我的模型试金石。如果我能相当好地控制贪吃蛇，那么我就知道我的模型相当不错。所以是的，Link 应用有所有这些功能。它现在还有网页网格。它也是我通常连接电脑的方式。他们现在给了我很多语音控制功能。我可以说“连接”或“植入物断开”，只要我有充电器在手，我就可以连接。充电器也是我连接 Link 应用的方式。要连接电脑，我必须把植入物充电器放在头上才能唤醒它，因为植入物在不使用时总是处于休眠模式。我想有一个设置可以定期唤醒它，所以我们可以设置为半小时或 5 小时，如果我只是想让它定期唤醒的话。所以是的，我会连接 Link 应用，然后进行各种操作：当天的校准，可能还有身体映射。我有一个类似作业的标签，因为我非常健忘，经常忘记做事。所以我有很多他们希望我做的数据收集任务。

Yeah, yeah. So Snake is kind of like my litmus test for models. If I can control Snake decently well, then I know I have a pretty good model. So yeah, the Link app has all of those. It has web Grid in it now. It's also how I connect to the computer just in general. So they've given me a lot of voice controls with it at this point. I can say like "connect" or "implant disconnect" and as long as I have the charger handy, then I can connect to it. The charger is also how I connect to the Link app. To connect to the computer, I have to have the implant charger over my head when I want to connect to have it wake up, because the implant is in hibernation mode always when I'm not using it. I think there's a setting to wake it up every so often, so we could set it to half an hour or 5 hours or something if I just want it to wake up periodically. So yeah, I'll connect to the Link app and then go through all sorts of things: calibration for the day, maybe body mapping. I have like a little homework tab because I am very forgetful and I forget to do things a lot. So I have a lot of data collection things that they want me to do.

身体映射是数据收集的一部分，还是也是……

Is the body mapping part of the data collection or is that also part of the...

是的，它是。这是他们希望我每天做的事情，但我一直偷懒，因为我做了很多媒体采访和旅行。所以我是一个糟糕的首位候选人，因为我一直在偷懒不做作业。但是的，这只是他们希望我每天做的事情，用来追踪 Neuralink 随着时间的推移表现如何，并且我想，可以给 FDA 提供一些东西，用来制作各种花哨的图表，展示“嘿，这是 Neuralink 在第一天、第 90 天和第 180 天的表现”等等。

Yeah, it is. It's something that they want me to do daily, which I've been slacking on because I've been doing so much media and traveling so much. So I've been a terrible first candidate for how much I've been slacking on my homework. But yeah, it's just something that they want me to do every day to track how well the Neuralink is performing over time and have something to give, I imagine, to the FDA to create all sorts of fancy charts and show like, "Hey, this is how the Neuralink is performing day one versus day 90 versus day 180" and things like that.

校准步骤是什么样的？是像“向左移动，向右移动”吗？

What's the calibration step like? Is it like "move left, move right"?

这是一个泡泡游戏。所以屏幕上会出现黄色的泡泡。一开始是开环。开环是我仍然不完全理解的东西。我和 Bliss 从技术角度讨论了很长时间两者的区别。所以很高兴听到你的说法。开环基本上是我无法控制光标。光标会在屏幕上自行移动，而我通过意图跟随光标到不同的泡泡。然后我的算法会根据我这样做时收到的信号进行训练。他们用了几种不同的方式。他们称之为“中心到目标”。所以中间会有一个泡泡，然后周围有八个泡泡，光标会从中间移动到一侧，比如中间到左边，回到中间，到上面，到中间，到右上，然后他们会绕着圆圈这样做。我会一直跟随那个光标。然后它会根据我的意图进行训练，也就是它期望我在整个过程中的意图。

It's a bubble game. So there will be like yellow bubbles that pop up on the screen. At first it is open loop. Open loop is something that I still don't fully understand. Me and Bliss talked for a long time about the difference between the two from the technical side. So it'd be great to hear your side of the story. Open loop is basically I have no control over the cursor. The cursor will be moving on its own across the screen and I am following by intention the cursor to different bubbles. Then my algorithm is training off of what the signals it's getting are as I'm doing this. There are a couple different ways that they've done it. They call it "center out target". So there will be a bubble in the middle and then eight bubbles around that, and the cursor will go from the middle to one side, say middle to left, back to middle, to up, to middle, to up right, and they'll do that all the way around the circle. And I will follow that cursor the whole time. Then it will train off of my intentions, what it is expecting my intentions to be throughout the whole process.

你能具体说说当你说“跟随”时吗？是的，你不是指用眼睛，而是用你的意图。

Can you actually speak to when you say "follow"? Yes, you don't mean with your eyes, you mean with your intentions.

是的，所以通常在校准时，我会做尝试性动作，因为我认为这样效果更好。我认为随着校准的进行，更好的模型会让使用想象动作变得更容易。

Yeah, so generally for calibration I'm doing attempted movements because I think it works better. I think the better models as I progress through calibration make it easier to use imagined movement.

等等，等等。所以用尝试性动作进行校准会创建一个模型，让你之后使用意念力非常有效？

Wait, wait. So calibrated on attempted movement will create a model that makes it really effective for you to then use the force?

是的。我试过用想象动作进行校准，但出于某种原因效果不太好。所以那是中心到目标。还有一种方式是随机目标会出现在屏幕上，同样：我只是跟随光标到屏幕上的那个目标。我试过用想象动作进行这些，但出于某种原因，模型的质量没有那么高。当我们进入闭环时，我没有大量尝试过，所以也许我们现在做校准的不同方式可能会让它好一点。但我发现的是，在校准过程中会有一个点，我可以使用想象动作。

Yes. I've tried doing calibration with imagined movement and it just doesn't work as well for some reason. So that was the center out targets. There's also one where a random target will pop up on the screen and it's the same: I just follow along with wherever the cursor is to that target all across the screen. I've tried those with imagined movement and for some reason models just don't give as high level of quality. When we get into closed loop, I haven't played around with it a ton, so maybe the different ways we're doing calibration now might make it a bit better. But what I've found is there will be a point in calibration where I can use imagined movement.

在那之前，运动根本不起作用。所以如果我做 45 分钟的校准，前 15 分钟我无法使用想象运动；它就是不工作，不知为什么。过了某个点之后，我就能感觉到它了。我能看出它的移动方式不同了。这是我能想到的最好描述。它几乎就像在我行动之前就预判了我要做什么。所以用尝试运动 15 分钟后，某个时刻我能感觉到，当我将眼睛移到下一个目标时，光标开始跟上，好像它开始理解、学习我要做什么。

Movement before that point it doesn't really work. So if I do calibration for 45 minutes, the first 15 minutes I can't use imagined movement; it just doesn't work for some reason. And after a certain point, I can just sort of feel it. I can tell it moves different. That's the best way I can describe it. It's almost as if it is anticipating what I am going to do again before I go to do it. So using attempted movement for 15 minutes, at some point I can kind of tell when I move my eyes to the next target that the cursor is starting to pick up, like it's starting to understand, it's learning what I'm going to do.

首先，你在这方面是真正的先驱，这太酷了。你在探索如何最有效地完成每一个环节。从中可以学到很多经验，所以感谢你在所有这些超级技术层面上的开拓。听到校准方式不同时体验感也不同，这也很酷，因为我想你的大脑在做不同的事情，所以感觉不同。尝试为这些感觉定义词汇和度量会很有趣，但归根结底，你也可以通过蛇形游戏或网页网格来测量实际表现，看看什么真正有效。你说对于开环校准，目前尝试运动效果最好？

First of all, it's really cool that you are a true pioneer in all of this. You're exploring how to do every aspect of this most effectively. There are so many lessons learned from this, so thank you for being a pioneer in all these super technical ways. It's also cool to hear that there's a different feeling to the experience when it's calibrated in different ways, just because I imagine your brain is doing something different and that's why there's a different feeling. Trying to define the words and measurements to those feelings would be interesting, but at the end of the day you can also measure your actual performance on whether it's snake or web grid, you can see what actually works well. And you're saying for the open loop calibration, the attempted movement works best for now?

是的，是的。开环时，你不会得到你做了某事的反馈。

Yep, yep. So the open loop, you don't get the feedback that you did something.

这令人沮丧吗？

Is that frustrating?

不，不，这对我来说很合理。我们在开环中做过有光标和没有光标的校准。所以有时，比如中心向外任务，你会从气泡亮起开始校准，我朝着那个气泡推动。当它被推向气泡大约 3 秒后，气泡会爆掉，然后我回到中心。所以我完全是靠我的意图来做这一切。反正它学到的就是这个，所以只要我按照他们希望我做的去做，就像沿着黄砖路走，一切都会顺利。

No, no, it makes sense to me. We've done it with a cursor and without a cursor in open loop. So sometimes it's just, say for the center out, you'll start calibration with a bubble lighting up and I push towards that bubble. Then when it's pushed towards that bubble for say 3 seconds, the bubble will pop and then I come back to the middle. So I'm doing it all just by my intentions. That's what it's learning anyway, so it makes sense that as long as I follow what they want me to do, like follow the yellow brick road, it'll all work out.

你真是充满了精彩的引用。气泡游戏好玩吗？

You're full of great references. Is the bubble game fun?

是啊，他们总是觉得让我做校准很过意不去。比如，“哦，我们要做 40 分钟的校准了。”我就说，“好吧，你们想做两次吗？”我总是主动要求做他们需要的任何事。我非常乐意做。这并不糟糕。我可以躺在那里，或者坐在椅子上，和一群很棒的人一起做这些事。我可以进行很棒的对话，给他们反馈，聊各种各样的事情。我还可以在背景电视上放点东西，分散一下注意力。一点也不糟糕。

Yeah, they always feel so bad making me do calibration. Like, 'Oh, we're about to do a 40-minute calibration.' I'm like, 'All right, do you guys want to do two of them?' I'm always asking to do whatever they need. I'm more than happy to do it. It's not bad. I get to lie there and sit in my chair and do these things with some great people. I get to have great conversations, I can give them feedback, I can talk about all sorts of things. I could throw something on my TV in the background and kind of split my attention between them. It's not bad at all.

有分数吗？比如你能在气泡游戏中做得更好吗？

Is there a score that you get? Like can you do better on the bubble game?

没有，但我很想要。我很想要。是的，记下 Noland 的建议：让它更有趣，游戏化。是的，我非常喜欢网页网格的一点就是因为我好胜心很强。BPS 越高，分数越高，我就知道自己做得越好。所以我想我曾经问过其中一个人，能不能在校准中给我一些数值反馈。我想知道他们在看什么。比如，“哦，你在做校准时我们看到这个数字，这在我们这边意味着校准进展顺利。”我会很喜欢，因为我想知道我做得怎么样。但他们也告诉我，这不一定是——对应的；那个数字实际上并不总是意味着校准进展顺利。所以它不是 100% 准确的，他们不想因此扭曲我的体验，或者让我根据那个数字改变做法，如果那个数字并不总是准确反映模型最终结果的话。至少我是这么理解的。有一件事我确实问过他们，而且我非常喜欢追求的是，在校准快结束时，目标之间有一个时间间隔。我喜欢把这个数字尽可能压低。一开始，我点爆气泡之间可能需要 4、5、6 秒，但到结束时，我喜欢把它控制在 1.5 秒以下，如果能到 1 秒就更好了，因为在我看来，这很好地对应到网页网格上——如果我能每秒击中一个目标，那我就做得非常非常好。

No, I would love that. I would love that. Yeah, writing down suggestions from Noland: make it more fun, gamified. Yeah, that's one thing that I really enjoy about web grid is because I'm so competitive. The higher the BPS, the higher the score, I know the better I'm doing. So I think I've asked at one point one of the guys if he could give me some sort of numerical feedback for calibration. I would like to know what they're looking at. Like, 'Oh, you know, we see this number while you're doing calibration and that means on our end that we think calibration is going well.' I would love that because I would like to know if what I'm doing is going well or not. But then they've also told me that it's not necessarily one-to-one; that number doesn't actually mean calibration is going well in some ways. So it's not 100%, and they don't want to skew what I'm experiencing or want me to change things based on that if that number isn't always accurate to how the model will turn out or how the end result will be. That's at least what I got from it. One thing I do, I have asked them, and something I really enjoy striving for is towards the end of calibration there is a time between targets. So I like to keep that number as low as possible. At the beginning it can be 4, 5, 6 seconds between me popping bubbles, but towards the end I like to keep it below 1.5 or if I could get it to 1 second between bubbles, because in my mind that translates really nicely to something like web grid where I know if I can hit a target once every second, I'm doing real real well.

这是在校准中获得分数的一种方式：速度，你能多快从一个气泡到另一个气泡。

That's a way to get a score on the calibrations: the speed, how quickly can you get from bubble to bubble.

是的。所以有开环，然后进入闭环。闭环已经开始给你一种感觉，因为你得到了模型好坏的反馈。

Yeah. So there's the open loop, and then it goes to the closed loop. The closed loop can already start giving you a sense because you're getting feedback of how good the model is.

所以闭环就是我第一次获得光标控制的时候？

So closed loop is when I first get cursor control?

是的。他们是这样向我描述的——作为一个不懂这些的人，每次和他们在一起时我都是房间里最笨的人，我谦卑地说——就是我正在闭合这个回路。所以我实际上是那个完成这个回路的人，不管这个回路是什么。我甚至不知道回路是什么；他们从没告诉过我。他们只说有一个回路，一开始它是开的，我无法控制，然后我获得了控制权，它就闭合了，所以我是在完成这个回路。

Yes. And how they've described it to me, someone who does not understand this stuff—I am the dumbest person in the room every time I'm with any of them, with all humility—is that I am closing the loop. So I am actually now the one that is finishing the loop of whatever this loop is. I don't even know what the loop is; they've never told me. They just say there is a loop, and at one point it's open and I can't control, and then I get control and it's closed, so I'm finishing the loop.

校准通常需要多长时间？你说像 10、15 分钟？

How long does the calibration usually take? You said like 10, 15 minutes?

嗯，他们正努力把这个时间降得很低。这是我们最近一直在努力的方向：尽可能降低时间，这样如果人们需要每天、每隔一天或每周做一次校准，他们就不希望人们长时间坐在那里做校准。我想他们希望降到 5 分钟或更短，至少在我们目前的情况下是这样。如果永远不用做校准就好了。所以我相信随着我们对大脑的了解越来越多，我们最终会达到那个目标。我认为那是梦想。目前，为了获得非常非常好的模型，我要做 40 或 45 分钟的校准。我不介意。就像我说的，他们总是觉得很过意不去，但如果这能让我得到一个能在网页网格上打破这些记录的模型，我愿意做两个小时。

Well, they're trying to get that number down pretty low. That's what we've been working on a lot recently: getting it down as low as possible so that if this is something people need to do on a daily basis, or every other day, or once a week, they don't want people sitting in calibration for long periods of time. I think they wanted to get it down to 5 minutes or below, at least where we're at right now. It'd be nice if you never had to do calibration. So we'll get there at some point, I'm sure, the more we learn about the brain. I think that's the dream. Right now, for me to get really, really good models, I'm in calibration 40 or 45 minutes. And I don't mind. Like I said, they always feel really bad, but if it's going to get me a model that can break these records on web grid, I'll stay in it for two hours.

我们来谈谈正事。网页网格。我看到一个演示，Bliss 说截至三月，你在网页网格中选中了 89,000 个目标。你能解释一下这个游戏吗？什么是网页网格？要成为网页网格的世界级选手并不断打破世界纪录，需要什么？

Let's talk business. So web grid. I saw a presentation where Bliss said by March you selected 89,000 targets in web grid. Can you explain this game? What is web grid and what does it take to be a world-class performer in web grid as you continue to break world records?

是的，就像金牌得主。嗯，你知道，我要感谢……

Yeah, it's like a gold medalist. Well, you know, I'd like to thank...

所有帮助我走到今天的人——我的教练、我的父母，他们每天凌晨 5 点开车送我去训练。感谢上帝，还有我自己的奉献精神……运动员的采访总是这样，完全就是那个模板，对吧。

Everyone who's helped me get here, my coaches, my parents for driving me to practice every day at 5 in the morning. Like to thank God, and just overall my dedication to the... The interviews with athletes are always like that exact, it's like that template, yeah.

Web Grid 就是一个网格。字面意思，就是一个网格。你可以把它设得很大或很小。网格上的一个格子会亮起，然后你去点击它。这是他们衡量 BCI 好坏的基准测试方法。所以很简单：你只需要点击目标。只有一个蓝色单元格出现，你要把鼠标移过去点击它。我喜欢在更大的网格上玩，因为网格越大，每次点击获得的 BPS（每秒比特数）就越高。所以我一般玩 35x35 的网格，然后其中一个小方块（称为目标）会亮起，你把光标移过去点击它，然后一直重复。

So Web Grid is a grid. It's literally just a grid. You can make it as big or as small as you want. A single box on that grid will light up, and you go and click it. It is a way for them to benchmark how good a BCI is. So it's pretty straightforward: you just click targets. Only one blue cell appears, and you're supposed to move the mouse to there and click on it. I like playing on bigger grids because the bigger the grid, the more BPS (bits per second) you get every time you click one. So I'll play on like a 35x35 grid, and then one of those little squares (call it target) will light up, and you move the cursor there and click it, and then you do that forever.

你一开始能达到每秒 8 比特，最近突破了这个记录？

And you've been able to achieve at first 8 bits per second, and you recently broke that?

是的，我现在是 8.5。本来在我来奥斯汀的前一天就能打破这个记录，但最后出现了大约 5 秒的延迟，我只能等延迟降下来再继续点击。当时我大概是 8.01，然后延迟了 5 秒，之后点击的三个目标都停留在 8.01。所以如果我在延迟期间能点击的话，我可能已经达到……不知道，可能到 9 了。所以我离得很近，非常接近。但这次奥斯汀之行完全影响了我玩 Web Grid 的能力。

Yeah, I'm at 8.5 right now. I would have beaten that literally the day before I came to Austin, but I had like a 5-second lag right at the end, and I just had to wait until the latency calmed down, and then I kept clicking. But I was at like 8.01, and then 5 seconds of lag, and then the next like three targets I clicked all stayed at 8.01. So if I would have been able to click during that time of lag, I probably would have hit... I don't know, I might have hit 9. So I'm there, I'm really close. And then this whole Austin trip has really gotten in the way of my Web Grid playing ability.

真让人沮丧。所以你满脑子都在想这个？

Frustrating. So that's all you're thinking about right now?

是的，我知道。我只是想做得更好。我想达到 9。我觉得 9 非常非常可行。我已经很接近了。我想 10 的话，也许下个月就能达到。如果我真的努力，可能几周内就能做到。

Yeah, I know. I just want to do better. I want to hit 9. I think 9 is very, very achievable. I'm right there. I think 10 I could hit maybe in the next month. I could do it probably in the next few weeks if I really push.

我觉得你和埃隆基本上是同一个人。上次我和他做播客时，他非常沮丧，因为他作为机器人角色打不过 Uber Lilith。那大概是一年前的事了。就像你一样，我能感觉到他大脑里有一部分一直在想：“我希望我现在就在尝试。”我觉得他那天晚上就做到了。他熬夜做到了，这让我觉得不可思议。

I think you and Elon are basically the same person. Last time I did a podcast with him, he came in extremely frustrated that he can't beat Uber Lilith as a Droid. That was like a year ago. I think like solo and you, I could just tell there's some percentage of his brain the entire time was thinking, 'I wish I was right now attempting.' I think he did it that night. He stayed up and did it that night, which is crazy to me.

从根本上看，这真的很鼓舞人心。你所做的事情也以这种方式鼓舞人心，因为这不仅仅关乎游戏。你所做的一切都有影响。通过在 Web Grid 上努力表现，你帮助所有人弄清楚如何构建整个系统：解码、软件、硬件、校准，所有的一切。如何让所有这些协同工作，这样你才能把其他事情做得很好。

It's in a fundamental way really inspiring. And what you're doing is inspiring in that way because it's not just about the game. Everything you're doing there has impact. By striving to do well on Web Grid, you're helping everybody figure out how to create the system: the decoding, the software, the hardware, the calibration, all of it. How to make all of that work so you can do everything else really well.

是啊，真的很有趣。这也是其中的一部分：让它变得有趣。它让人上瘾。我开玩笑说，他们在我脑子里植入这个东西的时候，一定是按了个开关，让我对这些游戏更敏感，让我对 Web Grid 上瘾之类的。

Yeah, it's just really fun. That's also part of the thing: making it fun. It's addicting. I've joked about what they actually did when they went in and put this thing in my brain. They must have flipped a switch to make me more susceptible to these kinds of games, to make me addicted to Web Grid or something.

你知道 Bliss 的最高分吗？

Do you know Bliss's high score?

知道，他说大概是 14 还是 17？17.1 左右。

Yeah, he said like 14 or something. 17? 17.1 or something.

17.01？

17.01?

对，他告诉我他在地板上玩，还吃花生酱，并且禁食。很奇怪。听起来像作弊，像兴奋剂。

Yeah, he told me he does it on the floor with peanut butter and he fasts. It's weird. It sounds like cheating, sounds like performance enhancing.

不，就像诺兰第一次玩这个游戏时，他问我们玩得有多好。我记得你当时就说你要打败我。总有一天我会达到那个水平。我完全相信你。我觉得我能行。我很期待。

No, like the first time Nolan played this game, he asked how good we are at this game. And I think you told me right then you're going to try to beat me. I'm going to get there someday. I fully believe you. I think I can. I'm excited for that.

所以我一开始用的是驻留光标，这严重限制了我玩 Web Grid 的能力。基本上每次点击都要等 3 秒。

So I've been playing first off with the dwell cursor, which really hampers my Web Grid playing ability. Basically I have to wait 3 seconds for every click.

哦，所以你没法直接点击？必须通过驻留来点击？3 秒，太糟糕了。这严重限制了我能达到的高度。

Oh, so you can't do the click? So you have to click by dwelling? 3 seconds, which sucks. It really slows down how high I'm able to get.

我仍然能达到每分钟 50 多次试验，这已经很不错了。因为我可以……有一个设置是移动速度要多慢才能触发点击。所以我能大致判断什么时候接近那个阈值，然后稍微提前一点开始点击，这样当我点击时，并不是完全停在目标上方，而是在前往目标的路上稍微提前一点，以精确把握时机。

I still hit like 50 something trials per minute in that, which was pretty good. Because I'm able to... there's one of the settings that is also how slow you need to be moving in order to initiate a click. So I can tell sort of when I'm on that threshold to start initiating a click just a bit early, so I'm not fully stopped over the target when I go to click. I'm doing it on my way to the target, a little early, to try to time it just right.

哇，所以你在目标前稍微减速？这简直是领先表现。

Wow, so you're slowing down just a hair right before the target? This is like lead performance.

但 3 秒的上限还是很糟糕。不过我可以降到 0.2 和 0.1。0.1 是什么？对，我也试过一点。要玩 0.1 的话，我必须调整大量不同的参数，而我现在还不能完全控制这些参数。它还会改变模型的训练方式。如果我在 Web Grid 中训练一个模型，比如在模型上做引导，基本上就是他们在玩 Web Grid 时根据我产生的 Web Grid 数据来训练模型。所以如果我玩 10 分钟 Web Grid，他们就可以专门用这些数据来训练，为我提供一个更好的模型。如果我用 0.1 来玩……

But it still sucks that there's a ceiling of 3 seconds. Well, I can get down to 0.2 and 0.1. 0.1's what? Yeah, and I've played with that a little bit too. I have to adjust a ton of different parameters in order to play with 0.1, and I don't have control over all that on my end yet. It also changes how the models are trained. If I train a model in Web Grid, like a bootstrap on a model, which basically is them training models as I'm playing Web Grid based off of the Web Grid data that I'm generating. So if I play Web Grid for 10 minutes, they can train off that data specifically in order to get me a better model. If I do that with 0.1...

0.3 和 0.1 对比，模型出来的结果不一样。它们的交互方式差别非常大，所以我得非常小心。我发现用 0.3 在某些方面其实更好，除非我能用 0.1 并调整所有参数，那样更理想，因为显然 0.3 比 0.1 快，所以我能达到目标。

3 versus 0.1, the models come out different. The way they interact is just much, much different, so I have to be really careful. I found that doing it with 0.3 is actually better in some ways, unless I can do it with 0.1 and change all the different parameters. Then that's more ideal, because obviously 0.3 is faster than 0.1, so I could get there.

你现在能用大脑点击吗？是用悬停光标的那种点击。

Can you click using your brain for right now? It's the hover clicking with the dwell cursor.

在所有的线程回缩问题发生之前，我们一直在校准点击——左键点击、右键点击。那是我之前用悬停光标打破纪录前的天花板。我想在 35x35 的网格上，用左键和右键点击，因为难度更大，所以每秒比特数（BPS）更高。

Before all the thread retraction stuff happened, we were calibrating clicks — left click, right click. That was my previous ceiling before I broke the record again with the dwell cursor. I think on a 35x35 grid with left and right click, you get more BPS (bits per second) using multiple clicks because it's more difficult.

哦，因为什么？你要么做左键点击，要么做右键点击。颜色不同吗？就像这样：蓝色目标代表左键点击，橙色目标代表右键点击，他们就是这么做的。

Oh, because what is it? You're supposed to do either a left click or a right click. Is it different color? Like this: blue targets for left click, orange targets for right click is what they had done.

所以我之前的纪录是 7.5，用的是蓝色和橙色目标。我想如果我现在回到那种方式，做点击校准，并且能自己发起点击，我最多几天就能突破 10 的天花板。

So my previous record of 7.5 with the blue and the orange targets. I think if I went back to that now, doing the click calibration and being able to initiate clicks on my own, I would break that 10 ceiling in a couple days max.

是啊，你会开始让 Bliss 担心他的 17 了。你觉得我们为什么没给他 EXA？正是。

Yeah, you'll start making Bliss nervous about his 17. Why do you think we haven't given him the EXA? Exactly.

那么线程回缩的感觉怎么样？

So what would it feel like with the retractions?

有一些线程回缩了。那感觉糟透了，真的非常艰难。他们告诉我的那天，正好是我在 Neuralink 弗里蒙特工厂进行大型参观的日子。就在我们去之前他们告诉了我，真的很难接受。我最初的反应是：“好吧，进去，修好它。进去，把它拿出来修好。”第一次手术非常轻松。我睡着了，几小时后醒来，就这样。我没有任何疼痛，也没吃任何止痛药。所以我知道，如果他们愿意，第二天就可以进去放一个新的，如果那是必要的，因为我只想让情况变好，不想失去能力。我玩它玩得很开心，持续了几周，一个月。它为我打开了这么多扇门，这么多新的可能性，我不想失去它。我觉得如果我先看到了山顶的风景，然后一个月后一切崩塌，那将是命运的残酷转折。而且我知道——说是山顶，但我的看法是，我刚刚开始爬山，还有那么多我知道可能的事情。所以失去这一切真的非常非常艰难。但在去工厂的路上——大概五分钟车程——我和父母谈了这件事，我祈祷了。我对自己说：“我不会让这件事毁了我的一天。我不会让它毁了他们为我安排的这次精彩参观。我想去向大家展示我有多感激他们所做的一切。我想去见所有让这一切成为可能的人，我想去度过我人生中最美好的一天之一。”我做到了。那太棒了，绝对是我有幸经历过的最美好的一天之一。然后有几天，我情绪非常低落。之后的头几天，我只是不知道它是否还能再工作。然后我做出了决定：即使我失去了使用 Neuralink 的能力，即使我失去了未来的一切，如果我能以任何方式继续给他们提供数据，我就会去做。如果我需要每天做一些数据收集或身体映射，持续一年，我也会去做，因为我知道我所做的一切都在帮助后来的人。这就是我想要的。我想我做这一切的初衷就是为了帮助别人，我知道任何我能帮忙的事，我都会继续做，即使我再也不能使用光标。我很高兴能成为其中一部分，我所做的一切都只是额外收获。这是我得以体验的东西，我知道这对后来的人会有多棒。所以不如继续前进。

There is some of the threads retracted. That sucked. It was really, really hard. The day they told me was the day of my big Neuralink tour at their Fremont facility. They told me right before we went over there. It was really hard to hear. My initial reaction was, "All right, go in, fix it. Go in, take it out and fix it." The first surgery was so easy. I went to sleep, a couple hours later I woke up, and here we are. I didn't feel any pain, didn't take any pain pills or anything. So I just knew that if they wanted to, they could go in and put in a new one the next day if that's what it took, because I just wanted it to be better and I wanted not to lose the capability. I had so much fun playing with it for a few weeks, for a month. It had opened up so many doors for me, so many more possibilities that I didn't want to lose it. I thought it would have been a cruel twist of fate if I had gotten to see the view from the top of this mountain and then have it all come crashing down after a month. And I knew — say the top of the mountain, but how I saw it was I was just now starting to climb the mountain, and there was so much more that I knew was possible. So to have all of that be taken away was really, really hard. But then on the drive over to the facility — five minute drive, whatever it is — I talked with my parents about it, I prayed about it. I was just like, "You know, I'm not going to let this ruin my day. I'm not going to let this ruin this amazing tour that they have set up for me. I want to go show everyone how much I appreciate all the work they're doing. I want to go meet all of the people who have made this possible, and I want to go have one of the best days of my life." And I did. It was amazing, and it absolutely was one of the best days I've ever been privileged to experience. And then for a few days, I was pretty down in the dumps. For the first few days afterwards, I was just like, I didn't know if it was ever going to work again. And then I just made the decision that even if I lost the ability to use the Neuralink, even if I lost out on everything to come, if I could keep giving them data in any way, then I would do that. If I needed to just do some data collection every day or body mapping every day for a year, then I would do it, because I know that everything I'm doing helps everyone to come after me. And that's all I wanted. I guess the whole reason that I did this was to help people, and I knew that anything I could do to help, I would continue to do, even if I never got to use the cursor again. I was just happy to be a part of it, and everything that I had done was just a perk. It was something that I got to experience, and I know how amazing it's going to be for everyone to come after me. So might as well just keep trucking along.

话虽如此，你还是努力恢复了性能。这就像从《洛奇 1》到《洛奇 2》。那么你是什么时候第一次意识到这是可能的，是什么给了你力量、动力和决心去做到，重新提升并打破你之前的纪录？

Well that said, you were able to work your way up to get the performance back. So this is like going from Rocky one to Rocky two. So when did you first realize that this is possible, and what gave you the strength, the motivation, the determination to do it, to increase back up and beat your previous record?

是的，我在几周内就做到了。这感觉又像在采访运动员，太棒了。我要感谢我的父母。恢复之路漫长而艰难，可能有很多困难，也有黑暗的日子。我想是几周后，然后出现了一个转折点。我想他们改变了测量我大脑神经元尖峰的方式。Bliss，帮我一下？

Yeah, I was within a couple weeks. Again, this feels like I'm interviewing an athlete, this is great. I like to thank my parents. The road back was long and hard, probably many difficulties, there were dark days. It was a couple weeks, I think, and then there was just a turning point. I think they had switched how they were measuring the neuron spikes in my brain. Bliss, help me out?

是的，我们测量单个神经元行为的方式。所以我们从单个尖峰检测切换到了所谓的尖峰频带功率。如果你看过之前我和 DJ 的片段，你可能已经了解了一些内容。

Yeah, the way in which we were measuring the behavior of individual neurons. So we're switching from sort of individual spike detection to something called spike band power. If you watch the previous segments with either me or DJ, you probably have some content.

好的，所以当他们做出改变时，就像灵光一现。就像，“哦，这管用了”，而且看起来我们可以继续推进。我立刻看到了性能的提升。他们切换时我能感觉到。我当时想，“这更好，这很好。之前几周——三四周，因为那是在他们告诉我之前——之前的一切都很糟糕。让我们继续做现在做的。”那时，并不是说，“哦，我知道我现在在网页网格上只有四或五 BPS，而我之前是 7.5。”但我知道如果我们继续这样做，我就能回到那个水平。然后他们给了我悬停光标，一开始悬停光标很糟糕——显然不是我要的——但它给了我一条继续使用它的路，希望能继续帮忙。所以我就这样做了，再也不回头。就像我说的，我本来就是个随遇而安的人。

Okay, so when they did that, it was kind of like a light bulb moment. Like, "Oh, this works," and this seems like we can run with this. And I saw the uptick in performance immediately. I could feel it when they switched over. I was like, "This is better, this is good. Everything up till this point for the last few weeks — three or four weeks, because it was before they even told me — everything before this sucked. Let's keep doing what we're doing now." And at that point, it was not like, "Oh, I know I'm still only at, say, in web grid terms, four or five BPS compared to my 7.5 before." But I know that if we keep doing this, then I can get back there. And then they gave me the dwell cursor, and the dwell cursor sucked at first — it's obviously not what I want — but it gave me a path forward to be able to continue using it and hopefully to continue to help out. And so I just ran with it, never looked back. Like I said, I'm just kind of a person who rolls with the punches anyway.

过程是怎样的？找出一种对 Noah 真正有效的尖峰检测方法的反馈循环是什么样的？

What was the process? What was the feedback loop on figuring out how to do the spike detection in a way that would actually work well for Noah?

好问题。也许先描述一下实际更新是如何工作的：基本上是对你的植入物进行更新。我们只是对他的植入物进行了无线软件更新，就像你更新特斯拉或 iPhone 一样。那个固件改变使我们能够记录某种平均值……

Yeah, it's a great question. So maybe just to describe first how the actual update worked: it basically an update to your implant. So we just did an over-the-air software update to his implant, the way you'd update your Tesla or your iPhone. And that firmware change enabled us to record sort of averages of...

那悬停点击用起来怎么样？你会不会有时候不小心点到东西？避免误点有多难？

So how's the hover click? Do you accidentally click stuff sometimes? Like how hard is it to avoid accidentally clicking?

我基本上得一直让它动。就像我说的，有一个阈值，低于它就会触发点击。所以如果我降到阈值以下，它就会开始计时，我有 3 秒时间移动光标，否则就会点击。如果我不想让它到那个地步，我就保持一定速度移动，比如在屏幕上画圈、来回移动，避免它点击东西。我几周前注意到，没植入设备的时候，我也会下意识地来回或画圈移动手，就像在防止光标点击一样，连睡觉前都这样。我当时就想，好吧，这有点问题。

I have to continuously keep it moving basically. So like I said, there's a threshold where it will initiate a click. So if I ever drop below that, it'll start and I have 3 seconds to move it before it clicks anything. And if I don't want it to ever get there, I just keep it moving at a certain speed and like constantly doing circles on screen, moving it back and forth to keep it from clicking stuff. I actually noticed a couple weeks back that when I was not using the implant, I was just moving my hand back and forth or in circles like I was trying to keep the cursor from clicking, and I was just doing it while I was trying to go to sleep, and I was like, okay, this is a problem.

为了防误点吧。那会不会带来问题，比如玩游戏时不小心点到什么？

To avoid the clicking, I guess. Does that create problems like when you're gaming, accidentally click a thing?

对，下棋时就会。我输过好几盘棋，就是因为不小心点错了。我记得第一次赢你，就是因为一次误点。

Yeah, yeah, it happens in chess. I've lost a number of games because I'll accidentally click something. I think the first time I ever beat you was because of an accidental click.

这借口不错，对吧？每次输了都可以说是不小心的。

It's a nice excuse, right? You can always anytime you lose, you could just say that was accidental.

你说应用从你最初使用的版本一改进很大，变化很大。能聊聊你和团队经历的试错过程吗？200 多页笔记。你们来回协作改进的过程是怎样的？

You said the app improved a lot from version one when you first started using it. It was very different. So can you just talk about the trial and error that you went through with the team? 200 plus pages of notes. Like what's that process like of working back and forth and working together to improve the thing?

主要就是我日复一日地使用，然后跟他们说：嘿，能帮我做这个吗？给我这个。我想能那样做。我需要这个。我觉得很多需求他们可能根本想不到，直到有人真正在用这个应用、用这个植入设备。有些东西他们永远也不会想到，或者非常个人化，比如我自己的偏好。我有点担心后面来的人，他们想要的东西可能和我设置的不一样，或者和我给团队的建议不同。他们看到我提的一些需求可能会想：这什么馊主意，他怎么会要这个？所以我真的很期待下一个人加入，我敢保证他们会想到我从未想过的东西，会提出一些改进，让我觉得：哇，这主意真棒，我怎么没想到。而且他们也会反驳我，比如：你让他们做的这个，其实不好，我们换个方式。我很乐意看到这种情况。但整个过程就是和不同的游戏、应用、互联网、电脑本身的各种交互。到处都会冒出无数 bug。所以我就是尽可能多地使用，告诉他们什么好用、什么不好用、我希望哪里能更好。然后他们接受反馈，通常能为我创造出神奇的东西。他们用我完全想象不到的方式解决问题。他们做什么都特别棒。所以我真的很感激能给他们反馈，他们能从中做出成果，因为我的很多反馈其实很蠢，就是：我想要这个，你们想想办法。然后他们回来时，方案考虑得非常周全，比我想到或能实现的要好得多。他们太棒了，真的非常酷。

It's a lot of me just using it day in and day out and saying like, hey, can you guys do this for me? Give me this. I want to be able to do that. I need this. I think a lot of it just doesn't occur to them maybe until someone is actually using the app, using the implant. It's just something that they never would have thought of, or it's very specific to even like me, maybe what I want. It's something I'm a little worried about with the next people that come, is you know, maybe they will want things much different than how I've set it up or what the advice I've given the team. And they're going to look at some of the things I've asked for and be like, that's a dumb idea, why would he ask for that? And so I'm really looking forward to get the next people on, because I guarantee that they're going to think of things that I've never thought of, and they're going to think of improvements I'm like, wow, that's a really good idea, I wish I would have thought of that. And then they're also going to give me some pushback about like, yeah, what you are asking them to do here, that's a bad idea, let's do it this way. And I'm more than happy to have that happen. But it's just a lot of different interactions with different games or applications, the internet, just with the computer in general. There's tons of bugs that end up popping up left, right, and center. So it's just me trying to use it as much as possible and showing them what works and what doesn't work and what I would like to be better. And then they take that feedback and they usually create amazing things for me. They solve these problems in ways I would have never imagined. They're so good at everything they do. And so I'm just really thankful that I'm able to give them feedback and they can make something of it, because a lot of my feedback is really dumb. It's just like, I want this, please do something about it. And they'll come back and it's super well thought out and it's way better than anything I could have ever thought of or implemented myself. So they're just great, they're really, really cool.

随着 BCI 社区发展，你愿意和其他植入新设备的人交流吗？你希望和他们建立什么样的关系？因为你说过他们可能对如何使用设备有不同想法。你会被他们的网页网格成绩吓到吗？

As the BCI community grows, would you like to hang out with the other folks with new links? Like what relationship, if any, would you want to have with them? Because you said they might have a different set of ideas of how to use the thing. Would you be intimidated by their web grid performance?

不会，我希望他们来竞争。我希望他们第一天就把我打得落花流水。我希望他们超越我，碾压我，甚至翻倍。因为一方面，这只会推动我变得更好，我非常好胜。我希望别人来推动我。我认为这对任何想取得伟大成就的人来说都很重要：身边需要有能推动你变得更好的人。我甚至在 X 上开过玩笑：等下一批人选定，就像 buddy cop 电影配乐一样。我很兴奋能有其他人一起做这件事，分享经验。我非常乐意和他们交流，只要他们愿意，我也很乐意给他们建议。我不知道自己能给什么建议，但如果他们有疑问，我很乐意解答。

No, no, I hope they compete. I hope day one they like wipe the floor with me. I hope they beat it and they crush it, you know, double it if they can. Just because on one hand, it's only going to push me to be better, 'cause I'm super competitive. I want other people to push me. I think that is important for anyone trying to achieve greatness: they need other people around them who are going to push them to be better. And I even made a joke about it on X once: like once the next people get chosen, like buddy cop music. I'm just excited to have other people to do this with and to share experiences with. I'm more than happy to interact with them as much as they want, more than happy to give them advice. I don't know what kind of advice I could give them, but if they have questions, I'm more than happy.

你对临床试验的下一位参与者有什么建议？

What advice would you have for the next participant in the clinical trial?

他们应该享受这个过程，因为这真的很有趣。而且我希望他们非常非常努力，因为这不仅是为了我们自己，也是为了后来的人。如果他们需要什么，可以来找我，也可以去找 Neuralink。Neuralink 能移山倒海。他们尽一切可能为我做任何事，这是一个了不起的支持系统。它让我在很多问题上、很多想做的事情上感到安心。他们一直都在，这真的非常好。所以我会告诉他们，不要害怕带着任何问题、任何顾虑、任何想用这个设备做的事情去找 Neuralink，只要 Neuralink 能提供帮助，我知道他们一定会。还有，就是拼命干吧，因为……

That they should have fun with this, because it is a lot of fun. And that I hope they work really, really hard, because it's not just for us, it's for everyone that comes after us. And you know, come to me if they need anything, and go to Neuralink if they need anything. Man, Neuralink moves mountains. They do absolutely anything for me that they can, and it's an amazing support system to have. It puts my mind at ease for so many things that I have had questions about, so many things I want to do. And they're always there, and that's really, really nice. And so I just, I would tell them not to be afraid to go to Neuralink with any questions that they have, any concerns, anything that they're looking to do with this, and any help that Neuralink is capable of providing, I know they will. And I don't know, just work your ass off, because it's it's...

也许可以聊聊你现在有了 Neuralink 植入物后能做什么，比如这种与外界互动方式带来的自由。你整晚自己玩电子游戏，那是一种自由。你能谈谈那种自由吗？

Maybe it's good to talk about what you have been able to do now that you have a Neuralink implant, like the freedom you gain from this way of interacting with the outside world. You play video games all night and you do that by yourself. That's a kind of freedom. Can you speak to that freedom that you gain?

是的，这就是我想要的。像我这样处境的人，只想要更多的独立性。我能减轻身边人多少负担，就越好。如果我能不通过家人或朋友、不需要他们帮忙就能与世界互动，那就更好。如果我能整晚坐在电脑前，不需要别人扶我起来，比如把 iPad 放在我能用的位置，然后让他们整晚等我用完，那就能减轻我们所有人的负担。这是我唯一能要求的。我永远感激 Neuralink，我知道我的家人也这么想。能够随时独立做事情，这对我来说意味着一切。

Yeah, it's all I want. People in my position, they just want more independence. The more load I can take away from people around me, the better. If I'm able to interact with the world without using my family, without going through any of my friends, needing them to help me with things, the better. If I'm able to sit up on my computer all night and not need someone to sit me up, say on my iPad in a position where I can use it, and then have to have them wait up for me all night until I'm ready to be done using it, that takes a load off of all of us. It's really all I can ask for. It's something I could never thank Neuralink enough for, and I know my family feels the same way. Just being able to have the freedom to do things on my own at any hour of the day or night means the world to me.

当你凌晨 2 点独自玩 Webgrid 时，我想象四周一片漆黑，只有屏幕发光，你全神贯注。你脑子里在想什么？还是处于心流状态，大脑放空，像那些禅宗大师一样？

When you're up at 2 a.m. playing Webgrid by yourself, I imagine it's darkness and there's just a light glowing and you're focused. What's going through your mind? Or are you in a state of flow where the mind is empty, like those Zen masters?

通常我会放音乐。我有一个巨大的播放列表，所以我就是跟着音乐摇摆。同时这也像一场与时间的赛跑，因为我一直在看植入物还剩多少电量。比如，好，我还有 30%，相当于 X 时间，这意味着我必须在接下来一个半小时内打破纪录，否则今晚就没戏了。所以那有点压力。当电量高于 50% 时，我想，好吧，我还有时间。当降到 30% 然后 20% 时，我就想，好吧。10% 时，一个小弹窗会出现在这里，真的会打乱我的 Webgrid 节奏。它会告诉我低电量弹窗出现了，我就想，这真的会搞砸我。所以如果我要打破纪录，我必须在接下来 30 秒内完成，否则那个弹窗会挡住我的 Webgrid。然后我点击它，回到 Webgrid，我想，好吧，这意味着我还有 10 分钟这东西就没电了。这就是我脑子里通常在想的东西，还有正在播放的歌曲。我就是想打破那些纪录，太想了。玩 Webgrid 时我唯一想要的就是这个。它已经不再是那种“哦，这只是个悠闲的活动，我享受它因为它感觉很好，让我放松”的状态。不，一旦我进入 Webgrid，你最好打破这个纪录，否则你就是在浪费人生中的 5 个小时。我不知道，就是很有趣，伙计。

Generally, it is me playing music of some sort. I have a massive playlist, so I'm just rocking out to music. And then it's also just like a race against time, because I'm constantly looking at how much battery percentage I have left on my implant. Like, all right, I have 30%, which equates to X amount of time, which means I have to break this record in the next hour and a half or else it's not happening tonight. So it's a little stressful when that happens. When it's above 50%, I'm like, okay, I got time. It starts getting down to 30 and then 20, it's like, all right. 10%, a little pop-up is going to pop up right here and it's going to really screw my Webgrid flow. It's going to tell me that the low battery pop-up comes up, and I'm like, it's really going to screw me over. So if I'm going to break this record, I have to do it in the next like 30 seconds or else that pop-up is going to get in the way, cover my Webgrid. Then after that, I go click on it, go back into Webgrid, and I'm like, all right, that means I have 10 minutes left before this thing's dead. That's what's going on in my head generally, that and whatever song is playing. And I just want to break those records so bad. It's all I want when I'm playing Webgrid. It has become less of like, oh, this is just a leisurely activity that I enjoy doing because it feels so nice and puts me at ease. No, once I'm in Webgrid, you better break this record or you're going to waste like 5 hours of your life right now. And I don't know, it's just fun, man.

你试过用两个或三个目标玩 Webgrid 吗？那样能获得更高的 BPS 吗？你能做到吗？

Have you ever tried Webgrid with two targets and three targets? Can you get higher BPS with that? Can you do that?

你是说不同颜色的目标？多个目标？那会改变什么吗？是的，BPS 是目标数量乘以正确减去错误再除以时间的对数。所以你可以把不同的点击看作基本上使活跃目标数量翻倍。明白了。所以基本上，选项越多，BPS 越高，任务越难。还有你之前玩过的禅模式，那是无限的，它用网格覆盖整个屏幕。我不知道还有什么。是的，所以你可以说那太疯狂了。他不喜欢它，因为它不显示 BPS。所以我让他们在背景里放了一个巨大的 BPS 数字。现在它就像禅模式的反面，是超级困难模式，比如金属模式。背景里就一个巨大的数字。我们应该叫它金属模式，那名字好多了。

You mean like different color targets? Multiple targets? Does that change the thing? Yeah, so BPS is a log of number of targets times correct minus incorrect divided by time. So you can think of different clicks as basically doubling the number of active targets. Got it. So you know, basically higher BPS, the more options there are, the more difficult the task. And there's also like Zen mode you've played in before, which is like infinite, it covers the whole screen with a grid. And I don't know what else. Yeah, and so you can go like that's insane. Yeah, he doesn't like it because it didn't show BPS. So I had them put in a giant BPS in the background. So now it's like the opposite of Zen mode, it's like super hard mode, like metal mode. It's just like a giant number in the back. We should name that metal mode, it's a much better name.

你还玩《文明 6》。

You also play Civilization 6.

我超爱《文明 6》。是的，通常选韩国。我确实选。韩国很棒的一点是他们专注于科技胜利，这不是计划好的。我玩韩国好几年了，然后 Neuralink 的事情发生了，所以有点契合。但我注意到科技胜利的关键是，如果你能快速推进科技，快速推进科学，那你就能做任何事。在游戏某个时刻，你在科技上会远远领先所有人，你会有火枪手、步兵、有时还有飞机，而别人还在用弓箭战斗。所以如果你想赢得征服胜利，你只需要把科学推进到某个点，然后去消灭世界其他地方。或者你可以一路走科学路线，以那种方式获胜，你会远远领先所有人，因为你产生的科学太多了，差距巨大。我甚至因为专注科学而意外地以其他方式赢过。我显然只玩科学，一路只搞科学，只搞科技，我试图解锁科技树上的每一个科技，然后意外地通过外交胜利赢了。我气坏了。它就在一回合结束了游戏。就像，哦，你赢了，你太外交了。我就想，我不想这样。我应该对更多人宣战之类的。太糟糕了。但有了科技，你不需要庞大的文明，尤其是韩国。你可以保持很小。所以我通常只发展到某个军事单位，然后把它们放在边境周围，把所有人都挡在外面，然后我就只管发展。非常孤立主义。不错，只专注于科学和科技。就这样。

I love Civ 6. Yeah, usually go with Korea. I do. Yeah, so the great part about Korea is they focus on science tech victories, which was not planned. I've been playing Korea for years, and then all of the Neuralink stuff happened, so it kind of aligns. But what I've noticed with tech victories is if you can just rush tech, rush science, then you can do anything. At one point in the game, you will be so far ahead of everyone technologically that you will have like musket men, infantrymen, planes sometimes, and people will still be fighting with like bows and arrows. So if you want to win a domination victory, you just get to a certain point with the science and then go and wipe out the rest of the world. Or you can just take science all the way and win that way, and you're going to be so far ahead of everyone because you're producing so much science that it's not even close. I've accidentally won in different ways just by focusing on science. I was playing only science, obviously, just science all the way, just tech, and I was trying to get like every tech in the tech tree and stuff, and then I accidentally won through a diplomatic victory. I was so mad. It just ends the game one turn. It was like, oh, you won, you're so diplomatic. I'm like, I don't want to do this. I should have declared war on more people or something. It was terrible. But you don't need like giant civilizations with tech, especially with Korea. You can keep it pretty small. So I generally just get to a certain military unit and put them all around my border to keep everyone out, and then I will just build up. Very isolationist. Nice, just work on the science and the tech. That's it.

你说得听起来好有趣。太有趣了。我还看到了《文明 7》的预告片。天哪，我太兴奋了。那可能就要出了。来吧，《文明 7》，联系我。我什么都能 alpha beta 测试。等等，它什么时候出？

You're making it sound so fun. It's so much fun. And I also saw a Civilization 7 trailer. Oh man, I'm so pumped. And that's probably coming out. Come on, Civ 7, hit me up. I'll alpha beta test whatever. Wait, when does it come out?

是的，明年。

Yeah, next year.

你还希望 Link 应用和整个体验有哪些改进？

What other stuff would you like to see improved about your Link app and just the entire experience?

我想恢复按需点击，就像常规点击那样。那太好了。我希望能够连接到更多设备。现在只能连电脑。我想在手机上用，或者在不同的游戏机、不同平台上用。我希望能够……

I would like to get back to the click on demand, like the regular clicks. That would be great. I would like to be able to connect to more devices. Right now it's just the computer. I'd like to be able to use it on my phone or use it on different consoles, different platforms. I'd like to be able to...

老实说，我想尽可能多地控制东西。比如能控制一个 Optimus 机器人就太酷了，那会非常棒。Link 应用本身，我们似乎已经逐渐明确了它未来的样子。至少我已经得到了很多我想要的功能。我唯一还想说的是，希望能更多地控制所有那些我可以用光标调整的参数。有很多因素会影响光标的移动方式，我现在有大约三四个参数，比如增益和摩擦。可能还有两倍数量的参数涉及速度和驻留光标。所以我想要全部的控制权。我希望尽可能多地控制我的环境。尤其是你想要一个高级模式，就像菜单里通常有基础模式，而你是那种高级用户。没错，那就是我想要的。我希望对这个系统有尽可能多的控制。所以这就是我全部的要求：把一切都给我。

Control as much stuff as possible honestly. Like an Optimus robot would be pretty cool. That would be sick if I could control an Optimus robot. The Link app itself, it seems like we are getting pretty dialed in to what it might look like down the road. Seems like we've gotten through a lot of what I want from it, at least. The only other thing I would say is like more control over all the parameters that I can tweak with my cursor and stuff. There's a lot of things that go into how the cursor moves in certain ways, and I have like three or four of those parameters: gain and friction. And there's maybe double the amount of those with velocity and then with the actual dwell cursor. So I would like all of it. I want as much control over my environment as possible. Especially you want like advanced mode, like in menus there's usually basic mode and you're one of those folks like the power user. Yeah, that's what I want. I want as much control over this as possible. So that's really all I can ask for: just give me everything.

语音功能有用吗？就是在其他所有功能之外还能说话？

Has speech been useful? Like just being able to talk also in addition to everything else?

是的，你是说在我使用的时候？语音转文字？哦对。或者你打字？因为还有一个键盘。有一个虚拟键盘。这是另一个我想进一步改进的地方：找到一种不同的打字或输入方式。目前基本上是听写和一个可以用光标操作的虚拟键盘。但我们尝试过手指拼写，比如手语的手指拼写，这看起来很有前景。我脑子里有个想法，它会和光标的学习曲线非常相似——我从尝试移动过渡到了想象移动。我有一种直觉，总有一天我会进行手指拼写，而不再需要实际尝试去拼写。我只需要想一下我想要的字母，它就会弹出来。那将非常棒。这很有挑战性，你需要付出很多努力才能实现这个飞跃，但那会很棒。然后从字母到单词是另一步。现在只是手语字母的手指拼写，但如果它能识别这个，那么它应该能识别整个手语语言。所以如果我能沿着这个方向做点什么，或者只是手语拼写的单词，如果我能以合理的速度拼写并且它能识别，那么我就能直接通过思考来完成同样的事情。在见识了光标控制之后，我看不出为什么不行。我看不出它为什么行不通，但我们需要进一步尝试。

Yeah, you mean like while I'm using it? Speech to text? Oh yeah. Or do you type? Because there's also a keyboard. There's a virtual keyboard. That's another thing I would like to work more on: finding some way to type or text in a different way. Right now it is dictation basically and a virtual keyboard that I can use with the cursor. But we've played around with finger spelling, like sign language finger spelling, and that seems really promising. So I have this thought in my head that it's going to be a very similar learning curve that I had with the cursor, where I went from attempted movement to imagined movement. At one point I have a feeling, this is just my intuition, that at some point I'm going to be doing finger spelling and I won't need to actually attempt to finger spell anymore. That I'll just be able to think the letter that I want and it'll pop up. That would be epic. That's challenging, that's a lot of work for you to take that leap, but that would be awesome. And then going from letters to words is another step. Right now it's finger spelling of just the sign language alphabet, but if it's able to pick that up, then it should be able to pick up the whole sign language language. So if I could do something along those lines, or just the sign language spelled word, if I can spell it at a reasonable speed and it can pick that up, then I would just be able to think that through and it would do the same thing. I don't see why not after what I saw with the cursor control. I don't see why it wouldn't work, but we'd have to play around with it more.

你训练自己从尝试移动过渡到想象移动的过程是怎样的？花了多长时间？那么这种过程需要多久？

What was the process in terms of training yourself to go from attempted movement to imagined movement? How long did that take? So how long would this kind of process take?

嗯，大概过了几周它就自然而然地发生了。但现在我知道这是可能的，我想我可以用在其他事情上。我觉得会简单得多。

Well, it was a couple weeks before it just happened upon me. But now that I know that was possible, I think I could make it happen with other things. I think it would be much, much simpler.

你会升级植入设备吗？

Would you get an upgraded implant device?

当然，绝对会，只要他们允许。所以你没有任何顾虑？对你来说，手术、你的经历，一切都无怨无悔？没有，到目前为止一切都很好。你只是不断升级。是啊，为什么不呢？我已经看到它对我的生活产生了多大的影响，而且我知道从现在开始一切只会越来越好。所以我很乐意升级。

Sure, absolutely, whenever they'll let me. So you don't have any concerns? For you, the surgery, your experience, all of it was no regrets? No, everything's been good so far. You just keep getting upgrades. Yeah, I mean why not? I've seen how much it's impacted my life already, and I know that everything from here on out is just going to get better and better. So I would love to get the upgrade.

你对哪些未来功能感到兴奋？超出这种心灵感应之外的？

What future capabilities are you excited about? Sort of beyond this kind of telepathy?

视觉很有趣。比如对于盲人，让他们能够看见，或者用于语言。是的，这方面有很多很酷的东西。我们在谈论大脑，而这只是运动皮层的东西。还有更多可以做的。视觉功能让我着迷。我认为让一个人有生以来第一次获得视力将非常非常酷。这可能比帮助像我这样的人更令人惊叹。那听起来简直不可思议。语言功能也很有趣：能够进行某种实时翻译并消除语言障碍会很酷。任何它能解决的实际障碍，比如语言障碍，都会非常非常酷。此外，还有很多不同的残疾都源于大脑，你有可能解决其中很多问题。我知道已经有植入大脑的设备可以帮助癫痫患者。我想这个也能做同样的事情。所以你可以做类似的事情。我知道甚至像 Joe Rogan 这样的人也谈论过用不同方式刺激大脑的可能性。我不确定其中很多做法有多符合伦理，老实说这超出了我的理解范围。但我知道，当我们谈论大脑，能够进入并物理性地做出改变来帮助人们或改善他们的生活时，有很多事情可以做。所以我非常期待这一切的到来，而且我认为这并不遥远。我觉得很多功能都能在我有生之年实现，假设我能活得很长的话。

Vision is interesting. So for folks who are blind, enabling people to see, or for speech. Yeah, there's a lot that's very cool about this. I mean we're talking about the brain, so this is just motor cortex stuff. There's so much more that can be done. The vision one is fascinating to me. I think that is going to be very, very cool to give someone the ability to see for the first time in their life. That might be more amazing than even helping someone like me. That just sounds incredible. The speech thing is really interesting: being able to have some sort of real-time translation and cut away that language barrier would be really cool. Any sort of actual impairment that it could solve, like with speech, would be very, very cool. And then also there are a lot of different disabilities that all originate in the brain, and you would be able to hopefully solve a lot of those. I know there's already stuff to help people with seizures that can be implanted in the brain. This would do, I imagine, the same thing. So you could do something like that. I know that even someone like Joe Rogan has talked about the possibilities with being able to stimulate the brain in different ways. I'm not sure how ethical a lot of that would be, that's beyond me honestly. But I know that there is a lot that can be done when we're talking about the brain and being able to go in and physically make changes to help people or to improve their lives. So I'm really looking forward to everything that comes from this, and I don't think it's all that far off. I think a lot of this can be implemented within my lifetime, assuming that I live a long life.

你指的是像抑郁症患者或类似情况的人可能得到帮助？是的，像拨动开关一样让人快乐。我知道 Joe 更多是从这个角度谈论的：你想体验迷幻之旅的感觉，比如你想体验服用蘑菇或类似东西的感觉，比如 DMT。就像你可以直接在大脑中拨动那个开关。我的朋友 Bane 谈到过能够抹去部分记忆，然后重新第一次体验事物，比如你最喜欢的电影或最喜欢的书。快速抹掉它，然后重新爱上《哈利·波特》之类的。我告诉他，我不知道怎么看待人们能够随意抹去部分记忆这件事。这对我来说有点可疑。他说他们已经在这么做了，所以听起来挺靠谱的。我很喜欢记忆回放，就是那种高分辨率回放所有记忆。是的，我看过一集《黑镜》讲这个。我不觉得我想要。是啊，《黑镜》总是考虑最坏的情况，这很重要。我觉得人们没有足够考虑最好的情况或一般的情况。我不知道我们人类是怎么回事。

What you were referring to is things like people suffering from depression or things of that nature potentially getting help? Yeah, flip a switch like that make someone happy. I know Joe has talked about it more in terms of like you want to experience what a drug trip feels like, like you want to experience what it's like to be on mushrooms or something like that, DMT. Like you can just flip that switch in the brain. My buddy Bane has talked about being able to wipe parts of your memory and re-experience things for the first time, like your favorite movie or your favorite book. Just wipe that out real quick and then refall in love with Harry Potter or something. I told him I was like I don't know how I feel about people being able to just wipe parts of your memory. That seems a little sketchy to me. He's like they're already doing it, so sounds legit. I would love memory replay, just like actually high resolution replay of all memories. Yeah, I saw an episode of Black Mirror about that once. I don't think I want it. Yeah, so Black Mirror always kind of considered the worst case, which is important. I think people don't consider the best case or the average case enough. I don't know what it is about us humans.

人们总爱想最坏的情况。我们喜欢戏剧性。比如，这项新技术会怎么害死所有人？我们就爱这个。对，来看吧。希望人们别对我太这么想，那会毁了我很多计划。

Want to think about the worst possible thing. We love drama. It's like, how is this new technology going to kill everybody? We just love that. Like, yes, let's watch. Hopefully people don't think about that too much with me. It'll ruin a lot of my plans.

是啊，是啊。我猜你得接管世界了。我是说，你……我喜欢你的推特。你发过：“自从植入 Neuralink，我想开个关于听到脑子里有声音的玩笑，但感觉人们会误解。而且我脑子里的声音告诉我别开。”对对对。请永远别停。

Yeah, yeah. I assume you're going to have to take over the world. I mean, you're... I love your Twitter. You tweeted: 'I'd like to make jokes about hearing voices in my head since getting the Neuralink, but I feel like people would take it the wrong way. Plus the voices in my head told me not to.' Yeah, yeah, yeah. Please never stop.

那你刚才说到 Optimus。你希望能控制机械臂，还是整个 Optimus？

So you're talking about Optimus. Is that something you would love to be able to do, to control the robotic arm or the entirety of Optimus?

哦，当然，当然，绝对。

Oh yeah, for sure, for sure, absolutely.

你觉得能跟世界进行物理交互，这件事本身就有本质上的不同吗？

You think there's something fundamentally different about just being able to physically interact with the world?

哦，100%。嗯，这个……我还知道另一件事，就是通过植入大脑、让 Neuralink 做到这一点，从而赋予人们感受触觉等能力。这也可以被转化、传递到 Optimus 上。两者之间有很多很酷的互动。而且，就像你说的，仅仅是物理交互。我是说，我自己做不到的 99% 的事情，显然需要护工来帮我做。如果 Optimus 机器人能做到，我就能过上极其独立的生活，不再那么拖累身边的人。那会改变像我这样的人的生活，至少直到这个病被治好。但能这样物理地与世界互动，真是太棒了。而且不只是作为护工，还有像我说过的：能读一本书。想象一下，Optimus 机器人能把一本书打开在我面前，再次闻到那种味道。那时我可能还是感觉不到，或者也许通过触觉功能又能感觉到了。但读纸质书和盯着屏幕或听有声书是不一样的。我其实不喜欢有声书。我听过很多了，但真的不喜欢。我更愿意读纸质书。

Oh, 100%. Um, this... I know another thing with being able to give people the ability to feel sensation and stuff too, by going in with the brain and having the Neuralink maybe do that. That could be something that could be translated through, transferred through the Optimus as well. Like, there's all sorts of really cool interplay between that. And then also, like you said, just physically interacting. I mean, 99% of the things that I can't do myself, obviously I need a caretaker for someone to physically do things for me. If an Optimus robot could do that, like I could live an incredibly independent life and not be such a burden on those around me. And that would change the way people like me live, at least until whatever this is gets cured. But being able to interact with the world physically like that would just be amazing. And not just for having it be a caretaker or something, but something like I talked about: just being able to read a book. Imagine an Optimus robot just being able to hold a book open in front of me, get that smell again. I might not be able to feel it at that point, or maybe I could again with the sensation and stuff. But there's something different about reading a physical book than staring at a screen or listening to an audiobook. I actually don't like audiobooks. I've listened to a ton of them at this point, but I don't really like them. I would much rather read a physical copy.

所以你很想体验的一件事是打开书，拿到面前，感受纸张的触感。

So one of the things you would love to be able to experience is opening the book, bringing it up to you, and to feel the touch of the paper.

是啊，哦天哪，触感，气味。我就是觉得，纸上的文字有种特别的东西。你知道，Kindle 之类也复制了那种纸张颜色，但就是不一样。就这么简单的一件事。

Yeah, oh man, the touch, the smell. I mean, it's just something about the words on the page. And you know, they've replicated that page color on the Kindle and stuff, but it's just not the same. So just something as simple as that.

所以你怀念的一件事是触觉。

So one of the things you miss is touch.

是的，我确实怀念。世界上我接触的很多东西，比如衣服，或者任何我实际接触的物理物品，很多时候我身边的人会拿过来在我脸上蹭，或者放在我身上让我感受重量。他们会拿衬衫在我身上蹭，让我感受布料。触觉有一种很深刻的东西，我非常怀念。我很想再次体验，但走着瞧吧。

I do, yeah. A lot of things that I interact with in the world, like clothes or literally any physical thing that I interact with in the world, a lot of times what people around me will do is they'll just come rub it on my face, they'll lay something on me so I can feel the weight. They will rub a shirt on me so I can feel fabric. Like, there's something very profound about touch, and it's something that I miss a lot. And something I would love to do again, but we'll see.

如果你有了一只能触摸的手，第一件事会做什么？

What would be the first thing you do with a hand that can touch?

给你妈妈一个拥抱。之后呢？对吧？是啊，是啊。我知道自从我出事以来，我几乎每天都在向上帝祈求一件事：有一天能活动，哪怕只是我的手，这样我就能握握妈妈的手，让她知道我有多在乎她、多爱她。所以顺着这个思路，能跟周围的人互动：握手、拥抱。我不知道，任何这类事情。能自己吃饭——我可能会变得很胖，那会是件非常糟糕的事。还有在实体棋盘上赢 Bliss 一盘国际象棋。是啊，是啊。我是说，好处太多了。只要能想办法把 Bliss 拉低到我的水平。因为他真的太棒了，他的一切都那么超凡脱俗。只要能让他降点格，我就很高兴。

Give your mom a hug. After that, right? Yeah, yeah. I know it's one thing that I've asked God for basically every day since my accident: just being able to one day move, even if it was only like my hand, so that way I could squeeze my mom's hand or something, just to show her how much I care and how much I love her and everything. So along those lines, being able to just interact with the people around me: handshake, give someone a hug. I don't know, anything like that. Being able to help me eat — I'd probably get really fat, which would be a terrible, terrible thing. Also beat Bliss in chess on a physical chess board. Yeah, yeah. I mean, there are just so many upsides. And any way to find some way to feel like I'm bringing Bliss down to my level. Because yeah, he's just such an amazing guy, and everything about him is just so above and beyond. Anything I can do to take him down a notch, I'm happy.

是啊，让他谦虚点。他需要。好，他就坐在我旁边。你有没有想通过，为什么上帝让好人经历这样的苦难？

Yeah, humble him a bit. He needs it. Okay, as he's sitting next to me. Did you ever make sense of why God puts good people through such hardship?

哦天哪。我认为这完全关乎我们有多需要上帝。我认为没有黑暗就没有光明。如果我们所有人都一直快乐，就永远没有理由去寻求上帝。我觉得那就没有好坏的概念了。而且我认为，尽管世界上有黑暗和邪恶，但它们让我们更加珍惜美好和拥有的一切。而且，你知道，我出事的时候，我对我最好的朋友说的第一件事——就在出事后的头一两个月——我说：“你知道，这场事故的一切让我理解和相信上帝是真实的，真的有一位上帝，我和他的交流都是真实而有意义的。”而他说：“恰恰相反，看到你经历这场事故，他相信没有上帝。”这是非常不同的反应。但我相信这是上帝考验我们、塑造我们品格的方式，让我们经历试炼和磨难，确保我们明白他有多宝贵，他赐予我们的一切以及给予我们的时间有多宝贵，然后希望我们能从中成长。我认为这是我们存在的一大部分意义：不是过轻松的生活、做容易的事，而是走出舒适区，真正挑战自己，因为我认为这才是我们成长的方式。

Oh man. I think it's all about understanding how much we need God. And I don't think that there's any light without the dark. I think that if all of us were happy all the time, there would be no reason to turn to God ever. I feel like there would be no concept of good or bad. And I think that as much as the darkness and the evil that's in the world, it makes us all appreciate the good and the things we have so much more. And I think, you know, when I had my accident, one of the first things I said to one of my best friends — and this was within like the first month or two after my accident — I said, 'You know, everything about this accident has just made me understand and believe that God is real, and that there really is a God basically, and that my interactions with him have all been real and worthwhile.' And he said, 'If anything, seeing me go through this accident, he believes that there isn't a God.' It's a very different reaction. But I believe that it is a way for God to test us, to build our character, to send us through trials and tribulations to make sure that we understand how precious he is and the things that he's given us and the time that he's given us, and then to hopefully grow from all of that. I think that's a huge part of being here: not to just have an easy life and do everything that's easy, but to step out of our comfort zones and really challenge ourselves, because I think that's how we grow.

关于我们正在进行的这一切，什么给了你希望？文明？

What gives you hope about this whole thing we have going on? Civilization?

哦天哪。我认为人是我最大的灵感来源。哪怕只是在 Neuralink 待了几个月，看着人们的眼睛，听他们讲述为什么做这件事——这太鼓舞人心了。我知道他们可以去别的地方，做更轻松的工作，在别处做 XYZ 那些没什么意义的事。但他们在这里，他们想改善人类，想改善身边的人，改善他们生命中接触过的人。他们想为自己可能有残疾的家人创造更好的生活，或者他们看到像我这样的人，就说：“我能为此做点什么，所以我要去做。”而人一直是我在这个世界上连接最深的东西。我一直是个热爱与人打交道的人，我喜欢了解人。

Oh man. I think people are my biggest inspiration. Even just being at Neuralink for a few months, looking people in the eyes and hearing their motivations for why they're doing this — it's so inspiring. And I know that they could be other places, at cushier jobs, working somewhere else doing X Y Z that doesn't really mean that much. But instead, they're here and they want to better humanity, and they want to better just the people around them, the people that they've interacted with in their life. They want to make better lives for their own family members who might have disabilities, or they look at someone like me and they say, 'You know, I can do something about that, so I'm going to.' And it's always been what I've connected with most in the world: people. I've always been a people person, and I love learning about people.

我喜欢了解人们如何发展以及他们来自哪里。看到人们愿意为像我这样的人付出多少，即使他们不必这样做，他们不辞辛劳地让我的生活变得更好，这让我对整个人类充满了希望。这显示了我们在乎多少，以及当我们齐心协力做出改变时，我们有多大的能力。我知道世界上有很多不好的事情，但过去一直有，将来也还会有。这显示了人类的韧性，我们能够承受什么，以及我们多么希望在那里互相帮助，并从中获得多大的满足感。我认为这是我们在这里的原因之一：就是互相帮助。意识到还有人在乎并愿意帮助，这总是给我希望。

I love learning about how people developed and where they came from. Seeing how much people are willing to do for someone like me when they don't have to, going out of their way to make my life better, gives me a lot of hope for humanity in general. It shows how much we care and how much we're capable of when we all come together to make a difference. I know there's a lot of bad in the world, but there always has been and always will be. That shows human resiliency, what we're able to endure, and how much we want to be there and help each other, and how much satisfaction we get from that. I think that's one of the reasons we're here: just to help each other. Realizing that there are people out there who still care and want to help always gives me hope.

感谢你成为这样一个人类，在经历一切后仍然是一个伟大的人，并且激励了许多人，包括我自己，原因有很多，包括你在 Web Grid 上史诗般、难以置信的出色表现。我今晚会整夜训练，试图赶上你。

Thank you for being one such human being, continuing to be a great human being through everything you've been through, and being an inspiration to many people, to myself for many reasons, including your epic, unbelievably great performance on Web Grid. I will be training all night tonight to try to catch up.

你能做到的。我相信你。等你从奥斯汀之行回来后，你最终能打败 Bliss。

You can do it. I believe in you. Once you come back from the Austin trip, you can eventually beat Bliss.

是的，当然。绝对。我为你加油。全世界都在为你加油。谢谢你做的一切，伙计。

Yeah, for sure. Absolutely. I'm rooting for you. The whole world is rooting for you. Thank you for everything you've done, man.

谢谢，伙计。感谢你收听这段与 Nolan Arbaugh 的对话，以及之前与 Elon Musk、DJ Saw、Matthew MacDougall 和 Bliss Chapman 的对话。要支持本播客，请查看描述中的赞助商。现在，让我用 Aldous Huxley 在《知觉之门》中的话作为结尾：“我们生活在一起，彼此作用与反作用；但无论何时何地，我们始终是孤独的。殉道者们手拉手走进竞技场；他们被分别钉在十字架上。拥抱中，恋人们拼命试图将彼此隔绝的狂喜融合成一个单一的自我超越；但徒劳无功。就其本质而言，每一个具身的灵魂都注定要承受并享受其孤独。感觉、情感、洞察、幻想——所有这些都属于私密，除非通过符号和间接的方式，否则无法交流。我们可以汇集关于经验的信息，但永远无法汇集经验本身。从家庭到国家，每一个人群都是一个孤岛宇宙的社会。”感谢收听，希望下次再见。

Thanks, man. Thanks for listening to this conversation with Nolan Arbaugh, and before that with Elon Musk, DJ Saw, Matthew MacDougall, and Bliss Chapman. To support this podcast, please check out our sponsors in the description. And now, let me leave you with some words from Aldous Huxley in The Doors of Perception: 'We live together, we act on and react to one another; but always and in all circumstances we are by ourselves. The martyrs go hand in hand into the arena; they are crucified alone. Embraced, the lovers desperately try to fuse their insulated ecstasies into a single self-transcendence; in vain. By its very nature, every embodied spirit is doomed to suffer and enjoy its solitude. Sensations, feelings, insights, fancies—all these are private and, except through symbols and at second hand, incommunicable. We can pool information about experiences, but never the experiences themselves. From family to nation, every human group is a society of island universes.' Thank you for listening, and hope to see you next time.