Thinking Machines 谈 AI 的下一章

让我们从今天和你正在做的事情开始。你在 Thinking Machines 构建交互模型。你说这些模型让人类保持参与。这到底是什么意思？

Let's start with today and what you're working on. You are building interaction models at Thinking Machines. Models that you say keep humans in the loop. What exactly does that mean?

过去一年半，我们一直在构建前沿 AI 实验室的基础，而交互模型是我们专注于人机协作的第一个具体方向。我们创办 Thinking Machines 的原因正是想建立一个真正聚焦于人机协作的前沿 AI 实验室。这意味着很多方面，也有具体的研究方向，但我们想通过交互模型来展示我们首批成果之一。交互模型是一种新型模型。我们目前使用的模型都是基于回合制的：你说，它说，然后它在你给出提示后开始思考。当它思考时，它几乎又聋又瞎，无法感知周围发生的任何事情。然后轮到你说话时，它也无法感知你说话的方式。这不是实时的。相比之下，人与人之间的互动非常丰富。我们在沉默、思考、打断彼此时都传递了大量信息。交互模型能够捕捉所有这些细微差别。它们不是基于回合，而是基于时间，持续接收音频、文本、视频，并持续输出。我们将时间切分成 20 毫秒的片段，这让你能捕捉到打断、同时说话等现象，真正实现人机之间高带宽的丰富交互。我们认为这对于实现智能体能力、让人类在 AI 进步过程中保持参与至关重要。

We've been working for the past year and a half on the foundations of building a frontier AI lab and with the specific focus that we have, the interaction models were a first look at our concentrated bet towards human-AI collaboration. The reason we even started Thinking Machines is because we wanted to build a frontier AI lab that's really focused on the human-AI collaboration piece. That means a lot of things and there are specific research bets that go into that, but we wanted to showcase our work in one of the first bets through the interaction models. The interaction models are a new kind of model. If you consider the types of models that we work with today, they are very turn-based. So, you talk, they talk, then they go off and think once you've given a prompt on what it is that you want to do. While they're thinking, it's almost like they're deaf and blind. They cannot perceive anything else about what's going on. Then it's your turn and while you're talking, they really cannot perceive anything about how you're talking. It's not happening in real time. By contrast, our interactions with each other are very rich. There is a lot of information in our interactions when we are silent, when we're thinking, when we're interrupting one another. Interaction models are able to capture all of this nuance. They are not turn-based, they are more like time-based interaction where they are continuously taking in audio, text, video, and continuously providing output. We cut this up in chunks of 20 milliseconds and this enables you to catch things like interruptions and simultaneous speech and really create a rich high bandwidth interaction between humans and machines, which we think is critical to enable agency and enable people to be more in the loop as we advance AI further.

你基本上是在从零开始构建一个 AGI 实验室。OpenAI、Anthropic、Google、Meta 都遥遥领先，都在竞相构建更智能的模型。你下的赌注是什么，而他们没有？你认为他们低估了什么？

You're basically trying to build an AGI lab from scratch. You've got OpenAI, Anthropic, Google, Meta all with a significant head start. All of them racing to build smarter models. What is the bet that you're making that they aren't and what do you think they are underestimating?

首先，我认为推动 AI 前沿发展是极其正和的。有很多空间容纳不同的视角和技术发展方式，多样性是好的。拥有多样化的视角、构建技术的方式和不同的产品对世界有益。这是一件非常困难的事情，所以玩家并不多。进入门槛极高。但在创造差异化方面，我认为空间很大。我一直对推动 AI 系统前沿充满热情，我认为这能为文明带来巨大的变革潜力。但这并非命中注定的结果。我们构建和部署系统的方式至关重要。我认为目前工作很少的一个领域是让机器智能更接近知识所在之处。我的意思是，推动前沿 AI 系统有一条路径是非常自主的，不太依赖现实的混乱或人类的日常经验。这是一种快速推进 AI 系统自主性的方式。自主性当然是其中一部分，而且非常重要。但我认为缺失的部分是我们尚未投入足够工作的领域：真正关注人类意图、交互的混乱性、赋能人类，并将前沿 AI 系统构建为更像思维工具。我认为最先进的 AI 系统是人类所能拥有的最不可思议的思维工具。那么，这如何改变我们的思维方式？我们仍在思考，而它正在改变思维的本质和我们思考的内容。这部分我们很熟悉。从古至今，深层技术改变了我们思考的内容，比如语言、文字、数字。想象一下，如果你必须用罗马数字做乘法，那将是痛苦的。但我们发明了今天的数字，这开启了整个数学领域；一个孩子也能很快地做数学。因此，它带来了这些切实的新思维方式。我认为这就是摆在我们面前的机会：扩展我们思考的内容，拥有新的、切实的思考对象。这需要非常有意地在研究和产品方向上努力。

First of all, I think advancing the frontier of AI is incredibly positive sum. I think there is plenty of space for many different perspectives and ways of developing the technology and plurality is good. Having plurality of perspectives, ways of building technology, different products is great for the world. This is a pretty hard thing to do, so that's why we don't actually have many players. The barrier to entry is incredibly high. But in terms of creating something differentiated, I do think there is plenty of room. I have always been very passionate about advancing the frontier of AI systems and I think there is potential for so much transformation for civilization that comes from that. But it's not a predestined outcome. The way we go about building it and deploying the systems really matters. I think an area where there is very little work done so far is bringing the machine intelligence closer to where the knowledge is. What I mean by that is there is one path of advancing frontier AI systems which is very autonomous and doesn't rely too much on the messiness of reality or the experience humans have day-to-day. That's quite a fast way of advancing AI systems very autonomously. Autonomy is definitely a part of it and it's a very important part. But I think a missing part where we haven't done much work is really focusing on human intent, the messiness of interaction, enabling people more, and building frontier AI systems more like tools for thought. I think the most advanced AI systems are the most incredible tools for thought that humanity can ever have. So how can this change the way that we think? And where we're still thinking and it's changing the nature of thought and what we're thinking about. This part is familiar to us. Since the beginning of time, deep technologies have changed what we think about, like language, writing, numerals. Imagine if you had to do your multiplication with Roman numerals, it would be miserable. But we invented today's numerals and this enabled a whole area of mathematics; a child can do mathematics very quickly. So it enabled these very tangible new ways of thoughts. I think this is the opportunity ahead of us, this possibility to expand what we think about and have new tangible things that we think about. This requires very intentional research work and product work in this direction.

我采访你时是 2023 年初，ChatGPT 刚刚改变了一切。你是 OpenAI 的 CTO。我采访过的几个人说你基本上在管理公司。只是说说而已。当你离开 OpenAI 并创立 Thinking Machines 时，你是奔向某物还是逃离某物？

When I interviewed you, it was early 2023, ChatGPT had just changed everything. You were CTO of OpenAI. Few folks I talked to said you basically ran the place. Just saying. When you left OpenAI and founded Thinking Machines, were you running towards something or away from something?

一旦我弄清楚那是什么，我绝对是奔向某物。但我在 OpenAI 的经历非常棒。我非常幸运能与世界上一些最敬业、最有才华的人共事。这非常特别。我对那段经历充满感激。最终，我对这项技术应该如何发展有了自己的看法，而且是非常强烈的看法。一旦你形成了如此强烈的观点，从零开始创业是非常难得的。这是一种罕见的特权。我认为拥有 Thinking Machines 这样的公司让我们有机会专注于我们最有信心的领域，并围绕这一信念构建和定位整个公司。

I most definitely was running towards something once I figured out what the thing was. But I had an incredible experience at OpenAI. I was so incredibly lucky to work with some of the most dedicated and most talented people in the world. That's incredibly special. I'm very grateful for that experience. Eventually I had my own view and very strong view of how I think this technology ought to be developed and it's very rare to start something from scratch once you have developed such a strong perspective on it. That's a rare privilege to have and I think having a company like Thinking Machines gives us an opportunity to focus on where we have the highest conviction and build and orient the entire company around that conviction.

带我回到那年的董事会危机，那年晚些时候。你在宣誓后作证说，当 AI 面临灾难性崩溃风险时你很担心。你对 Sam Altman 的领导力提出了担忧。但在那一刻你必须采取行动。回顾过去，你认为你当时做对了吗？

Take me back to the board crisis of that year, later that year. You testified under oath that you were worried when AI was at catastrophic risk of falling apart. You raised concerns about Sam Altman's leadership. But in that moment you had to act. Looking back, do you think you got that moment right?

那是一个非常紧张的时刻，情况非常复杂。我相信很多人都曾处于感觉不可能的局面，必须迅速做出非常艰难的决定。

It was a very intense time and it was a very complex situation and I'm sure many people have been in situations that have felt impossible where you have to make really hard calls and very quickly.

我认为这种复杂性的一部分在于，外界看来这一切似乎是一夜之间发生的，但对我来说，这是多年思考的结果——关于使命、治理、如何建立一个能够以责任感打造持久变革性技术的团队。这个组织多年来一直存在很多复杂性，我们也考虑了很多。这次发生的具体事件，这个关键时刻，在时间上非常紧张。当董事会征求我的反馈时，我给出了反馈，我坚持这一点。当他们做出决定并让我担任临时 CEO 时，我照做了。当我意识到他们的决定可能对公司造成灾难性后果，事情可能会分崩离析时，我觉得我必须迅速行动。尽管表面上看起来非常混乱，但我认为在每一个时间点，我都非常清楚自己必须做什么。

And I think there is a part of this complexity that wasn't to the world it appeared that it happened overnight but to me it was years of thinking about the mission, the governance, how you build a team that can build durable transformational technologies with that responsibility. There was a lot of complexity to the organization that was there for years and we had thought about a lot. This particular thing that happened, this acute moment, there was a lot of intensity to it in time. And when the board asked me for feedback, I shared feedback, and I stand by that. And when they made the decision and asked me to step up as interim CEO, I did that. And when I realized that their decision was potentially catastrophic for the company, and things would potentially fall apart, I feel like I had to act very quickly. And even though on the surface it just looked very chaotic, I think that each point in time, I felt very clear about what I had to do.

嗯。

Mhm.

因为我最关心的是使命、使命的延续性、以及人和团队。这不是抽象的东西，而是和我一起工作了很多年、我非常在乎的真实的人。而这一切都即将可能崩溃。所以我非常清楚我必须做什么来提供连续性和稳定性，帮助让 Sam 回来，恢复局面，让团队到位，然后交付 GPT-4o 和 o1。所以正是这个原则让我非常清楚自己必须做什么。回想起来，我觉得我本应该在理解过渡计划上多停顿一下。当然，事后看来，根本没有任何过渡计划，也没有在透明度、带领团队、提供连续性方面做太多思考。回想起来，我本应该在这方面多停顿一下。

Because the thing that I cared the most about was the mission, the continuity of the mission, and the people, and the team. And this is not like an abstract thing. It's real people that I worked with for many, many years and cared very deeply about. And all of this was about to potentially implode. So it was very clear to me what I had to do to provide continuity, stability, and help bring Sam back, restore that, get the team in place to then deliver GPT-4o and o1. And so that was the principle that made it very clear to me what I had to do. In retrospect, I think that I would have paused more on understanding the transition plan. And of course, with the benefit of hindsight, there wasn't any transition plan, and there wasn't much thought put into transparency, bringing the team along, providing continuity. And in retrospect, I would have paused more on that.

有趣。前 OpenAI 董事会成员 Helen Toner 作证说，Mira 在观望风向，却没意识到自己就是风。如果你没有做你所做的事，你认为会发生什么？

Interesting. Helen Toner testified, former OpenAI board member. Mira was waiting to see which way the wind would blow, and she didn't realize she was the wind. What do you think would have happened if you didn't do what you did?

我认为 OpenAI 很可能会崩溃。

I think quite likely OpenAI would have imploded.

案件因技术性问题被驳回，所以法院从未判定 OpenAI 的领导者是否违背了他们的使命。建造世界上最强大技术的人们的品格有多重要？谁的手在控制旋钮？

The case got thrown out on a technicality, so the court never decided whether the leaders of OpenAI breached their mission. How much does the character of the people building the most powerful technology in the world matter? Whose hand is on the dial?

我认为人们的正直、品格、价值观非常重要，因为每天都有很多决策、微观决策要做，你必须信任你的团队在做正确的判断。我确实认为这方面有很多关注，这很好。但关注较少的是制度设计、决策、透明度、增加人们实际为自己做决定的自主权。所以不必像权威那样说这是安全的、这是好的、一个批准印章，而是每个人都可以自己权衡什么对他们有效。我认为我们今天构建 AI 系统的方式非常集中。这是传统方式的一部分，因为我们没有真实世界的数据和经验。推进 AI 的唯一方式是在孤岛和真空中进行。但我认为现在是不同的建设时代，我们可以从真实世界的能力、张力、限制中学到很多，并用这些数据和信息来实际引导研究方向。这使人们能够真正为自己思考。人们经常问我关于 ChatGPT 以及它的影响，当然从技术角度看它是宏伟的。但我认为 ChatGPT 最重要的影响是将 AI 带入公众意识。每个人通过与它互动来理解它是什么，而不是被告知 AI 能做什么、能力和限制是什么。

I think the integrity, character, values of the people matter a lot because there are a lot of decisions, micro decisions you have to make every day, and you have to trust your team that they're making the right calls. And I do think there's plenty of focus on that, and that's great. Where there is less focus is on the institutional design, decision-making, transparency, increasing the level of agency that people have to actually decide for themselves. So it doesn't have to be like an authority that says this is safe, this is good, a stamp of approval, but each person can weigh for themselves what works for them. And I think the way that we're going about building AI systems today is just very concentrated. And it's a part of the legacy way because we didn't have real-world data and experience. The only way to advance AI was in silo and in a vacuum. But I think today it's a different time to build where we can actually learn a lot from the capabilities, tensions, limitations in the real world, and use that data and information to actually steer the direction of research. And this enables people to actually think for themselves. Often people will ask me about ChatGPT and how the impact of all of that, and of course it's magnificent from a technology perspective. But I think the most important aspect of our impact of ChatGPT was bringing AI into the public consciousness. And people everyone kind of understanding what it is by interacting with it versus being told what AI can do and what the capabilities and limitations are.

你认为 AI 这个时刻对领导者有什么要求？我们应该信任现在掌权的领导者吗？我们应该信任 Sam Altman 吗？

What do you think the AI this moment demands of a leader and should we trust the leaders in power right now? Should we trust Sam Altman?

我认为每个人都应该拥有工具和信息，能够为自己做出这些决定。理想情况下，治理和决策的结构不应依赖于一个人。应该有制衡。我认为谁在开发系统以及人们的品格非常重要，但我确实认为讨论过于集中在这一点上，而没有足够广泛地思考制衡和系统，因为即使是善意的人也会犯错，他们可能错误估计决策的后果。所以道德不是一切。你必须考虑实际的决策结构、透明度和治理。这些都是复杂的事情，为了让尽可能多的人参与其中，你必须分享知识。你必须分享工具。这也是我们实验室采取更开放方法的部分原因。

I think that everyone should have the tools and information to be able to make these decisions for themselves. And ideally the structure of governance and decision-making should not hinge on one person. There should be checks and balances. I think it's very important who is working on the systems and the character of people, but I do think that the conversation gets too wrapped up there and not enough thinking more broadly about checks and balances and system because even people that are well-intentioned can make mistakes and they can misestimate the consequences of making a call. So morality is not everything. You have to think about the actual decision-making structures and transparency and governance. And these are all complicated things and to get as many people involved in these things as possible, you actually have to share the knowledge. You have to share tools. And this is part of the reason why we've actually taken a more open approach with our lab.

所以，这正是我的下一个问题：你学到的一切如何塑造你在 Thinking Machines 正在构建的东西、你构建的方式以及你想要创造的文化？

So, that was my next question, which is how is everything that you've learned shaping what you're building at Thinking Machines and how you're building and the culture that you want to create?

是的，我坚信继续构建前沿 AI 系统的方式是带领人们一起前进，并让人类参与其中。实际上，让人类参与其中并不完全准确，因为它听起来像是一个检查点，我们签字批准然后就可以继续了。这更像是创建不是自主前进并抛弃文明的系统，而更像是一辆双人自行车，两个人都在踩踏板。但当你上坡时，也许更强壮的人踩得更用力。但两只手都在方向盘上。这非常重要，因为这是一个不同的系统。这是一个为协作设计的系统。这就是我们试图用 Thinking Machines 构建的，我认为它非常有差异化。我希望它能增加人们的自主权。同时，它也将帮助我们引导研究方向，以创造更符合价值的输出。

Yeah, I think I have very high conviction that the way to continue building frontier AI systems is to bring people along. And to have humans in the loop. Actually having humans in the loop doesn't quite describe it because it sounds like a checkpoint where we're signing off something and then you're good to go. It's more like creating systems that are not just autonomously advancing and leaving civilization behind, but are more like a tandem bike where both people are pedaling. But when you're going up a hill, maybe whoever is stronger is pedaling harder. But both hands are on the wheel. And that's quite important because that's a different system. It's a system designed for collaboration. And that's what we're trying to build with Thinking Machines and I think it's quite differentiated. And I hope that it will increase the level of agency that people have. And also, it will help us steer the research direction towards creating outputs that are more value aligned.

因此，通过这种方法，你不仅能获得实用性，还能实现对齐，就像真正创造出在现实世界中有用的技术。

And so, you also get alignment as a result of this approach, in addition to usefulness, like actually creating technologies that are useful in the real world.

你雇佣了很多顶尖人才。有报道称出现了九位数的交易，也有一些高调的离职。你如何描述这场人才争夺战？有多残酷？我们应该如何看待这些离职？

You've hired a lot of top talent. With reports of nine-figure deals, there've also been some high-profile departures. How would you describe the war for talent? How brutal is it? And what should we read into these exits?

建立前沿 AI 实验室的一个重要部分就是拥有合适的人才。这些人不仅要有能力，还要与你的整体使命、信念以及你试图实现的目标保持一致。我不会称之为战争，因为那可能意味着出价最高者获胜。我认为在这个领域工作的大多数人真正关心的是推动领域进步。现在确实是一个疯狂的时期，很多事情都是前所未有的。在如此竞争激烈的时期从零开始建立前沿 AI 实验室，强度令人难以置信。这导致了我们看到的许多不确定性、不可预测性和波动性。但我认为，当你试图在如此短的时间内压缩进展时，其他初创公司在 5 年、10 年内发生的好事和坏事，都会在几个月或一年内发生。我认为我们看到的很多事情都可以放在这个背景下来理解。只是压缩了进展的速度。每当有好事发生，坏事也会随之而来。所以你必须平衡两者。但人们离开的原因各不相同，也许他们的热情转向了其他工作。我认为高额薪酬数字确实吸引了人们的想象力，因为它们显然非常大。但我确实认为，对于一些最受欢迎的人来说，这并非主要故事。这里有很多事情在发生，从零开始建立一家公司非常紧张，更不用说前沿 AI 实验室了。所以这是建立公司和做任何从零到一的事情所面临的挑战和痛苦的一部分。

It's definitely a big part of building a frontier AI lab, having the right people. And that's people that have the competence to do it, but also are aligned with your overall mission, conviction, what you're trying to achieve. I wouldn't call it a war because it might mean that the highest bidder wins. And I think for the most part, people that are working in this field genuinely care about advancing the field. Now, it is an absolutely crazy time, and a lot of it is unprecedented. It's incredibly intense to build a frontier AI lab from scratch during such competitive times. And so, that leads to a lot of uncertainty, unpredictability, some of the volatility that we've seen. But I think when you're trying to compress progress in such a short amount of time, things that happen in other startups over the course of 10 years, 5 years, both good and bad, are going to happen in the course of a few months, in a course of a year. And I think part of what we're seeing is contextualized in that. Just compressing the amount of progress that's happening. And whenever you have something good, something bad will come with it. So, you have to balance the two. But people leave for different reasons, maybe their passion evolved for what they want to work on. I think the high numbers and the compensation numbers capture the imagination of people because obviously they're very big. But I do think that some of the most sought-after people, that's not the main story. And I think there is a lot that goes on here, and it is very intense to build a company from scratch, let alone a frontier AI lab. So that's part of the challenges and suffering of building a company and doing anything zero to one.

Dario Amodei 预测了大量白领失业。但 Sam 最近收回了他关于就业末日的一些预测。你认为行业在哪里过于悲观，又在哪里过于乐观？比如，Mira Murati 对未来的愿景是什么？

Dario Amodei has predicted mass white-collar job loss. Sam, though, recently walked back some of his predictions about a job apocalypse. Where do you think the industry is being too pessimistic and too optimistic? Like, what is Mira Murati's vision for the future?

预测反乌托邦或乌托邦感觉过于简单化，因为事实是，我们在如何构建这项技术、构建什么工具以及如何部署方面实际上拥有很大的自主权。所以这不是一个注定的结果。当然存在这些风险。我们都理解构建前沿 AI 系统带来的巨大潜力，这也是我们致力于此的原因。我认为围绕不确定性和负面影响的讨论很多。我同意其中许多风险。也许我可能不同意或采取不同路径的地方在于，我认为我们有很大的自主权。就像这个时期，人类和 AI 系统都掌握着方向盘，我们可以合作，这是一个非常重要的时期，必须正确把握。我们越能减少新能力和巨大能力变化带来的不连续性，就越好。这就是为什么我们采用 Thinking Machines 这种方法，也是公司存在的原因。

Predicting a dystopia or a utopia feels very simplified because the truth is we actually have a lot of agency in how we build this technology, in the tools that we're building, how we're deploying it. And so it's not a predestined outcome. There are certainly those risks. We all understand the potential for greatness that comes with building frontier AI systems, and that's why we're working on them. And I think there's been a lot of talk around the uncertainty, around the downsides. And I agree with a lot of these risks. And perhaps where I might disagree or take a different path is that I think we have a lot of agency. Like this period of time where both humans and AI systems have their hands on the wheel, and we can collaborate is very important time to get right. And the more that we can reduce the discontinuity that comes from new capabilities and huge change in capabilities, the better. And this is why we took this approach with Thinking Machines, and why the company exists.

所以你说目标是让人类参与其中，但有没有一个点人类不再需要参与？然后会发生什么？

So you say the goal is to keep humans in the loop, but is there ever a point where humans don't need to be in the loop? And then what happens?

这是可能的。这更多是关于对齐意图和价值观。但如果你现在就把进步简化为将人类从开发循环中移除，那么我认为未来当 AI 系统更强大时，我们几乎没有可能做对。所以我认为更可能、更持久的路径是尽可能长时间地让人类参与其中，并真正确保这个时期非常有意义，从而以促进和推动文明的方式推进 AI。

It is possible. It's more about aligning intent and aligning values. But if you reduce progress to removing humans from this loop of development already now, then I see very little future possibilities that we can get this right in the future when AI systems are even more capable. And so I think the more likely path and more durable path to advance AI in a way that enables and advances civilization is by keeping humans in the loop for as long as we can and really making sure that this period is actually very meaningful.

你筹集了很多钱。期望很高。如果说过去几个月的 AI 新闻有什么是清楚的，那就是竞争非常激烈。你认为你有那种杀手本能去对抗 OpenAI、Anthropic、Meta、Google、中国和 X 吗？这是一个竞争激烈的世界。

You raised a lot of money. There's great expectations. If anything's clear from the last few months in AI news, it's a cutthroat competition out there. Do you think you have that killer instinct to take on OpenAI and Anthropic and Meta and Google and China and X? Like it's a competitive world.

竞争非常激烈，我们确实筹集了很多钱。我们为此感到自豪，但这并不是什么更大的成就。我们并没有打算打破某种记录。真正重要的是你用这些钱做了什么。我们不是一家普通的公司，所以我们需要大量资本来建设基础设施、科学基础以及所有必要的条件，才能真正声称要构建差异化的前沿 AI 系统。所以我认为这部分本身并不独特。至于杀手本能，那并不是真正激励我的东西。我认为实际上有很大的空间。我们正在构建一项具有无限潜力的技术。我认为要捕捉所有这些潜力很难。而激励我的是真正捕捉到一部分潜力，创造对世界有用的东西，以有用且增强人类自主性、推动文明进步的方式将其带入世界。我认为存在健康的竞争，竞争是好的。它能为人们创造更好的产品和技术。它在很多方面提高了标准。我尊重许多正在做这件事的公司。但我的动机并非每天如此。当我早上醒来时，我并没有想着如何杀死竞争对手。

It is extremely competitive and we did raise a lot of money. We're proud of that, but that's not any bigger accomplishment. We didn't set out to break some sort of record. It's really what you do with that. And we're not a normal company, so we do need a lot of capital in order to build the infrastructure, the foundations of science, and all that's required to actually have a claim at building frontier AI systems that are differentiated. And so I think that part in itself is not unique. And in terms of killer instinct, that's not really what motivates me. I think there's actually a lot of room. We're building a technology that has infinite potential. And I think that it's going to be hard to capture all of that potential. And what motivates me is really capturing part of that potential, creating useful things in the world, bringing it into the world in a way that's useful and increases human agency and advances our civilization. I think there is healthy competition and competition is good. It creates better products and better technologies for people. It raises the bar in many ways. And I respect a lot of the companies that are doing this. But my motivation is not necessarily day-to-day. When I wake up in the morning, I am not thinking about how to kill the competitor.

你说你计划在今年晚些时候发布一个预览版。你们进展如何？我们会看到什么？随着其他公司上市，你认为它们会分心，而你有更多的发展空间吗？

You said you plan to release a preview later this year. How far along are you? What will we see? With all of these other companies going public, do you think they'll be distracted and you have a little more room to run?

我们走自己的路。当然，竞争很激烈，我们必须快速行动，但平衡这一点与持久的长期进展很重要。我非常关心我们今天做出的决定是否有利于我们的长期成功。

We're on our own path. Though, of course, the competition is fierce and we have to move quickly, but it's important to balance that with durable, long-term progress. I care a lot about the decisions that we make today being good for our long-term success.

这是我每天努力向团队灌输的理念。在如何组建团队、如何构建基础设施以及真正抵制短期压力方面，有很多细节。在某些情况下，你确实必须接受压力。但对我们来说，这只是第一步。通过展示交互模型，让我们所思考和关心的内容更加具体化。我预计未来几个月，模型方面的能力会不断增强，会有更多这方面的产品。让技术和产品自己说话，让一切更加显而易见。

And that's something that I really try to instill in the team day-to-day. There is a lot of details here with how you build the team, how you build the infrastructure, and really resisting the short-term pressures. And in some cases, you do have to kind of embrace the pressure. But yeah, I would say for us, this is just a first step. And in showcasing the interaction models and making it more concrete what it is that we think about and care about. And I expect the next few months to show increased capabilities on the model side. More products in this direction. And make it more obvious, like really letting the technology and the product speak for themselves.

那么，如果 Thinking Machines 取得了超乎你最疯狂预期的成功，五年后会有什么今天不存在的东西？

So, if Thinking Machines succeeds beyond your wildest expectations, what exists in 5 years that doesn't exist today?

预测未来极其困难。但我想说，最重要的是创造一个未来，无论我们每天或每周工作多少小时，我们都能感受到一种自主感、尊严感以及对未来的可能性。我希望我们能继续推进能力，实现许多进步，并以这种方式让我们保持希望，同时感受到我们可以推动未来的可能性。

It is extremely difficult to predict the future. But I would say that the most important thing would be to create a future where regardless of how many hours of work we do day-to-day or week-to-week, we feel a sense of agency, a sense of dignity, and possibility about the future. And I hope that we'll continue to advance the capabilities that will enable a lot of progress, and we'll do it in this way that will keep us hopeful and also with a sense of possibility that we can drive about the future.

那么，为更少的不可能和更多的可能性干杯。谢谢。

Well, here's to less impossibility and more possibility. Thank you.