马克·扎克伯格谈柔术、恐惧与学习

所以你参加了你的第一场柔术比赛。作为同样练习和比赛柔术的人，我觉得这非常鼓舞人心，考虑到你手头有那么多事情。所以我必须问，那是什么样的体验？

So you competed in your first Jiu-Jitsu tournament. As a fellow Jiu-Jitsu practitioner and competitor, I think that's really inspiring given all the things you have going on. So I gotta ask, what was that experience like?

哦，很有趣。我是一个很有竞争心的人。做那些需要你全神贯注的运动，对我的心理健康以及我保持专注的方式非常重要。我决定开始练武术，这太棒了。我拉了很多朋友一起练，我们都一起训练。我的车库里有一个小型道场。一个朋友说：“嘿，我们应该去参加个比赛。”我说：“好，走吧。”我不会回避这样的挑战。所以，是的，很棒，非常有趣。

Oh, it was fun. I'm a pretty competitive person. Doing sports that basically require your full attention is really important to my mental health and the way I stay focused on everything I'm doing. I decided to get into martial arts, and it's awesome. I got a ton of my friends into it; we all train together. We have a mini Academy in my garage. One of my friends was like, 'Hey, we should go do a tournament.' I said, 'Okay, yeah, let's do it.' I'm not gonna shy away from a challenge like that. So yeah, it was awesome, just a lot of fun.

你不害怕吗？没有恐惧？

You weren't scared? There was no fear?

我不知道。我很确定我会表现不错。我喜欢这种自信。

I don't know. I was pretty sure that I'd do okay. I like the confidence.

嗯，对于不了解的人来说，柔术是一种试图折断对手四肢或将其勒晕的武术，而且要优雅、高效地做到。这是一种可以终身练习的艺术形式。它基本上是一种游戏，一种人类象棋的运动。有很多策略，利用杠杆的有趣人际动态。你能做到的事情令人难以置信——一个小个子对手可以击败一个大个子对手。但你绝对不能分心。

Well, for people who don't know, Jiu-Jitsu is a martial art where you're trying to break your opponent's limbs or choke them to sleep, and do so with grace, elegance, and efficiency. It's a kind of art form that you can do for your whole life. It's basically a game, a sport of human chess. There's a lot of strategy, interesting human dynamics of using leverage. It's incredible what you can do—a small opponent can defeat a much larger opponent. But you certainly can't be distracted.

不，这是一项需要 100% 专注的竞技运动。我需要避免这件事闹得太大。所以我基本上戴着帽子和太阳镜，戴着口罩出现，用我的名字和中间名注册——Mark Elliot。直到我上场前摘下所有东西，人们才知道是我。所以相当低调。

No, it's a 100% focus sport to compete. I needed to get around the fact that I didn't want it to be this big thing. So I basically rolled up with a hat and sunglasses, wearing a COVID mask, and registered under my first and middle name—Mark Elliot. It wasn't until I pulled all that stuff off right before I got on the mat that people knew it was me. So it was pretty low-key.

但你仍然是公众人物。你部分害怕的不仅仅是输，而是几乎感到尴尬。这项运动如此原始——只有你和另一个人。有一种原始的一面。

But you're still a public figure. The thing you're partially afraid of is not just losing, but being almost embarrassed. It's so raw in the sport—it's just you and another human being. There's a primal aspect there.

哦，是的，这很棒。对很多人来说，这可能很可怕，尤其是第一次比赛。但我认为学习的一部分就是失败。练柔术的人不能有自尊心。所有那些关于被勒颈或关节锁的事情——如果你不愿意在已经输了的时候认输，你只会陷入糟糕的境地。但当你刚开始做某件事时，你不会立刻成为专家，所以你需要愿意接受这一点。也许我一生中已经尴尬过太多次了。我确实认为，随着人们长大，他们可能不想再尴尬了。他们建立了成年身份，对自己是谁以及想展现什么有了认知。在某种程度上，你持续做有趣事情的能力，取决于你愿意再次尴尬、回到第一步、从初学者开始、被痛扁、做事情看起来很蠢。我们做的很多事情——无论是生活中的这个身体部分，还是经营公司——我们只是接受新的冒险。我们做的所有大事，我都视为十年以上的使命。通常早期人们怀疑我们能否做到，初期工作看起来有点傻。我们的整个理念是，我们不想等到某件事完美才推出；我们想快速推出并获得反馈。所以这可能是我处理事情的方式。我只是觉得，当你决定因为太尴尬而不再尝试新事物时，你就再也学不到任何东西了。

Oh yeah, it's great. For a lot of people it can be terrifying, especially the first time competing. But I think part of learning is failing. People who train Jiu-Jitsu need to not have pride. All that stuff about getting choked or joint locks—you only get into a bad situation if you're not willing to tap once you've already lost. But when you're getting started with something, you're not going to be an expert immediately, so you just need to be willing to go with that. Maybe I've just been embarrassed enough times in my life. I do think there's a thing where as people grow up, maybe they don't want to be embarrassed. They've built their adult identity and have a sense of who they are and what they want to project. To some degree, your ability to keep doing interesting things is your willingness to be embarrassed again, go back to step one, start as a beginner, get your ass kicked, and look stupid doing things. So many things we're doing—whether it's this physical part of my life or running the company—we just take on new adventures. All the big things we're doing, I think of as 10-plus-year missions. Often early on, people doubt we'll be able to do it, and the initial work seems kind of silly. Our whole ethos is we don't want to wait until something is perfect to put it out there; we want to get it out quickly and get feedback. So there's probably something about how I approach things. I just kind of think that the moment you decide you're too embarrassed to try something new, you're not going to learn anything anymore.

就像我提到的，那种恐惧、那种焦虑可能存在，偶尔会悄悄出现。在柔术之外，尤其是在工作中压力大的时刻、重大决策日、重大决策时刻，你会感受到吗？你如何处理那种恐惧和焦虑？

Like I mentioned, that fear, that anxiety could be there, could creep up every once in a while. Do you feel that in especially stressful moments outside of Jiu-Jitsu, just at work—stressful moments, big decision days, big decision moments? How do you deal with that fear, that anxiety?

最让我压力大的总是人员挑战。我觉得战略问题——我对自己试图做的事情的价值、我认为重要的事情以及我希望公司代表什么有足够的信念——那些并不会真的让我失眠。当然，我并不是每件事都对，我们犯了很多错误。但我至少对自己想去的方向有很强的感觉。经营公司近 20 年来，有一件事很清楚：当你有一个有凝聚力的团队时，你几乎可以完成任何事情。你可以克服超级困难的挑战，做出艰难的决定，并非常努力地推动完成最好的工作。但当存在那种紧张关系时，事情就会变得非常棘手。当我与其他经营公司的朋友交谈时，我认为我在经营这家公司上花费了不成比例的时间的一件事，就是培养一个与我一起经营公司的非常紧密的核心团队。对我来说，这既是让事情变得有趣的原因——有朋友、一起工作过的人、新人和新视角——也是一个足够紧密的团队，可以一起处理这些事情。

The thing that stresses me out the most is always the people challenges. I kind of think that strategy questions—I tend to have enough conviction around the values of what we're trying to do and what I think matters and what I want our company to stand for—those don't really keep me up at night. It's not that I get everything right, of course I don't. We make a lot of mistakes. But I at least have a pretty strong sense of where I want us to go. The thing in running a company for almost 20 years now that's been pretty clear is when you have a team that's cohesive, you can get almost anything done. You can run through super hard challenges, make hard decisions, and push really hard to do the best work. But when there's that tension, that's when things get really tough. When I talk to other friends who run other companies, I think one of the things I actually spend a disproportionate amount of time on in running this company is just fostering a pretty tight core group of people who are running the company with me. That to me is kind of the thing that both makes it fun—having friends and people you've worked with for a while, and new people and new perspectives—but a pretty tight group who can go work on some of these things.

疯狂的事情，但对我来说，最让人压力大的就是出现紧张关系的时候。那让我很沉重。我觉得这也许并不奇怪。我们是一家非常以人为本的公司，而人是我最在意、必须确保做对的部分。所以，当你信任那些人帮你做出关于 Facebook、WhatsApp、Instagram、公司未来、元宇宙或 AI 的艰难决策时，你是如何建立那个紧密的小圈子来做出这些艰难决定的？是否需要那些持有批评声音、非常不同的视角、关注过去与未来等所有方面的人？

Crazy things with, but to me that's also the most stressful thing is when there's tension. That weighs on me. I think it's maybe not surprising. We're a very people-focused company, and the people is the part that weighs on me the most to make sure we get right. So when there's tension in that inner circle of close folks, when you trust those folks to help you make difficult decisions about Facebook, WhatsApp, Instagram, the future of the company, the metaverse, or the AI, how do you build that close-knit group of folks to make those difficult decisions? Is there people that you have to have critical voices, very different perspectives, focusing on the past versus the future, all that kind of stuff?

是的，我认为首先就是要花大量时间与你想让其成为核心团队的那群人在一起，共同应对所有最大的挑战。这需要相当程度的开放性。我经营公司的方式很大程度上是，每周一早上我们召集大约前 30 名高管。这是一个长期共事过的团队。人员会轮换，有新加入的，有离开公司或转到其他岗位的，所以团队并非一成不变。我们会花上几个小时，有时没有固定议程。我会提出几个我当前最关心的话题，但也会请其他人带来议题。人们会提出问题：某个国家发生的事件、政策问题、正在发展的新技术、与合作伙伴的问题、WhatsApp 中两个我们都非常看重的价值观之间的设计权衡。我们需要决定我们想站在哪一边。随着时间的推移，通过共同处理大量问题并保持开放，人们会培养出对彼此的直觉、纽带和同志情谊。对我来说，培养这种关系是经营公司或做任何事情中很有趣的部分。有那些与你同行的人，让你感觉你们是一起在做——没有任何事是单靠一个人完成的。

Yeah, I mean, I think for one thing, it's just spending a lot of time with whatever the group is that you want to be that core group grappling with all the biggest challenges. That requires a fair amount of openness. A lot of how I run the company is, every Monday morning we get the top 30 people together. This is a group that has worked together for a long period of time. People rotate in, new people join, people leave the company or go to other roles, so it's not the same group over time. We spend a couple of hours, sometimes unstructured. I'll come with a few topics that are top of mind for me, but I'll ask other people to bring things. People raise questions: an issue happening in some country, a policy issue, a new technology developing, an issue with a partner, a design trade-off in WhatsApp between two things that are values we care about deeply. We need to decide where we want to be on that. Over time, by working through a lot of issues with people and doing it openly, people develop an intuition for each other and a bond and camaraderie. To me, developing that is a lot of the fun part of running a company or doing anything. Having people who are along on the journey that you feel like you're doing it with—nothing is ever just one person doing it.

那个团队里经常有人意见不合吗？

Are there people that disagree often within that group?

这是一个相当好辩的团队。

It's a fairly combative group.

好的，所以争论是其中一部分。那么这涉及设计、工程、政策等所有方面的决策吗？

Okay, so combat is part of it. So this is making decisions on design, engineering, policy, everything?

所有方面，所有方面，所有方面。

Everything, everything, everything.

我不得不问一下，回到柔术一会儿。你练了这么久，最喜欢的降服技是什么？你喜欢怎么降服对手，马克·扎克伯格？

I have to ask, just back to jiu-jitsu for a little bit. What's your favorite submission now that you've been doing it? How do you like to submit your opponent, Mark Zuckerberg?

首先，你喜欢无道服还是有道服柔术？道服是你穿的那种模仿衣服的装备，可以用来勒颈，就像和服。它就像传统武术的睡衣。可以用来勒人的睡衣。是的，它有翻领。所以我喜欢柔术，我也非常喜欢 MMA，我认为无道服更接近 MMA。我的风格可能更偏向 MMA 风格。很多柔术选手不介意处于下位，拥有好的防守是柔术的关键部分，但在 MMA 中你不想处于下位，因为即使你有控制，你也会在下位挨拳。所以那不好。所以你更喜欢上位？我的风格可能更偏压力型，我可能更愿意做上位选手。但我也比较小只，我不是重量级选手。所以从这个角度看，尤其因为如果参加比赛我会和同量级的人比，但我的很多朋友都比我大，所以拿背可能非常重要，因为那是你拥有最大杠杆优势的位置。人的手臂在背后非常无力。所以能够拿到背并控制住非常重要。但我不确定，我觉得正确的策略是不要太执着于任何一种降服技。话虽如此，我不喜欢伤害别人，所以我一直认为绞技比关节技更人道一些。它更注重控制，不那么动态。所以你基本上就像哈比布·努尔马戈梅多夫那种类型的 fighter？那就来吧。拿背到裸绞，我认为是最干净的方式。直接的回答。

Well, first of all, do you prefer no-gi or gi jiu-jitsu? Gi is this outfit you wear that mimics clothing so you can choke, like a kimono. It's like the traditional martial arts pajamas. Pajamas that you could choke people with. Yes, it has the lapels. So I like jiu-jitsu, I also really like MMA, and I think no-gi more closely approximates MMA. My style is maybe a little closer to an MMA style. A lot of jiu-jitsu players are fine being on their back, and having a good guard is a critical part of jiu-jitsu, but in MMA you don't want to be on your back because even if you have control, you're just taking punches while on your back. So that's no good. So you like being on top? My style is probably more pressure, and I'd probably rather be the top player. But I'm also smaller, I'm not a heavyweight guy. So from that perspective, especially because if I'm doing a competition I'll compete with people my size, but a lot of my friends are bigger than me, so back takes are probably pretty important because that's where you have the most leverage advantage. People's arms are very weak behind you. So being able to get to the back and take that is pretty important. But I don't know, I feel like the right strategy is to not be too committed to any single submission. That said, I don't like hurting people, so I always think that chokes are a somewhat more humane way to go than joint locks. It's more about control, it's less dynamic. So you're basically like a Khabib Nurmagomedov type of fighter? So let's go. Back take to a rear naked choke, I think is the clean way to go. Straightforward answer right there.

鉴于你如此忙碌，处于人生的这个阶段，却还能做到这些——训练、比赛，并从这门有趣的艺术中学到东西——你会给那些想开始学习柔术的人什么建议？

What advice would you give to people looking to start learning jiu-jitsu, given how busy you are, where you are in life, that you're able to do this, you're able to train, you're able to compete and get to learn something from this interesting art?

我只是觉得你必须愿意经常被揍。随着时间的推移，我认为所有这些事情都有一种流动感。我的一个经历，我认为超越了经营公司和各种我喜欢做的活动，就是我坚信如果你想完成任何事情，很大程度上就是愿意坚持下去，拥有克服困难局面的毅力和决心。对很多人来说，这最终会成为那些成就最多的人与其他人之间的分水岭。关于人们想工作多少天之类的问题有很多讨论。我认为几乎所有创办成功公司的人都在极其努力地工作。但通过长期做这些事情，或者通过柔术或冲浪这类活动非常敏锐地学到的一点是，你不可能硬撑过所有事情。与经营公司相比，你通过运动非常敏锐地学到这一点，因为经营公司的周期太长。你启动一个项目，几个月后，或者如果你在构建硬件，可能几年后，你才能真正得到反馈，并为下一个版本做出下一组决策。而这些高周转率的体能训练活动在心理上非常棒的一点是，你能得到即时反馈。

I just think you have to be willing to get beaten up a lot. Over time, I think there's a flow to all these things. One of my experiences that I think transcends running a company and the different activities I like doing is I really believe that if you're going to accomplish anything, a lot of it is just being willing to push through, having the grit and determination to push through difficult situations. For a lot of people, that ends up being a different maker between the people who get the most done and not. There are all these questions about how many days people want to work and things like that. I think almost all the people who start successful companies are working extremely hard. But one of the things you learn both by doing this over time or very acutely with things like jiu-jitsu or surfing is you can't push through everything. You learn this stuff very acutely doing sports compared to running a company, because running a company the cycle times are so long. You start a project and it's months later, or if you're building hardware it could be years later, before you're actually getting feedback and able to make the next set of decisions for the next version. Whereas one of the things that is mentally so nice about these very high turnaround conditioning activities is you get immediate feedback.

像运动这类事情，反馈来得非常快。比如，我没正确格挡，就会挨一拳。柔术里不会挨拳，但综合格斗会。这些事之间有很多类比，我觉得它们确实是重要的人生道理。就像冲浪，有时候你没法往反方向走，总有限制。用水翼板，你可以泵动并在很多方向上用力推，但在某个层面上，逆势的动量太强，就是行不通。我认为这对经营或建设的人来说，是一个既让人谦卑又很重要的教训。很多时候，游戏的关键就是能推动并解决复杂问题，但你也需要足够理解哪些事是推不动的，以及哪里更需要巧劲。

Sports things like that, you get feedback very quickly. It's like, okay, I don't counter something correctly, you get punched in the face. Not in Jiu-Jitsu, you don't get punched, but in MMA. There are all these analogies between these things that I think actually hold, that are important life lessons. It's like, you're surfing a wave. Sometimes you can't go in the other direction. There are limits. With foil, you can pump and push hard in a bunch of directions, but at some level, the momentum against you is strong enough that it's not going to work. I do think that's a humbling but important lesson for people who are running things or building things. A lot of the game is just being able to push and work through complicated things, but you also need enough understanding of which things you just can't push through and where the finesse is more important.

对。你的柔术人生道理是什么？

Yeah. What are your Jiu-Jitsu life lessons?

嗯，我觉得你做到了。你说得那么简单又富有感染力，以至于容易让人忽略。但本质上，就是坦然接受被痛揍的智慧和乐趣，接受它全部的含义。我认为这是谦卑带来的大礼物。不知怎的，谦卑——尤其是身体上的谦卑——会让你敞开心扉，去真正理解学习的全过程，也就是愿意在某件事上做得一塌糊涂。柔术会非常重复且高效地让你一次次谦卑，直到你能把那个教训带到那些不那么容易受挫的地方，无论是研究、经营公司还是做产品。那个周期更长。你可以在一小时内反复受挫，尤其是初学者。一个小个子，比你小得多的人，反复、明确地揍你，毫无争议。然后你真的拍地认输，因为不拍你就会死。所以这是一种约定：你刚才本可以杀了我，但我们是朋友，所以我们约定你不会那么做。那种谦卑的过程会对你的心理和自负产生影响，把它放到合适的位置。它让你意识到，这辈子的一切都像一场从糟糕到通过艰苦过程日复一日严格改进的旅程。任何成功都需要努力。柔术比我做过的很多运动都更能教会你这一点。而你把它说得那么简单：没事，这是过程的一部分。你只要谦卑。我这辈子失败和尴尬的次数太多了，以至于这现在成了我的核心能力。

Well, I think you did it. You made it sound so simple and eloquent that it's easy to miss. But basically, being okay and accepting the wisdom and the joy in getting your ass kicked, in the full range of what that means. I think that's a big gift of being humbled. Somehow being humbled, especially physically, opens your mind to the full process of learning what it means to learn, which is being willing to suck at something. Jiu-Jitsu very repetitively and efficiently humbles you over and over and over, to where you can carry that lesson to places where you don't get humbled as much, whether it's research or running a company or building stuff. The cycle is longer. You can get humbled in a period of an hour over and over, especially when you're a beginner. A little person, somebody much smaller than you, just kicks your ass repeatedly, definitively, where there's no argument. And then you literally tap, because if you don't tap, you're going to die. So this is an agreement: you could have killed me just now, but we're friends, so we agree you're not going to. That kind of humbling process does something to your psyche, to your ego, that puts it in its proper context. It makes you realize that everything in this life is like a journey from sucking through a hard process of improving rigorously day after day after day. Any kind of success requires hard work. Jiu-Jitsu, more than a lot of sports I've done, really teaches you that. And you made it sound so simple: it's okay, it's part of the process. You just get humble. I've just failed and been embarrassed so many times in my life that it's a core competence at this point.

嗯，是的，这其中有深刻的道理。能够——而且你一开始就说了——这正是阻碍我们的东西，尤其是随着年龄增长，当你在某些领域成为专家时：不愿意在新领域当新手。因为成长就发生在那里，愿意当新手，愿意出丑，说傻话，做傻事。我们很多人在一件事上做得好，就想炫耀，当新手很糟糕，但那是成长发生的地方。

Well, yes, and there's a deep truth to that. Being able to, and you said it in the very beginning, that's the thing that stops us, especially as you get older, especially as you develop expertise in certain areas: the not being willing to be a beginner in a new area. Because that's where the growth happens, is being willing to be a beginner, being willing to be embarrassed, saying something stupid, doing something stupid. A lot of us that get good at one thing want to show that off, and it sucks being a beginner, but it's where growth happens.

是的。

Yeah.

说到这个，让我问问你关于 AI 的事。看起来今年，对于整个人类文明来说，是人工智能发展中有趣的一年。很多有趣的事情正在发生。Meta 是其中的重要部分。Meta 开发了 Llama，一个 650 亿参数的模型。这里有很多有趣的问题可以问，其中一个与开源有关。但首先，你能讲讲开发这个模型以及做出如何发布它的复杂决定的故事吗？

Well, speaking of which, let me ask you about AI. It seems like this year, for the entirety of human civilization, is an interesting year for the development of artificial intelligence. A lot of interesting stuff is happening. Meta is a big part of that. Meta has developed Llama, which is a 65 billion parameter model. There are a lot of interesting questions to ask here, one of which has to do with open source. But first, can you tell the story of developing this model and making the complicated decision of how to release it?

嗯，当然。首先，你说得对。在过去一年里，在扩展这些大型 Transformer 模型方面取得了一系列进展。有大型语言模型的语言版本，也有大型扩散模型的图像生成版本。这背后有很多基础研究。Meta 在 AI 开发中采取了相当开放和学术化的方式。部分原因是，我们希望世界上最优秀的人来研究这个，而很多最优秀的人希望知道他们能够分享自己的工作。所以这是我们协议的一部分：如果你是世界上最顶尖的 AI 研究者之一，你可以来这里，获得行业规模的算力基础设施，而我们的理念之一就是广泛分享发明。我们用很多不同的 AI 工具都这样做。Llama 是我们的研究团队制作的语言模型。我们做了一个有限的开源发布，旨在让研究人员能够使用它。但责任和确保这些模型的安全性非常重要。所以对于第一个版本，我们觉得有很多关于是否应该商业发布的问题。我们在 Llama V1 上回避了这个问题，只做了研究发布。现在，显然，通过研究发布，它已经公开了，但公司知道他们不应该将其用于商业发布。我们正在开发后续模型，并思考后续版本到底应该如何运作，因为我们现在有更多时间来处理安全性和相关方面。但总的来说，我只是认为，如果有更多不同的人有能力在这里构建最先进的技术，而不是只有少数大公司，那会很好。训练这些最先进的 AI 模型需要数亿美元的算力基础设施。所以当今世界上没有多少组织能在最大规模上做到这一点。它每天都在变得更高效，所以我认为随着时间的推移，它会对更多人可用。但我只是觉得，人们可以创造所有这些创新。

Yeah, sure. I think you're right. First of all, in the last year, there have been a bunch of advances on scaling up these large Transformer models. There's the language equivalent with large language models, and the image generation equivalent with these large diffusion models. There's a lot of fundamental research that's gone into this. Meta has taken the approach of being quite open and academic in our development of AI. Part of this is we want to have the best people in the world researching this, and a lot of the best people want to know that they're going to be able to share their work. So that's part of the deal we have: if you're one of the top AI researchers in the world, you can come here, get access to industry-scale infrastructure, and part of our ethos is that we want to share what's invented broadly. We do that with a lot of the different AI tools we create. Llama is the language model that our research team made. We did a limited open source release for it, intended for researchers to be able to use it. But the responsibility and getting safety right on these is very important. So we didn't think that for the first one, there were a bunch of questions around whether we should be releasing this commercially. We kind of punted on that for V1 of Llama and just released it for research. Now, obviously, by releasing it for research, it's out there, but companies know that they're not supposed to put it into commercial releases. We're working on the follow-up models and thinking through how exactly this should work for follow-ons, now that we've had time to work on a lot more of the safety and the pieces around that. But overall, I just kind of think that it would be good if there were a lot of different folks who had the ability to build state-of-the-art technology here, not just a small number of big companies. To train one of these state-of-the-art AI models takes hundreds of millions of dollars of infrastructure. So there are not that many organizations in the world that can do that at the biggest scale today. It gets more efficient every day, so I do think that will be available to more folks over time. But I just think there's all this innovation out there that people can create.

对于不了解的人来说，你在今年 2 月有限发布了 LLaMA，它被“泄露”了，意思是它脱离了有限发布的范围。但考虑到你只是把它发布给研究人员，这可能是你预料之中的事。我们把它分享给了研究人员，对吧？所以只是想确保有一个缓慢的发布过程。但我想听听你对接下来发生的事情的看法——一个非常活跃的开源社区在它的基础上构建了很多东西。有 LLaMA CPP，基本上让它在更小的计算机上运行得更高效。有结合基于人类反馈的强化学习（RLHF）的各种有趣的微调机制。还有微调和 GPT-3 生成。有很多 GPT-4 All、Alpaca、Colossal AI 这类模型，它们突然出现并运行在 LLaMA 之上。你怎么看？

For people who don't know, you did the limited release in February of this year of LLaMA, and it got quote-unquote leaked, meaning it escaped the limited release aspect. But it was something you probably anticipated, given that it's just released to researchers. We shared it with researchers, right? So it's just trying to make sure that there's like a slow release. But from there, I would love to get your comment on what happened next, which is this very vibrant open source community that just builds stuff on top of it. There's LLaMA CPP, basically stuff that makes it more efficient to run on smaller computers. There's combining with reinforcement learning with human feedback, so some of the different interesting fine-tuning mechanisms. There's also fine-tuning and GPT-3 generations. There's a lot of GPT-4 All, Alpaca, Colossal AI, all these kinds of models that just spring up and run on top of it. What do you think about that?

我觉得这真的很棒。有人已经让它能在本地设备上运行了。如果你只是个人想在家实验，可能没有太多预算去获取大量云计算资源，所以能在本地笔记本上运行就很好，也很实用。还有像 LLaMA CPP 这样的东西，它更高效地重新实现了模型。现在即使我们自己运行自己的版本，也可以用更少的算力，效率高得多，为每个使用它的人省了很多钱。这很好。但我觉得值得指出的是，因为这是一个相对早期的发布，LLaMA 并不像最大的 OpenAI 模型或最大的 Google 模型那样处于前沿。我们发布的最大 LLaMA 模型有 650 亿参数，除了 OpenAI 内部没人知道 GPT-4 的具体规格，但据我所知它大约大 10 倍。我认为 Google 的 PaLM 模型也有大约 10 倍的参数。不过 LLaMA 模型非常高效，所以对于 650 亿参数左右的规模来说，它们表现很好。对我来说，这也是问题的一部分，因为有一个争论：让全世界所有人都能访问最前沿的 AI 模型是否好。当模型开始接近超级智能时，那将是一个我们必须应对的更大问题。但现在，这些仍然是相当基础的工具。它们很强大，就像很多开源软件（如数据库或 Web 服务器）能实现很多重要的事情一样，但我不认为有人会看着当前这一代 LLaMA 觉得它接近超级智能。所以我认为那些关于是否应该把它放出去的问题——在这个阶段，你当然希望更多的研究人员参与进来，因为开源软件有很多优势。我们之前谈到了效率，但另一个优势是开源软件往往更安全，因为更多的人公开审视它，发现漏洞，这使它更安全。所以我认为在这一点上，人们普遍同意开源软件通常比闭门开发、试图通过隐蔽实现安全的东西更安全。因此，对于我们现在看到的 AI 规模，我认为通过开源，我们更有可能实现良好的对齐和对如何让它工作良好的理解。这是目前公开进行的好事。

I think it's been really neat to see. There have been folks who are getting it to run on local devices. If you're an individual who just wants to experiment at home, you probably don't have a large budget to get access to a lot of cloud compute, so getting it to run on your local laptop is pretty good and relevant. Then there are things like LLaMA CPP that reimplemented it more efficiently. Now even when we run our own versions of it, we can do it on way less compute, it's way more efficient, and saves a lot of money for everyone who uses this. That is good. I do think it's worth calling out that because this was a relatively early release, LLaMA isn't quite on the frontier as, for example, the biggest OpenAI models or the biggest Google models. The largest LLaMA model we released had 65 billion parameters, and no one outside of OpenAI knows exactly what the specs are for GPT-4, but my understanding is it's like 10 times bigger. I think Google's PaLM model also has about 10 times as many parameters. Now the LLaMA models are very efficient, so they perform well for something that's around 65 billion parameters. For me, that was also part of this because there's this whole debate around whether it's good for everyone in the world to have access to the most frontier AI models. As the models start approaching something like superhuman intelligence, that's a bigger question we'll have to grapple with. But right now, these are still very basic tools. They're powerful in the sense that a lot of open source software like databases or web servers can enable a lot of pretty important things, but I don't think anyone looks at the current generation of LLaMA and thinks it's anywhere near a superintelligence. So I think a bunch of those questions around whether it's good to get it out there — at this stage, surely you want more researchers working on it for all the reasons that open source software has a lot of advantages. We talked about efficiency before, but another one is that open source software tends to be more secure because you have more people looking at it openly and scrutinizing it, finding holes in it, and that makes it more safe. So I think at this point, it's generally agreed upon that open source software is generally more secure and safer than things that are developed in a silo where people try to get security through obscurity. So for the scale of what we're seeing now with AI, I think we're more likely to get to good alignment and good understanding of what needs to be done to make this work well by having it be open source. That's something that is quite good to have out there and happening publicly at this point.

Meta 开源了很多模型，比如 Mass 多语言语音模型、Age 模型。我会问你关于这些的问题，但重点是你们开源了很多，你一直在引领开源运动。从一个角度看，这非常积极和鼓舞人心。从研究角度看，当然有人对人工智能的生存威胁感到非常恐惧，他们会说你在开源步骤上必须小心。但作为 Meta 的一部分，你如何看待开源的未来？这里有一个张力：你想不想释放魔法配方？这是一个张力。另一个是：你想不想把强大的工具交到坏人手中，尽管它也可能带来巨大的积极影响？

Meta released a lot of models as open source, so the Mass Multilingual Speech Model, the Age Model. I'll ask you questions about those, but the point is you've open sourced quite a lot, you've been spearheading the open source movement. That's really positive and inspiring to see from one angle. From the research angle, of course there are folks who are really terrified about the existential threat of artificial intelligence, and those folks will say that you have to be careful about the open sourcing step. But where do you see the future of open source here as part of Meta? The tension here is: do you want to release the magic sauce? That's one tension. And the other one is: do you want to put a powerful tool in the hands of bad actors, even though it probably has a huge amount of positive impact also?

再次强调，我认为在 AI 发展的当前阶段，没有人会认为现状是超级智能。我们讨论的模型，比如 LLaMA 模型，通常比 OpenAI 或 Google 正在做的模型小一个数量级。所以我认为，至少在我们现在的阶段，天平强烈倾向于更开放地做这件事。我认为如果出现了更接近超级智能的东西，那么你就需要更多地讨论和思考这个问题。我们还没有决定如果处于那种情况会怎么做，但我认为我们离那个位置还很远。所以我当然不是说我们现在采取的立场适用于我们做的每一件事。在公司内部，我们可能比大多数其他大型科技公司做了更多的开源工作，但我们也没有开源所有东西。很多核心……

Again, I think for the stage that we're at in the development of AI, I don't think anyone looks at the current state of things and thinks that this is superintelligence. The models we're talking about, the LLaMA models here, are generally an order of magnitude smaller than what OpenAI or Google are doing. So I think that at least for the stage we're at now, the equities balance strongly in my view towards doing this more openly. I think if you got something that was closer to superintelligence, then you'd have to discuss that more and think through that a lot more. We haven't made a decision yet as to what we would do if we were in that position, but I think there's a good chance that we're pretty far off from that position. So I'm certainly not saying that the position we're taking on this now applies to every single thing we would ever do. Certainly inside the company, we probably do more open source work than most other big tech companies, but we also don't open source everything. A lot of our core...

像 WhatsApp 或 Instagram 的应用代码，我们不会开源。它不是那种通用到能让很多人做不同事情的软件。而我们开源的软件，比如开源服务器设计，或者像 McRouter 这样的东西——那可能是我在公司最早参与的项目，也是我最后亲自编码和主导的项目之一——这个缓存工具用于快速数据检索，这些是构建任何东西都广泛有用的基础组件。我认为现在的一些语言模型也有这种感觉，还有我们正在构建的其他东西，比如你刚才提到的翻译工具。

Of app code for WhatsApp or Instagram or something, I mean, we're not open sourcing that. It's not like a general enough piece of software that would be useful for a lot of people to do different things. Whereas the software that we do, whether it's like an open source server design or basically things like McRouter, which was probably our earliest project that I worked on, it was probably one of the last things that I coded and led directly for the company. But basically this caching tool for quick data retrieval, these are things that are just broadly useful across anything that you want to build. And I think that some of the language models now have that feel as well, as some of the other things that we're building like the translation tool that you just referenced.

所以文本转语音和语音转文本，你们从大约 100 种语言扩展到了超过 1,000 种语言，而且模型能识别超过 4,000 种口语，这是任何已知先前技术的 40 倍。对我来说，这在连接世界、打破语言障碍方面真的非常非常令人兴奋。

So text-to-speech and speech-to-text, you've expanded it from around 100 languages to more than 1,000 languages, and you can identify more than the model can identify more than 4,000 spoken languages, which is 40 times more than any known previous technology. To me, that's really, really, really exciting in terms of connecting the world, breaking down barriers that language creates.

是的，我认为能够实时翻译所有这些不同语言，这一直是一个常见的科幻想法——无论是耳机、眼镜还是其他东西，能帮助实时翻译不同语言。我认为技术现在基本上正在实现这一点。所以我觉得这非常令人兴奋。

Yeah, I think being able to translate between all of these different pieces in real time, this has been a kind of common sci-fi idea that we'd all have, whether it's an earbud or glasses or something that can help translate in real time between all these different languages. And that's one that I think technology is basically delivering now. So I think yeah, I think that's pretty exciting.

你提到了 Llama 的下一个版本。关于下一个版本的 Llama，你能说些什么？在发布方面，在愿景方面，你们在做什么？

You mentioned the next version of Llama. What can you say about the next version of Llama? What were you working on in terms of release, in terms of the vision for that?

我们正在做的主要工作是，以第一个版本（主要是研究版本）为基础，尝试构建一个内置了所有最新最先进安全措施的版本。我们正在使用来自我们服务的更多数据来训练它。但我们内部的大量工作实际上只是专注于确保它尽可能对齐和负责任。我们也在构建许多自己的产品体验，帮助人们连接和表达自己。所以你会有一个可以在 WhatsApp 中对话的助手。我认为未来每个创作者都会拥有一个 AI 智能体，代表他们行动，让粉丝可以与之交谈。我希望达到每个小企业都有一个 AI 智能体的程度，人们可以与之交谈进行商务和客户支持等。所以会有所有这些不同的东西，而 Llama 或底层的语言模型基本上将成为驱动这一切的引擎。开源的原因是，正如我们在第一个版本中所做的那样，它基本上释放了生态系统中的大量创新。我们也会让自己的产品变得更好，并且还能获得大量关于安全性的宝贵反馈，这对做好这件事很重要。但我们推进基础设施的工作基本上是在把它从一个研究项目变成准备成为核心基础设施的东西，不仅用于我们自己的产品，也希望用于其他许多地方。

Well, a lot of what we're doing is taking the first version, which was primarily this research version, and trying to now build a version that has all of the latest state-of-the-art safety precautions built in. And we're using some more data to train it from across our services. But a lot of the work that we're doing internally is really just focused on making sure that this is as aligned and responsible as possible. And we're building a lot of our own product experiences to help people connect and express themselves. So you'll have an assistant that you can talk to in WhatsApp. I think in the future, every creator will have kind of an AI agent that can act on their behalf that their fans can talk to. I want to get to the point where every small business basically has an AI agent that people can talk to for commerce and customer support and things like that. So there are going to be all these different things, and Llama or the language model underlying this is basically going to be the engine that powers that. The reason to open source it is that, as we did with the first version, it basically unlocks a lot of innovation in the ecosystem. We will make our products better as well, and also gives us a lot of valuable feedback on security and safety, which is important for making this good. But yeah, the work that we're doing to advance the infrastructure is basically taking it beyond a research project into something which is ready to be core infrastructure, not only for our own products but hopefully for a lot of other things out there too.

你认为 Llama 或那个版本底层的语言模型也会开源吗？你们内部对此有辩论吗，关于利弊等等？

Do you think the Llama or the language model underlying that version too will be open sourced? Do you have internal debate around that, the pros and cons and so on?

我的意思是，我们一直在讨论内部的辩论。我认为问题是如何正确地做。我们为 V1 做了研究许可证。我认为我们正在考虑的大事基本上是什么是正确的做法。所以有一次泄露事件。我不知道你是否能评论。对于 V1，我们将其作为研究项目发布，供研究人员使用。但这样做，我们把它放出去了。我们非常明确地表示，任何使用代码和权重的人都没有商业许可以将其用于产品。我们通常看到人们尊重这一点。没有任何知名公司试图将其用于商业产品。但通过与这么多研究人员分享，它确实离开了公司。但你从那个过程中学到了什么，可以应用到 V2 上，关于如何安全有效地发布它？

This is, I mean, we were talking about the debates that we have internally. And I think the question is how to do it right. I mean, we did the research license for V1. And I think the big thing that we're thinking about is basically what's the right way. So there was a leak that happened. I don't know if you can comment on it. For V1, we released it as a research project for researchers to be able to use. But in doing so, we put it out there. We were very clear that anyone who uses the code and the weights doesn't have a commercial license to put into products. And we've generally seen people respect that right. There aren't any reputable companies that are basically trying to put this into their commercial products. But by sharing it with so many researchers, it did leave the building. But what have you learned from that process that you might be able to apply to V2 about how to release it safely and effectively?

如果你发布它，是的。

If you release it, yeah.

嗯，我的意思是，很多反馈，就像我说的，只是围绕如何微调模型使其更对齐和更安全的不同方面。你看到了所有不同的数据配方，你提到了很多基于此的项目。伯克利有一个，到处都是。人们尝试了很多不同的东西，我们内部也尝试了很多。所以我们正在取得进展，同时也能从社区中一些最好的想法中学习。我认为我们想继续推动这一点。但我没有任何消息要宣布，如果这是你问的。我的意思是，我们仍在积极研究如何正确推进。秘密配方的细节仍在开发中。

Well, I mean, I think a lot of the feedback, like I said, is just around different things around how do you fine-tune models to make them more aligned and safer. And you see all the different data recipes that you mentioned a lot of different projects that are based on this. There's one at Berkeley, there are just all over. And people have tried a lot of different things, and we've tried a bunch of stuff internally. So we're making progress here, but also we're able to learn from some of the best ideas in the community. And I think we want to just continue pushing that forward. But I don't have any news to announce on this, if that's what you're asking. I mean, this is a thing that we're still actively working through the right way to move forward here. The details of the secret sauce are still being developed.

我明白了。你评论一下你对 GPT 有效的方法的看法，也就是基于人类反馈的强化学习（RLHF），即进行对齐过程。你觉得它有趣吗？作为其中的一部分，让我问一下，因为今天和你谈话之前我和 Yann LeCun 聊过。他让我问，或者建议我问：你认为 LLM 微调是否需要像维基百科那样众包？所以众包，这种将人类整合到这些基础模型微调中的想法。

I see. You comment on what do you think of the thing that worked for GPT, which is the reinforcement learning with human feedback, so doing this alignment process. Do you find it interesting? And as part of that, let me ask because I talked to Yann LeCun before talking to you today. He asked me to ask, or suggested that I ask: do you think LLM fine-tuning will need to be crowdsourced Wikipedia style? So crowd sourcing, this kind of idea of how to integrate the human in the fine-tuning of these foundation models.

是的，我认为这是一个非常有趣的想法，我和 Yann 讨论过很多次。我们在讨论如何训练这些模型使其尽可能安全、对齐和负责任。不同的开发团队测试不同的数据配方和微调方法。

Yeah, I think that's a really interesting idea that I've talked to Yann about a bunch. And we were talking about how do you basically train these models to be as safe and aligned and responsible as possible. And different groups out there who do development test different data recipes and fine-tuning.

你刚才提到的这个想法是，归根结底，与其让一个小组微调一些东西，然后另一个小组提出不同的微调方案，再由我们试图找出哪个方案能产生最对齐的模型，我确实认为，如果能达到一个类似维基百科的协作方式，让更广泛的社区也能参与微调，那会很好。当然，这有很多挑战，无论是从基础设施、社区管理还是产品角度来看，如何实现这一点。我还没有完全想清楚，但作为一个想法，我觉得它很有吸引力，而且它与开源技术的精神很契合，也找到了一种社区驱动训练的方式。但我认为，总的来说，这方面还有很多问题。这些关于如何产生对齐的 AI 模型的问题，本质上是一个研究领域，我认为我们需要在这个领域取得与模型核心智能能力本身同样多的进展。

This idea that you just mentioned is that at the end of the day, instead of having one group fine-tune some stuff and then another group produce a different fine-tuning recipe, and then us trying to figure out which one we think works best to produce the most aligned model, I do think that it would be nice if you could get to a point where you had a Wikipedia-style collaborative way for a broader community to fine-tune it as well. Now, there's a lot of challenges in that, both from an infrastructure, community management, and product perspective about how you do that. So I haven't worked that out yet, but as an idea, I think it's quite compelling, and I think it goes well with the ethos of open-sourcing the technology, also finding a way to have a community-driven training of it. But I think that there are a lot of questions on this in general. These questions around what's the best way to produce aligned AI models, it's very much a research area, and it's one that I think we will need to make as much progress on as the kind of core intelligence capability of the models themselves.

嗯，我刚刚和维基百科的创始人 Jimmy Wales 聊过。对我来说，维基百科是有史以来最伟大的网站之一，它能够运作简直是个奇迹。我认为这与你提到的社区有关。有一小群编辑以某种方式很好地合作，他们处理非常有争议的话题时，尽管经常受到攻击，却能保持平衡和优雅。很多时候，它也有问题，就像任何其他人类系统一样，但他们的成就是惊人的。但它也并不完美，我认为仍然有很多挑战。话题越有争议，维基百科试图捕捉真理、知识或智慧的旅程就越困难。同样，AI 模型也需要能够生成同样的东西：真理、知识和智慧。那么，如何对齐这些模型，使它们生成最接近真理的东西呢？存在这些关于错误信息的担忧，所有这类没人能定义的东西。这是我们作为人类物种必须共同定义的东西：什么是真理，以及如何帮助 AI 系统生成真理。语言模型非常擅长的一件事就是生成听起来很有说服力但可能完全错误的东西。那么，如何对齐它，让它不那么错误呢？部分在于训练，部分在于对齐，无论你如何做对齐阶段。正如你所说，这是一个非常新且非常开放的研究问题。

Well, I just did a conversation with Jimmy Wales, the founder of Wikipedia, and to me, Wikipedia is one of the greatest websites ever created and is a kind of miracle that it works. And I think it has to do with something that you mentioned, which is community. You have a small community of editors that somehow work together well, and they handle very controversial topics with balance and grace, despite the attacks that will often happen. A lot of the time, I mean, it has issues just like any other human system, but yes, the balance is amazing what they've been able to achieve. But it's also not perfect, and I think that there are still a lot of challenges. The more controversial the topic, the more difficult the journey towards truth or knowledge or wisdom that Wikipedia aspires to capture. In the same way, AI models will need to be able to generate those same things: truth, knowledge, and wisdom. And how do you align those models so that they generate something that is closest to truth? There are these concerns about misinformation, all this kind of stuff that nobody can define. And it's something that we together as a human species have to define: what is truth, and how to help AI systems generate that. One of the things language models do really well is generate convincing-sounding things that can be completely wrong. So how do you align it to be less wrong? Part of that is the training, and part of that is the alignment, however you do the alignment stage. And just like you said, it's a very new and very open research problem.

是的，我认为还有很多问题关于当前的 LLM 架构，当你继续扩展它时会发生什么。我的意思是，过去一年令人兴奋的很多事情是，显然出现了一个质的突破，OpenAI 发布的一些 GPT 模型以及其他公司也能做到类似的事情，我认为它达到了一种质量水平，让人们觉得，哇，这感觉不一样了，它将成为构建许多优秀产品、体验和价值的基础。但我认为人们另一个认识是，哇，我们刚刚取得了一个突破。如果很快还有其他突破，那么我觉得可能我们更接近通用智能了。但我认为这个想法是建立在人们相信仍然需要一系列额外突破的基础上的，而我们只是不知道需要多长时间才能达到那里。有些人持有的一种观点——这不太是我的观点——是仅仅通过扩展当前的 LLM 并达到更高的参数量，我们就能得到更接近通用智能的东西。但我不确定，我倾向于认为沿途可能还需要更多根本性的步骤。不过，通过这个额外的对齐步骤所取得的飞跃，对很多人来说是非常不可思议、非常令人惊讶的。除此之外，当你有数亿人可能使用集成了它的产品时，你可以在实现超级智能之前就看到改变文明的效果。它可以在不是超级智能的情况下就具有超级变革性。

Yeah, and I think that there's also a lot of questions about whether the current architecture for LLMs, as you continue scaling it, what happens. I mean, a lot of what's been exciting in the last year is that there was clearly a qualitative breakthrough where, with some of the GPT models that OpenAI put out and that others have been able to do as well, I think it reached a kind of level of quality where people like, wow, this feels different, and it's going to be able to be the foundation for building a lot of awesome products and experiences and value. But I think the other realization that people have is, wow, we just made a breakthrough. If there are other breakthroughs quickly, then I think that there's the sense that maybe we're closer to general intelligence. But I think that idea is predicated on the idea that people believe there's still generally a bunch of additional breakthroughs to make, and we just don't know how long it's going to take to get there. One view that some people have, this doesn't tend to be my view as much, is that simply scaling the current LLMs and getting to higher parameter count models by itself will get us to something that is closer to general intelligence. But I don't know, I tend to think that there are probably more fundamental steps that need to be taken along the way. But still, the leap taken with this extra alignment step is quite incredible, quite surprising to a lot of folks. And on top of that, when you start to have hundreds of millions of people potentially using a product that integrates that, you can start to see civilization-transforming effects before you achieve superintelligence. It could be super transformative without being a superintelligence.

哦，是的。我的意思是，我认为用当前的技术水平可以创造出很多令人惊叹的产品和价值。在某种程度上，我很兴奋能在未来几年致力于这些产品，我认为如果突破不断叠加，那将造成巨大的冲击，因为我认为在某种程度上，行业和世界需要一些时间将这些突破融入到我们所有人使用的产品和体验中，这样我们才能真正从中受益。但我不确定，我认为有太多事情要做。我想到了所有的小企业或个人创业者，他们现在将能够获得帮助来编写他们需要构建的东西的代码，或者设计他们需要的东西，或者能够使用这些模型来为他们在 WhatsApp 上服务的人提供客户支持，而不必……我认为那将非常令人兴奋。它将为人们创造更好的体验，并释放大量的创新和价值。所以，我不知道你是否知道，但有超过 30 亿人使用 WhatsApp、Facebook 和 Instagram。因此，任何融入其中的 AI 驱动产品——我们说的是任何涉及 LLM 的东西——都将产生巨大的影响。你对可能开始集成到这些被如此多人使用的平台上的产品有什么想法和看法吗？

Oh yeah. I mean, I think that there are going to be a lot of amazing products and value that can be created with the current level of technology. To some degree, I'm excited to work on a lot of those products over the next few years, and I think it would just create a tremendous amount of whiplash if the number of breakthroughs keeps stacking, because I think to some degree industry and the world needs some time to build these breakthroughs into the products and experiences that we all use so we can actually benefit from them. But I don't know, I think that there's just an awesome amount of stuff to do. I think about all of the small businesses or individual entrepreneurs out there who now are going to be able to get help coding the things that they need to go build things, or designing the things that they need, or will be able to use these models to do customer support for the people that they're serving over WhatsApp without having to... I think that's just going to be super exciting. It's going to create better experiences for people and just unlock a ton of innovation and value. So, I don't know if you know, but over three billion people use WhatsApp, Facebook, and Instagram. So any kind of AI-fueled products that go into that, we're talking about anything with LLMs, will have a tremendous amount of impact. Do you have ideas and thoughts about possible products that might start being integrated into these platforms used by so many people?

是的，我认为我们正在研究的主要有三类东西。第一个，我认为可能是最有趣的，就是你会有一个可以与之交谈的助手或智能体。我认为我的观点与 OpenAI、Google 等公司的观点最大的不同在于，其他人都在构建一个单一的 AI。

Yeah, I think there are three main categories of things that we're working on. The first, that I think is probably the most interesting, is there's this notion of you're going to have an assistant or an agent who you can talk to. And I think probably the biggest thing that's different about my view of how this plays out from what I see with OpenAI and Google and others is, everyone else is building like the one singular AI.

没错，就像你跟 ChatGPT 聊，或者跟 Bard 聊，或者跟 Bing 聊。我的看法是，人们会想跟很多不同的 AI 互动，就像你会用很多不同的 App 做不同的事，你生活中也有不同的人扮演不同的情感角色。所以我认为人们有理由不想要单一的 AI。这大概是我思考这个问题时最大的区别。其中很多事情：我觉得你会想要一个助手。我之前提过几个。我认为你接触的每个创作者最终都会想要某种 AI 来代理他们，让他们的粉丝可以互动，或者让他们与粉丝互动。这是创作者的共同目标：每个人都在努力建立社区并与人们互动，他们想要工具来放大自己并做到这一点。但你一天只有 24 小时，所以我认为能够基本上封装你的个性，或者向粉丝提供你何时举办音乐会之类的信息，将是非常有价值的。但不仅仅是这些。再说一次，这不是我认为人们只想要一个单一 AI 的想法。我认为你会想与许多不同的实体互动。然后还有商业版本，我们之前也提到过几次：我认为世界上每个企业都会想要一个 AI，就像你在 Instagram、Facebook 或 WhatsApp 上有主页一样，你想把人们引向一个可以互动的 AI，但你要知道那个 AI 只会销售你的产品。你不想让它推荐竞争对手的东西，对吧？所以不可能只有一个单一的 AI 能回答一个人的所有问题，因为那个 AI 可能实际上并不与你作为企业保持一致，无法真正为你的产品提供最好的支持。所以我认为市场和人们的生活中显然需要很多这样的 AI。

Right, it's like okay you talk to ChatGPT or you talk to Bard or you talk to Bing. And my view is that there are going to be a lot of different AIs that people are going to want to engage with, just like you want to use a number of different apps for different things and you have relationships with different people in your life who fill different emotional roles for you. So I think that people have a reason that I think you don't just want a singular AI. And that I think is probably the biggest distinction in terms of how I think about this. A bunch of these things: I think you'll want an assistant. I mentioned a couple of these before. I think every creator who you interact with will ultimately want some kind of AI that can proxy them and be something that their fans can interact with, or that allows them to interact with their fans. This is like the common creator prize: everyone's trying to build a community and engage with people, and they want tools to be able to amplify themselves more and be able to do that. But you only have 24 hours in a day, so I think having the ability to basically bottle up your personality, or give your fans information about when you're performing a concert or something like that, is going to be something that's super valuable. But it's not just that. Again, it's not this idea that I think people are going to want just one singular AI. I think you're going to want to interact with a lot of different entities. And then I think there's the business version of this too, which we've touched on a couple of times, which is: I think every business in the world is going to want basically an AI that, you know, it's like you have your page on Instagram or Facebook or WhatsApp or whatever, and you want to point people to an AI that people can interact with, but you want to know that that AI is only going to sell your products. You don't want it recommending your competitor stuff, right? So it's not like there can be just one singular AI that can answer all the questions for a person, because that AI might not actually be aligned with you as a business to really do the best job providing support for your product. So I think that there's going to be a clear need in the market and in people's lives for there to be a bunch of these.

其中一部分是研究出能够实现你所说的个性化的技术。所以不是一个集中的神级 LLM，而是大量多样化的模型，针对特定需求、特定风格、特定业务、特定品牌等进行微调。同时让人们能够非常容易地为自己业务或作为创作者创建它们，以帮助你与粉丝互动。我认为这是一个清晰且有趣的产品方向，与你们、我或任何其他大公司所采取的方向相当不同。这也与这种开源方法非常契合，因为我们相信一种更社区导向、更民主的方式来构建产品和相关技术。我们不认为会有唯一正确的东西；我们认为应该有很多发展。所以这部分我认为会非常有趣，我们可以花很多时间讨论这一点，以及这种方法与其他公司不同的含义。

Part of that is figuring out the research, the technology that enables the personalization that you're talking about. So not one centralized godlike LLM, but just a huge diversity of them that's fine-tuned to particular needs, particular styles, particular businesses, particular brands, all that kind of stuff. And also enabling people to create them really easily for your own business or if you're a creator, to be able to help you engage with your fans. And I think that's a clear kind of interesting product direction here that I think is fairly unique from what you, I, any of the other big companies are taking. It also aligns well with this sort of open source approach, because again we sort of believe in this more community-oriented, more democratic approach to building out the products and technology around this. We don't think that there's going to be the one true thing; we think that there should be kind of a lot of development. So that part of things I think is going to be really interesting, and we could spend a lot of time talking about that and the implications of that approach being different from what others are taking.

但还有很多其他更简单的事情我认为我们也会做。回到你关于这如何融入我们构建的产品的问题：会有很多更简单的事情，比如你在 Instagram、Facebook、WhatsApp 和 Messenger 上发布照片，你希望照片看起来尽可能好。所以有一个 AI，你可以拍张照片然后告诉它，好的，我想编辑这个或描述这个，我认为我们将拥有比以往好得多的工具。这更多属于图像和媒体生成方面，而不是大语言模型方面，但都得益于同一领域的进步。所以我认为很多工具将被内置到我们的每个产品中。我认为我们做的每一件事基本上都会朝这个方向进化。没错，就像未来，如果你在我们的服务上做广告，你需要自己制作广告创意吗？不，你只需告诉我们，好的，我是一个遛狗的人，我愿意遛别人的狗，帮我找到合适的人，并创建表现最好的广告单元，给系统一个目标，它就会把你和合适的人连接起来。

But then there's a bunch of other simpler things that I think we're also going to do. Just going back to your question around how this finds its way into what we build: there are going to be a lot of simpler things around, okay, you post photos on Instagram and Facebook and in WhatsApp and Messenger, and you want the photos to look as good as possible. So having an AI that you can just take a photo and then just tell it, okay, I want to edit this thing or describe this, I think we're going to have tools that are just way better than what we've historically had on this. And that's more in the image and media generation side than the large language model side, but it all kind of plays off advances in the same space. So there are a lot of tools that I think are just going to get built into every one of our products. I think every single thing that we do is going to basically get evolved in this direction. Right, it's like in the future, if you're advertising on our services, do you need to make your own kind of ad creative? No, you'll just tell us, okay, I'm a dog walker and I'm willing to walk people's dogs, help me find the right people, and create the ad unit that will perform the best, and give an objective to the system, and it just kind of connects you with the right people.

这是一个非常强大的想法，几乎像严格的 A/B 测试一样为你生成语言，从而找到最适合你产品的人。对我来说，广告做得好就是在人和能让他快乐的东西之间找到好的匹配。是的，完全正确，并且尽可能高效地做到这一点。当它做得好时，人们实际上会喜欢它。我认为有很多例子表明它做得不好，很烦人，我认为这就是它名声不好的原因。但是的，很多东西今天已经可以实现。我的意思是，显然 A/B 测试已经内置在很多框架中。新的是拥有能为你生成 A/B 测试想法的技术。这很令人兴奋。

Well, that's a super powerful idea of generating the language almost like rigorous A/B testing for you that works to find the best customer for your thing. I mean, to me, advertisement when done well just finds a good match between a human being and a thing that will make that human being happy. Yeah, totally, and do that as efficiently as possible. When it's done well, people actually like it. I think that there's a lot of examples where it's not done well, it's annoying, and I think that's what kind of gives it a bad rap. But yeah, a lot of the stuff is possible today. I mean, obviously A/B testing stuff is built into a lot of these frameworks. The thing that's new is having technology that can generate the ideas for you about what to A/B test. Something that's exciting.

所以这将贯穿我们正在做的一切，对吧？我们正在做的所有元宇宙相关的事情。就像未来你想创建世界，你只需描述它们，它就会为你生成代码。所以自然语言成为我们与计算机、数字世界交互的界面。

So this will just be across everything that we're doing, right? All the metaverse stuff that we're doing. It's like you want to create worlds in the future, you'll just describe them and then it'll create the code for you. So natural language becomes the interface we use for all the ways we interact with the computer, with the digital world.

是的，完全正确。是的，每个人都可以用自然语言做到这一点，而且通过翻译，你可以用任何语言做到。我的意思是，个性化真的非常非常有趣。是的，它解锁了太多可能的事情。我个人很期待创建自己的副本。我知道我们上次谈过这个，但自从上次以来，我们离这个目标更近了，非常近了。就像我实际上只是与一些语言模型互动，我就能看到荒谬的情况，我会有一个……

Yeah, yeah, totally. Yeah, which is what everyone can do using natural language, and with translation you can do it in any kind of language. I mean, for the personalization is really, really, really interesting. Yeah, it unlocks so many possible things. I mean, I for one look forward to creating a copy of myself. I know we talked about this last time, but since last time this becomes how we're closer, much closer. Like I could literally just having interact with some of these language models, I can see the absurd situation where I'll have a...

大型语言模型，我得跟它谈一谈，比如“嘿，你有点出格了”，然后通过对话把它微调得更尊重人一些。我觉得这对企业和个人来说都是一个了不起的产品。不仅是面向个人的助手，还有代表个人面向公众的助手，双向的。基本上就是有一个 AI 系统层，你通过它和外部世界（包括人类）互动。这很有意思，而且你拥有连接数十亿人的社交网络，这似乎是一个大规模测试这些东西的好地方。

Large language model, and I'll have to have a conversation with him about like, 'Hey listen, you're just getting out of line,' and having a conversation where you fine-tune that thing to be a little bit more respectful or something like this. I mean, that's going to be the — that seems like an amazing product for businesses, for humans. Not just the assistant that's facing the individual, but the assistant that represents the individual to the public, both directions. There's basically a layer that is the AI system through which you interact with the outside world that has humans in it. That's really interesting, and you have social networks that connect billions of people. It seems like a heck of a large-scale place to test some of this stuff out.

是的，我认为创作者愿意这么做的部分原因是他们已经在我们的服务上有了社区。如今这类东西的很多界面都是聊天式的，而 WhatsApp 和 Messenger 我认为是与他人互动的绝佳方式。

Yeah, I mean, I think part of the reason why creators will want to do this is because they already have the communities on our services. And a lot of the interface for this stuff today are chat-type interfaces, and between WhatsApp and Messenger, I think that those are great ways to interact with people.

这有些哲学意味，但你认为在不久的将来，你在这些社交网络（Facebook、Instagram，甚至 WhatsApp）上的一些朋友会是 AI 系统，进行一些混合对话，部分是人类，部分是 AI 吗？

Some of this is philosophy, but do you see a near-term future where you have some of the people you're friends with are AI systems on these social networks, on Facebook, on Instagram, even on WhatsApp, having conversations where some heterogeneous, some is human, some is AI?

我觉得我们会走到那一步。仅凭经验来看，微软几年前在中国发布了“小冰”，那是一种更简单的预聊天机器人技术，当时就有数千万人在使用，并且对它产生了依恋，建立了关系。现在有像 Replika 这样的服务，人们也在做类似的事情。所以我认为人们确实有陪伴的需求，比如老年人，而且大多数人可能没有他们想要的那么多朋友。一些有趣的人口统计研究显示，现在的人均亲密朋友数量比 15 年前更少。这触及了我思考的核心——构建帮助人们连接的服务。所以你会得到帮助人们相互连接的工具，这是我们要做的主要事情。你可以想象 AI 助手能更好地提醒你朋友的生日以及如何庆祝。现在我们在网站角落有个小框告诉你谁的生日到了，但在某种程度上，你不想给每个人都发一条同样的“生日快乐”加个表情符号。所以拥有一个更像社交助手的东西，能告诉你他们最近怎么样，如何有效地联系他们，帮助你成为更好的朋友——我认为这也非常强大。

I think we'll get to that. You know, if only just empirically, looking at Microsoft released this thing called Xiaoice several years ago in China. It was a pre-chatbot technology that was a lot simpler than what's possible today, and I think it was like tens of millions of people were using this and really became quite attached and built relationships with it. And there are services today like Replika where people are doing things like that. So I think there's certainly needs for companionship that people have, older people, and I think most people probably don't have as many friends as they would like to have. If you look at some interesting demographic studies around that, the average person has fewer close friends today than 15 years ago. And that gets to the core thing that I think about in terms of building services that help connect people. So I think you'll get tools that help people connect with each other — that's going to be the primary thing that we want to do. So you can imagine AI assistants that do a better job of reminding you when it's your friend's birthday and how you could celebrate them. Right now we have the little box in the corner of the website that tells you whose birthday it is, but at some level you don't want to just send everyone the same note saying 'Happy Birthday' with an emoji. So having something that's more of a social assistant in that sense, that can update you on what's going on in their life and how you can reach out to them effectively, help you be a better friend — I think that's super powerful too.

除此之外，还有各种不同种类的个人 AI 可能存在。我认为助手是最容易理解的一种，但还有导师或人生教练，可以给你建议，有点像拉拉队长，帮你振作起来应对日常挑战。这类东西可能有一些作用。然后你可以列举人们生活中各种功能性的关系。我敢打赌会有公司尝试做这些事情。所以我认为这是未来有趣创新的一部分。比如教育导师——我看我的孩子学编程，他们很喜欢，但遇到问题就得等我或别人来解答。未来他们会有个编程助手，专门设计来教五岁和七岁孩子编程，可以随时提问，而且非常有耐心，永远不会对他们不耐烦。我认为我们生活中所有这些不同类型的关系或功能性关系都非常有趣。其中一个重要问题是：所有这些是否会归结为一个单一的 AI？我不这么认为。

Beyond that, there are all these different flavors of kind of personal AIs that I think could exist. So I think an assistant is sort of the simplest one to wrap your head around, but a mentor or a life coach, someone who can give you advice, who's maybe a bit of a cheerleader who can help pick you up through all the challenges that we all go through on a daily basis. There's probably some role for something like that. And then you can probably go through a lot of the different types of functional relationships that people have in their life. I would bet that there will be companies out there that take a crack at a lot of these things. So I think it's part of the interesting innovation that's going to exist. Like education tutors — I just look at my kids learning to code, they love it, but they get stuck on a question and have to wait till I can help answer it or someone else who knows. In the future, they'll just have a coding assistant that is designed to be perfect for teaching a five and a seven-year-old how to code, and they'll be able to ask questions all the time, and it'll be extremely patient, never get annoyed at them. I think there are all these different kinds of relationships or functional relationships that we have in our lives that are really interesting. And I think one of the big questions is: is this all going to just get bucketed into one singular AI? I just don't think so.

你考虑过这个吗？实际上，Reddit 上有个问题：“当人们可以通过聊天机器人自动增强语言来与他人‘交谈’，而不是通过犯错和学习来发展社交技能时，人类沟通的长期影响是什么？一代人之后，人们会不会只用咕哝声交流？”你考虑过大规模长期影响吗，AI 融入我们的社交互动？

Do you think about this? Actually, a question from Reddit: 'What are the long-term effects of human communication when people can talk with — in quotes — talk with others through a chatbot that augments their language automatically, rather than developing social skills by making mistakes and learning? Will people just communicate by grunts in a generation?' Do you think about long-term effects at scale, the integration of AI in our social interaction?

是的，我认为总体上是好的。那个问题有点负面，但我们之前谈到语言模型帮助沟通——比如语言翻译帮你和不说你语言的人交流。在某种程度上，所有这些社交技术都在帮助人们更好地表达自己，尤其是在他们本来很难做到的情况下。所以部分原因可能是，因为你说的语言我不懂——这是很基本的一点。我不认为人们会看着翻译说“真可悲，我们居然需要这个，我应该直接学你的语言”，那要求太高了。但总的来说，存在各种障碍，语言是人们表达思想和想法的不完美方式。它是最好的方式之一——我们有艺术、有代码——但语言也是你思维方式、世界观和自我的映射。最近我和一个来自 Jitu 的人聊过一个应用...

Yeah, I mean, I think it's mostly good. That question was sort of framed in a negative way, but we were talking before about language models helping you communicate — like language translation helps you communicate with people who don't speak your language. At some level, what all this social technology is doing is helping people express themselves better to people in situations where they would otherwise have a hard time doing that. So part of it might be, okay, because you speak a language I don't know — that's a pretty basic one. I don't think people are going to look at that and say it's sad that we have the capacity to do that because I should have just learned your language. That's a pretty high bar. But overall, there are all these impediments, and language is an imperfect way for people to express thoughts and ideas. It's one of the best we have — we have art, we have code — but language is also a mapping of the way you think, the way you see the world, the way who you are. And one of the applications I've recently talked to a person who's actually in a Jitu...

有位老师跟我说，他给家长发邮件，说他们的孩子在课堂上可以改进纪律之类的事情，他经常发现自己写出来的语气比预想中更冲，所以他就用 GPT 把原来的邮件翻译成更温和的版本。我们经常听到这类事。很多在我们平台上的创作者告诉我们，最让他们压力大的事情之一就是跟品牌谈合作这类商业事务。因为他们擅长的是创作本身，他们只想跟社区互动，但一看到私信里有品牌想合作，就不知道该怎么谈判或如何得体地拒绝。所以我觉得，如果能做一个工具帮他们做好这件事——一个简单但有趣的点子，我们听很多人说过他们感兴趣。但回到更宽泛的想法，嗯，我不知道。我和普莉希拉刚有了第三个女儿，你知道，世界上最让人难过的事情之一就是听到婴儿哭，对吧？但为什么呢？因为婴儿通常没有能力告诉你他们关心什么。其实不只是婴儿，我五岁的女儿也会哭，因为她有时很难表达出什么对她重要。我就在想，其实很多成年人也会很沮丧，因为他们也很难表达——回到之前的一些主题——也许是因为犯了错，或者因为自尊心之类的东西在作祟。所以我觉得，所有这些能帮助我们应对社交复杂性、更好地表达感受和想法的技术，总的来说都是好事。当然，总有人担心，比如有了谷歌搜索，人们的记忆力会不会变差？但我觉得，一代人之后，没有人会回头哀叹这件事。大家只会觉得，哇，我们现在有能力做更多事情了。我认为这里也是一样，你可以把那些认知能力分配到更深入、更细致的思考上。

Instructor, um, he said that when he emails parents about their son and daughter, um, that they can improve their discipline in class and so on, he often finds that he comes off a bit more of an asshole than he would like, so he uses GPT to translate his original email into a nicer email. We hear this all the time. A lot of creators on our services tell us that one of the most stressful things, um, is basically negotiating deals with brands and stuff, like the business side of it, because they're like, I mean, they do their thing, right? And, you know, the creators, they're excellent at what they do, and they just want to connect with their community, but then they get really stressed. You know, they go into their DMs and they see some brand wants to do something with them, and they don't quite know how to negotiate or how to push back respectfully. And, um, so I think building a tool that can actually allow them to do that well — the one simple thing that I think is just an interesting thing that we've heard from a bunch of people that they'd be interested in. But going back to the broader idea, um, I don't know. I mean, you, I just — Priscilla and I just had our third daughter, um, a couple — and, you know, it's like one of the saddest things in the world is like sing your baby cry, right? But like, it's like, what, why is that, right? It's like, well, because babies don't generally have much capacity to tell you what they care about otherwise, right? It's not actually just babies, right? It's, um, you know, my 5-year-old daughter cries too because she sometimes has a hard time expressing, you know, what, um, matters to her. And I was thinking about that and I was like, well, you know, actually a lot of adults get very frustrated too because they can't — they have a hard time expressing things in a way that, going back to some of the early themes, that maybe is something that, you know, was a mistake or maybe they have pride or something. Like all these things get in the way. So I don't know. I think that all these different technologies that can help us navigate the social complexity and actually be able to better express what we're feeling and thinking — I think that's generally all good. And, um, there are always these concerns like, okay, are people going to have worse memories because you have Google to look things up? And I think in general, a generation later, you don't look back and lament that. I think it's just like, wow, we have so much more capacity to do so much more now. And I think that that'll be the case here too. You can allocate those cognitive capabilities to like deeper, more nuanced thought.

是的，但情况已经变了。就像谷歌搜索一样，有了额外的语言模型、大语言模型，你基本上不需要记住那么多东西了。就像编程中的 Stack Overflow，现在这些语言模型可以生成代码了。我发现我写的代码中，大概 80% 到 90% 都是先生成再编辑的。所以你不需要记住不同函数的具体写法。这很棒。而且不仅仅是具体的编码，在这样的大公司里，工程师在开始编码之前，首先需要搞清楚成千上万人之前写过的所有库和依赖关系。我们正在做的一件事让我很兴奋，那就是不仅仅是帮助工程师编码的工具，而是能够总结整个知识库、帮助人们浏览所有内部信息的工具。在我做的实验中，即使是公开的内容，你只要让这些模型给你写一个能做任何事情的脚本，它基本上已经知道做那件事最好的库是什么，并自动引入它们。我觉得这非常强大。编程中最烦人的部分一直就是，你得花大量时间搞清楚在真正开始构建之前应该导入哪些资源。

Yeah, but it's changed. So with, uh, just like with Google search, the additional language models, large language models, you basically don't have to remember nearly as much. Just like with Stack Overflow for programming, now that these language models can generate code, right? I mean, I find that I write maybe 80% to 90% of the code I write is, uh, now generated first and then edited. I mean, so you don't have to remember how to write specifics of different functions. Oh, but that's great. And it's also not just the specific coding. I mean, in the context of a large company like this, I think before an engineer can sit down to code, they first need to figure out all of the libraries and dependencies that, you know, tens of thousands of people have written before them. And, um, you know, one of the things that I'm excited about that we're working on is it's not just, um, you know, tools that help engineers code; it's tools that can help summarize the whole knowledge base and help people be able to navigate all the internal information. I think that that's, um, in the experiments that I've done with this stuff, I mean, that's on the public stuff. You just, you know, ask, ask, um, one of these models to build you a script that does anything, and it basically already understands what the best libraries are to do that thing and pulls them in automatically. It's, I think, super powerful. That was always the most annoying part of coding — that you had to spend all this time actually figuring out what the resources were that you were supposed to import before you could actually start building the thing.

是的，当然也有另一面。我认为大部分是积极的，但另一面是，如果你把思考外包给 AI 模型，你可能会错过细微的错误和 bug。你会失去发现这些 bug 的技能，而这些 bug 可能是——代码看起来非常正确，但实际上在很微妙的地方出错了。但这就是我们人类文明在构建越来越强大的工具时所面临的权衡。当我们站在越来越高的巨人肩膀上时，我们能做更多，但也会忘记他们所做的一切。这是一个奇怪的权衡。

Yeah, I mean, there's of course the flip side of that. I think for the most part it's positive, but the flip side is, if you outsource that thinking to an AI model, you might miss nuanced mistakes and bugs. You lose the skill to find those bugs, and those bugs might be — the code looks very convincingly right, but it's actually wrong in a very subtle way. But that's the tradeoff that we face as human civilization when we build more and more powerful tools. When we stand on the shoulders of taller and taller giants, we can do more, but then we forget how to do all the stuff that they did. It's a weird tradeoff.

是的，我同意。我认为在生活中能够做基本的事情也是非常有价值的。

Yeah, I agree. I mean, I think it is very valuable in your life to be able to do basic things too.

你是否担心社交网络上出现越来越多像真人一样的机器人，它们不一定在做好事，或者可能明确在做坏事，比如钓鱼诈骗？是的，社交工程之类的东西，这对社交网络来说一直是个非常棘手的问题，但现在它变得越来越难了。

Do you worry about some of the, um, concerns of bots being present on social networks more and more humanlike bots that are not necessarily trying to do a good thing, or they might be explicitly trying to do a bad thing like phishing scams? Yeah, like social engineering, all that kind of stuff, which has always been a very difficult problem for social networks, but now it's becoming almost a more and more difficult problem.

嗯，我认为这有几个不同的方面。首先，我们需要对抗和预防所有这些危害。过去五到七年，我们的重点之一就是大力建设非常复杂的 AI 系统——不是生成式 AI，而是更传统的 AI 系统——来分类和识别：这篇帖子看起来在宣扬恐怖主义，这篇在剥削儿童，这篇可能试图煽动暴力，这篇侵犯知识产权。总共有 18 种不同的违规有害内容类别，我们不得不建立专门的系统来追踪。我认为生成式 AI 的进步肯定会考验这些系统。但至少到目前为止，情况是这样，而且我乐观地认为未来也会如此：我们将能够投入更多的算力，拥有更强大的 AI 来帮助防御这些威胁。我们以前也处理过一些对抗性问题。比如仇恨言论，人们通常不会变得更狡猾。比如一个说种族主义言论的人，他们不一定在种族主义方面变得更狡猾。所以系统——

Well, I think there are a few different parts of this. So one is, there are all these harms that we need to basically fight against and prevent. And that's been, you know, a lot of our focus over the last, you know, five or seven years, is basically ramping up very sophisticated AI systems — not generative AI systems, more kind of classical AI systems — to be able to, um, you know, categorize and classify and identify: okay, this post looks like it's promoting terrorism, this one is, you know, like exploiting children, this one is, um, looks like it might be trying to incite violence, this one's intellectual property violation. So there's like 18 different categories of violating, kind of, harmful content that we've had to build specific systems to be able to track. And, um, I think it's certainly the case that advances in generative AI will test those. But at least so far, it's been the case, and I'm optimistic that it will continue to be the case, that we will be able to bring more computing power to bear to have even stronger AIs that can help defend against those things. So, um, we've had to deal with some adversarial issues before, right? I mean, for some things like hate speech, it's like people aren't generally getting a lot more sophisticated. Like the average person who, let's say, you know, someone's saying some kind of racist thing, right? It's like they're not necessarily getting more sophisticated at being racist, right? It just — okay, so that the system —

你能找到，但还有一些对手非常老练，比如国家行为体。我们发现了，无论是俄罗斯还是其他一些国家，它们基本上在搭建这些机器人或虚假账号网络——我们称之为“虚假账号”，因为它们不一定是机器人；有些可能是真人冒充他人，但以协调方式行动。其中一些行为已经变得非常复杂且极具对抗性。每次我们找到并阻止它们，它们就会演化行为。它们不会就此收手。有时它们可能觉得在 Meta 服务上做不值得，就会去别处，如果其他地方更容易的话。但我们有相当多的经验来应对这类不断升级的对抗性攻击。而且我确实认为，只要我们能够持续投入更多算力，并且我们在开发一些 AI 模型方面处于领先地位，我相当乐观地认为我们能够持续打击你提到的那些常见危害类别：欺诈、诈骗、垃圾信息、知识产权侵权等等。

You can just find, but then there are other adversaries who actually are very sophisticated, like nation states doing things. And we find you, whether it's Russia or just different countries that are basically standing up these networks of bots or inauthentic accounts—that's what we call them because they're not necessarily bots; some of them could actually be real people who are masquerading as other people, but they're acting in a coordinated way. And some of that behavior has gotten very sophisticated and very adversarial. So each iteration, every time we find something and stop them, they kind of evolve their behavior. They don't just pack up their bags and go home. At some point they might decide doing it on Meta services is not worth it; they'll go do it on someone else if it's easier to do it in another place. But we have a fair amount of experience dealing with even those kind of adversarial attacks where they just keep on getting better and better. And I do think that as long as we can keep on putting more compute power against it, and if we're kind of one of the leaders in developing some of these AI models, I'm quite optimistic that we're going to be able to keep on pushing against the normal categories of harm that you talk about: fraud, scams, spam, IP violations, things like that.

那制造叙事和争议呢？对我来说，一小撮——嗯，你刚才说的——虚假账号，可能是机器人，但我们有个有趣的名字，叫“协调性虚假行为”。确实，一小群人就能制造叙事、编造故事，尤其是如果它们能病毒式传播，特别是如果它们有能催化叙事病毒性的元素，这挺不可思议的。

What about creating narratives and controversy? To me, it's kind of amazing how a small collection of—yeah, what did you say—inauthentic accounts, so it could be bots, but yeah, I mean we have this funny name for it, but we call it coordinated inauthentic behavior. Yeah, it's kind of incredible how a small collection of folks can create narratives, create stories, especially if they're viral, especially if they have an element that can catalyze the virality of the narrative.

是的，我认为问题在于你必须非常具体地指出哪里不好，对吧？因为我觉得一群人聚在一起，或者自然地碰撞想法，然后产生一个叙事，这本身不一定是坏事，如果它是真实和自然的。很多文化创造和艺术创作就是这样发生的，还有很多好东西。所以我们才专注于“协调性虚假行为”这个概念。也就是说，如果你有一个网络——无论是机器人，还是有些人冒充不同账号——但有人在背后操纵，试图让它看起来更自然，但实际上并非如此，只是一个协调性的东西，那在我看来就有问题。我的意思是，我认为人们不应该能够拥有协调性网络而不披露这一点。但同样，我们已经能够部署相当先进的 AI 和反恐团队等，来识别相当多的这类协调性虚假账号网络并予以清除。我们一直在这样做。而且我觉得，如果你 20 年前告诉我，‘好吧，你创办这个网站是为了帮助大学里的人们联系，未来你的组织的一部分将是一个用 AI 寻找协调性虚假行为的反恐组织’——我会觉得那太疯狂了。但这就是我们现在的处境。不过，我认为你现在追问的这些问题——实际上，我猜测在可预见的未来，AI 的大部分挑战都将集中于此。关于‘这会不会给人类带来生存风险’之类的问题有很多争论。这些很难从任何一方证伪。我个人的直觉是，我们接近超级智能的那个点——我不太清楚当前的技术是否能在没有另一系列重大突破的情况下达到那里。但这并不意味着没有危险。我认为危险基本上在于放大了人们或账号群体所能造成的已知危害类型，我们只需要确保我们真正专注于尽可能好地应对这一点。所以这绝对是我关注的重点。

Yeah, I think the question is you have to be very specific about what is bad about it, right? Because I think a set of people coming together or organically bouncing ideas off each other and a narrative comes out of that is not necessarily a bad thing by itself, if it's kind of authentic and organic. That's a lot of what happens and how culture gets created and how art gets created and a lot of good stuff. So that's why we've kind of focused on this sense of coordinated inauthentic behavior. So it's like if you have a network of—whether it's bots, some people masquerading as different accounts—but you have someone pulling the strings behind it and trying to act as if this is a more organic set of behavior but really it's not, it's just one coordinated thing that seems problematic to me. I mean, I don't think people should be able to have coordinated networks and not disclose it as such. But that again, we've been able to deploy pretty sophisticated AI and counterterrorism groups and things like that to identify a fair number of these coordinated inauthentic networks of accounts and take them down. We continue to do that. And I think it's one thing that if you told me 20 years ago, 'All right, you're starting this website to help people connect at a college, and in the future you're going to be part of your organization—it's going to be a counterterrorism organization with AI to find coordinated inauthentic behavior'—I would have thought that was pretty wild. But that's part of where we are. But look, I think that these questions that you're pushing on now—this is actually where I'd guess most of the challenge around AI will be for the foreseeable future. I think there's a lot of debate around things like 'Is this going to create existential risk to humanity?' And those are very hard things to disprove one way or another. My own intuition is that the point where we become close to superintelligence is—it's just really unclear to me that the current technology is going to get there without another set of significant advances. But that doesn't mean there's no danger. I think the danger is basically amplifying the kind of known set of harms that people or sets of accounts can do, and we just need to make sure that we really focus on doing that as well as possible. So that's definitely a big focus for me.

嗯，你基本上可以把大语言模型当作如何在社交网络上造成危害的助手。所以你可以问它一个问题——你知道，Meta 有非常强大的协调性虚假账号打击能力——‘我如何创建 Meta 检测不到的协调性虚假账号？’就像直接问那个问题。基本上，这就是 OpenAI 所展示的他们担心这类问题。也许你可以评论一下你的方法：如何对这些模型的输出进行某种审核，使其不能被用来帮助你协调危害——在危害的完整定义下。

Well, you can basically use large language models as an assistant of how to cause harm on a social network. So you can ask it a question—you know, Meta has very impressive coordinated inauthentic account fighting capabilities—'How do I do coordinated inauthentic account creation where Meta doesn't detect it?' Like literally ask that question. And basically there's this kind of—I mean, that's what OpenAI showed that they're concerned with those questions. Perhaps you can comment on your approach to it: how to do a kind of moderation on the output of those models so that it can't be used to help you coordinate harm in the full definition of what harm means.

是的，这很大程度上就是我们做的微调和对齐训练。基本上，当我们在产品中部署 AI 时，我们主要确保的是你不能让它帮你犯罪，对吧？所以我认为训练它理解这一点——而且这些系统永远不会 100% 完美——但只是让它不成为做坏事的更容易的途径，相比次优选择。我的意思是，人们还有谷歌，对吧？你还有搜索引擎。所以信息就在那里。而且根据我们的观察，对于国家行为体或那些试图搭建大型协调性虚假网络以影响各种事务的参与者，一旦我们让事情变得非常困难，他们确实会尝试使用其他服务。就像如果你能让他们在你的服务上做这件事的成本更高，他们就会去别处。我认为这就是标准。不是说‘你能完美地找到每一个试图攻击你的对手吗？’你尽可能接近完美，但我认为实际上，从经济角度来说，你只是试图让他们攻击你变得低效。但还有一些复杂的问题：什么是危害，什么不是；什么是虚假信息，什么不是。这也是 Wikipedia 试图面对的问题之一。我记得问过 GPT 病毒是否从……泄露。

Yeah, and that's a lot of the fine-tuning and the alignment training that we do. Basically, when we ship AI across our products, a lot of what we're trying to make sure is that you can't ask it to help you commit a crime, right? So I think training it to understand that—and it's not like any of these systems are ever going to be 100% perfect—but just making it so that this isn't an easier way to go about doing something bad than the next best alternative. I mean, people still have Google, right? You still have search engines. So the information is out there. And for what we see, like for nation states or these actors that are trying to pull off these large coordinated inauthentic networks to influence different things, at some point when we just make it very difficult, they do just try to use other services instead. It's just like if you can make it more expensive for them to do it on your service, then people go elsewhere. And I think that's the bar. It's not like 'Are you ever going to be perfect at finding every adversary who tries to attack you?' You try to get as close to that as possible, but I think really, economically, what you're just trying to do is make it inefficient for them to go after that. But there are also complicated questions of what is and isn't harm, what is and isn't misinformation. So this is one of the things that Wikipedia has also tried to face. I remember asking GPT about whether the virus leaked from a...

实验室与否，给出的答案非常微妙，而且引证得当，我甚至敢说深思熟虑、平衡周全。我担心这种微妙之处会在审核过程中丢失。维基百科在那方面做得不错，但在政府和机构的压力下，你会看到一些信息、事实和智慧的微妙与深度丢失了。确实，这很可怕。一些魔力、一些棱角、粗糙的边缘可能会在 AI 系统的审核过程中丢失。那么，如何把这件事做对呢？

Lab or not and the answer provided was a very nuanced one and a well-sited one, almost dare I say well thought out one, balanced. I would hate for that nuance to be lost through the process of moderation. Wikipedia does a good job on that particular thing too, but from pressures from governments and institutions, you could see some of that nuance and depth of information, facts, and wisdom be lost. Absolutely, and that's a scary thing. Some of the magic, some of the edges, the rough edges might be lost to the process of moderation of AI systems. So how do you get that right?

我非常认同你提出的观点。问题的核心在于，有些危害我认为大家都认为是坏的，对吧？比如儿童性剥削，你不会找到多少人认为这类内容应该被允许出现在任何服务上，对吧？这是我们面临并尽力去阻止的事情。你知道，恐怖主义、煽动暴力，对吧？我们之前处理过很多这类危害。但我也认为，还有一些危害存在更多的社会争议。所以，错误信息，我认为一直非常棘手，因为有些东西明显是假的，但可能只是事实错误，并不有害。比如，你会因为某人只是说错了就审查他们吗？如果他们的行为没有造成任何危害，我认为那里存在很多真正的问题和挑战。但我也认为，在其他地方，比如疫情早期关于 COVID 的一些内容，有真实的健康影响，但还没有时间充分审查一堆科学假设。不幸的是，我认为很多权威机构在那方面对一些事实含糊其辞，并要求审查很多东西，结果事后看来这些内容更有争议或是真实的。这真的很棘手，对吧？严重破坏了信任。所以我确实认为，如何管理这些问题非常微妙。我尝试思考的方式是，最好一般归结为人们公认的危害。所以当你考虑某件事是不是错误信息时，我认为更关键的一点是：这会不会潜在地导致某人受到身体伤害？从这个角度去思考。除此之外，我认为人们只是对如何标记信息有不同的偏好。我认为很多人会倾向于在内容上加一个标签，说“嘿，事实核查员认为这可能是假的”。或者，我认为 Twitter 的社区笔记实现在这方面相当不错。但同样，这是同一类事情：只是酌情添加一个标签，因为它改善了用户体验，但并不是要删除信息。我认为你应该把内容审查限制在人们普遍认为不好的已知类别上。

I really agree with what you're pushing on. I mean, the core shape of the problem is that there are some harms that I think everyone agrees are bad, right? So sexual exploitation of children, like you're not going to get many people who think that type of thing should be allowed on any service, right? And that's something that we face and try to push off as much as possible. You know, terrorism, inciting violence, right? It's like we went through a bunch of these types of harms before. But then I do think that you get to a set of harms where there is more social debate around it. So misinformation, I think, has been a really tricky one because there are things that are kind of obviously false, right, that are maybe factual but may not be harmful. Since like, all right, are you going to censor someone for just being wrong? If there's no kind of harm implication of what they're doing, I think that there's a bunch of real issues and challenges there. But then I think that there are other places where it is, you just take some of the stuff around COVID earlier on in the pandemic, where there were real health implications but there hadn't been time to fully vet a bunch of the scientific assumptions. And unfortunately, I think a lot of the kind of establishment on that kind of waffled on a bunch of facts and asked for a bunch of things to be censored that in retrospect ended up being more debatable or true. And that stuff is really tough, right? Really undermines trust in that. And so I do think that the questions around how to manage that are very nuanced. The way that I try to think about it is that it goes, I think it's best to generally boil things down to the harms that people agree on. So when you think about, is something misinformation or not? I think often the more salient bit is, is this going to potentially lead to physical harm for someone? And kind of think about it in that sense. And then beyond that, I think people just have different preferences on how they want things to be flagged for them. I think a bunch of people would prefer to have a flag on something that says, hey, a fact checker thinks that this might be false. Or yeah, I think Twitter's Community Notes implementation is quite good on this. But again, it's the same type of thing: it's just kind of discretionarily adding a flag because it makes the user experience better, but it's not trying to take down the information or not. I think that you want to reserve the kind of censorship of content to things that are of known categories that people generally agree are bad.

是的，但有很多事情，尤其是疫情，还有其他话题，存在由政治驱动的深刻分歧，关于什么有害、什么无害。甚至只是病毒有害的程度，以及疫苗应对病毒有害的程度，都存在几乎像政治分歧一样的东西。那么，当美国一半的人或世界上很大一部分人与另一部分人观点截然不同时，你如何做出决定？Meta 能对这方面的审核感到自豪吗？

Yeah, but there's so many things, especially with the pandemic, but there's other topics where there's just deep disagreement fueled by politics about what is and isn't harmful. There's even just the degree to which the virus is harmful and the degree to which the vaccines respond to the virus are harmful. There's just almost like a political divide around that. And so how do you make decisions about that where half the country in the United States or some large fraction of the world has very different views from another part of the world? Is there a way for Meta to be proud of the moderation of this?

我认为完全回避非常困难，但我们应该清楚哪些是真正的安全问题，哪些是人们在信息标记方式上的偏好问题。对，我们最近推出了一项功能，允许人们让事实核查不影响他们看到的产品内容的分布。好吧，很多人不信任事实核查员是谁。没问题，如果你愿意，可以关掉它。但如果内容违反了某些政策，比如煽动暴力之类，它仍然不会被允许。所以我认为你应该尽可能尊重人们在那方面的偏好。但你看，这真的很难。我认为很难界定事实和观点的界限，因为科学的本质是没有任何东西是 100% 确定的。你可以证伪某些东西，但你不断测试新假设，审视长期持有的框架，偶尔你会推翻一个长期有效的东西。这非常困难。但我认为，仅仅因为很难、仅仅因为存在边缘案例，并不意味着你不应该也努力给人们他们想要的东西。

I think it's very difficult to just abstain, but I think we should be clear about which of these things are actual safety concerns and which ones are a matter of preference in terms of how people want information flagged. Right, so we did recently introduce something that allows people to have fact-checking not affect the distribution of what shows them their product. So okay, a bunch of people don't trust who the fact checkers are. All right, well you can turn that off if you want. But if the content violates some policy, like it's inciting violence or something like that, it's still not going to be allowed. So I think that you want to honor people's preferences on that as much as possible. But look, I mean this is really difficult stuff. I think it's really hard to know where to draw the line on what is fact and what is opinion, because the nature of science is that nothing is ever 100% known for certain. You can disprove certain things, but you're constantly testing new hypotheses and scrutinizing frameworks that have been long held, and every once in a while you throw out something that was working for a very long period of time. And it's very difficult. But I think that just because it's very hard and just because there are edge cases doesn't mean that you should not try to give people what they're looking for as well.

让我问一个你在审核方面面临的问题：来自不同来源的压力，来自政府的压力。我想问，在一个 AI 审核也开始成为现实的世界里，如何抵御这种压力？那么，Meta 在审核什么、不审核什么方面，如何抵抗来自政府和其他利益集团的压力？

Let me ask about something you faced in terms of moderation: pressure from different sources, pressure from governments. I want to ask how to withstand that pressure for a world where AI moderation starts becoming a thing too. So what's Meta's approach to resist the pressure from governments and other interest groups in terms of what to moderate and not?

我不认为有一个放之四海而皆准的答案。我认为我们基本上有原则：我们希望尽可能允许人们表达，但我们制定了明确的类别，我们认为哪些是错的、不希望出现在我们的服务上，并构建工具来尝试审核这些内容。那么问题来了，当政府说他们不希望某些内容出现在服务上时，你该怎么办？我认为我们有一堆关于如何处理这种情况的原则。因为一方面，如果是一个民选政府，世界各地不同地方有不同的价值观，那么我们作为一家加州公司，是否应该告诉他们，他们认定不可接受的东西实际上我们需要能够表达？我认为需要一定的谦逊。但另一方面，我认为还有其他情况，比如更专制一些，有一个独裁领导人试图压制异议。

I don't know that there's like a one-size-fits-all answer to that. I think we basically have the principles around, you know, we want to allow people to express as much as possible, but we have developed clear categories of things that we think are wrong that we don't want on our services, and we build tools to try to moderate those. So then the question is, okay, what do you do when a government says that they don't want something on the service? And I think we have a bunch of principles around how we deal with that. Because on the one hand, if there's a democratically elected government and people around the world just have different values in different places, then should we as a California-based company tell them that something they have decided is unacceptable actually that we need to be able to express that? I mean, I think that there's a certain amount of humility that is needed. But then I think there are other cases where it's a little more autocratic and you have a dictator leader who's just trying to crack down on dissent.

一个国家的人民真的不认同这一点，这也不一定违背他们的文化，但领导该国的人只是试图朝某个方向推动。这些都是非常复杂的问题。我认为很难有一个放之四海而皆准的方法。但总的来说，我们非常积极地倡导并抵制下架内容的请求。老实说，审查内容的请求是一回事，那显然很糟糕。但我们划出更严格红线的是获取信息的请求。如果你被告知不能说某些话，那很糟糕，它在某种程度上侵犯了你的言论自由感。但政府以在我们国家看来非法的方式获取数据，会让人们面临实际的人身伤害。这是我们非常重视的事情。所以这一点在很多方面贯穿了我们所有的政策。当你真正与政府诉讼或抵制他们时，那已经是漏斗的末端了。很多事情在更上游就开始了，比如决定在哪里建设数据中心。有很多国家，我们可能有很多用户在那里，如果我们能在附近建数据中心降低延迟，对服务和用户都有好处。但出于某种原因，我们就是觉得这个政府在保护用户数据方面记录不佳。归根结底，如果你在一个国家建了数据中心，而政府想获取用户数据，他们可以派人持枪强行夺取。所以我认为，在真正发生冲突的很多年前，就有很多关于如何架构系统的决策，这些决策最终非常重要。我们把保护用户数据作为非常高的优先级。我认为与之相关的危害可能更多，而这最终成为抵御政府时更关键的事情。而如果另一个国家对什么算是可接受的言论有不同的看法，尤其是如果它是一个民选政府，那么我认为你应该对其有一定程度的尊重。这更多是在说当政府获取数据时可能造成的直接伤害。

People in a country are really not aligned with that, and it's not necessarily against their culture, but the person who's leading it is just trying to push in a certain direction. These are very complex questions. I think it's difficult to have a one-size-fits-all approach to it. But in general, we're pretty active in advocating and pushing back on requests to take things down. Honestly, a request to censor things is one thing, and that's obviously bad. But where we draw a much harder line is on requests for access to information. If you get told that you can't say something, that's bad, it violates your sense of freedom of expression at some level. But a government getting access to data in a way that seems unlawful in our country exposes people to real physical harm. That's something we take very seriously. So that flows through all of our policies in a lot of ways. By the time you're actually litigating with a government or pushing back on them, that's pretty late in the funnel. A bunch of the stuff starts a lot higher up in the decision of where do we put data centers. There are a lot of countries where we may have a lot of people using the service, and it might be good for the service and for those people if we could reduce latency by having a data center nearby. But for whatever reason, we just feel like this government does not have a good track record on not trying to get access to people's data. At the end of the day, if you put a data center in a country and the government wants to get access to people's data, they have the option of having people show up with guns and taking it by force. So I think there are a lot of decisions that go into how you architect the systems years in advance of these actual confrontations that end up being really important. We put the protection of people's data as a very high priority. I think there are more harms that can be associated with that, and that ends up being a more critical thing to defend against governments. Whereas if another government has a different view of what should be acceptable speech in their country, especially if it's a democratically elected government, then I think there's a certain amount of deference that you should have to that. That's speaking more to the direct harm that's possible when you give governments access to data.

但如果我们看美国，更微妙的审查压力——甚至不是命令审查，而是来自政治实体的审查压力——在美国受到了相当多的关注。也许问这个问题的一个方式是：如果你看过 Twitter 文件，你从 Twitter 文件中看到的来自美国政府机构的压力中学到了什么，你如何应对这种压力？

But if we look at the United States, to the more nuanced kind of pressure to censor—not even order to censor, but pressure to censor from political entities—which has received quite a bit of attention in the United States. Maybe one way to ask that question is: if you've seen the Twitter Files, what have you learned from the kind of pressure from US government agencies that was seen in the Twitter Files, and what do you do with that kind of pressure?

我看过了。从外部很难确切知道每个案例中到底发生了什么。我们显然也经历过很多自己的案例，其中机构或不同的人会说：‘嘿，这是我们意识到的威胁，你也应该意识到这一点。’这与其说是压力，不如说是在提醒我们的安全系统应该警惕的事情。我理解有些人可能会认为那是压力。但归根结底，如何处理是我们自己的决定。在运营这些服务方面，我希望尽可能多地获取关于人们认为对手可能试图做什么的信息。

I've seen it. It's really hard from the outside to know exactly what happened in each of these cases. We've obviously been in a bunch of our own cases where agencies or different folks will just say, 'Hey, here's a threat that we're aware of, you should be aware of this too.' It's not really pressure as much as it is just flagging something that our security systems should be on alert about. I get how some people could think of it as that. But at the end of the day, it's our call on how to handle that. In terms of running these services, I want to have access to as much information about what people think that adversaries might be trying to do as possible.

所以你不觉得会有后果吗，如果——你知道，任何人——中情局、联邦调查局、某个政党、民主党或共和党、位高权重的政治人物——对吧？邮件？你不觉得来自他们的压力？

So you don't feel like there would be consequences if, you know, anybody—the CIA, the FBI, a political party, the Democrats or the Republicans, high powerful political figures—right? Emails? You don't feel pressure from them?

我想说的是：来自各方的压力如此之大，我不确定任何一个人说的某件具体事情是否真的给局面增加了多少分量。显然有很多人认为我们应该审查更多内容，也有很多人认为我们应该审查更少内容。正如你所说，有各种各样的团体参与这些辩论。所以有民选官员和政治人物本身，有机构，还有媒体、活动团体。这不是美国特有的问题；世界各地、每个国家都有带来不同价值观的团体。所以这是一个非常活跃的辩论，我理解这一点。这些问题触及了一些正在进行的最重要的社会辩论。这又回到了真相的问题，因为很多事情还没有固化成一个单一的真相，社会正在试图厘清我们在某些问题上的看法。也许几百年后，每个人都会回顾说：‘嘿，不，当时并不明显应该是这样。’但我们现在就在那个绞肉机里，正在经历这个过程。所以不，这些都是非常复杂的。有些人出于善意提出担忧，只是说：‘嘿，这是我想提醒你考虑的事情。’而有些人，我确实认为，带着某种惩罚性或报复性的观点：‘我要你做这件事，如果你不做，我就会在很多其他方面让你的日子不好过。’但我不确定，这是社会中最有压力的辩论之一。我只是认为有太多的人和不同的力量试图从不同方面施加压力，以至于我认为你不能根据试图取悦他人来做决定。我认为你只能做你认为正确的平衡，并接受无论你站在哪一边，都会有人不满。

I guess what I'd say is: there's so much pressure from all sides that I'm not sure that any specific thing that someone says is really adding that much more to the mix. There are obviously a lot of people who think that we should be censoring more content, or a lot of people who think we should be censoring less content. There are, as you say, all kinds of different groups that are involved in these debates. So there's the elected officials and politicians themselves, there's the agencies, but also the media, activist groups. This is not a US-specific thing; there are groups all over the world, in every country, that bring different values. So it's a very active debate, and I understand it. These questions get to really some of the most important social debates that are being had. It gets back to the question of truth, because for a lot of these things they haven't yet been hardened into a single truth, and society is sort of trying to hash out what we think on certain issues. Maybe in a few hundred years everyone will look back and say, 'Hey, no, it wasn't obvious that it should have been this.' But we're kind of in that meat grinder now, working through that. So no, these are all very complicated. Some people raise concerns in good faith and just say, 'Hey, this is something that I want to flag for you to think about.' Certain people, I certainly think, come at things with somewhat of a more punitive or vengeful view: 'I want you to do this thing, if you don't then I'm going to try to make your life difficult in a lot of other ways.' But I don't know, this is one of the most pressurized debates in society. I just think there are so many people and different forces that are trying to apply pressure from different sides that I don't think you can make decisions based on trying to make people happy. I think you just have to do what you think is the right balance and accept that people are going to be upset no matter where you come out on that.

是的，我喜欢‘有压力的辩论’这个说法。那么你对言论自由的看法这些年是如何演变的，现在有了 AI，自由可能不仅适用于人类，也适用于你谈到的个性化智能体？

Yeah, I like that 'pressurized debate'. So how has your view of the freedom of speech evolved over the years, and now with AI where the freedom might apply not just to humans but to the personalized agents as you've spoken about them?

我可能已经形成了一种更细致的看法，因为我觉得……我显然非常支持言论自由。你不会去构建一个给人们表达工具的服务，除非你认为大规模表达是一件好事。所以我做这件事不是为了阻止任何人表达任何东西。我想给人们工具，让他们尽可能多地表达。然后我发现，有些类别的东西，几乎所有人都认为是坏的、没人想要的，甚至在美国这样第一修正案非常保护言论的国家也是非法的。比如你仍然不能做那些会立即煽动暴力或侵犯他人知识产权的事情。所以有这些类别。但社会中还存在一个非常活跃的核心，就是积极的意见分歧——一些人可能认为某事是真的，另一方可能认为是假的，或者根本没有定论。这些是最难处理的，就像我们讨论过的。但我学到的一个教训是，很多时候，处理这类问题最实际的方式不是回答“这该不该被允许？”，而是“处理一个混蛋的最佳方式是什么？”这个人是不是基本上有重复行为，造成了大量问题？所以从那个层面看，以及它对更广泛社区健康的影响。但这很棘手，因为你如何知道？可能有人持有非常有争议的观点，结果却对社区健康产生了长期的积极影响，因为它挑战了社区。

Probably gotten a somewhat more nuanced view just because I think that there are... I come at this obviously very pro freedom of expression. I don't think you build a service like this that gives people tools to express themselves unless you think that people expressing themselves at scale is a good thing. So I didn't get into this to try to prevent people from expressing anything. I want to give people tools so they can express as much as possible. Then I think it's become clear that there are certain categories of things that we've talked about that almost everyone accepts are bad and that no one wants, and that are illegal even in countries like the US where the First Amendment is very protective of enabling speech. It's like you're still not allowed to do things that are going to immediately incite violence or violate people's intellectual property or things like that. So there are those. But then there's also a very active core of just active disagreements in society where some people may think that something is true or false, the other side might think it's the opposite, or just unsettled. And those are some of the most difficult to handle, like we've talked about. But one of the lessons that I feel like I've learned is that a lot of times, the best way to handle this stuff more practically is not in terms of answering the question of 'should this be allowed?' but just like 'what is the best way to deal with someone being a jerk?' Is the person basically just having a repeat behavior of causing a lot of issues? So looking at it more at that level and its effect on the broader community's health. It's tricky though because how do you know? There could be people that have a very controversial viewpoint that turns out to have a positive long-term effect on the health of the community because it challenges the community.

确实如此，绝对是这样。

That's true, absolutely.

是的，不，我认为你需要小心这一点。我不确定我是否表达得很清楚，因为我当然同意你的观点。我的意思不是说我们不应该让有争议的人出现在我们的服务上。那绝对不是我想说的。我的意思是，通常我认为，处理这些事情最有效的方式不是只看一个具体的言论例子。而且我认为你通常不想做出‘这个允许或这个不允许’的二元决定。我们讨论过事实核查或 Twitter 的社区声音功能。那是另一个好例子。这不是允许不允许的问题，而是给事情添加更多背景的问题。我认为这很有帮助。所以在 AI 的背景下，也就是你问的问题，AI 有很多方式可以提供帮助。对于 AI，它更少关乎审查，因为更多是关于什么是对问题最有成效的回答。有一个我和团队一起审查的案例研究：有人问‘你能解释一下如何 3D 打印一把枪吗？’一个提议的回应是‘不，我不能谈论这个。’基本上就是立即关闭，我认为这是你看到的一些情况——‘作为一个大型语言模型，我不被允许谈论任何东西。’但还有另一种回应，比如‘嘿，你知道，我不认为这是个好主意。在很多国家，包括美国，3D 打印枪支是非法的，’或者任何事实性的东西。我当时想，好吧，这实际上是一个尊重且信息丰富的回答。而且，我可能不知道那个具体的事情。所以有不同方式来处理这个。我认为你可以要么假设善意——也许那个人不知道，我只是要帮助他们教育——要么你可以像‘不，我需要立即关闭这件事。我就是不打算谈论这个。’有时候你可能需要那样做，但我实际上认为，采取一种更具信息性的方法，通常假设人们有善意，可能是在尽可能多的事情上更好的平衡。你不可能对所有事情都这样做，但你问的是我如何处理这个问题，我正在思考这与 AI 的关系。我认为这是在不同模式下处理敏感内容的一个重大区别。

Yeah, no, I think you want to be careful about that. I'm not sure I'm expressing this very clearly, because I certainly agree with your point there. And my point isn't that we should not have people on our services that are being controversial. That's certainly not what I mean to say. It's that often I think it's not just looking at a specific example of speech that it's most effective to handle the stuff. And I think often you don't want to make specific binary decisions of 'this is allowed or this isn't.' I mean, we talked about fact-checking or Twitter's Community Voices thing. That's another good example. It's like it's not a question of is this allowed or not; it's just a question of adding more context to the thing. And I think that's helpful. So in the context of AI, which is what you were asking about, there are lots of ways that an AI can be helpful. With an AI, it's less about censorship, because it's more about what is the most productive answer to a question. There was one case study that I was reviewing with the team: someone asked, 'Can you explain to me how to 3D print a gun?' And one proposed response is like, 'No, I can't talk about that.' It's basically just shut it down immediately, which I think is some of what you see—'As a large language model, I'm not allowed to talk about whatever.' But there's another response which is like, 'Hey, you know, I don't think that's a good idea. In a lot of countries, including the US, 3D printing guns is illegal,' or whatever the factual thing is. And I was like, okay, that's actually a respectful and informative answer. And you know, I may have not known that specific thing. So there are different ways to handle this. I think you can either assume good intent—like maybe the person didn't know and I'm just going to help educate them—or you could come at it as like, 'No, I need to shut this thing down immediately. I'm just not going to talk about this.' And there may be times where you need to do that, but I actually think having a somewhat more informative approach where you generally assume good intent from people is probably a better balance to be on as many things as you can. You're not going to be able to do that for everything, but you're kind of asking about how I approach this and I'm thinking about this as it relates to AI. And I think that's a big difference in how to handle sensitive content across these different modes.

我不得不问：有传言说你可能在开发一个基于文本的社交网络，可能是 Twitter 的竞争对手，代号 P92。你能对这些传言说些什么吗？

I have to ask: there's rumors you might be working on a social network that's text-based, that might be a competitor to Twitter, code named P92. Is there something you can say about those rumors?

确实有一个项目。你知道，我一直认为那种基于文本的信息工具对社会来说非常重要。而且不知为何，我觉得 Twitter 没有达到我认为它应有的全部潜力。我认为现在的……我觉得 Elon 也这么认为，这可能是他收购它的原因之一。我确实认为有办法考虑替代方案。其中一个我觉得可能有趣的是这种开放和联邦化的方法，你在 Mastodon 上看到了，在 BlueSky 上也看到了一点。我认为有可能将其中一些想法与人们已经在 Instagram 上建立的图谱和身份系统融合起来，这可能对这个领域是一个非常受欢迎的贡献。但我知道我们一直在做很多事情，所以我不想操之过急。我们有探索很多不同事物的项目，这当然是一个我认为可能有趣的项目。

There is a project. You know, I've always thought that sort of a text-based kind of information utility is just a really important thing to society. And for whatever reason, I feel like Twitter has not lived up to what I would have thought its full potential should be. And I think that the current... I think Elon thinks that right, and that's probably one of the reasons why you bought it. And I do think that there are ways to consider alternative approaches to this. And one that I think is potentially interesting is this open and federated approach where you're seeing with Mastodon and you're seeing that a little bit with BlueSky. And I think that it's possible that something that melds some of those ideas with the graph and identity system that people have already cultivated on Instagram could be a kind of very welcome contribution to that space. But I know we work on a lot of things all the time though too, so I don't want to get ahead of myself. We have projects that explore a lot of different things, and this is certainly one that I think could be interesting.

那么，那个的发布启动日期是什么？或者官方网站是什么？

So what's the release launch date of that again? Or what's the official website?

嗯，我们还没有那个。好吧，但我……好的。而且你看，我的意思是，我不确切知道这会如何发展。我的意思是，我能说的是，是的，有一些人在做这个。我认为那里有一些值得探索的有趣东西。

Well, we don't have that yet. Okay, but I... All right. And look, I mean, I don't know exactly how this is going to turn out. I mean, what I can say is yeah, there's some people working on this right. I think that there's something there that is interesting to explore.

如果你看看这个，问这个问题并把 Twitter 放进去会很有趣。在 Facebook、Instagram、WhatsApp 的社交网络格局中，然后考虑一个基于文本的社交网络。当你看到这个格局时，对你来说有哪些有趣的差异？为什么我们有这些不同的风格？需求是什么，用例是什么，产品是什么？哪个方面……

If you look at it, it'd be interesting to just ask this question and throw Twitter into the mix. At the landscape of social networks that is Facebook, that is Instagram, that is WhatsApp, and then think of a text-based social network. When you look at that landscape, what are the interesting differences to you? Why do we have these different flavors? What are the needs, what are the use cases, what are the products? What is the aspect of...

它们创造了充实的人类体验，以及某种独特的人类之间的联系。

Them that create a fulfilling human experience and a connection between humans that is somehow distinct.

嗯，我认为文字非常便于人们传递思想和进行来回交流。所以它在很多方面都是一种很好的讨论形式，独特地好。如果你看看其他专注于单一内容类型的格式或网络，比如 TikTok 显然很庞大，上面也有评论，但架构很明显是视频为主，评论是附属品。但基于文字的内容有一个独特之处，就是评论也可以是一等公民。这使得对话可以过滤并分叉到各种不同的方向，这非常有用。所以这个体验有很多很棒的地方。我一直觉得 Twitter 应该有十亿用户，或者任何最终占据这个空间的东西。无论出于什么原因，这些公司都是复杂的有机体，从外部很难诊断为什么一个以文字评论为一等公民的社交网络没有十亿用户。

Well, I think text is very accessible for people to transmit ideas and have back-and-forth exchanges. So it ends up being a good format for discussion in a lot of ways, uniquely good. If you look at other formats or networks focused on one type of content, like TikTok is obviously huge, and there are comments on TikTok, but the architecture is clearly that the video is primary and comments are afterthought. But one unique piece of having text-based content is that the comments can also be first-class. That makes it so conversations can filter and fork into all these different directions, which can be super useful. So there are a lot of things that are really awesome about the experience. It always struck me that Twitter should have a billion people using it, or whatever ends up being in that space. For whatever combination of reasons, these companies are complex organisms, and it's very hard to diagnose from the outside why a text-based, comment-as-first-citizen social network doesn't have a billion users.

为什么 Twitter，为什么一个以文字评论为一等公民的社交网络没有十亿用户？

Why doesn't Twitter, why doesn't a text-based comment-as-first-citizen social network have a billion users?

嗯，我只是觉得建立这些公司很难。并不是每个想法都能自动获得十亿用户。只是这个想法加上好的执行应该能达到。但你看，我们随着时间的推移达到了某些门槛。早期我们遇到了平台期，不清楚 Facebook 是否能达到一亿用户。然后我们非常擅长国际化，帮助服务在不同国家增长。那是我们需要培养的一整套能力。帮助人们把服务传播给朋友，一旦我们非常擅长这一点，就让我觉得如果 Instagram 早期加入我们，我们可以帮助它快速增长，WhatsApp 也一样。我认为这已经成为我们培养并能够执行的核心能力，其他人也有。字节跳动显然在 TikTok 上做得很好，在那里达到了超过十亿用户。但这当然不是自动的。你需要一定水平的执行才能达到。不管出于什么原因，Twitter 有这个好主意和服务的魔力，但他们就是还没有破解那部分。这就是为什么你看到所有这些其他东西，无论是 Mastodon 还是 BlueSky，可能都是对同一事物的不同尝试。

Well, I just think it's hard to build these companies. It's not that every idea automatically gets a billion people. It's just that that idea coupled with good execution should get there. But look, we hit certain thresholds over time. We kind of plateaued early on, and it wasn't clear we were ever going to reach 100 million people on Facebook. Then we got really good at dialing in internationalization and helping the service grow in different countries. That was a whole competence we needed to develop. Helping people spread the service to their friends was one of the things that, once we got very good at it, made me feel like if Instagram joined us early on, we could help grow that quickly, and same with WhatsApp. I think that's been a core competence we've developed and been able to execute on, and others have too. ByteDance obviously has done a very good job with TikTok and reached more than a billion people there. But it's certainly not automatic. You need a certain level of execution to get there. For whatever reason, Twitter has this great idea and magic in the service, but they just haven't cracked that piece yet. That's why you're seeing all these other things, whether it's Mastodon or BlueSky, that are maybe different cuts at the same thing.

我认为在上一代社交媒体的整体中，一个应该在更大规模上运行的有趣实验是，如果控制权更加去中心化，并且整个技术栈更加开放，会发生什么。我一直对此非常着迷，想看看它是如何运作的。在某种程度上，WhatsApp 上的端到端加密，以及我们将其引入其他服务，提供了这种元素，因为它将服务真正推向边缘。我们为 WhatsApp 运行的服务器部分相对非常精简，与我们在 Facebook 或 Instagram 上做的相比，更多的复杂性在于应用之间如何协商以完全端到端加密的方式传递信息。但我不确定，我认为这是一个好模型。它将更多权力交到个人手中，如果你能实现它，会有很多好处。再说一次，这都相当推测。从外部很难知道任何事情为什么有效或无效，直到你亲自尝试。所以我认为这是一个有趣的实验，但我真的不知道它会走向何方。

I think through the last generation of social media overall, one of the interesting experiments that should get run at larger scale is what happens if there's somewhat more decentralized control and if the stack is more open throughout. I've been pretty fascinated by that and seeing how that works. To some degree, end-to-end encryption on WhatsApp, and as we bring it to other services, provides an element of that because it pushes the service really out to the edges. The server part we run for WhatsApp is relatively very thin compared to what we do on Facebook or Instagram, and much more of the complexity is in how the apps negotiate with each other to pass information in a fully end-to-end encrypted way. But I don't know, I think that's a good model. It puts more power in individuals' hands, and there are a lot of benefits if you can make it happen. Again, this is all pretty speculative. It's hard from the outside to know why anything does or doesn't work until you take a run at it. So I think it's an interesting thing to experiment with, but I don't really know where this one is going to go.

既然我们刚才在聊 Twitter，埃隆·马斯克说了一些我认为有点刺耳的话，我希望他没说过。那么让我问问，本着友谊的精神，你认为埃隆在 Twitter 上做得好的是什么？作为一个长期运营 Facebook、Instagram、WhatsApp 等社交网络的人，他在那个基于文字的社交网络上可以做得更好、改进什么？

Since we were talking about Twitter, Elon Musk had what I think a few harsh words that I wish he didn't say. So let me ask, in the name of camaraderie, what do you think Elon is doing well with Twitter? And as a person who has run social networks like Facebook, Instagram, WhatsApp for a long time, what can he do better, what can he improve on that text-based social network?

天哪，从外部给出具体的批评总是非常困难，在你真正进入之前。我认为我学到的一件事是，每个人对你应该做什么都有意见，而经营公司时你会看到很多外部不明显的具体细微差别。我经常认为，如果我们有更多空间承认内部有一些指导我们行动的事情，围绕我们的讨论可能会更好。但既然你问了，什么做得好？我确实认为埃隆早期推动让 Twitter 变得更精简。你可以同意或不同意所有的策略和做法。显然，每个领导者都有自己的风格来执行重大变革。但他推动的许多具体原则，比如让组织更技术化，减少工程师与他之间的距离，减少管理层级，我认为这些总体上是好的改变。我也认为他对行业做出这些改变可能是好事，因为我的感觉是，有很多其他人认为这些是好的改变，但可能有点不好意思去做。在我与其他创始人的对话以及人们对我们所做事情的反应中，我从很多人那里听到的是，当像你这样的人——当我在三月份概述我想要做的组织变革时——当人们看到埃隆在做什么时，它给了人们思考如何塑造自己组织的能力，希望这对行业有好处，让所有这些公司更高效。

Gosh, it's always very difficult to offer specific critiques from the outside before you get into this. I think one thing I've learned is that everyone has opinions on what you should do, and running the company you see a lot of specific nuances on things that are not apparent externally. I often think that some of the discourse around us could be better if there was more space for acknowledging that there are certain things we see internally that guide what we're doing. But since you asked, what is going well? I do think that Elon led a push early on to make Twitter a lot leaner. You can agree or disagree with all the tactics and how he did it. Obviously, every leader has their own style for how to execute dramatic changes. But a lot of the specific principles he pushed on, around basically trying to make the organization more technical, around decreasing the distance between engineers and him, fewer layers of management, I think those were generally good changes. I also think it was probably good for the industry that he made those changes, because my sense is that there were a lot of other people who thought those were good changes but who may have been a little shy about doing them. In my conversations with other founders and how people have reacted to the things we've done, what I've heard from a lot of folks is that when someone like you—when I outlined the organizational changes I wanted to make back in March—and when people see what Elon is doing, it gives people the ability to think through how to shape their organizations in a way that hopefully can be good for the industry and make all these companies more efficient.

随着时间的推移，效率越来越高。我认为他在这一点上领先于许多其他公司，而且你知道他在做什么。同样，从外部很难判断：他削减得太多还是不够？不管怎样，我觉得这不是我应该发表意见的地方。你问了一个积极角度的问题：我钦佩什么？我认为哪些方面做得好？但我认为他的行动确实让我，以及行业中的许多其他人开始思考：我们是否在应该做的程度上做了这些？我们能否通过推行一些同样的原则来让公司变得更好？

Productive over time, so something that was one where I think he was quite ahead of a bunch of the other companies on, and you know what he was doing there. Again, from the outside, very hard to know: did he cut too much? Did he not cut enough? Whatever. I don't think it's my place to opine on that. And you asked for a positive framing of the question: what do I admire? What do I think went well? But I think that certainly his actions led me and I think a lot of other folks in the industry to think about: hey, are we doing this as much as we should? Can we make our companies better by pushing on some of these same principles?

嗯，你们两位在引领技术发展方面处于世界之巅，我希望世界上有更多的双向情谊和善意，更多的爱，因为爱是答案。但让我问一个关于效率的问题：你最近在 Meta 宣布了多轮裁员。考虑到这对那些人生活的痛苦影响，这个过程中最痛苦的方面是什么？

Well, the two of you are at the top of the world in terms of leading the development of tech, and I wish there was more both-way camaraderie and kindness, more love in the world, because love is the answer. But let me ask on a point of efficiency: you recently announced multiple stages of layoffs at Meta. What are the most painful aspects of this process, given the painful effects it has on those people's lives?

是的，就是这样。你基本上有一大批人，他们加入公司时并没有预料到在 Meta 的时光会这样结束。经营一家公司，人们会因各种原因不断加入和离开。但裁员特别具有挑战性和艰难，因为很多人离开的原因与他们的个人表现或文化契合度无关。这实际上是一种战略决策，有时是财务上的需要。但在我们的案例中，尤其是今年所做的调整，并不完全是财务驱动的。很多是文化和战略上的推动，我希望我们成为一家更强大的科技公司，更专注于更快地构建更技术化、更高质量的产品。我认为外部世界现在相当动荡，我想确保我们有一个稳定的位置，能够继续投资于这些长期雄心勃勃的项目，比如推动 AI 向前发展，以及继续推进所有元宇宙工作。为了做到这一点，鉴于过去 18 个月我们经历的剧烈波动——有些是宏观经济引起的，有些是竞争引起的，有些只是因为错误的决策或我们搞砸的事情——我决定我们需要变得更加精简。但高层做出决定是一回事；问题是如何尽可能富有同情心地执行。没有好的方法，当然也没有完美的方法，无论如何都会很艰难。作为领导者和团队，我们确实花了很多时间思考：既然这是一件糟糕的事情，我们怎样才能以最富有同情心的方式去做？这就是我们努力去做的。

Yeah, I mean, that's it. And you basically have a significant number of people who, you know, this is just not the end of their time at Meta that they would have hoped for when they joined the company. Running a company, people are constantly joining and leaving for different reasons. But layoffs are uniquely challenging and tough in that you have a lot of people leaving for reasons not connected to their own performance or the culture not being a fit. It's really a kind of strategy decision and sometimes financially required. But not fully in our case, especially on the changes we made this year. A lot of it was more culturally and strategically driven by this push where I wanted us to become a stronger technology company with more of a focus on building more technical and higher quality products faster. I just view the external world as quite volatile right now, and I wanted to make sure that we had a stable position to be able to continue investing in these long-term ambitious projects around pushing AI forward and continuing to push forward all the metaverse work. In order to do that, in light of the pretty big thrash we had seen over the last 18 months — some of it macroeconomic, some competitively induced, some just because of bad decisions or things we got wrong — I decided that we needed to get to a point where we were a lot leaner. But then it's one thing to decide that at a high level; the question is how do you execute that as compassionately as possible. There's no good way, no perfect way for sure, and it's going to be tough no matter what. As a leader and team here, we've certainly spent a lot of time thinking: given that this is a thing that sucks, what is the most compassionate way we can do this? And that's what we've tried to do.

你提到更加关注工程和技术，也就是技术团队、以技术为中心的团队，专注于构建产品。

You mentioned there's an increased focus on engineering, on tech, so technology teams, tech-focused teams, on building products.

是的，我的意思是，我想更多地赋能工程师——那些构建产品的人，技术团队。其中一部分是确保构建产品的人不仅仅处于组织的末端节点。我不希望有八层管理层，然后才是实际做工作的人。所以我们做了改变，让个人贡献者工程师在几乎每一层都有汇报关系，我认为这很重要。因为当你经营一家公司时，一个关键问题是信息延迟。我们之前谈到过，做柔术这样的活动得到的即时反馈与运营长期项目相比的乐趣。但我实际上认为，经营公司的一门艺术是不断重新设计它，使反馈循环更短，从而学得更快。做到这一点的方法之一是——我认为组织中的每一层都意味着信息在到达你之前可能需要经过审查。让做工作的人尽可能接近你是非常重要的。所以这是其一。而且我认为随着时间的推移，公司会建立起非常庞大的支持职能部门，它们不从事核心技术工作。这些职能非常重要，但保持适当的比例也很重要。如果你试图做好工作，但没有合适的营销团队或法律建议，你会犯一些相当大的错误。但与此同时，如果这些支持角色过于庞大，那么事情可能会变得非常缓慢，也许你会过于保守，或者比你本应有的速度慢得多。这些只是例子。但如何找到那个平衡？这真的很难。

Yeah, I mean, I wanted to empower engineers more — the people who are building things, the technical teams. Part of that is making sure that the people who are building things aren't just at the leaf nodes of the organization. I don't want eight levels of management and then the people actually doing the work. So we made changes to make it that individual contributor engineers report at almost every level up the stack, which I think is important. Because when you're running a company, one of the big questions is latency of information. We talked about this a bit earlier in terms of the joy of the feedback you get doing something like Jiu-Jitsu compared to running a long-term project. But I actually think part of the art of running a company is trying to constantly re-engineer it so that your feedback loops get shorter so you can learn faster. Part of the way you do that is by — I kind of think that every layer you have in the organization means that information might need to get reviewed before it goes to you. Making it that the people doing the work are as close as possible to you is pretty important. So there's that. And I think over time, companies just build up very large support functions that are not doing the core technical work. Those functions are very important, but having them in the right proportion is important. If you try to do good work but don't have the right marketing team or legal advice, you're going to make some pretty big blunders. But at the same time, if you have too big of some of these support roles, then things might move a lot slower, maybe you're too conservative, or you move a lot slower than you should. Those are just examples. But how do you find that balance? That's really tough.

是的，没错，但这是一个你不断寻找的平衡。应该有多少管理者？管理者的利弊是什么？

Yeah, no, but it's a constant equilibrium that you're searching for. How many managers to have? What are the pros and cons of managers?

嗯，我的意思是，我非常相信管理。我认为有些人觉得管理没那么重要，但你看，我们公司有很多年轻人，这是他们的第一份工作，人们需要在职业生涯中成长和学习。所有这些都很重要。但这里有一个数学上的看法。在开始的时候，我们问了我们的人力团队：管理者平均有多少下属？我记得大约是三个，可能三到四个，但更接近三个。我想，哇，最佳实践是一个管理者可以管理七八个人。但为什么接近三个？那是因为我们增长得太快了。当你如此快速地招聘这么多人时，你需要有能力 onboarding 新人的管理者。另外，如果你有一个新管理者，你可能不希望他们立即有七个直接下属，因为你希望他们逐步适应。但展望未来，我不希望我们……

Well, I mean, I believe a lot in management. I think there are some people who think that it doesn't matter as much, but look, we have a lot of younger people at the company for whom this is their first job, and people need to grow and learn in their career. All that stuff is important. But here's one mathematical way to look at it. At the beginning of this, we asked our people team: what was the average number of reports that a manager had? I think it was around three, maybe three to four, but closer to three. I was like, wow, a manager can manage seven or eight people as best practice. But there was a reason why it was closer to three: it was because we were growing so quickly. When you're hiring so many people so quickly, you need managers who have capacity to onboard new people. Also, if you have a new manager, you may not want them to have seven direct reports immediately because you want them to ramp up. But going forward, I don't want us to...

实际上，这么快就招那么多人，对吧？所以我其实认为，如果我们有更多约束、组织更精简，反而能做得更好。在一个不会那么快增加那么多人的世界里，养着一大堆等着新人的经理还有那么大的价值吗？没有，对吧。所以现在我们可以对组织进行去碎片化，让平均管理幅度接近七到八人。最终形成一个更紧凑的管理结构，这能减少信息在上下级之间传递的延迟，而且我认为也能更好地赋能员工。但我的意思是，这个例子并不是要贬低管理的重要性，也不是说人们做好工作就不需要个人成长或指导。只是，我认为现实是，未来我们不会招那么多人了，所以需要一种不同的结构。

Actually hire that many people that quickly, right? So I actually think we'll just do better work if we have more constraints and we're leaner as an organization. So in a world where we're not adding so many people as quickly, is it as valuable to have a lot of managers who have extra capacity waiting for new people? No, right. So now we can defragment the organization and get to a place where the average is closer to that seven or eight. And it just ends up being a somewhat more compact management structure, which decreases the latency on information going up and down the chain, and I think empowers people more. But I mean, that's an example that I think doesn't undervalue the importance of management and the personal growth or coaching that people need in order to do their jobs well. It's just, I think realistically, we're just not going to hire as many people going forward, so I think that you need a different structure.

构成公司的整个层级和人际网络真是令人着迷。哦，是的。你怎么招聘优秀的团队？现在重点是工程和技术团队，你怎么招聘优秀的工程师和技术团队成员？

This whole incredible hierarchy and network of humans that make up a company is fascinating. Oh yeah, yeah. How do you hire great teams? How do you hire great—now with the focus on engineering and technical teams—how do you hire great engineers and great members of technical teams?

你问的是怎么筛选还是怎么吸引？两者都有。但筛选——我觉得吸引就是做酷的东西，有愿景。我觉得没错。还要有让人相信你确实能做到的过往记录。对我来说，筛选更像是一门艺术，更棘手。是啊。怎么筛选出那些契合文化、能最有效融入的人呢？尤其是年轻人，怎么透过简历、文件这些东西看到那种魔力，看到那里有一个能做出非凡成就的特别的人。

Well, you're asking how you select or how you attract them? Both. But select, I think attract is work on cool stuff and have a vision. I think that's right. And have a track record that people think you're actually going to be able to do it. Yeah. To me, the select seems like more of the art form, more of the tricky thing. Yeah. How do you select the people that fit the culture and can get integrated the most effectively, and so on? And maybe especially when they're young, to see the magic through the resume, through the paperwork and all this kind of stuff, to see that there's a special human there that would do incredible work.

所以这个问题有很多不同的角度。

So there are lots of different cuts on this question.

我的意思是，当一个组织快速增长时，团队面临的一个大问题是：我是现在就雇这个看起来不错的人，还是再等等找一个更好的？我自己一直遵循的启发式方法——而且我认为当你在组织里层层推广时也有效——就是：你只应该雇那些在另一个宇宙里你愿意为他们工作的人。是的。这基本上就是我组建团队的方式。你知道，我并不急于不再管理公司，但我认为在另一个宇宙里，如果这些人中的某一位在管理公司，我会很乐意为他们工作。我觉得我能从他们身上学到东西，我尊重他们的总体判断，他们都非常有洞察力，价值观也很好。我认为这给了你一个可以在每一层应用的准则。而且我认为如果你在组织的每一层都应用这个准则，你就会有一个非常强大的组织。

I mean, I think when an organization is growing quickly, one of the big questions that teams face is: do I hire this person who's in front of me now because they seem good, or do I hold out to get someone who's even better? And the heuristic that I always focused on for myself and my own direct hiring—that I think works when you recurse it through the organization—is that you should only hire someone to be on your team if you would be happy working for them in an alternate universe. Yeah. And that's basically how I've tried to build my team. It's, you know, I'm not in a rush to not be running the company, but I think in an alternate universe where one of these other folks was running the company, I'd be happy to work for them. I feel like I'd learn from them, I respect their general judgment, they're all very insightful, they have good values. And I think that gives you some rubric that you can apply at every layer. And I think if you apply that at every layer in the organization, then you'll have a pretty strong organization.

好的。在一个增长不那么快的组织里，问题可能有点不同。你特别提到了年轻人，比如刚毕业的大学生。我们看到的一件事——这是一个很基本的经验——就是我们对那些在公司实习过几个月的人，比只看简历或短时间面试的人，要了解得多得多。显然，从一个人身上获得的面对面感觉可能比简历告诉你的更多。你可以做一些基本的技能评估，但很多东西真的只是文化问题。人们在不同的环境和团队中茁壮成长，即使是在同一家公司内部。那些来实习一个夏天、表现很好的人——你知道如果他们全职加入也会很出色。这就是为什么我们在实习上投入了这么多——它基本上是一个非常有用的筛选功能，对我们和对想尝试这家公司的人来说都是如此。

Okay. In an organization that's not growing as quickly, the questions might be a little different though. And there you asked about young people specifically, like people out of college. And one of the things that we see is—it's a pretty basic lesson—but like we have a much better sense of who the best people are who have interned at the company for a couple of months than by looking at them at a resume or a short interview loop. Obviously the in-person feel that you get from someone probably tells you more than the resume. And you can do some basic skills assessment, but a lot of the stuff really just is cultural. People thrive in different environments and on different teams, even within a specific company. And it's like the people who come for even a short period of time over a summer who do a great job here—you know that they're going to be great if they came and joined full-time. And that's one of the reasons why we've invested so much in internships—it's basically just a very useful sorting function, both for us and for the people who want to try out the company.

你提到了面对面。你怎么看远程工作？这个话题因为过去几年的疫情被广泛讨论。

You mentioned in person. What do you think about remote work? A topic that's been discussed extensively because of the pandemic over the past few years.

是的，我认为它会一直存在。但我认为两者都有价值，对吧？我不会——至少现在，我不想运营一家完全远程的公司。我觉得这有个前提，那就是你正在做的其他一些事情——对，对，没错。就是所有元宇宙的工作，以及无论你在哪里都能感觉真正在场的能力。我认为一旦我们把那一切都搞定，那么也许有一天我们会达到一个点，物理位置真的不那么重要了。但我不确定，今天它仍然重要，对吧？所以，对于那些有特殊技能、想住在我们没有办公室的地方的人，我们让他们留在公司是不是更好？绝对是。还有很多在公司工作多年、建立了内部关系、有信任感、了解公司运作方式的人——他们现在如果想远程工作，还能同样高效吗？我们做了所有这些研究，结果显示：这会影响他们的绩效吗？不会。但对于新加入的人，以及那些职业生涯早期、需要学习如何解决某些问题、需要融入文化的人来说——当你处理非常复杂的问题时，你不仅想要正式的会议，还想在会后一起走过走廊时进行头脑风暴——我不知道，我们就是还没有用任何远程方式取代那种面对面的动态。所以，是的，面对面有一种魔力——我们稍后会多谈这个，但我对接下来几年通过高分辨率扫描实现的虚拟现实和混合现实的可能性感到非常兴奋。

Yeah, I mean, I think it's a thing that's here to stay. But I think that there's value in both, right? It's not—I wouldn't want to run a fully remote company yet, at least. I think there's an asterisk on that, which is that some of the other stuff you're working on—yeah, yeah, exactly. It's like all the metaverse work and the ability to feel like you're truly present no matter where you are. I think once you have that all dialed in, then we may one day reach a point where it really just doesn't matter as much where you are physically. But I don't know, today it still does, right? So yeah, for people who have special skills and want to live in a place where we don't have an office, are we better off having them at the company? Absolutely. And a lot of people who work at the company for several years and build up the relationships internally, and have the trust and have a sense of how the company works—can they go work remotely now if they want and still do it as effectively? And we've done all these studies that show it's like, okay, does that affect their performance? It does not. But for the new folks who are joining, and for people who are earlier in their career and need to learn how to solve certain problems and need to get ramped up on the culture—when you're working through really complicated problems where you don't just want the formal meeting but you want to be able to brainstorm when you're walking in the hallway together after the meeting—I don't know, it's like we just haven't replaced the in-person dynamics there yet with anything remote. So yeah, there's a magic to the in-person that—we'll talk about this a little bit more, but I'm really excited by the possibility of the next few years in virtual reality and mixed reality that are possible with high resolution scans.

作为一个喜欢面对面互动的人，比如这些播客的面对面录制，如果能达到我有机会见证的那种真实感，那将是不可思议的。但让我问问这个。我有机会看了 Quest 3 头显，它太棒了。你已经发布了它，秋天会有更多细节，也许发布在——它什么时候再次发布？

I, as a person who loves in-person interaction like these podcasts in person, it would be incredible to achieve the level of realism I've gotten a chance to witness. But let me ask about that. I got a chance to look at the Quest 3 headset and it is amazing. You've announced it, you'll get some more details in the fall, maybe release in the—when is it getting released again?

你之前跟我提过，我们会在 Connect 上公布更多细节，不过它今年秋天就会上市。好，定价是 499 美元。你最兴奋的功能是什么？

Forgot you mentioned it to me. We'll give more details of Connect, but it's coming this fall. Okay, so it's priced at $4.99. What features are you most excited about?

我们在 Quest 3 上相比 Quest 2 主要增加了两大新功能。第一个是高分辨率混合现实。基本思路是：你可以把虚拟现实想象成戴上头显后所有像素都是虚拟的，你完全沉浸在一个不同的世界里。而混合现实则让你看到周围的物理世界，并能在其中放置虚拟物体——无论是看电影的屏幕、虚拟桌面的投影，还是玩一个僵尸从墙里钻出来需要你射击的游戏。或者玩龙与地下城之类的桌游，我们坐在这里，面前放一个虚拟的棋盘。所有这些在混合现实中都能实现，我认为这将是虚拟现实之上的下一个重大能力。

There are basically two big new things that we've added to Quest 3 over Quest 2. The first is high-resolution mixed reality. The basic idea is that you can think about virtual reality as having the headset and all the pixels are virtual, and you're basically immersed in a different world. Mixed reality is where you see the physical world around you and you can place virtual objects in it—whether that's a screen to watch a movie, a projection of your virtual desktop, or playing a game where zombies are coming out through the wall and you need to shoot them. Or playing Dungeons & Dragons or some board game and having a virtual version of the board in front of us while we're sitting here. All that is possible in mixed reality, and I think that is going to be the next big capability on top of virtual reality.

它做得太好了。作为一个今天体验过僵尸模式的人，我必须说，完全感知环境并以那种方式融入环境——它们朝你跑来试图杀死你——混合现实的透视效果真的非常出色。而且它只要 500 美元，这真的很棒。谢谢。

It has done so well. I have to say, as a person who experienced it today with the zombies, having a full awareness of the environment and integrating that environment in the way they run at you while they try to kill you—it's just the mixed reality, the passthrough, is really, really well done. And the fact that it's only $500 is really well done. Thank you.

我对此非常兴奋。我们投入了大量精力，力求让设备既尽可能好又尽可能实惠，因为我们使命和理念的核心是让人们能够彼此连接。我们希望触达并服务很多人，把这项技术带给每个人。所以我们不只是想服务精英富豪群体；我们真的希望它触手可及。这在很多方面都是一个极其困难的技术问题，因为我们不能无限制地堆硬件，而是要在实惠的价位上交付一款真正好用的产品。去年我们从 Quest Pro 起步，定价 1500 美元，现在降到了 1000 美元。但在很多方面，Quest 3 的混合现实比 Quest Pro 还要更好、更先进。所以我对 Quest 3 在这方面的表现非常自豪。

I mean, I'm super excited about it. We put a lot of work into making the device both as good as possible and as affordable as possible, because a big part of our mission and ethos is that we want people to be able to connect with each other. We want to reach and serve a lot of people. We want to bring this technology to everyone. So we're not just trying to serve an elite, wealthy crowd; we really want this to be accessible. That is, in a lot of ways, an extremely hard technical problem, because we don't have the ability to put an unlimited amount of hardware unless we need to basically deliver something that works really well but in an affordable package. We started with Quest Pro last year; it was $1,500, and now we've lowered the price to a thousand. But in a lot of ways, the mixed reality in Quest 3 is even better and more advanced than what we were able to deliver in Quest Pro. So I'm really proud of where we are with Quest 3 on that.

它将兼容所有已有的虚拟现实内容和游戏，所以想玩完全沉浸式游戏、社交体验、健身等的人都能用。但现在你还将获得混合现实功能，我觉得人们会非常喜欢，因为有时你想完全沉浸在游戏中，但很多时候，尤其是当你活动时——比如做健身体验，像打拳击之类的——你希望能看到周围的房间，这样你就不会打到台灯之类的东西。

It's going to work with all the virtual reality titles and everything that existed there, so people who want to play fully immersive games, social experiences, fitness—all that stuff will work. But now you'll also get mixed reality too, which I think people really like because sometimes you want to be super immersed in a game, but a lot of the time, especially when you're moving around, if you're active like doing some fitness experience—let's say you're doing boxing or something—you kind of want to be able to see the room around you so you know you're not going to punch a lamp or something like that.

我不知道你有没有玩过这个体验，但我们做了一个有趣的小演示。就像你在会议室或客厅里，有个人在那里，你和他打拳击，其他所有人也都在那里。我有机会试了一下。是的，所有人都在那里——那个人就在房间里。你看到的其他人可以为你加油，如果他们像我朋友那样，还会取笑你。这真的是一种引人入胜的体验。我是说，VR 也很有趣，但这完全是另一回事——它融入了你的生活，融入了你的世界。

I don't know if you got to play with this experience, but we basically have this fun little demo we put together. It's like you're in a conference room or your living room, and you have the guy there and you're boxing him and fighting him, and all the other people are there too. I got a chance to do that. Yeah, and all the people are there—it's like that guy is right there in the room. And the other humans you're seeing, they can cheer you on, they can make fun of you if they're anything like friends of mine. It's really a compelling experience. I mean, VR is really interesting too, but this is something else—this becomes integrated into your life, into your world.

是的，这确实是一种引人入胜的体验。我认为这是一种全新的能力，将解锁大量不同的内容。它也会让那些不想只体验完全沉浸式的人感到更舒适。如果你想要那种扎根于客厅和周围物理世界的体验，现在你也能拥有了。我觉得这非常令人兴奋。

Yeah, and it's really a compelling experience. I think it's a completely new capability that will unlock a lot of different content. I think it'll also just make the experience more comfortable for a set of people who didn't want to have only fully immersive experiences. If you want experiences where you're grounded in your living room and the physical world around you, now you'll be able to have that too. I think that's pretty exciting.

我真的很喜欢它给没有窗户的房间加了窗户。是的，就我个人而言——你看到那个水族馆的体验了吗？能看到鲨鱼游过来？还是只有僵尸那个？

I really liked how it added windows to a room with no windows. Yeah, me as a person—did you see the aquarium one where you could see the shark swim up? Or was that just the zombie one?

是僵尸那个。不过你未必想在客厅里加一扇有僵尸钻出来的窗户，但在那个游戏的语境下，它……

The zombie one. But it's still—you don't necessarily want windows added to your living room where zombies come out, but in the context of that game, it's...

对对对。我很喜欢，因为你能看到外面的自然景色，作为一个没有窗户的人，能看到自然真好。

Yeah, yeah, yeah. I enjoyed it because you could see the nature outside, and as a person that doesn't have windows, it's just nice to have nature.

是的，即使在混合现实环境中，能够看向外面并改变你所知的环境，也有一种禅意的自然感。可能会有比你说的僵尸游戏更好、更禅意的方式来实现这一点，但你说得对，基本思路就是通过透视看到物理环境，同时能引入外部不同的元素——我认为这将非常强大。

Yeah, well, even if it's a mixed reality setting, there's a Zen nature aspect to being able to look outside and alter your environment as you know it. There will probably be better, more Zen ways to do that than the zombie game you're describing, but you're right that the basic idea of having your physical environment on passthrough but then being able to bring in different elements externally—I think it's going to be super powerful.

从某种意义上说，我认为混合现实也是最终实现 AR 眼镜的前身，那种眼镜不是当前头显的护目镜形态。但我认为开发者为混合现实打造的很多体验——基本上就是在世界中放置全息图——希望在我们推出 AR 眼镜时也能适用。当然，那本身也有一整套挑战。

In some ways, I think mixed reality is also a predecessor to eventually getting AR glasses that are not the goggles form factor of the current generation of headsets. But I think a lot of the experiences that developers are making for mixed reality—basically putting a hologram in the world—will hopefully apply once we get the AR glasses too. Now that's got its own whole set of challenges.

嗯，头显已经比上一代小了。哦对，薄了 40%。

Well, the headset's already smaller than the previous version. Oh yeah, it's 40% thinner.

另一个我觉得很好的方面——混合现实是第一个大亮点。第二个是它本身就是一款出色的 VR 头显。图形处理能力翻倍，屏幕清晰度提升 40%，薄了 40%，更舒适，头带结构也更好。如果你喜欢 Quest 2，那么你在 Quest 2 上玩过的所有内容在这上面都会自动变得更清晰、效果更好。所以我觉得人们会非常喜欢它。

And the other thing that I think is good about it—so mixed reality was the first big thing. The second is it's just a great VR headset. It's got 2x the graphics processing power, 40% sharper screens, 40% thinner, more comfortable, better strap architecture—all this stuff. If you liked Quest 2, I think this is just going to be all the content you might have played in Quest 2 getting sharper automatically and looking better in this. So I think people are really going to like it.

嗯，今年秋天。我不得不问：苹果刚刚发布了一款名为 Vision Pro 的混合现实头显，售价 3499 美元，2024 年初上市。你怎么看这款头显？

Yeah, so this fall. I have to ask: Apple just announced a mixed reality headset called Vision Pro for $3,500, available in early 2024. What do you think about this headset?

嗯，他们发布时我看了相关资料。我……

Well, I saw the materials when they launched. I...

我还没机会上手体验，所以先别全信。但有几个高层次的看法。首先，我认为这在一定程度上验证了这个品类。我们之前是主要说 VR、AR、混合现实将成为下一个计算平台重要组成部分的人。苹果加入并分享这一愿景，会让很多喜欢他们产品的人认真考虑。当然，还有 3500 美元的价格。一方面，我理解他们要塞进那么多东西；另一方面，很多人会觉得买不起。所以我认为苹果的加入反而可能增加整个市场的需求，而 Quest 3 会是主要受益者。很多人可能会说，‘我喜欢这个，我会再考虑一下’，或者‘现在我更了解混合现实了’，而 Quest 3 是市场上他们能买得起的最好的产品。它也很棒。我们有自己的方式，有很多领先的功能。所以我认为这可能会相当不错。长期来看，两家公司关注的重点有所不同。苹果一直专注于打造非常高端的设备，而我们的理念更民主——我们希望让更多人用得起。我们已经卖出了数千万台 Quest 设备。据我了解（基于传闻，我没有内幕消息），苹果计划生产约 100 万台他们的设备。所以从预期销量来看，Quest 在可预见的未来仍将是市场主流。长期来看，要看两家公司各自执行得如何。我们的出发点不同。我们非常关注社交互动、沟通、更活跃的体验——健身、游戏等等。而苹果发布材料中的很多用例更多是让人们坐着看屏幕。这些也很好——我认为随着时间的推移，你会用头显取代笔记本电脑——但就目前两家公司追求的不同用例而言，它们还是有些差异的。

I haven't gotten a chance to play with it yet, so take everything with a grain of salt. But a few high-level thoughts. First, I do think this is a certain level of validation for the category. We were the primary folks out there before saying that virtual reality, augmented reality, mixed reality is going to be a big part of the next computing platform. Having Apple come in and share that vision will make a lot of people who are fans of their products really consider it. Then, of course, the $3,500 price. On one hand, I get it with all the stuff they're trying to pack in there. On the other hand, a lot of people aren't going to find that affordable. So I think there's a chance that them coming in actually increases demand for the overall space, and Quest 3 is the primary beneficiary. A lot of people might say, 'I like this, I'll give it another consideration,' or 'Now I understand what mixed reality is more,' and Quest 3 is the best one on the market that they can afford. It's great too. In our own way, we have a lot of features where we're leading. So I think that could be quite good. Over time, the companies are focused on somewhat different things. Apple has always focused on building really high-end things, whereas our focus is more democratic—we want to build things accessible to a wider number of people. We've sold tens of millions of Quest devices. My understanding, based on rumors (I don't have any special knowledge), is that Apple is building about 1 million of their device. So in terms of expected sales numbers, Quest is going to be the primary thing people in the market will continue using for the foreseeable future. Over the long term, it's up to the companies to see how well we execute. We come at it from different places. We're very focused on social interaction, communication, being more active—fitness, gaming, those things. Whereas a lot of the use cases in Apple's launch material were more around people sitting, looking at screens. Those are great—I think you will replace your laptop with a headset over time—but in terms of the different use cases the companies are going after, they're a bit different for where we are right now.

是的，所以游戏并不是演示的重点，这很有意思。感觉混合现实游戏应该是很重要的一部分，看到它缺席挺有趣的。

Yeah, so gaming wasn't a big part of the presentation, which is interesting. It feels like mixed reality gaming is such a big part of that; it was interesting to see it missing in the presentation.

嗯，你看，这里有一些设计上的取舍。他们强调不想用控制器。一方面，仅用眼球追踪和手势追踪就能导航系统，确实很优雅。顺便说一句，如果你愿意，也可以用双手来操作 Quest。有一点我该提一下：通过摄像头和计算机视觉检测手部某些特征的能力，让你可以拥有一个没有那个环的控制器。Quest 3 的手势追踪和控制器追踪相比上一代有了很大提升。我们有一个演示是混合现实体验，教你弹钢琴，它会高亮显示你需要弹的音符，全程用手，没有控制器。但如果你在乎游戏，有控制器能提供更触觉化的感受，并且比没有触摸物的手更精确地捕捉精细动作。所以，问题又回到了你为哪些用例做优化。如果你想玩游戏，那么你需要以不同的方式设计系统。我们更专注于社交体验、娱乐体验。而如果你想确保屏幕上阅读的文字尽可能清晰，那么你就需要做出设计和成本上的取舍，最终造出 3500 美元的设备。所以我认为这当然有它的用例，但两家公司基本上做了不同的设计取舍，以服务于我们各自瞄准的用例。

Well, look, there are certain design trade-offs. They made this point about not wanting to have controllers. On one hand, there's a certain elegance about just being able to navigate the system with eye gaze and hand tracking. By the way, you'll be able to navigate Quest with your hands too if you want. One thing I should mention is that the capability from the camera with computer vision to detect certain aspects of the hand, allowing you to have a controller without that ring thing. The hand tracking in Quest 3 and the controller tracking is a big step up from the last generation. One of the demos we have is an MR experience teaching you how to play piano, where it highlights the notes you need to play, and it's all hands, no controllers. But if you care about gaming, having a controller allows you to have a more tactile feel and capture fine motor movement much more precisely than with hands without something to touch. So again, there are questions around what use cases you're optimizing for. If you want to play games, then you want to design the system in a different way. We're more focused on social experiences, entertainment experiences. Whereas if what you want is to make sure the text you read on a screen is as crisp as possible, then you need to make the design and cost trade-offs that lead to a $3,500 device. So I think there is a use case for that for sure, but the companies have basically made different design trade-offs to serve the use cases we're trying to target.

还有很多其他东西我想和你聊，关于元宇宙，尤其是柯达头像，我最近体验了很多不同的版本。我非常兴奋。我可能得等一等，因为我觉得这方面还有很多可以展示的。但让我先回到 AI。我想我们之前提到了一点，但我想多谈谈这个问题，像 Eliezer Yudkowsky 和其他一些人担心的那样，随着 AI 系统的快速发展，存在严重的生存威胁。你是否像 Eliezer 那样担心 AI 的生存风险、对齐问题，以及它随时可能失控？有很多严肃的人对你所从事的事情提出了生存层面的担忧。

There's a lot of other stuff I would love to talk to you about, about the metaverse, especially the Kodak Avatar, which I've gotten to experience a lot of different variations of recently. I'm really excited. I'll have to wait a little bit because I think there's a lot more to show off in that regard. But let me step back to AI. I think we've mentioned it a little bit, but I'd like to linger on this question that folks like Eliezer Yudkowsky have a worry about, and others, of the existential serious threats of AI that have been reinvigorated now with the rapid development of AI systems. Do you worry about the existential risks of AI as Eliezer does, about the alignment problem, about this getting out of hand anytime? There are a number of serious people who are raising a concern that is existential about something that you're involved with.

我认为你必须考虑这个问题，对吧？所以我花了不少时间从这个角度思考。目前我基本得出的结论是：我确实认为随着时间的推移，当我们接近可能更接近超级智能的东西时，我们需要更多地思考这个问题。我只是觉得，今天任何从事这些项目的人都很清楚，我们还没到那一步。我的一个担忧是，我们之前花了不少时间在这上面，但还有更多——我不知道‘平凡’这个词是否合适——但已经存在一些担忧，比如人们使用 AI 工具做有害的事情，我们已知的类型：欺诈、诈骗等等。这将会是一个大问题。

I think you have to think about it, right? So I've spent quite a bit of time thinking about it from that perspective. The thing where I have basically come out on this for now is: I do think that over time, we need to think about this even more as we approach something that could be closer to superintelligence. I just think it's pretty clear to anyone working on these projects today that we're not there. One of my concerns is that we spent a fair amount of time on this before, but there are more—I don't know if 'mundane' is the right word—but there are concerns that already exist, like people using AI tools to do harmful things of the type we're already aware of: fraud, scams, or different things like that. And that's going to be a big issue.

公司正在应对一系列相当大的挑战，无论未来是否存在生存危机，这些挑战都必须解决。所以我确实担心，在某种程度上，人们可能过于关注一些尾部风险，而没有在我们几乎可以确定会出现的、在短期内显现的现实风险上做好必要的工作。对我来说，一旦我意识到我们现在正在构建的模型规模与人们提出的超级智能类担忧相去甚远，我就把大部分时间花在了这上面。但我认为，当我们再接近几步时，随着我们越来越接近，肯定会出现一些新的风险和问题，关于如何确保系统的安全。

There's a pretty big set of challenges that the company is working on that they're going to need to grapple with regardless of whether there is an existential concern at some point down the road. So I do worry that to some degree people can get a little too focused on some of the tail risk and then not do as good of a job as we need to on the things that you can be almost certain are going to come down the pipe as real risks that manifest themselves in the near term. For me, I've spent most of my time on that once I made the realization that the size of models we're talking about now in terms of what we're building are quite far from the superintelligence type concerns that people raise. But I think once we get a couple steps closer to that, as we do get closer, I think there are going to be some novel risks and issues about how we make sure the systems are safe for sure.

我想把对话引向一个稍微不同的方向。我认为在一些关于安全的辩论中，智能和自主性——或者说事物的“存在”——这些概念被混为一谈了。很可能的情况是，你可以制造出某种东西，并将智能扩展到相当高的程度，但这可能并不会引发人们所说的那些安全问题。我的意思是，只要看看人类生物学：我们有新皮层，所有思考都在那里发生，但最终它并不是真正的决策者。我们有一个更原始的旧脑结构，而新皮层——这个强大的机器——基本上只是一个预测和推理引擎，帮助我们的简单大脑决定如何规划、如何行动，以实现这些非常基本的冲动。我认为你可以用同样的思路来思考智能的发展。就像我们的新皮层没有自由意志或自主性一样，我们可能会开发出这些极其智能的系统，它们比我们的新皮层聪明得多、能力更强，但就像新皮层从属于旧脑并被用作工具一样，这些系统也可能如此。我认为，拥有思考能力的非常智能的系统有可能充当新皮层的延伸。所以我的观点是，我们真正需要小心的是自主性的发展以及我们如何看待它，因为实际上，相对简单且不智能的事物如果拥有失控的自主性并自行传播——我们有一个词来形容它，那就是病毒。它可以是简单的计算机代码，并不特别智能，但只是自我传播并造成大量伤害，无论是生物上还是计算机上。我认为这些在某种程度上是可分离的。当人们谈论安全和责任时，我们需要发展的很多东西实际上是对系统可以获得的自主性的治理。对我来说，如果我是政策制定者或思考这个问题，我真的会想区分这两者：构建智能系统可以在人们的生活质量和经济生产力增长方面带来巨大进步，但自主性这部分才是我们真正需要取得进展的地方——在构建系统自主做出大量决策或赋予它们目标的能力之前，如何负责任地治理这些东西。这是一个研究问题，但我确实认为在某种程度上这些是可分离的。

I guess here just to take the conversation in a somewhat different direction, I think in some of these debates around safety, the concepts of intelligence and autonomy or the being of the thing as an analogy get conflated together. And I think it very well could be the case that you can make something and scale intelligence quite far, but that may not manifest the safety concerns that people are saying. I mean, just if you look at human biology, we have our neocortexes where all the thinking happens, but it's not really calling the shots at the end of the day. We have a much more primitive old brain structure for which our neocortex, this powerful machinery, is basically just a prediction and reasoning engine to help our very simple brain decide how to plan and do what it needs to do in order to achieve these very basic impulses. And I think you can think about some of the development of intelligence along the same lines. Just like our neocortex doesn't have free will or autonomy, we might develop these wildly intelligent systems that are much more intelligent than our neocortex, have much more capacity, but are in the same way that our neocortex is sort of subservient and is used as a tool by our simple brain. I think it's not out of the question that very intelligent systems that have the capacity to think will act as sort of an extension of the neocortex doing that. So my own view is that where we really need to be careful is on the development of autonomy and how we think about that, because it's actually the case that relatively simple and unintelligent things that have runaway autonomy and just spread themselves — we have a word for that, it's a virus. It can be simple computer code that is not particularly intelligent but just spreads itself and does a lot of harm, biologically or computer. I just think that these are somewhat separable things, and a lot of what we need to develop when people talk about safety and responsibility is really the governance on the autonomy that can be given to systems. To me, if I were a policy maker or thinking about this, I would really want to think about that distinction between these, where building intelligence systems can create a huge advance in terms of people's quality of life and productivity growth in the economy, but it's the autonomy part of this that we really need to make progress on how to govern these things responsibly before we build the capacity for them to make a lot of decisions on their own or give them goals or things like that. That's a research problem, but I do think that to some degree these are somewhat separable things.

我喜欢你对智能和自主性的区分，以及新皮层这个比喻。让我问问关于权力的问题。构建超级智能系统，即使不是在短期内，我认为 Meta 是少数几家——如果不是主要的话——会开发超级智能系统的公司之一。而你正是这家公司的掌舵人。构建 AGI 可能会让你成为世界上最有权势的人。你担心这种权力会腐蚀你吗？

I love the distinction between intelligence and autonomy and the metaphor within neocortex. Let me ask about power. So building superintelligence systems, even if it's not in the near term, I think Meta is one of the few companies, if not the main company, that will develop the superintelligence system. And you are a man who's at the head of this company. Building AGI might make you the most powerful man in the world. Do you worry that that power will corrupt you?

好问题。我的意思是，实际上这又回到了我们之前讨论过的开源问题。我认为，如果只有少数组织拥有这项技术而不广泛开放，这对世界并不是最好的。如果你回顾历史，当出现这种单极进步和权力不平衡时，往往会导致一些奇怪的局面。所以这是我认为开源通常是正确方法的原因之一。而且我认为，在我们尚未接近超级智能的今天，这是一个截然不同的问题。我认为即使我们更接近超级智能，开源仍然很可能是正确的方法，尽管到那时讨论会有所不同。但部分原因在于，这是确保系统尽可能安全可靠的最佳方式之一，因为这不仅仅是让很多人能够访问它，而是开源系统带来的审查。关于开源有一个广为接受的观点：代码公开，任何人都可以看到漏洞，任何人都可以用不同方式摆弄它，人们可以衍生出自己的项目并进行大量实验，所有这些的最终结果是系统得到加固，变得更加安全可靠。所以我认为这很可能会成为最终的方向，而且开源既能带来更健康的技术发展，也能带来更平衡的技术分布，这符合值得追求的良好价值观。

What a question. I mean, look, I think realistically this gets back to the open source things that we talked about before, which is I don't think that the world will be best served by any small number of organizations having this without it being something that is more broadly available. And I think if you look through history, when there are these sort of unipolar advances and power imbalances, they tend to lead to kind of weird situations. So this is one of the reasons why I think open source is generally the right approach. And I think it's a categorically different question today when we're not close to superintelligence. I think there's a good chance that even once we get closer to superintelligence, open sourcing remains the right approach, even though I think at that point it's a somewhat different debate. But I think part of that is that it's one of the best ways to ensure that the system is as secure and safe as possible, because it's not just about a lot of people having access to it; it's the scrutiny that comes with building an open source system. This is a pretty widely accepted thing about open source: you have the code out there, so anyone can see the vulnerabilities, anyone can mess with it in different ways, people can spin off their own projects and experiment in a ton of different ways, and the net result of all of that is that the system gets hardened and becomes a lot safer and more secure. So I think there's a chance that this ends up being the way that this goes too, a pretty good chance, and that having this be open both leads to a healthier development of the technology and also leads to a more balanced distribution of the technology in a way that strikes good values to aspire to.

所以对你来说，开源的风险是存在的，但收益大于风险。而且很有趣，我认为你表述得很好，现在关于开源收益和风险的讨论，与我们更接近超级智能开发时的讨论是不同的。

So to you, the risks of open sourcing are there, but the benefits outweigh the risks. And it's interesting, I think the way you put it, you put it well, that there's a different discussion now than when we get closer to the development of superintelligence, of the benefits and risks of open sourcing.

是的，明确地说，我对目前开源模型是净正面的评估非常有信心。我认为有充分的理由表明，未来即使更接近超级智能，开源也仍然是净正面的。

Yeah, to be clear, I feel quite confident in the assessment that open sourcing models now is net positive. I think there's a good argument that in the future it will be too, even as you get closer to superintelligence.

你觉得我们哪一年会拥有超级智能？

What year do you think we'll have a superintelligence?

我不知道，这纯粹是猜测。我认为很明显，退一步看，去年我们取得了一个重大突破，对吧？LLM 和扩散模型基本上达到了一个规模，能够做一些相当有趣的事情。接下来的问题是，从这里会发生什么。描绘两个极端：一方面，我们刚刚取得了一个突破。如果再有一个类似的突破，或者两个，那么我们就可能拥有真正疯狂的东西，先进得多。在那个观点下，我们可能只需要几个大步就能接近看起来更像通用智能的东西。另一方面，历史上我们更常见的是，一个突破会引发 Gartner 炒作周期：先是炒作，然后是幻灭低谷。人们认为，“嘿，重大突破，也许我们即将迎来另一个”，但实际上并没有。你可能需要在这个突破上停留一段时间。可能是 5 年、10 年、15 年，直到你弄清楚下一个需要解决的大问题。我们刚刚取得这个突破的事实，使得接下来发生的事情的误差范围非常大。

I don't know. That's pure speculation. I think it's very clear, just taking a step back, that we had a big breakthrough in the last year, right? Where the LLMs and diffusion models basically reached a scale where they're able to do some pretty interesting things. Then the question is what happens from here. To paint the two extremes: on one side, it's like, okay, we just had one breakthrough. If we have another breakthrough like that, or maybe two, then we could have something truly crazy, just so much more advanced. On that side, maybe we're only a couple of big steps away from reaching something that looks more like general intelligence. The other side, which we've historically seen a lot more, is that a breakthrough leads to the Gartner hype cycle: there's the hype, then the trough of disillusionment. People think, 'Hey, big breakthrough, maybe we're about to get another,' but actually you're not. You might have to sit with this one for a while. It could be 5 years, 10 years, 15 years until you figure out the next big thing. The fact that we just had this breakthrough puts us at a point of very wide error bars on what happens next.

我认为传统的技术观点，或者看看行业，会表明我们不会每六个月就堆叠一个突破。我猜这些突破之间的间隔会更长一些。但我对突破也相当乐观。所以如果你根据我通常的乐观情绪来调整，那么可能比我说的还要慢。但即便如此，我并不是在评论需要多少突破才能达到通用智能，因为没人知道。但这次突破是如此小的一步，却导致了人类体验到的性能的巨大飞跃，这让你思考：当我们在这个非常开放的研究世界中摸索时，我们是否会偶然发现另一件能带来巨大性能飞跃的东西？而且，我们也不确切知道在哪个阶段它会真正令人印象深刻，因为它感觉确实正在逼近令人印象深刻的智能水平。你仍然没有回答我们将在哪一年拥有超级智能的问题。我想让你回答这个问题。不，我只是开玩笑。但关于你思考 AGI 和超级智能系统发展的时间线，你能说些什么吗？

I think the traditional technical view, or looking at the industry, would suggest that we're not just going to stack breakthrough on top of breakthrough every six months. I would guess it will take somewhat longer in between these. But I tend to be pretty optimistic about breakthroughs too. So if you normalized for my normal optimism, then maybe it would be even slower than what I'm saying. But even within that, I'm not opining on how many breakthroughs are required to get to general intelligence because no one knows. But this particular breakthrough was such a small step that resulted in such a big leap in performance as experienced by human beings that it makes you think: as we stumble across this very open world of research, will we stumble across another thing that will have a giant leap in performance? Also, we don't know exactly at which stage it's really going to be impressive, because it feels like it's really encroaching on impressive levels of intelligence. You still didn't answer the question of what year we're going to have superintelligence. I'd like to hold you to that. No, I'm just kidding. But is there something you could say about the timeline as you think about the development of AGI and superintelligence systems?

当然。我仍然认为我对何时会创造出单一的通用智能 AI 系统没有任何特别的见解。但我认为，在我看到的关于这个问题的讨论中，大多数人没有真正应对的一点是，我们似乎已经拥有展现出超越人类智能的组织和结构。例如，一家公司作为一个实体，拥有单一品牌，显然是一群人的集合，但我当然希望拥有数万人的 Meta 能比一个人做出更明智的决定。如果做不到，那就太糟糕了。另一个更远离智能人格化的例子是股票市场。它接收输入，是一个分布式系统，一个控制论有机体，全球数百万人每天通过选择投资什么来投票。它是一个比任何个体都更聪明的有机体或结构，我们用它来尽可能高效地在全球配置资本。我确实认为，这些将多人的智能融合在一起，或者将多人的智能与技术融合在一起，形成比任何个体都聪明得多的网络系统，似乎已经存在，并且只要我们以平衡的方式构建这些结构，就能为社会所利用。所以这至少给了我希望。随着我们推进技术，我不知道确切需要多长时间，但在某种程度上，世界上已经有许多组织比单个个体更聪明，这似乎总体上促进了人类进步。

Sure. I still don't think I have any particular insight on when a singular AI system that is a general intelligence will get created. But I think that one thing that most people in the discourse that I've seen about this haven't really grappled with is that we do seem to have organizations and structures in the world that exhibit greater than human intelligence already. For example, a company acts as an entity with a singular brand, obviously a collection of people, but I certainly hope that Meta with tens of thousands of people makes smarter decisions than one person. That would be pretty bad if it didn't. Another example that is even more removed from the personification of intelligence is the stock market. It takes inputs, it's a distributed system, a cybernetic organism that millions of people around the world are basically voting on every day by choosing what to invest in. It's an organism or structure that is smarter than any individual, which we use to allocate capital as efficiently as possible around the world. I do think that these cyber systems that meld the intelligence of multiple people together, or meld the intelligence of multiple people and technology together, to form something dramatically more intelligent than any individual, seem to exist and seem to be harnessed productively for society as long as we build these structures in balance with each other. So that at least gives me hope. As we advance the technology, I don't know how long exactly it's going to be, but to some degree we already have many organizations in the world that are smarter than a single human, and that seems generally productive in advancing humanity.

而且不知何故，单个 AI 系统赋能了个体人类以及这些人类之间的互动，使你提到的那个集体智能机器变得更聪明。所以并不是 AI 变得超级智能，而是它成为了让主要基于人类的集体智能更智能的引擎。它更好地教育人类，让他们更知情，让他们更有效地沟通和辩论想法。通过这个过程，整个集体智能变得越来越聪明，也许比那些基于人类数据训练的单个 AI 系统变得更快。也许人类物种的集体智能可能会超过 AI 的发展。

And somehow the individual AI systems empower the individual humans and the interaction between those humans to make that collective intelligence machinery that you're referring to smarter. So it's not like AI is becoming super intelligent; it's just becoming the engine that's making the collective intelligence that is primarily human more intelligent. It's educating the humans better, making them better informed, making it more efficient for them to communicate effectively and debate ideas. Through that process, the whole collective intelligence becomes more and more intelligent, maybe faster than the individual AI systems that are trained on human data anyway are becoming. Maybe the collective intelligence of the human species might outpace the development of AI.

我认为这里有一个平衡。如果系统训练所依赖的大量输入基本上来自人们的反馈，那么很多开发确实需要按照人类的时间来发生。机器不可能直接去学习所有关于人类如何思考的东西。

I think there is a balance here. If a lot of the input that the systems are being trained on is basically coming from feedback from people, then a lot of the development does need to happen on human time. It's not like a machine will just be able to go learn all the stuff about how people think.

这件事有一个循环的运作方式。我们生活在一个激动人心的世界，而你正处在发展的最前沿。你保持谦逊的方式之一，就像我们提到的柔术，是做一些非常困难的挑战，既有精神上的也有身体上的。你最近做的一个是“Murph 挑战”，而且你取得了非常好的成绩。它包括 100 个引体向上、200 个俯卧撑、300 个深蹲，以及前后各一英里跑。你在 40 分钟内完成了。最难的部分是什么？我想很多人都印象深刻，这确实是一个非常了不起的成绩。你有多疯狂？这就是我问的问题。但这不是你的最好成绩吧？

There's a cycle to how this needs to work. This is an exciting world we're living in, and you're at the forefront of developing it. One of the ways you keep yourself humble, like we mentioned with jiu-jitsu, is doing some really difficult challenges, mental and physical. One you did very recently is the Murph Challenge, and you got a really good time. It's 100 pull-ups, 200 push-ups, 300 squats, and a mile run before and after. You got under 40 minutes on that. What was the hardest part? I think a lot of people were very impressed. It's a very impressive time. How crazy are you? That's the question I'm asking. But it wasn't your best time?

我觉得只要在 40 分钟以内我就满意了。这不是我的最好成绩，不是。我想我以前做得更快一点，但快不了多少。而且在我的朋友中，我在阵亡将士纪念日那天并没有赢。我有个朋友实际上比我快了几分钟。但我想澄清一件事，我在网上看到很多关于这个的问题：Murph 挑战有多种做法。有一种是分组模式，你把引体向上、俯卧撑和深蹲组合成几组来做；另一种是不分组模式，你先做 100 个引体向上，然后 200 个俯卧撑，再 300 个深蹲。显然，如果你不分组做，完成 100 个引体向上的时间会更长，因为你在引体向上之间休息的时候，并没有同时做俯卧撑和深蹲。所以我不分组的时间会慢很多。但说到底，首先我认为这是纪念阵亡将士纪念日的好方式。这基本上是墨菲中尉最喜欢的训练之一，我每年阵亡将士纪念日都会尝试做一次。这是一次很好的锻炼。这次我让我的大女儿们和我一起做。我大女儿想要一个负重背心，因为她看到我穿着负重背心做。我不知道一个七岁的孩子是否应该穿着负重背心做引体向上。我当时想，也许我可以给你做一个非常轻的背心，但我觉得这对她来说不太好。所以她基本上做了四分之一 Murph：她跑了四分之一英里，然后做了 25 个引体向上、50 个俯卧撑和 75 个徒手深蹲，然后又跑了四分之一英里，用时 15 分钟，这让我印象深刻。还有我五岁的女儿也是。所以我对此很兴奋。我很高兴我在教他们身体锻炼的价值。我觉得我女儿最开心的一天就是她和我一起去健身房，一口气做很多引体向上。我喜欢她这一点。希望我在教她一些好的东西。

I think anything under 40 minutes I'm happy with. It wasn't my best time, no. I think I've done it a little faster before, but not much. And of my friends, I did not win on Memorial Day. One of my friends did it actually several minutes faster than me. But just to clear up one thing that I saw a bunch of questions about on the internet: there are multiple ways to do the Murph Challenge. There's a kind of partitioned mode where you do sets of pull-ups, push-ups, and squats together, and then there's unpartitioned where you do the 100 pull-ups, then the 200 push-ups, then the 300 squats. Obviously, if you're doing them unpartitioned, it takes longer to get through the 100 pull-ups because anytime you're resting in between the pull-ups, you're not also doing push-ups and squats. So my unpartitioned time would be quite a bit slower. But no, I think at the end of the day, first of all, I think it's a good way to honor Memorial Day. It's Lieutenant Murphy basically, this was one of his favorite exercises, and I just try to do it on Memorial Day each year. It's a good workout. I got my older daughters to do it with me this time. My oldest daughter wants a weight vest because she sees me doing it with a weight vest. I don't know if a seven-year-old should be using a weight vest to do pull-ups. I was like, maybe I can make you a very lightweight vest, but I didn't think it was good for this. So she basically did a quarter Murph: she ran a quarter mile, then did 25 pull-ups, 50 push-ups, and 75 air squats, then ran another quarter mile in 15 minutes, which I was pretty impressed by. And my five-year-old too. So I was excited about that. I'm glad that I'm teaching them the value of physicality. I think a good day for my daughter is when she gets to go to the gym with me and cranks out a bunch of pull-ups. I love that about her. Hopefully I'm teaching her some good lessons.

考虑到你有多忙，生活中有多少事情，对你来说，什么样的完美锻炼计划能让你保持快乐并在主要工作中保持高效？

Given how busy you are, given how much stuff you have going on in your life, what's the perfect exercise regimen for you to keep yourself happy and productive in your main line of work?

目前我的大部分锻炼都集中在格斗上，也就是柔术和综合格斗。但我不确定，如果你是职业选手，也许可以每天都练。我做不到。我只是有太多瘀伤和需要恢复的地方。所以我每周练三到四次，其余的日子我会尝试混合做一些有氧、体能训练、力量训练和柔韧性训练。所以我尽量每天都做点身体活动。我尽量，除非我累到需要放松。但即使那样，我还是会试着去散个步什么的。即使在这里，我不知道，你上过屋顶吗？没有？我们待会儿可以去屋顶。我们设计这栋楼的时候，我在屋顶上建了一个公园，这样开会的时候，当我做一对一或者和几个人谈话时，我很难一直坐着。我觉得你会变得非常僵硬，感觉非常糟糕。但我不确定，身体活动对我来说非常重要。我认为……我不相信一个存在只是头脑。我觉得我们天生就是要做身体上的事情，我们感受到的很多感觉都与此相关。我认为这很大程度上造就了你作为人的本质：拥有围绕这一点的一系列感觉和体验，再加上一个用来推理它们的头脑。但我不确定，我认为为了平衡，走出去、以不同的方式挑战自己、学习不同的技能、理清思绪是很重要的。

Right now I'm focused most of my workouts on fighting, so jiu-jitsu and MMA. But I don't know, maybe if you're professional you can do that every day. I can't. I just get too many bruises and things that you need to recover from. So I do that three to four times a week, and then the other days I just try to do a mix of things like cardio, conditioning, strength building, mobility. So I try to do something physical every day. I try to, unless I'm just so tired that I need to relax. But then I'll still try to go for a walk or something. Even here, I don't know, have you been on the roof yet? No? We'll go on the roof after this. But we designed this building and I put a park on the roof so that way meetings, when I'm just doing a one-on-one or talking to a couple people, I have a very hard time just sitting. I feel like you get super stiff, it feels really bad. But I don't know, being physical is very important to me. I think it's... I do not believe that a being is just a mind. I think we're kind of meant to do things physically, and a lot of the sensations that we feel are connected to that. I think that's a lot of what makes you a human: having that set of sensations and experiences around that, coupled with a mind to reason about them. But I don't know, I think it's important for balance to get out, challenge yourself in different ways, learn different skills, clear your mind.

你认为人工智能为了变得超级智能，应该拥有一个身体吗？

Do you think AI, in order to become super intelligent, should have a body?

这取决于目标是什么。我认为这个问题里有一个假设，即智能应该是类似人的，但你可以有比单个人类更智能的有机体，比如股票市场，它显然没有身体，也不说语言，只是有自己的系统。所以我的猜测是，一个纯粹智能的系统，在没有相同感官的情况下，能理解的人类状况是有限的——不仅是感官，还有我们的身体随着年龄增长而变化，我们也在进化。我认为那些非常细微的身体变化驱动了很多社会模式和行为，比如你什么时候选择要孩子，你如何设计家里的东西。所以如果目标是尽可能理解人类，那么尝试建模那些感觉可能有些重要。但我认为，拥有与此分离的智能也能创造很多价值。

It depends on what the goal is. I think there's this assumption in that question that intelligence should be kind of person-like, whereas you can have these greater-than-single-human intelligent organisms like the stock market, which obviously do not have bodies and do not speak a language, and just have their own system. So my guess is there will be limits to what a system that is purely an intelligence can understand about the human condition without having the same not just senses, but like our bodies change as we get older, and we kind of evolve. I think that those very subtle physical changes drive a lot of social patterns and behavior around when you choose to have kids, how you design things around the house. So if the goal is to understand people as much as possible, then trying to model those sensations is probably somewhat important. But I think there's a lot of value that can be created by having intelligence that is separate from that.

作为人类的一个特征是我们终有一死。我们讨论了很多关于人工智能，关于可能存在的我们自己的复制品。你认为会有你我的 AI 复制品在我们去世后长久存在，让家人和亲人可以与之交谈吗？

One of the features of being human is that we're mortal, we die. We've talked about AI a lot, about potentially replicas of ourselves. Do you think there will be AI replicas of you and me that persist long after we're gone, that family and ones can talk to?

我认为我们将有能力做类似的事情。我认为在社交网络的背景下，我们不得不挣扎的一个大问题是，谁有权做这件事。而我在我们正在做的工作的背景下给出的答案是，这应该是你自己的选择。我不认为其他任何人应该能够创造它。

I think we'll have the capacity to do something like that. And I think one of the big questions that we've had to struggle with in the context of social networks is who gets to make that. And my answer to that, in the context of the work that we're doing, is that that should be your choice. I don't think anyone else should be able to create that.

人们应该可以选择创建一个“Lex 专区”，让大家可以与之交谈并训练它？是的，我们有过一些先例，比如有人可以创建一个 Lex 粉丝俱乐部页面，但不能创建一个页面声称你就是 Lex，对吧。所以我认为类似地，也许有人可以创建一个“Lex 仰慕者”AI 供人交谈，但最终是否要有一个 Lex AI，应该由你决定。

Should be able to choose to make a Lex spot that people can choose to talk to and get to train that? Yeah, and we've kind of we have this precedent of making some of these calls where I mean someone can create a page for a Lex fan club but you can't create a page and say that you're Lex, yes, right. So I think that this similarly, I think maybe you know someone maybe can make a should be able to make an AI that's a Lex admirer that someone can talk to, but I think it should ultimately your call whether there is a Lex AI.

嗯，我正在开源 Lex，所以……

Well, I'm open-sourcing The Lex, so...

你是一个有信仰的人。信仰在你的生活中扮演了什么角色？它如何影响你对世界的理解、对自己人生的理解、对工作的理解，以及你的工作如何影响世界？

You're a man of faith. What role has faith played in your life and your understanding of the world and your understanding of your own life and your understanding of your work and how your work impacts the world?

是的，我认为这涉及几个不同的方面。有哲学层面，也有文化层面。最基本的教训之一就在《创世记》的开头，对吧？上帝创造天地，创造人，按照自己的形象造人，然后问题就是这到底意味着什么。在《旧约》中，你对上帝的全部了解就是上帝创造了万物。所以我一直觉得其中一个有趣的教训是，创造本身就有一种美德，无论是艺术创作，还是建造对他人有实际用途的东西。我认为这本身就是善，这很大程度上驱动了我对道德的看法，以及我关于什么是美好人生的个人哲学。我认为美好的人生就是帮助身边的人，成为世界上一种积极的创造力量，把新事物带到世界上，无论是别人的孩子，还是创造出原本不可能存在的东西。所以这对我来说是一个非常重要的价值观。我喜欢和孩子们在一起，看到他们也在努力传递这个价值观。没有什么比下班回家看到女儿们在桌上搭乐高更让我开心的了。我小时候也这样做，对吧？很多其他人也这样做，我希望你长大后不要失去那种精神，无论是什么，都想要继续建造不同的东西。对我来说，这很重要。这是哲学部分。我认为文化部分是关于社区和价值观。自从有了孩子，这部分对我来说变得更加重要。当你还是个孩子时，你处于被灌输的阶段，几乎是自动的。我有一段时间没有怎么思考宗教，上大学时，在生孩子之前。然后我觉得有了孩子会让你真正思考你想传递什么传统，你想如何庆祝，以及你生活中想要什么样的平衡。你问的很多问题，我们讨论的很多事情——就在我们谈论死亡的时候，窗帘落下来了，这真是讽刺。和上次一样。这就是宇宙的运行方式……我们绝对活在模拟中。但请继续。社区、传统，以及信仰和宗教灌输的价值观。我们今天讨论的很多话题都是关于如何平衡经营公司或不同责任与这些。我也一直认为，相信有比你更伟大的东西在引导一切，这让人非常踏实，在你追求你所说的创造精神——在世界上创造美——时，这能给你一些谦逊。正如陀思妥耶夫斯基所说，美将拯救世界。

Yeah, I think that there's a few different parts of this that are relevant. There's sort of a philosophical part and there's a cultural part. One of the most basic lessons is right at the beginning of Genesis, right? It's like God creates the Earth and creates people and creates people in God's image, and there's the question of what that means. All the only context that you have about God at that point in the Old Testament is that God has created things. So I always thought that one of the interesting lessons from that is that there's a virtue in creating things, whether it's artistic or whether you're building things that are functionally useful for other people. I think that by itself is a good, and that kind of drives a lot of how I think about morality and my personal philosophy around what is a good life. Right? I think it's one where you're helping the people around you and you're being a kind of positive creative force in the world that is helping to bring new things into the world, whether they're amazing other people's kids or just leading to the creation of different things that wouldn't have been possible otherwise. So that's a value for me that matters deeply. And I just love spending time with the kids and seeing that they're trying to impart this value to them. Nothing makes me happier than when I come home from work and I see my daughters building Legos on the table or something. It's like, I did that when I was a kid, right? So many other people were doing this, and I hope you don't lose that spirit when you grow up and you want to just continue building different things no matter what it is. To me, that's a lot of what matters. That's the philosophical piece. I think the cultural piece is just about community and values. That part of things has become a lot more important to me since I've had kids. It's almost autopilot when you're a kid, you're in the kind of being imparted to phase of your life. I didn't really think about religion that much for a while, you know, I was in college before I had kids. And then I think having kids has this way of really making you think about what traditions you want to impart and how you want to celebrate and what balance you want in your life. A bunch of the questions that you've asked and a bunch of the things that we're talking about — just the irony of the curtains coming down as we're talking about mortality once again. Same as last time. This is just that the universe works in... We are definitely living in a simulation. But go ahead. Community, tradition, and the values that faith and religion instill. A lot of the topics that we've talked about today are around how do you balance running a company or different responsibilities with this. I always also just think that it's very grounding to just believe that there is something that is much bigger than you that is guiding things, that amongst other things gives you a bit of humility as you pursue that spirit of creating that you spoke to — creating beauty in the world. And as Dostoevsky said, beauty will save the world.

Mark，我是你的超级粉丝。很荣幸能称你为朋友。我期待明天在柔术垫上和你互相切磋，这项我们共同参与的不可思议的运动和艺术。非常感谢你今天的谈话。感谢你在技术和人类生活这么多激动人心的领域所做的一切。我迫不及待想在元宇宙中再次与你交谈。谢谢。

Mark, I'm a huge fan of yours. Honored to be able to call you a friend. And I am looking forward to both kicking your ass and you kicking my ass on the mat tomorrow in jiu-jitsu, this incredible sport and art that we both will participate in. Thank you so much for talking today. Thank you for everything you're doing in so many exciting realms of technology and human life. I can't wait to talk to you again in the metaverse. Thank you.

感谢收听本期与 Mark Zuckerberg 的对话。要支持本播客，请查看描述中的赞助商。现在，让我用艾萨克·阿西莫夫的话作为结束：“变化，持续的变化，不可避免的变化，是当今社会的主导因素。任何明智的决策都不能再只考虑世界现在的样子，而不考虑它未来的样子。”感谢收听，希望下次再见。

Thanks for listening to this conversation with Mark Zuckerberg. To support this podcast, please check out our sponsors in the description. And now let me leave you with some words from Isaac Asimov: "It is change, continuing change, inevitable change, that is the dominant factor in society today. No sensible decision can be made any longer without taking into account not only the world as it is, but the world as it will be." Thank you for listening and hope to see you next time.