Sam Altman：把不可能的赌注做成平台，并承认习惯比模型更慢

主持人 I just brought up Toby Luque and the fact that I recorded with him previously. Why'd you say that you think he's one of the most interesting CEOs right now? 我刚才提到了 Toby Luque，以及我之前和他录过一期。你为什么说，你觉得他是现在最有意思的 CEO 之一？

嘉宾 One of the things that struck me the most about Toby is in the very early days of AI and then at every moment along the curve of its development, he has been the most forward-leaning CEO. He's in there like writing the software himself. He is experimenting with it. He like sends us extremely detailed feedback on the product offering, on the capabilities of the models. 关于 Toby，最打动我的一点是：在 AI 最早的那些日子，以及后来发展曲线上的每一个时刻，他都是最往前倾的那位 CEO。他自己就在里面写软件，自己在做实验。他还会给我们发非常详细的反馈，关于产品形态、关于模型的能力。

He was before anybody else was saying this, he was like, "We are not an NPC company and thus we are going to adopt agents. Otherwise, you know, we're totally screwed. We're going to build it ourselves." Every time I talk to him, he is at the edge of what anyone, CEO or not, is doing. He builds himself. He understands it. He has like a great deep feel and he is always six eight months ahead of like any other CEO. 在别人还没这么说之前，他就说：「我们不是一家 NPC 公司，所以我们会采用 agents。否则我们就彻底完了。我们会自己做。 」每次我跟他聊，他都站在任何人——不管是不是 CEO——正在做的事情的最前沿。他自己动手做，他懂这件事，他有很深的手感，而且他总是比其他任何 CEO 领先六到八个月。

主持人 Do you remember when he wrote it and it's probably like a year and a half ago, maybe 2024, he wrote that letter saying that like the first thing you have to do is see if AI can solve your problem. And then even back then it was maybe I don't know, 18 months ago, three, four months ago, people went crazy. They thought it was ridiculous. 你还记得他写那封信的时候吗，。大概一年半前，也许是 2024 年，他写了那封信，说你首先要做的事就是看 AI 能不能解决你的问题。即便当时，也许是 18 个月前，甚至三四个月前，人们还是疯了，觉得这很荒唐。

嘉宾 It was ridiculous. This is my point. Like he's just consistently been ahead. He has been correct. He's leaned in. He's very no So there's like no hype. There's nothing other than like, "Here's what it can really do right now. Here's what I think it'll be able to do soon. Here's where I'm going to push the company here." And just like extremely deep understanding of where it's at. 当时确实荒唐。这就是我的观点。他就是一直领先。他是对的。他往里倾。他非常……所以没有炒作。没有别的，就是：「它现在真正能做什么。我认为它很快能做什么。我准备把公司往这里推。」而且就是对它现在处在什么位置有极深的理解。

主持人 I never even thought of that. How much of a benefit it has to be for somebody in your position where you have somebody like that giving you intense and very direct and clear product feedback. 我甚至从没想过这一点。对你这种位置的人来说，有这样一个人给你强烈、非常直接、非常清楚的产品反馈，会是多大的好处。

嘉宾 A lot of people send product feedback. He is the only person at the intersection of like CEO of a large company and extremely accurate, detailed, on the cutting edge feedback. 很多人会发产品反馈。他是唯一处在这个交叉点上的人：大公司 CEO，同时又给出极其准确、细致、站在最前沿的反馈。

主持人 Yeah, he told me, I don't know if it was on the episode. They were if it was in the episode or if it was after, but he said he was very adamant. He's like, "We're going to look back in 2026." And I I want actually your opinion on this. I didn't even think to talk to you about this. We're going to look back on 2026 as the year that every business was up for grabs. 对，他跟我说，我不确定是不是在那一期节目里。他们… …如果是在节目里还是节目之后，但他说得很坚决。他说：「我们回头看 2026 年。 」我其实很想听你对这件事的看法。我甚至没想到要跟你聊这个。我们会把 2026 年看成每家企业都还没有定局的一年。

He said, "So, somebody is going to build the AI native version of Shopify." And he said, "And it's going to be me." And so, at night, he is literally trying to rebuild if if you started from scratch, what would you do with the current technology? 他说：「所以会有人做出 Shopify 的 AI native 版本。 」然后他说：「而且那个人会是我。 」所以到了晚上，他真的在尝试重建：如果你从零开始，用现在的技术，你会怎么做？

嘉宾 That was the other thing I was going to say about him is he does it himself. Like he is using these tools himself. He's writing software himself. He's trying the models himself. He is trying to like reimagine his work flows himself. Most CEOs, when you get to that level, have like teams of people that are managing teams of people that are trying to implement the thing and they're trying to like make you happy and they're trying to like, you know, smooth the rough edges. 我本来还想说他的另一点，。就是他自己动手。他自己在用这些工具，自己在写软件，自己在试模型，自己在重新想象自己的工作流。大多数 CEO 到了那个层级，都会有一队人管着另一队人去落地这件事，那些人想让你高兴，也想把粗糙的边磨平。

I think it's very hard to get the feel if you are not actually doing the thing and he he does it so hands-on all night long as far as I can tell. I'm not sure if 2026 will be the year that every business feels up for grabs. I might disagree with him a little bit there, uh, but I I I I get the spirit of that and I do understand that it feels like that's happening. 我觉得，如果你自己没有真正在做这件事，就很难有那种手感，而他据我所知，整晚都在这么上手地做。我不确定 2026 年会不会就是每家企业都觉得自己还没有定局的一年。在这一点上我可能和他稍有不同，但我懂他想表达的精神，也理解为什么会有那种感觉。

主持人 Do you think that's even possible? Like whether it's 2026 or 2046. 你觉得这甚至有可能吗？不管是 2026 年还是 2046 年。

嘉宾 I mean, obviously not literally every business. I think there are some things that are very anti-AI. Like the better AI gets, the more some businesses that have nothing to do with AI, I think will be harder to compete with because we'll really want these like authentic, non-technological experiences or we'll care more about sports teams or whatever. So, no, not everything, but I think there will be many software businesses that are very up for grabs. 我的意思是，显然不是字面上的每一家企业。我觉得有些事情是非常反 AI 的。AI 越好，一些跟 AI 毫无关系的生意，我觉得反而会更难被竞争掉，因为我们会非常想要那种真实的、非技术的体验，或者我们会更在乎球队之类的东西。所以不是所有事情，但我认为会有很多软件生意非常可能被重新抢走。

主持人 Would you disagree that on the timeline then? 那你是不同意时间线吗？

嘉宾 Yeah, I disagree on the timeline. I think it's going to take a little bit longer. 对，我不同意时间线。我觉得还要再久一点。

主持人 Okay, can you say more about that? 好，你能多说一点吗？

嘉宾 I love startups. Like I think startups are the coolest thing in the economy and uh, I've spent my career trying to like really understand startups. And I thought when we got to GPT-4, which was back in 20 23, I think, uh, that very quickly after that there was going to be much more disruption in software business being up for grabs right right away than turned out to be. 我热爱创业公司。我觉得创业公司是经济里最酷的东西，我整个职业生涯都在努力真正理解创业公司。我当时以为，当我们做到 GPT-4——大概是 2023 年——之后很快就会有多得多的颠覆，在软件生意马上被重新抢走这件事上，比后来实际发生的要快。

And the thing that I think I was wrong about a few things, uh, but one of them in terms of the speed, one of them is the economy just has so much inertia. People keep doing the same things they're doing. They keep buying from the same, uh, you know, company. They keep sort of wanting to use their tools in the same way. I think that's actually a positive in many ways and it's going to make this big transition in front of us go smoother and slower. 我觉得自己在几件事上判断错了，其中一件跟速度有关：经济有太多惯性。人们继续做他们正在做的事，继续向同一家公司买东西，继续想用原来的方式使用自己的工具。我觉得这在很多方面其实是好事，它会让我们眼前这场大转变走得更平滑、更慢。

I'm grateful for it, but I think it means we've all been too ambitious on timelines even with this incredible technology. I think AI is one of the most incredible technologies humanity's ever invented. Society and the economy will adapt more slowly. 我对此心怀感激，但我认为这意味着，即便有这么惊人的技术，我们所有人在时间线上都太雄心勃勃了。我觉得 AI 是人类发明过的最惊人的技术之一。社会和将会更慢地适应。

主持人 Yeah, it's funny. We were talking before we started recording that there's all these parallels to the history. Obviously, I read history for a living. When you were just talking, I wasn't even thinking about OpenAI and AI and Sam Altman. I was thinking of like reading this biography of Larry Ellison in like the '80s. He was just like, "Guys, this isn't a software problem problem. It's a people problem. We have to convince them. Like we can install software. 对，有意思。我们开录之前就在聊，这里有很多和历史平行的地方。显然，读历史就是我的工作。你刚才说话的时候，我甚至没在想 OpenAI、AI 和 Sam Altman。我在想的是读 Larry Ellison 的那本传记，大概是 80 年代。他当时就说：「各位，这不是软件问题，这是人的问题。我们必须说服他们。我们可以把软件装上去，他们不用。

They They're not using it. We have to change their behavior. The technology is there. It's like we have to now adapt humans so they actually start using the technology." 我们必须改变他们的行为。技术已经在那里了。我们现在必须让人适应，让他们真正开始用这项技术。 」

嘉宾 My own example of this was, uh, after Netflix came out and started shipping DVDs even before they started streaming, it was amazing to me that people still went to Blockbuster. It was incredible to me. Like I would just watch this cuz I kind of I drove by a Blockbuster on my way to and from school. And it was amazing to me that people still did it. And you know, like that is an example that has stuck in my head of like force of habit in the way people do things. 我自己的例子是，Netflix 出来、开始寄 DVD 之后，甚至在他们开始做流媒体之前，让我惊讶的是人们还是会去 Blockbuster。这让我觉得不可思议。我会盯着看，因为我上学来回路过一家 Blockbuster。人们居然还在那么做，这让我觉得很惊人。这个例子一直留在我脑子里：习惯的力量，人们做事的方式。

And changing behavior is just much harder than like the tech nerds realize. So, if we go back to this uproar of Toby writing that, you know, open letter or the letter to the people inside of his company, you're adopting this faster than anybody else because you're partially inventing them, right? So, are is there something where you're actually shocked at your own behavior or like, I know there's a better way to do this. 改变行为，比技术宅们以为的要难得多。所以，如果我们回到 Toby 写那封公开信、或者说写给公司内部的那封信所引发的哗然，你们采用得比任何人都快，因为你们自己也部分地在发明这些东西，对吧？

I'm even creating the product that could be better and yet I still can't get over this like habit, this force of habit? 所以，有没有什么时候你其实对自己的行为感到震惊，比如：我知道有更好的做法，我甚至在做那个可以更好的产品，可我还是跨不过这个习惯、这种习惯的力量？

主持人 100%. 百分之百。

嘉宾 Okay. 好。

主持人 I I love it. I don't think anyone's ever asked me this before. I've been waiting for this question. The thing to me that feels most psychologically inconsistent about myself is that I have for 20 years been using computers the same way. I now have a magic thing called Codex. So do you, so does everybody. That means I should completely be using my computer in a different way. I should not be clicking around uh, you know, pasting from one messaging app to another. 我太喜欢这个问题了。我觉得从来没人问过我这个。我一直在等这个问题。对我来说，最觉得自己心理上不一致的一点是：我用电脑的方式，二十年来一直是同一套。我现在有一个神奇的东西叫 Codex。你也有，每个人都有。这意味着我应该完全用另一种方式使用电脑。

I should not be scrolling mindlessly through my emails and trying to figure out which one is like least painful for me to open and respond when I don't want to be dealing with it. I should not be like keeping a to-do list and doing sort of this like these wrote computer tasks in the same way that I have for so long. And yet, there's like something in my mind that is encoded that like doing this kind of stuff is what it means to work and what it means to be productive. 我不该再点来点去，把内容从一个即时通讯应用贴到另一个。我不该漫无目的地刷邮件，试图找出哪一封对我来说最不痛苦、可以打开回复，而我其实根本不想处理。我不该再列一份待办清单，再用我用了这么久的同一套方式去做这些机械重复的电脑任务。可我脑子里好像编码了某种东西：做这类事才叫工作，才叫有生产力。

And if you asked me, I would never say I like doing it that way. I would in fact I would say the opposite and I and I think I would mean it. But like by revealed preference, I have a better way to do it now. 如果你问我，我绝不会说我喜欢那样做。事实上我会说相反的话，而且我觉得我是认真的。但按显示性偏好来看，我现在已经有更好的做法了。

I can do it faster. I can be using Codex for more of just like my day-to-day like got to get through this stack of emails, got to do this stuff on my to-do list, got to, you know, deal with all these things. And I still do it that way and it makes no sense other than I must like secretly like like it or feel good about it. 我可以做得更快。我可以把更多日常事务交给 Codex：得把这一摞邮件处理完，得把待办清单上的这些事做掉，得处理所有这些事情。可我还是用老办法，这完全说不通，除非我暗地里其实喜欢这样，或者这样做会让我感觉不错。

嘉宾 What do you think is going to has to change for you to actually adopt your own product in a more deep way? 你觉得要发生什么变化，你才会更深入地采用自己的产品？

主持人 I don't really know. I I mean, it's happening gradually and this might be the right answer, which is these things have to happen gradually and totally changing someone's like ingrained habits and workflows is difficult. 我不太清楚。我的意思是，它正在逐渐发生，而这也许就是正确答案：这些事情必须逐渐发生，彻底改变一个人根深蒂固的习惯和工作流是很难的。

Uh I think there are better products we can build with this technology that will make it more seamless to do that, but right now it feels like we're all kind of straddling these two worlds of, you know, we still have a computer we can use the old way and we have Codex that can use our computer in this amazing new way and we're like not sure which to use when for what. And I think this is mostly a product failure. 我觉得我们可以用这项技术做出更好的产品，让这种转变更顺滑，但现在的感觉是，我们都骑在两个世界之间：我们还有一台可以按老办法用的电脑，也有 Codex 能用这种惊人的新方式使用我们的电脑，而我们。不确定什么时候、为了什么该用哪一个。我觉得这主要是产品上的失败。我们现在所处的阶段，让我想起 iPhone 出现之前的智能手机。

The phase that we're in now reminds me of like smartphones before the iPhone. I was like an early adopter. I had like a Palm Trio in, you know, 2003 or 4 or whatever. 我当时是早期采用者。我大概在 2003 年或 2004 年有过一部 Palm Treo。

嘉宾 a Sidekick? Sidekick？

主持人 I never had a Sidekick. I thought they were super cool. I wanted one. I never had one. And a lot of the technology was there. Like it was missing multi-touch, but mostly it was missing like the product ideas that made the iPhone the iPhone. And I feel like we are now in a world where we have all of the technological pieces, but we have not had the iPhone moment of like completely changing how someone interfaces with technology. 我从来没有过 Sidekick。我觉得它们超酷，我想要一台，但从来没有过。很多技术当时已经在了。缺的是多点触控，但更缺的是那些让 iPhone 成为iPhone 的产品想法。我感觉我们现在处在这样一个世界：所有技术零件都有了，但还没有那个 iPhone 时刻，还没有彻底改变人与技术交互的方式。

嘉宾 We were talking about Toby's like Toby's out here building these himself, right? Uh we have a mutual friend in Josh Kushner. He says he's like there's a big comparison to be made between the way that Steve Jobs thought and the way he ran his company to way that he thinks he that you do. He wasn't the one obviously writing the code, he wasn't building the hardware, but he he's like I am patient zero. 我们刚才在聊 Toby，Toby 是自己动手在做这些，对吧？我们有一个共同的朋友 Josh Kushner。他说，Steve Jobs 思考和经营公司的方式，和他认为你做事的方式，有很大的可比性。他显然不是那个写代码的人，他也不是做硬件的人，但他说：我是零号病人。

I am making products that I myself want to use and essentially like everything that we saw with Apple was just basically what he wanted. 我在做我自己想用的产品，本质上我们在 Apple 看到的一切，基本上就是他想要的东西。

There's this great story in one of the books um where the they he they were supposed to have a meeting on uh I think one of the MacBook like the new MacBook laptops and the team prepares like all this huge presentation for Steve and they're like really nervous cuz of his commanding presence and he walks in and they think it's going to be like an hour meeting. He walks in and he shows them the laptop and he's like on off. You press the button and it comes on. 有本书里有一个很棒的故事：他们本来要开一个会，我想是关于某一代新的 MacBook 笔记本，团队为 Steve 准备了超大一套演示，他们非常紧张，因为他气场太强。他走进来，他们以为会是一个一小时的会。他走进来，把笔记本拿给他们看，说：开、关。你按一下按钮它就亮了。再按一下关上，马上。

Press off like immediately. And then he then he tries to open up the the MacBook. There's like a delay. He goes, "Make this." Meaning the MacBook like that. And then walks out the room. And that's the whole meeting. Like that there's a lot of examples in uh the history of Apple like that. Uh how do you approach it? Like how do you improve the product? Like are you just doing it through your own needs? Like how do you think about this? 然后他试着打开那台 MacBook，有一点延迟。他说：「做成这样。 」意思是 MacBook 要像开关那样。然后他就走出房间。整个会就这样。 Apple 历史上有很多这样的例子。你怎么做这件事？你怎么改进产品？你是只通过自己的需求来做吗？你怎么想这件事？

主持人 Most of my effort right now is on research and compute. I would love to be able to spend more time on product. We have great people thinking about the product here, but the most important thing that we can do is to create smart models and to be able to run them efficiently and abundantly for a lot of people. If we can get that right, I believe that everything else will follow. 我现在大部分精力都在研究和算力上。我很希望能在产品上花更多时间。我们这里有很优秀的人在想产品，但我们能做的最重要的事，是做出聪明的模型，并且能高效、充裕地为很多人运行它们。如果这件事做对了，我相信其他一切都会跟上。

主持人 Philosophically, I'm very inclined to say, you know, try to find the like the high-leverage difficult problem that will continue the exponential. And for us, this is like models and compute. I also just think those are like problems that naturally suit me. 在哲学上，我非常倾向于说：去找那个高杠杆、困难的问题，那个能让指数继续下去的问题。对我们来说，这就是模型和算力。我也只是觉得，这些问题天生适合我。

嘉宾 Why do they naturally suit you? 为什么它们天生适合你？

主持人 To scale compute in the way that we're doing this requires like it's a complex supply chain. There's like a lot of interesting partnerships uh to figure out which I like doing. There's like interesting financial challenges of how you're going to uh finance what is probably already or at least rapidly becoming the most expensive infrastructure project in history. 按我们现在这种方式去扩展算力，需要一条复杂的供应链。有很多有意思的合作关系要去理清，我喜欢做这个。还有有意思的财务挑战：你要怎么为这个大概已经是、或者正迅速成为历史上最昂贵的基础设施项目去融资。

Um the technology questions that go into building out compute at this scale from, you know, designing your own chip to the supply chain of fabs and people that make racks to to sort of the power systems for these things. I've always been interested in energy. Uh all come together. So, there are a lot of problems that are interesting across technology, business, policy, supply chain, logistics all together around building compute at this kind of scale. 把算力做到这个规模所涉及的技术问题，从设计自己的芯片，到晶圆厂和做机架的人的供应链，再到这些东西的电力系统。我一直对能源感兴趣。这些都会碰到一起。所以这里有很多有意思的问题，横跨技术、商业、政策、供应链、物流，全都围绕着以这种规模去建设算力。所以，我以前是创业投资者。

So, I used to be a startup investor. And the thing in my career that I have found closest to startup investing is managing a research program. There are all these ways in which they're really different, too. Like, you know, the average researcher and the average founder have I think, on the surface, look different for obvious reasons. 在我职业生涯里，我发现最接近创业投资的事情，就是管理一个研究项目。它们也有很多真正不同的地方。比如，平均一个研究者和平均一个创始人，表面上因为显而易见的原因看起来不一样。

But, there's like a lot of similarities about how you find the non-consensus bets, how you decide where to have conviction, how you understand what exponential growth looks like, how you manage like outlier talent, and how you how you identify even more. This is the research building that we're in. It's where I sit. 但有很多相似之处：你如何找到非共识的赌注，你如何决定在哪里有信念，你如何理解指数增长长什么样，你如何管理那种离群的人才，以及你如何识别更多这样的人。这就是我们现在所在的研究楼。我坐在这里。

嘉宾 Great. Say more about why the parallels between what you learned at Surbiton testing with doing research. 很好。再多说一点，你在创业投资里学到的东西，和做研究之间为什么会有这些平行。

主持人 One big one is the power law. Some people talk about this all the time in investing, which is you have to kind of like reprogram your brain cuz we don't seem naturally well suited to think this way. Um where, you know, your best investment will outperform all of your other investments put together. Your second best investment will outperform everything else put together after that. And AI research, at least, is like that as well. 很大的一点是幂律。投资里有人一直在讲这个：你必须重新给大脑编程，因为我们好像天生不太适合这样想。也就是说，你最好的一笔投资会超过你其他所有投资加在一起。你第二好的投资会超过那之后剩下的一切加在一起。至少 AI 研究也是这样。

When we started, people thought it was totally unlikely or almost impossible that AGI was possible. 我们刚开始的时候，人们觉得 AGI 完全不可能，或者几乎不可能。

嘉宾 What year is this? 这是哪一年？

主持人 2015. End of 2015. I mean, we just got, you know, hammered in the by like all of the intellectual giants of the field for saying that we were going after AGI. And then when we started really focusing on large language models, we got hammered again saying this is completely ridiculous. 2015 年。 2015 年底。我的意思是，我们当时被这个领域里所有知识巨头猛烈抨击，就因为我们说我们要追求 AGI。然后当我们真正开始聚焦大语言模型时，我们又被抨击，说这完全荒唐。

And we understood or I understood, at least, from my kind of like startup background, and I think other people understood in other ways, this point of high risk bets are okay as long as you take the ones where if they work, it's super valuable. And research research looks this way. The kind of people that make great researchers are sort of non-consensus, fresh approach, high energy, sort of non-standard is the word that keeps coming to mind, uh people. 我们理解，或者至少我从自己那种创业背景理解，其他人用别的方式也理解这一点：高风险的赌注是可以的，只要你选的是那些一旦做成就超级有价值的。而研究看起来就是这样。能成为伟大研究者的那种人，有点非共识、方法新鲜、能量很高，我脑子里反复出现的词是非标准。

嘉宾 You got to say more about non-standard. Can you be more specific? Are they spiky? 你得再多说一点「非标准」。你能更具体吗？他们是尖的吗？

主持人 You don't want to fund a founder who has a very slightly different take on the same idea as the last thousand people you talked to has tried to convince you and maybe convince themselves that somehow they're completely different and doing something totally new but it's mostly like trying to you know, fit in with the herd and be on the same track as everybody else and do what they're supposed to do which is start a startup and you know, they've heard Peter Thiel say enough times that you know, there's like something that you're supposed to be doing different that they kind of try to emulate that but they don't really mean it. 你不会想投一个创始人，他对同一个想法只有非常轻微不同的看法，。而这个想法是你刚聊过的上千人都有的；他试图说服你，也许也说服他自己，说他们完全不同、在做全新的事，但多半只是想融入羊群，走和其他人一样的轨道，做他们「该做」的事，也就是去开一家创业公司。他们听 Peter Thiel 说了太多次，说你应该做点不一样的事，于是他们有点在模仿那句话，但他们并不真正。

Like it's it's very clear to me when you have someone who just thinks differently than most other people and has is is willing to stand by convictions that are very unpopular may well be wrong but if right like at least they're going to be really right versus someone who is like a you know, thin veneer on the same idea that everybody else has. In 20 If in late 2015 we were starting Open AI, there were very few AGI efforts in the world. 当真。对我来说非常清楚：什么时候你碰到一个就是和大多数人想得不一样的人，并且愿意坚守那些非常不受欢迎、很可能是错的、但一旦对了就会对得很彻底的信念；对比那种人，只是在其他所有人都有的同一个想法上贴了一层很薄的表皮。如果在 2015 年末我们创办 OpenAI 的时候，全世界只有很少的 AGI 努力。

There was DeepMind one or two others that I can think of. It was like a very non-consensus thing to do. In that same year there were probably I'll just pick on it just cuz it came to mind but there are other categories too. There were probably many thousands of founders starting photo sharing apps. You know, that was probably like not as good of a thing to do. Today a lot of people want to start AI labs. 有 DeepMind，我能想到的还有一两个。那是一件非常非共识的事。同一年，我随口举这个例子，因为刚想到，当然还有别的品类：大概有好几千个创始人在做照片分享应用。那大概就不是那么好的一件事。今天很多人想创办 AI 实验室。

There are some handful of people, you know, two, three, whatever, doing something completely new um that actually wasn't possible until AI got this good but uh doesn't seem like a good idea yet. And like that is the thing that as a startup founder I always wanted to fund and the thing that mostly worked for me. There's a similar thing for researchers. 有那么一小撮人，两三个，随便说，在做完全新的事情，这些事情直到 AI 变得这么好才真正可能，但现在看起来还不像是好主意。而这正是我作为创业投资人一直想投的东西，也是对我来说多半奏效的东西。

There were a lot of researchers that would chase whatever the last thing was that worked and there were a number of researchers that had high conviction towards a new idea. And uh I think we were and are the best research lab for those people. 研究者也有类似的情况。有很多研究者会去追最近刚奏效的那件事，也有一些研究者对一个新想法有很强的信念。我觉得我们曾经是、现在也是最适合那些人的研究实验室。

嘉宾 I remember talking to Demis about this a few months ago and he thought, you know, it's in terms of like chasing after the way that you guys are. It's like, you know, there's the big three players, the money, the capital required. Like you're not There's not going to be like a fourth bigger player. But he's like there's like this 10 I forgot what the number was. I'll just make it up. 我记得几个月前跟 Demis 聊过这个，他认为，就大家追着你们这条路来说，大概就是三大玩家、所需的资金和资本。不会再有第四个更大的玩家。但他好像说有一个 10… …我忘了具体数字，我就编一个，说 10% 的可能性，会有某个像僧侣一样的研究者，会从一个我们从未考虑过的。

Say 10% chance that there's just some monk researcher that's going to approach in a way that just this angle we've never even considered. Totally. I don't know how to put a number on it, but there is some chance think you I'm making the number up, but it was like a small percentage. There is some chance of that, for sure. And I love that. Like I think that's why stuff stays exciting. I want to tell you about the presenting sponsor of this podcast, Ramp. 角度切入。完全同意。我不知道该怎么给它一个数字，但确实有某种可能性。我觉得那个数字是我编的，但就是一个很小的百分比。确实有那种可能性，肯定有。我喜欢这样。我觉得这就是事情保持兴奋的原因。我想跟你介绍一下本期播客的呈现赞助商 Ramp。我最近读了很多关于 SpaceX 的东西。

I have been reading a lot about SpaceX lately. SpaceX is one of the most valuable businesses in the world, and one of the main themes in the history of SpaceX is constantly attacking and questioning your cost. Ramp helps many of the most innovative businesses in the world do exactly that. SpaceX 是世界上最有价值的企业之一，SpaceX 历史里的一个主线，就是不断攻击和质疑你的成本。 Ramp 帮助世界上许多最有创新力的企业做的，正是这件事。运行在 Ramp 上的公司，费用中位数能砍掉 5%。

The median company running on Ramp cuts their expenses by 5%, and one thing SpaceX has demonstrated is that a religious dedication to controlling costs can help actually increase revenue because you can pursue opportunities you couldn't otherwise. And we see that in the Ramp data, too. SpaceX 证明过的一件事是：对控制成本近乎宗教般的投入，实际上可以帮助增加收入，因为你可以去追那些否则追不起的机会。我们在 Ramp 的数据里也看到了这一点。运行在 Ramp 上的公司，收入中位数也能增长 16%。

嘉宾 The median company running on Ramp also grows their revenue by 16%. So when you're running your business on Ramp and your competitors are not, you have a massive competitive advantage that compounds over time. Ramp is the only platform designed to make your finance team faster and happier. Many of the top founders and CEOs I know run their business on Ramp. I run my business on Ramp, and you should, too. 所以当你用 Ramp 经营公司，而你的竞争对手不用时，你就有一种会随时间复利的巨大竞争优势。 Ramp 是唯一一个被设计来让财务团队更快、更开心的平台。我认识的许多顶尖创始人和 CEO 都用 Ramp 经营公司。我自己的公司也用 Ramp，你也应该用。去 ramp.com，了解它如何帮你的企业省时间、省钱、并增长收入。

Go to ramp.com to learn how it can help your business save time, save money, and grow revenue. That is ramp.com. I found one of my all-time favorite quotes when I was reading the book Zero to One. The quote says, "The single most powerful pattern I have noticed is that successful people find value in unexpected places and they do this by thinking about business from first principles instead of formulas. That is exactly what AppLovin has done with their advertising platform. 就是 ramp.com。我读《Zero to One》这本书的时候，找到了我一直最喜欢的一句引言之一。那句话是：我注意到的最有力的一个模式是，成功的人会在意想不到的地方发现价值，他们做到这一点，是从第一性原理思考商业，而不是套公式。这正是 AppLovin 用他们的广告平台所做的事。

AppLovin connects you with over a billion potential new customers inside mobile games. AppLovin allows you to capture undivided attention. AppLovin ads are full-screen video ads that are watched for an average of 35 seconds. That is retention that blows other ad platforms out of the water and you can launch on AppLovin in minutes. You set the goal and AppLovin achieves it. There's no complex setup, no expertise needed and AppLovin scales quickly. AppLovin 让你连接到超过十亿个潜在新客户，就在手机游戏里面。 AppLovin 让你抓住不被分割的注意力。 AppLovin 的广告是全屏视频广告，平均会被看 35 秒。这种留存把其他广告平台远远甩在后面，而且你可以在几分钟内就在 AppLovin 上线。你设定目标，AppLovin 去达成。没有复杂的设置，不需要专业知识，AppLovin 扩展得很快。

They can put your ads in front of over a billion potential customers. Other businesses have seen immediate results, have scaled to hundreds of thousands of dollars of spend per day and increased their revenue by millions. So, you want to get started quickly before all of your competitors are on AppLovin and you can do that by going to applovin.com. That's applovin.com. Okay, so what is confusing to me? You went from founder to investor to back to founder. 他们可以把你的广告放到超过十亿个潜在客户面前。其他企业已经看到立竿见影的结果，已经把每天的花费扩到几十万美元，并把收入增加了数百万。所以你想在所有竞争对手都上 AppLovin 之前快速开始，你可以去 applovin.com。就是 applovin.com。好，那让我困惑的是什么？你从创始人变成投资人，再变回创始人。

But, why in 2015, like what got you interested in artificial intelligence to begin with that you're saying, "Hey, this is such a non-consensus thing. People think I'm crazy. I'm going to do it anyways." 但为什么是 2015 年，是什么让你一开始对人工智能产生兴趣，让你说：嘿，这是一件如此非共识的事。人们觉得我疯了。我还是要做。

主持人 Well, I had been interested in AI my whole life. I was like a very nerdy kid. I like, you know, I was like the kind of kid that spent Friday nights like playing on my computer and watching sci-fi reading sci-fi. And I always thought that AI would be um the most amazing kind of craziest thing. I never thought I'd actually get to work on it, but I always I always like loved it. Uh I even came to college sort of to study it. 我这辈子一直对 AI 感兴趣。我当时是个很宅的小孩。我就是那种周五晚上在电脑上玩、看科幻、读科幻的小孩。我一直觉得 AI 会是最惊人、最疯狂的那种东西。我从没想过自己真的会去做它，但我一直一直很爱它。我甚至上大学某种程度上就是为了学这个。

I worked in the AI lab the summer between my freshman and sophomore year. And nothing was working. In fact, like very memorably, a professor told me, "You can try all of these things. There's all these directions. The one thing we know doesn't work is deep learning. We tried that for a long time. You know, it's the it's the kind of the most guaranteed way to have a bad career. 大一和大二之间的那个夏天，我在 AI 实验室工作。当时什么都行不通。事实上，很难忘的是，有一位教授告诉我：这些方向你都可以试。有一件我们知道行不通的事，就是深度学习。我们试了很长时间。那是最能保证你职业生涯糟糕的办法。

嘉宾 And you know, I was like an impressionable freshman in college whatever. I I like I assumed that was true. 我当时就是个容易受影响的大学新生之类的。我以为那是真的。

So, you know, pursue these other things. It was clear to me at the time. This is now like kind of 2005. That AI was not working. And I happen to like accidentally get into startups but then very much fell in love with it and so I wouldn't even call it a career detour cuz it was super helpful uh looking back and becoming like a startup investor was was great. 所以就去追求其他那些方向。当时对我来说很清楚，那大概是 2005 年，AI 行不通。我碰巧误打误撞进了创业公司，然后非常爱上了这件事，所以我甚至不会把它叫做职业生涯的弯路，因为回头看它超级有帮助，后来成为创业投资人也很棒。

The sort of normal career path in Silicon Valley is you're like a or not the a a a common path is that you're a founder and then you like sort of semi-retire and you become an investor. We don't want that. 那种硅谷常见的职业路径是，你当创始人，然后有点半退休，变成投资人。我们不想要那样。

主持人 I heard you say that you're going to work on this for the rest of your career. 我听你说过，你准备把这当成余下整个职业生涯来做。

嘉宾 Yeah. 对。

主持人 I'm hopefully we're starting we're going to come on the show multiple times. I'm going to hold you to this. We don't need more founders that retire and invest. 我希望我们会开始、会多次上这档节目。我会拿这句话盯着你。我们不需要更多退休再去投资的创始人。

嘉宾 I don't want that. I don't want that. I don't want We have too many investors. 我也不想要那样。我不想要。我们投资人已经太多了。

主持人 Thank you. 谢谢。

嘉宾 I want to talk to you about this. But what I was going to say is I the the fact that I got to go in the other direction. I was like an investor first. And then I got into companies pretty unusual. 我想跟你聊这个。但我刚才想说的是，我能走相反的方向。我先当投资人，然后再进到公司里，这相当少见。

主持人 Very unusual. 非常少见。

嘉宾 And I'm super grateful for it uh because the like you get this unbelievable set of learnings and pattern matching if you really study and watch companies as an investor that has been super helpful to me. Running OpenAI. But it's like it's the opposite of normal direction. So, it's just like a very rare thing and I strongly recommend it. 我对此超级感激，因为如果你真的作为投资人去研究和观察公司，你会得到一套难以置信的学习和模式匹配，这对我经营 OpenAI 超级有帮助。但这和正常方向是反的。所以这是一件非常罕见的事，我强烈推荐。

主持人 Why is it helpful? 为什么有帮助？

嘉宾 If you're running a company, you have faced some number of similar decisions in your past like some number of like crux decisions and you've seen what works and what doesn't. And if you have to like you know, make a high-stakes strategy shift or like fire an executive in a really messy way. You have like whatever your own limited previous experience was over the last five or 10 years that you've been doing it. But as an investor,you kind of watch all the crux moments. 如果你在经营一家公司，你过去面对过若干类似的决策，若干那种关键决策，你见过什么奏效、什么不奏效。如果你必须做一个高风险的战略转向，或者以一种非常难看的方式解雇一位高管，你拥有的只是过去五到十年自己有限的那点经验。但作为投资人，。你几乎能看到所有关键时刻。

So, you don't get the kind of like operating practice that you do just day in and day out running a company, but you've seen a lot of the like big crux moments, a lot. Kind of all day long you see those. So, just the the the wealth of the data set that I have that was awesome. 所以你得不到那种日复一日经营公司才会有的操盘练习，但你见过大量的大关键时刻，很多。某种程度上你整天都在看这些。所以我拥有的那份数据集的丰厚程度，太棒了。

主持人 So, that plays in your head when you have a decision to make? 所以当你要做决策时，这些会在脑子里过一遍？

嘉宾 Yeah. I'm like, oh, this is what happened when this company had a similar thing or I saw this founder make this mistake or this founder got it really right. We were talking about that you studied the Industrial Revolution. We were talking about some great biographies that we both read earlier. 对。我会想，哦，这家公司碰到类似事情时发生了什么，或者我见过这个创始人犯过这个错，或者这个创始人做对了。我们刚才聊到你研究过工业革命。我们之前也聊过一些我们都读过的很棒的传记。

Uh my friend Daniel X says this about me cuz like I think the benefit of me doing this project my other podcast called Founders for 10 years is like so, he's like you're like an LLM trained on history of great entrepreneurs, but with the temperature turned up cuz you're crazy. Cuz I'm like super passionate about it in a weird way to be like obsessed with dead entrepreneurs, uh but it is helpful. 我朋友 Daniel X 这样说我，因为我觉得我做另一个播客 Founders 十年的好处是：他说你就像一个在伟大企业家历史上训练过的 LLM，只不过温度开得很高，因为你很疯。 【笑声】因为我以一种很怪的方式对这件事超级有热情，痴迷于已经去世的企业家，但这确实有帮助。

It's like, oh, like I'll be talking to a founder and they'll talk about something they dealt with. I'm like, oh, well, like Carnegie did this and Rockefeller did this and like you might want to try this. Like 就像，哦，我会跟一个创始人聊天，他们讲自己碰到的事。我就说，哦，Carnegie 做过这个，Rockefeller 做过这个，你也许可以试试这个。

主持人 And do you find that you have like one big insight all that or it's just like for any given scenario you have like what all these people did and how it comes together? 那你觉得自己是有一个很大的洞察，还是对任何给定场景，你都有这些人做过什么、以及它们如何合在一起？

嘉宾 I think it's depending on the personality of the founder, right? And so like when I was reading I've read your blog for years. I think like you're a great writer. You're very succinct. I like like how the brevity is just really appealing to me and I love numbered lists. It's weird that we both write in the same way and I feel like I'm reading your blog and I'm like this is the exact conclusion that I would come to based on all the reading. 我觉得这取决于创始人的性格，对吧？所以当我读… …我读你的博客好几年了。我觉得你是一个很棒的写作者。你非常简洁。我喜欢那种简短，它对我非常有吸引力，我也爱编号清单。很奇怪我们写作方式一样，我读的时候感觉像在读你的博客，然后想：基于我读过的所有东西，这正是我会得出的结论。

And like there's just a handful of principles that could be applied, but it's like it really depends on like who the founder is and what they want to do. This is what I'm trying to say is like let's go back to what we were talking about. I still like you're you're making a big jump cuz you know, you're one of the from what I hear one of the best investors of all time in Silicon Valley. You could just be rich and not really have to work cuz investors are kind of lazy. 就是有那么一小撮原则可以套用，但真的取决于创始人是谁、他们想做什么。我想说的是，让我们回到刚才聊的。我还是觉得你跨出了一大步，因为据我听说，你是硅谷有史以来最好的投资人之一。你本可以就当个有钱人，不必真的那么辛苦工作，因为投资人有点懒。

Uh I'm just kidding by the way. Uh kind of not. 我开玩笑的。也有点不是。

主持人 pretty I Having done both, I think I can say it's like much much much harder to run a company than being an investor. 相当……我两种都做过，我觉得我可以这么说：经营一家公司比当投资人难得多得多得多。

嘉宾 Exactly. And that's what you people should be doing, in my opinion. 正是如此。在我看来，人们就该去做那个。

主持人 with that. 带着那个。

嘉宾 So, then you're like, "Fuck that. I'm going to not take the easy route. I'm going to do the hardest thing ever, the thing that people think is impossible, thing you're going to be made fun of." 然后你就说：去他的，我不要走容易的路。我要去做最难的事，去做人们觉得不可能的事，去做你会被人取笑的事。

主持人 Yeah. 对。

嘉宾 I still need to understand, okay, so you're into it kid, like why would it appeal to a kid? You were living in St. Louis at the time. 我还是需要理解，好，所以你小时候就迷这个，它为什么会吸引一个小孩？你当时住在 St. Louis。

主持人 Yeah, I was living in St. Louis. 对，我当时住在 St. Louis。

嘉宾 Why would AI appeal to you back then? 那时候 AI 为什么会吸引你？

主持人 Well, I think like it appealed to every kind of computer nerd. Like I don't think it's that unusual about me. It just felt impossible. I think most people would say like of course that'd be the coolest thing ever, but it's totally impossible. I think the like the weird thing about me was like, "Okay, let's try." But I think everybody thought it Everybody would think it's awesome and something to something to go for. 我觉得它吸引了每一种。电脑宅。我不觉得这在我身上有多不寻常。它只是感觉不可能。我想大多数人会说：那当然会是最酷的事，但完全不可能。我觉得我奇怪的地方是：好，那我们试试。但我想每个人都会觉得它很棒，是一件值得去追求的事。

嘉宾 So, wait, that was a personality trait of yours as a kid that people told you that you couldn't do something, like your initial response was resistance? 所以等一下，这是你小时候的性格特点吗：别人告诉你你做不到某件事，你的第一反应是抗拒？

主持人 Not resistance, but like are you sure? Like why not? Let's try. Let's see what happens. Maybe I can. Maybe we can. I was like a very optimistic kid. And also like the more something seemed impossible, like the more intrigued I was. The idea that we could invent a technology that would let us do everything else, that would just empower people in this way that no other single technology could, that always seemed like innately incredibly appealing to me. 不是抗拒，而是。你确定吗？为什么不呢？我们试试。看看会发生什么。也许我可以。也许我们可以。我当时是个非常乐观的小孩。而且一件事看起来越不可能，我就越被吸引。我们可以发明一种技术，让我们能做其他一切，能以其他任何单一技术都做不到的方式赋能人，这个想法一直在我内心深处有惊人的吸引力。

It's like I want that thing. I want to be able to do everything else. Like I think another thing about that I kind of was like a personality trait as long as I remember is like, you know, it's like it is interesting to like really give people a lot more power, a lot more ability. In some sense, this is the whole arc of technology and I was for sure always a technology nerd. But like AI is the strongest version of that I can imagine. 就像：我要那个东西。我要能够做其他一切。我觉得关于我的另一件事，从我记事起就有点像一种性格特点：真正给人们多得多的力量、多得多的能力，是一件有意思的事。某种意义上，这就是技术的整条弧线，而我肯定一直是个技术宅。但 AI 是我能想象到的那个最强版本。

嘉宾 What did you think that it would enable back then? Like when you were a kid, you're like, "This seems like a cool technology. I want to do X. I can't do X unless AI is invented?" 那时候你觉得它会让什么成为可能？比如你还是小孩的时候，你会想：这好像是个酷技术。我想做 X。没有 AI 被发明出来，我就做不了 X。

主持人 It's always hard to remember like how much of this is the stuff that I actually thought at the time versus like what we're I was to build right Yeah, like how much my current work has like colored my memories of it for sure. As a kid I was like very into robots. 一直很难分清，有多少是我当时真正想的，有多少是。我们现在要去建造的东西。对，我现在的工作肯定已经给这些记忆上了色。小时候我对机器人非常着迷。

You know, we had like a robots club in my school and the robots at the time were like laughably I even remember at summer camp we had this like little turtle that you could control with a computer on the floor or on the table and thought that was just the coolest thing. There's something about like physical stuff moving controlled by a computer that I always thought was amazing. Now I am extremely interested in what AI can do to advance scientific discovery. 我们学校有机器人社，当时的机器人简直可笑。我甚至记得夏令营里有一只小乌龟，你可以用电脑在地板上或桌子上控制它，我觉得那简直是最酷的东西。有某种被电脑控制的物理东西在动，我一直觉得很惊人。现在我对 AI 能如何推进科学发现极其感兴趣。

In my memories as an adult I think I thought that was cool as a kid too but it feels just implausible and I assume that's an example of where like the memories have gotten more colored but now the fact that we can have AI go discover new physics and cure diseases and what it's already doing for math like I think this is I think this will be one of the most important areas even more important than automation of other tasks that AI can do just to help us understand more things. 在我作为成年人的记忆里，我觉得自己小时候也觉得那很酷，但那感觉完全不可信，我猜这就是记忆被上色的一个例子。但现在，我们可以让 AI 去发现新的物理、治愈疾病，以及它已经在数学上做的事，我觉得这会是最重要的领域之一，甚至比用 AI 去自动化其他任务更重要，只是为了帮我们理解更多事情。

We were talking earlier about this this book The Beginning of Infinity and rereading that book from today's vantage point I'm like man, AI's really going to help us do this do this important thing of understanding everything or as much as we can. I was definitely interested in the sort of like Star Trek version of like huge prosperity and abundance and and what AI could do to drive that. Maybe the memory of being interested in science is more real. 我们之前聊过《The Beginning of Infinity》这本书，从今天的视角重读，我会想：天哪，AI 真的会帮我们去做这件重要的事，去理解。一切，或者说尽可能多的东西。我当时肯定也对那种《Star Trek》版本感兴趣：巨大的繁荣和丰裕，以及 AI 能如何推动这些。也许我对科学感兴趣的那部分记忆更真实。

I also loved science and and just this idea that we could like because we were smart we could figure out how to understand the world and make predictions and do things that we couldn't without this deep understanding. I don't know, that seems like an really awesome. 我也热爱科学，以及这个想法：因为我们聪明，我们就能想办法理解世界、做出预测，去做没有这种深层理解就做不到的事。我不知道，那看起来真的很棒。

嘉宾 It's interesting how consistent over time what humans want from AI cuz like something you're describing is very similar. I just reread the biography of Claude Shannon for the second time and I had forgotten cuz I hadn't read the book in maybe 5 years and I forgot that him and Alan Turing used to meet every day for coffee when they were both at Bell Labs. This is like 1940s. Yeah. And they would just talk about AI. 有意思的是，人类想从 AI 得到什么，在时间上有多一致。因为你在描述的东西非常相似。我刚第二次重读 Claude Shannon 的传记，我都忘了，因为大概五年没读过那本书了。我忘了他和 Alan Turing 在 Bell Labs 的时候每天都会见面喝咖啡。

And they were both obsessed with their they thought it was inevitable back then. And they thought it was going to happen like 15 years from there. So like 1955 that we're going to have computers, which didn't exist, right? They had the analog versions. Uh that are that are going to be smarter than humans. And that anybody that thought that wasn't going to occur, they thought it was absolutely ridiculous. 那是 1940 年代。对。他们就只是聊 AI。他们都对这件事着迷，他们当时就觉得这不可避免。他们觉得大概再过 15 年就会发生，也就是大约 1955 年，我们会有计算机——当时还不存在，对吧？他们有的是模拟版本。那些计算机会比人更聪明。

And they're like, "Well, what would you want the computer to do?" He's like, "Solve math problems, write poetry, like solve uh cure diseases." Like you hear this over and over again. I have read a bunch of things that those guys wrote at the time. And I'm so sad they are not here to see it. Cuz they were so right about everything. We're finally the moment where AI is solving novel math problems. It is discovering other stuff. 任何觉得这不会发生的人，他们都觉得绝对荒唐。然后有人问：「那你想让计算机做什么？ 」他说：「解数学题，写诗，治愈疾病。 」你会一遍又一遍听到这些。我读过那些人当时写的很多东西。我非常难过他们没能活着看到这一切。因为他们几乎每件事都说对了。

It is, you know, you can argue about how good or not. I would say not very good, but it is writing poetry. It gets here like to what these guys I think they would have said, "All right, you've done it. Like this is it. We've got it." Um and that would be so cool. Yeah, this is the weird thing where everybody's just like, "Oh, it'll never do X." Like I talked to uh people in the music industry. 我们终于到了 AI 正在解决新颖数学问题的时刻。它在发现其他东西。它也在写诗，你可以争论写得好不好。我会说还不太好，但它写了。它走到了这些人会说的那个点：好了，你们做到了。就是这个。我们得到了。那会非常酷。对，奇怪的就是每个人都说：哦，它永远做不了 X。

It's like, "It's never going to make great music." And and then they're like, "Well, do you think it's going to like make a podcast?" I was like, "Of course it's going to." It's going to do everything that we can do at least to I would say better than like even right now like better than what we can do. It's a very bizarre thing where it's like it will never surpass what is happening at this current point that I happen to be alive. 我跟音乐行业的人聊，他们说它永远做不出伟大的音乐。然后他们又说：那你觉得它会做播客吗？我说：当然会。它会做我们能做的一切，至少我会说，甚至比我们现在能做的更好。这是一件非常古怪的事：它永远不会超越我碰巧活着的这个当下正在发生的事。

There's a deep human psychological flaw there. But here is a I think a more interesting question. Let's say it does make a great podcast. You know, two AIs are having a more interesting conversation than you and I are. Do you think people will care? Or will they want the one with the real people because we're all obsessed with people and the fact that it's not real people Yeah, for this is like more interesting. 这里有一种很深的人类心理缺陷。但这里有一个我觉得更有意思的问题。假设它真的做出了一个很棒的播客。两个 AI 正在进行一场比你我更有意思的对话。你觉得人们会在乎吗？还是他们会想要有真人的那一版，因为我们都对人着迷，而它不是真人。

It's like, "Oh, these two people who that I may be predisposed to like or dislike are having a conversation that's interesting to me." I think for like strictly like reference, like maybe my other podcast where I'm just saying, "Hey, this is an interesting ideas I read in this book." That could maybe get disrupted over the cases, but especially for people that were born before this happened, maybe it's different for your son, you know? 对，这一点更有意思。就像：哦，这两个我也许预先就喜欢或不喜欢的人，正在进行一场对我来说有意思的对话。我觉得对于那种严格的参考用途，比如我另一个播客，我只是说：嘿，这是我在这本书里读到的有意思的想法。那种情况也许会被颠覆，但对于这件事发生之前出生的人，也许对你儿子会不同，你知道吗？

主持人 Maybe. 也许。

嘉宾 But for me, it's just like I think humans are going to always be drawn to humans. 但对我来说，就是人类永远会被人吸引。

主持人 I really deeply believe that. I think there's like a lot of other jobs that could face significant transition, but stuff that's about people stuff that's about people's connection to connection to people and people liking other people, that stuff feels like it gets uh more valuable in a post-AI world, not less. 我非常深地相信这一点。我觉得有很多其他工作可能面临显著转变，但那些关于人的事，关于人与人的连接、人喜欢其他人的事，在后 AI 世界里，那些东西感觉会更有价值，而不是更少。

嘉宾 I may be actually the wrong person to talk about this 聊这个我也许。其实是错的人，。

主持人 because I kind of deeply desire, even though my entire work is digital, you know, broadcast all over the world, 因为我内心深处渴望，即便我的全部工作都是数字的、向全世界广播的，。

嘉宾 it's just like I deeply desire like more of an analog life. I like reading physical books. Like when I was talking to Kelly, I was like, "I don't want to get on Zoom. Call me. Or we'll talk in person." Like I like physical I don't like 我就是深深渴望更多模拟的生活。我喜欢读纸质书。我跟 Kelly 说话的时候就说：我不想上 Zoom。打电话给我。或者我们当面聊。我喜欢实体的，我不喜欢

主持人 like that, too. I don't read e-books. 我也喜欢那样。我不读电子书。

嘉宾 Yeah. I don't like Zoom meetings. I like to be like with people in the real world. 对。我不喜欢 Zoom 会议。我喜欢和人一起待在真实世界里。

主持人 I definitely think there's a subset of weirdos, and there's probably a lot of them that live in this city, that, you know, don't like humans and only want to communicate with computers, but it's just like I think that's a tiny percentage of humanity. 我。当然觉得有一小撮怪人，而且住在这座城市的大概还不少，他们不喜欢人类，只想和电脑交流，但那只是人类里很小的一个百分比。

嘉宾 I think it's a tiny percentage of humanity. I did This is why I think like the world is on the whole not going to be that different even with superintelligence. Like people are still going to be very fundamentally wired to care about other people, to want to be around other people, um to interact with other people. 我觉得那是人类里很小的一个百分比。这也是为什么我觉得，整体上这个世界即使有了超级智能也不会那么不同。人们仍然会非常根本地被接线成关心其他人、想待在其他人身边、与其他人互动。

And, you know, there will be some people who just like get obsessed with the models and just think humans are in the way or you know, danger to be contended with or whatever. 当然会有一些人彻底迷上模型，觉得人类只是挡路的东西，或者是需要应对的危险，诸如此类。

主持人 And for most of people, it'll be the whole point. 而对大多数人来说，人就是全部意义所在。

嘉宾 I think it's very important that when we do find people like that, to then be called out and make sure they don't acquire power. 我觉得非常重要的是，当我们真的发现那样的人，就要把他们指出来，并确保他们不会。获得权力。

主持人 I certainly agree with that. Maybe the two big risks that I'm most worried about with AI, which are a little bit in tension, one is like a a loss of control, where, you know, AI somehow just becomes too powerful in a way that we can't guarantee the control we want. And the other is power gets too centralized, where you have, you know, one company or model or person with too much power. 我当然同意这一点。也许我最担心的两个 AI 大风险，它们彼此还有点张力：一个是失控，AI 以某种方式变得太强大，我们无法保证自己想要的那种控制。另一个是权力过于集中，一家公司、一个模型或一个人拥有太多权力。

And in both of these, the fundamental thing is like I think it's a very anti-human position for either of these things to happen. The right approach is to say like we want people deeply in control of the future. We want people deeply empowered. People are the whole point of this all. 在这两件事里，根本的一点都是我觉得无论发生哪一件，都是非常反人类的立场。正确的做法是说：我们希望人深深地掌控未来。我们希望人被深深赋能。人就是这一切的全部意义。

Like that this is we are not going to sit here and, you know, gradually hand over control to an AI model because we don't trust or like people and you know, uh it's like a very misanthropic thing to say we're going to just like put all of our trust in this model and let it have all the power and decision-making over the world. But I think there are some people in the world who think that's the right outcome. 我们不会坐在这里，逐渐把控制权交给一个 AI 模型，因为我们不信任或不喜欢人。把我们所有的信任都交给这个模型，让它拥有对世界的全部权力和决策，是一件非常厌世的事。但我觉得世界上有些人认为那才是正确的结果。

There's like another version of this which is because we don't trust people, we have to limit who gets access to this technology and how they can use it and all of these terrible things could happen. And and, you know, out of fear of those, we are going to concentrate power in the hands of a few companies and they're going to, you know, we're not going to let other people use this. But we'll give them some benefits. 还有另一个版本：因为我们不信任人，我们必须限制谁能接触这项技术、他们能怎么用，以及所有这些可怕的事情可能发生。出于对这些事情的恐惧，我们要把权力集中在少数几家公司手里，然后我们不会让其他。人使用它。但我们会给他们一些好处。

Like my my caricature of this is I think there are some people in the AI field who who effectively say, "We're going to give the world a cure to all disease and we're going to make stuff really cheap in exchange for people giving up their autonomy and impact over the future and power and also in the name of safety and also like just absolutely rampant inequality. 我对这个的漫画式概括是：我觉得 AI 领域里有些人实际上在说，我们会给世界一个治愈所有疾病的办法，我们会让东西变得非常便宜，交换条件是人们放弃对自己未来的自主权和影响力，以及权力，而且还打着安全的名义，同时还伴随着极其猖獗的不平等。

Like there will be people that have access to huge amounts of wealth and power and other people just get a pretty good everything." And this is like a terrible sales pitch. This is a very anti-human sales pitch that somehow people feel willing to make. Why do you think they feel willing to make that? I think it's like fear and power. 就像有些人能获得巨大的财富和权力，其他人只是得到一个还不错的「一切」。这是一个糟糕的推销。这是一个非常反人类的推销，可不知为何有人愿意这样讲。你觉得他们为什么愿意这样讲？

I I think you can when people talk about the risks of AI, I think there are a lot of people who are so nervous about the magnitude of those risks and get so taken by that and feel the need to protect the world from that um that they're like, you know, we should trade off a lot of liberty for safety here because this is unlike other risks we've seen. But then I think that also ends up kind of like um a way to justify a lot of power seeking behavior. 我觉得是恐惧和权力。我觉得当人们谈论 AI 的风险时，有很多人被那些风险的量级吓住了，被它带走了，觉得需要保护世界免受这些，于是他们说：我们应该在这里用很多自由去换安全，因为这和其他我们见过的风险不一样。但这后来也会变成一种为大量求权行为辩护的方式。

嘉宾 Everything when I read like when I was saying the Claude Shannon and what Claude Shannon was saying or Alan Turing, at least in the books that I've read, it's more of like an optimistic like we're going to invent things that make our lives better and can do things for us. 我读到的所有东西，比如我刚才说的 Claude Shannon，以及 Claude Shannon 或 Alan Turing 所说的，至少在我读过的书里，更多是一种乐观：。我们会发明让生活更好、能为我们做事的东西。

主持人 You are totally right that if you go back to the Claude Shannon Alan Turing era, uh they talked about how wonderful AGI would be and all the things that it would do. Uh and when we started, we really had a lot of pressure from the doomers. Now, the part of the doomers that I agree with is this is a powerful technology and we should err on the side of side of safety and we should act with caution at each level of technology. 你完全正确，如果你回到 Claude Shannon 和 Alan Turing 那个时代，他们谈的是 AGI 会多么美妙，以及它会做的所有事情。而我们刚开始的时候，真的承受了来自末日派很大的压力。关于末日派，我同意的部分是：这是一项强大的技术，我们应该在安全这边犯错，应该在技术的每一个层级都谨慎行事。

The part of the doomers that I don't agree with is that it's an unsolvable problem. If you go back to the beginning of OpenAI, um I think there would have been two widely held opinions. Number one, not at all and certainly not in 10 years were we going to build something that was very AGI like. And then conditioned on if we did,we certainly were not going to be able to make it safe. 我不同意末日派的部分是：这是一个无法解决的问题。如果你回到 OpenAI 的起点，我觉得当时会有两个被广泛持有的观点。第一，我们完全不会、当然也不会在十年内，做出非常像 AGI 的东西。

You know, if you had an AI that was smarter in many ways than a lot of the smartest people, most of the smartest people, then, you know, the doomers would say surely at that point the world would have been destroyed. The alignment thing would have failed and they were just these very confidently held positions about what would have happened. A decade on, uh we have built something that I think most people would say at at the time would have said is very AGI like. 然后，在如果我们真的做出来这个条件下，我们当然也无法让它安全。如果你有一个 AI，在很多方面比很多最聪明的人、比大多数最聪明的人更聪明，那么末日派会说：到了那个点，世界肯定已经被摧毁了。对齐这件事会失败。这些都是非常自信地被持有的、关于会发生什么的立场。十年之后，我们已经做出了某种东西，我觉得大多数人在当时会说它非常像 AGI。

And you know, a lot of good things have happened and the kind of crazy bad predictions of the world ending have not happened. So, I think that should update people's predictions about the future. There are still higher stakes challenges in front of us to solve, but our approach, this is another thing I learned from startups, of the way you do things is to put things out into the world, get feedback from real customers, see where they break, see where they don't break. 而且，很多好事已经发生了，那些世界末日式的疯狂糟糕预测并没有发生。所以我觉得这应该更新人们对未来的预测。我们面前仍有更高赌注的挑战要解决，但我们的方法——这是我从创业公司学到的另一件事——做事的方式就是把东西放到世界上，从真实客户那里得到反馈，看它们在哪里会坏、在哪里不会坏。

That is the way you make a good product. That is also the way you make a safe product. And we have made way more progress on AI safety than I think most people thought we would when we started. 那就是你做出好产品的方式。那也是你做出安全产品的方式。我们在 AI 安全上取得的进展，比我想大多数人在我们刚开始时以为的要多得多。

嘉宾 Why? Because so many people there's billion people using your products on a weekly basis? 为什么？因为有那么多人，每周有十亿人在用你们的产品？

主持人 And each time we get a new level of model, we put it out in the world and we see what, you know, what works, what doesn't work, where people need us to relax the guardrails cuz they have good things they want to use it for, where we have alignment failures, where where we have safety systems failures. ChatGPT's only been out like less than 4 years. Billion people use it. And sensitive important stuff. 而且每一次我们得到新一级的模型，我们就把它放到世界上，看什么奏效、什么不奏效，人们需要我们在哪里放松护栏，因为他们有好事想拿它来做，我们在哪里出现对齐失败，在哪里出现。安全系统失败。 ChatGPT 问世还不到四年。十亿人在用它。而且是敏感、重要的用途。

And the fact that we can deliver something that is broadly considered safe, of course there's issues with it. Like in that short of a time frame with such a powerful technology, I think there is no way we could have done that in our three tower. And, you know, this is how I believe you build good safe robust useful technology and products. And I think it's a great a great learning of Y Combinator. 我们能在这么短的时间里，交付一个被广泛认为安全的东西——当然它有问题——用这么强大的技术，我觉得我们绝不可能关在象牙塔里做到这一点。而且，你知道，我相信这就是你建造好的、安全的、稳健的、有用的技术和产品的方式。我觉得这也是 Y Combinator 一个很棒的教训。

And it would have seemed to most of the AI safety people, you know, totally impossible to get to this stage and still have the level of safety guarantees we have now. I do think it gets harder from here, but I don't think you're going to solve it by disconnecting yourself from reality. 对大多数 AI 安全的人来说，走到现在这个阶段、同时还保有我们现在这种安全保证，当时会显得完全不可能。我确实觉得从这里开始会更难，但我不觉得你能靠切断和现实的连接来解决它。

嘉宾 Why does it get harder from here? Cuz we're as about the smartest people in the world are as about as smart as the smartest models in the world and that's going to flip right now? 为什么从这里开始会更难？因为我们大概和世界上最聪明的人一样聪明，而世界上最聪明的模型和我们差不多一样聪明，而。这一点现在就要翻转了，对吗？

主持人 Yeah, direction I think that's right. I think that the models are just so incredibly capable and improving on such a steep trajectory is that the unknown unknowns maybe they don't get harder relatively, but from an absolute perspective they they seem harder. And I think we'll have to make a bunch of difficult decisions about you know, when we delay development, when we sort of say, "Okay, you know what? 对，方向上我觉得是对的。我觉得模型已经强得不可思议，并且沿着一条很陡的轨迹在改进，所以那些未知的未知，也许相对来说不会更难，但从绝对角度看它们显得更难。我觉得我们将不得不做一堆困难的决定，关于我们什么时候推迟开发，什么时候说：好，你知道吗，现在让它接触现实，或者我们再等久一点，更认真地研究这个。

Let's have contact with reality now or let's let's wait longer to really study this more." So, I was on a plane recently and something that stuck in my mind is that the you know, the FAA FAA has helped make flying incredibly safe. Flying on the surface seems like this extremely dangerous thing. 所以我最近在飞机上，有一件事留在我脑子里：FAA 帮助让飞行变得极其安全。飞行表面上看起来是一件极其危险的事。

And you probably get on an airplane without giving it much thought. And this was certainly you know, airplanes are not that old in the long tradition of human history and this was certainly not the case at the beginning of airplanes. They have extremely robust accident reporting, extremely clear-eyed. You're never They never try to like, you know, hand-wave over something. They want to extract as much information as possible. 而你大概上飞机时不会多想。这在人类历史的漫长传统里当然还很新，飞机并不古老，在飞机刚出现的时候当然也不是这样。他们有极其稳健的事故报告，极其清醒。他们从不试图把事情糊弄过去。他们想提取尽可能多的信息。某种意义上，我觉得对任何新技术，这样一种方法都非常有效，而且常常被低估。

And in some sense,I think with any new technology, an approach like that works very well and is often under appreciated. So, when we started deploying our models, when we said, "We're going to put ChatGPT out in the world." We know the model's imperfect. Um we know it hallucinates. We know it can do other things, but we also know that the world's got to experience this technology and we've got to learn how to make it safe and we've got to put the power in people's hands. 所以当我们开始部署模型，当我们说我们要把 ChatGPT 放到世界上，我们知道模型不完美。我们知道它会幻觉。我们知道它还能做其他事，但我们也知道世界必须体验这项技术，我们必须学会如何让它安全，我们必须把力量交到人们手里。我们不能只用它来强加我们的世界观。

We cannot just use this to impose our worldview. We cannot use this to go sit in a lab and try to think through all the impacts, which won't work anyway because society and the models are going to co-evolve. Like, we have to all do this together as this joint product. And then we'll do very good accident recording. We will study when something goes wrong. We will put out a very clear postmortem. We will learn as much as we can. 我们不能用它坐在实验室里试图想遍所有影响，那反正也不会奏效，因为社会和模型会共同演化。我们必须作为这件共同的产品，一起做这件事。然后我们会做非常好的事故记录。出了问题我们会研究。我们会发布非常清楚的事后复盘。

We will not only improve our own technology and products, we'll try to share those learnings with other people building AI. I think that's worked surprisingly well so far, and that was like good examples from history of technology, good examples from startups. 我们会尽可能多地学习。我们不仅会改进自己的技术和产品，也会试着把这些学习分享给其他在做 AI 的人。我觉得到目前为止这出奇地有效，而这就是技术史上的好例子、创业公司里的好例子。

嘉宾 Deel is how the best founders turn the world into their talent pool. I've been studying how history's greatest founders operate for a decade, and one thing they all have in common is they understand that recruiting and hiring the very best talent is your most important priority. A players recognize other A players, which is why top companies like Ramp, Shopify, Eleven Labs, Uber, and DoorDash all use Deel. Deel 就是最优秀的创始人如何把全世界变成他们人才池的方式。我研究历史上最伟大的创始人如何运作已经十年了，他们的共同点之一是：他们理解招募和雇用最顶尖的人才是你最重要的优先级。 A 级玩家认出其他 A 级玩家，这就是为什么像Ramp、Shopify、Eleven Labs、Uber 和 DoorDash 这样的顶尖公司都在用 Deel。

Many of the top founders I know have personally invested in Deel after using their product. And what they discovered is that Deel is the best company in the world at building infrastructure for global hiring. Deel will help your business hire, pay, and manage any worker anywhere in the world, so you can retain the best talent anywhere, and spend the rest of your time focusing on what you do best, delivering value to your customers. 我认识的许多顶尖创始人在使用他们的产品之后，还亲自投资了 Deel。他们发现的是，Deel 是世界上最擅长为全球雇佣建设基础设施的公司。 Deel 会帮助你的企业在世界任何地方雇佣、支付和管理任何工作者，这样你就能留住任何地方的最优秀人才，把其余时间花在你最擅长的事上：为客户交付价值。

The founder of Eleven Labs has a great description of the value Deel can give your company. He said, "We built Eleven Labs to break down language and communication barriers. With Deel enabling us to hire and support exceptional talent anywhere, we can accelerate our innovation and bring more voices, stories, and ideas to every corner of the world." Deel is trusted by over 40,000 businesses. Learn how they can help your business today by going to deel.com/centra. Eleven Labs 的创始人对Deel 能给你的公司带来的价值有一个很好的描述。他说：「我们创立 Eleven Labs，是为了打破语言和沟通的障碍。有了 Deel 让我们能够在任何地方雇佣和支持杰出人才，我们就能加速创新，把更多声音、故事和想法带到世界每一个角落。 」Deel 被超过 4 万家企业信任。今天就去 deel.com/centra，了解他们如何帮助你的企业。就是 deel.com/centra。

That is deel.com/centra.

主持人 One thing that has to be disorienting for you, cuz I it doesn't make any sense to me, like, you know, essentially what I focus on is just entrepreneurship and entrepreneurship, right? So, all the podcasts I make are for the benefit of entrepreneurs. 有一件事对你来说一定很让人迷失方向，因为对我来说完全说不通。你知道，我本质上关注的就是创业和创业，对吧？所以我做的所有播客都是为了创业者的利益。

I'm glad other people listen, but it's like heavily focused on just trying to serve try to find useful information, whether it's in a biography of a dead entrepreneur or talking to somebody like you, that other entrepreneurs can benefit from this conversation, right? Or any of the podcasts that I make. So, in that, there's not like a lot of Actually, we love AI. But like what I I I I'm trying to figure out like if you can help me reconcile this like Everybody uses AI. 我很高兴其他人也听，但焦点非常集中在：试着提供有用的信息，不管是来自一位已故企业家的传记，还是和你这样的人聊天，让其他创业者能从这次对话中受益，对吧？或者从我做的任何播客中。所以在这件事上，并没有很多… …其实我们热爱 AI。但我在试图搞清楚你能不能帮我把这件事对上：每个人都在用 AI。

Everybody hates AI. What the hell's going on there? 每个人都恨 AI。这到底是怎么回事？

嘉宾 Well, people are always afraid of like rapid socioeconomic change. Talked about the Industrial Revolution earlier. I love I love reading about previous technological revolutions, too. And like people did not have universally warm and fuzzy feelings to the change that was happening during the throughout the Industrial Revolution. 人们总是害怕快速的社会经济变化。我们之前聊过工业革命。我也爱读以前的技术革命。人们在整个工业革命期间，对正在发生的变化并没有普遍温暖、模糊的好感。

I think it's probably a good feature of human society that we have some built-in inertia. We have some skepticism of rapid change. I think that probably helps society in times of turmoil or in times of you know, localized craziness or whatever. Um so some of it is probably good. And I think a feature of human biology, which I believe in never trying to fight too hard. 我觉得人类社会有一些内置的惯性，大概是一件好事。我们对快速变化有一些怀疑。我觉得这在动荡时期，或在局部疯狂的时期，大概能帮助社会。所以其中一些大概是好的。我也觉得人类生物学有一个特征，我相信永远不要太用力去对抗它。

I also think a lot of people building AI uh you know, have been off saying there's a 25% chance we're going to destroy the world and yet we're going to race ahead to do it because otherwise those bad guys will do it first or you know, it's like man, this thing is going to be really terrible and there's going to be 50% of the jobs are going to go away in the next year and we hope you all are okay, but seems really scary. 我还觉得很多在做 AI 的人一直在外面说：有 25% 的可能性我们会毁掉世界，可我们还是要抢着往前冲，否则那些坏人会先做；或者说，这东西会非常糟糕，明年 50% 的工作会消失，希望你们都还好，但看起来真的很可怕。

Like we have not as a field done a very good job of explaining to people what the benefits are and how the downsides can be mitigated and we certainly have not done a good job even if people have had answers like, you know, saying well, there's going to be universal basic income or work will be optional or whatever. There's been very little discussion from people about how and why it's important that people have more power and first personal freedom in the world, not less. 作为一个领域，我们并没有很好地向人们解释好处是什么、坏处如何被缓解。即便人们有过答案，我们也肯定没有做好，比如只是说会有。全民基本收入，或者工作将变成可选项，诸如此类。很少有人真正讨论：为什么人们在这个世界上拥有更多权力和第一人称的自由、而不是更少，是重要的，以及如何做到。

And that matters a lot to most people. The ability of people to influence their own future and collectively to design kind of where society is going to go and the autonomy that comes with that, very important. And I don't think a lot of people in the AI field they feel it for themselves, but they don't spend much time thinking about it, reflecting on it, acknowledging how important that is to other people. 这对大多数人非常重要。人们影响自己未来的能力，以及集体去设计社会将走向何方的能力，还有随之而来的自主，非常重要。我觉得 AI 领域里很多人自己能感觉到这一点，但他们没花多少时间去想它、反思它、承认这对其他人有多重要。

And so to go back to that like characterization of the sales pitch, characterization of this characterization of the sales pitch, I don't know if that's a word, from earlier. It is. Um the like, "Dear peasants, we will bequeath upon you these gifts of a cure for cancer and material wealth and some things and you know, great entertainment. 所以回到之前那种对推销的刻画，对这种推销的刻画，我不知道那是不是一个词。它是。就像：「亲爱的草民们，我们将赐给你们治愈癌症的礼物、物质财富和一些东西，还有很棒的娱乐。

And you stop complaining and we'll make all the decisions about the future and just trust us, you know, we'll be benevolent dictators." Not good, not good. As a lover of entrepreneurism and sort of like a student of what has made this incredible economic miracle of recent centuries work. 你们别再抱怨了，未来的所有决定我们来做，只要信任我们，我们会是仁慈的独裁者。 」不好，不好。作为一个热爱企业家精神的人，以及近几个世纪这场惊人经济奇迹何以奏效的学习者。

Really empowering people to go do new stuff and to push on the things they believe in and to have the freedom to create companies and invent technology and sort of pursue ideas and like the system around that that makes that happen. There is like nothing I believe in more strongly. And I think even if people don't see themselves as an entrepreneur ever, if they they may never want to start a big company, they do understand how important that is. 真正赋能人们去做新的事，去推进他们相信的东西，去拥有创办公司、发明技术、追求想法的自由，以及让这些发生的那套系统。没有什么是我更强烈相信的。我觉得即便人们从不把自己看成企业家，即便他们可能永远不想创办一家大公司，他们也理解这有多重要。

And then when you hear people kind of implicitly or explicitly saying there's going to be less of that with AI cuz a smaller number of people are going to have the power, but they're going to make great decisions and keep everybody safe. I think that's very scary to them. I also think that even if maybe most people don't want to start really big companies a lot of people want to start smaller companies and that has been hard. 然后当你听到人们有点隐含或明确地说，有了 AI 这些会变少，因为更少的人会拥有权力，但他们会做出伟大的决策并保证每个人安全。我觉得这对他们非常可怕。我也觉得，即便也许大多数人不想创办非常大的公司，很多人想创办更小的公司，而这向来很难。

That has been something that has required a fair amount of privilege and luck and resources to be able to do. And we are about to see the greatest boom in people starting smaller businesses that we have ever seen. I think AI is empowering that. 那件事一直需要相当多的特权、运气和资源才能做。而我们即将看到有史以来最大的一波人们创办更小生意的浪潮。我觉得 AI 正在赋能这件事。

Now, for some reason the field, including us, not talked about that enough even though we see all these signs of it and it's it's great and we have not built enough products to accelerate that but I think we're going to see a lot more of that. 不知为何这个领域，包括我们，即使看到了所有这些迹象，也还没有足够多地谈论它，这很棒，而我们还没有做出足够多的产品去加速它，但我觉得我们会看到更多。

主持人 It's funny we talked about Toby Lütke earlier. At the end of the conversation and I think that's in the episode he mentioned something I didn't think about it. He's like oh yeah you and me are in the same business. He's like we're both trying to create more entrepreneurs. He's building infrastructure for entrepreneurs I'm building educational and inspirational podcast for them. 有意思，我们之前聊过 Toby Lütke。谈话结束时，我想那是在节目里，他提到一件我没想到的事。他说：哦对，你和我是同一门生意。他说我们都在试图创造更多创业者。他在为创业者建造基础设施，我在为他们做教育和激励的播客。

And the crazy thing what you just said is like not only I think out of any new industry it sounds like that as industry the AI industry which it's doing the worst job I've probably ever seen. And I think part of it is just the ability you guys have to get out there and talk about the stuff that you're seeing and educate. There's a great book called the Intel Trinity and it tells the story of Intel. 而你刚才说的疯狂之处是：不仅如此，我觉得在任何新行业里，听起来 AI 这个行业大概是我见过做得最差的。我觉得部分原因只是你们有没有能力走出去，谈论你们正在看到的东西并去做教育。有一本很棒的书叫 the Intel Trinity，它讲的是 Intel 的故事。

And it's called the Trinity because the three main players are Bob Noyce, Andy Grove, and Gordon Moore. And when they there's a great story in the book that I never forgot. They go from inventing I think the integrated circuits to the microprocessor and they realized that technology was so important and it would scare the their potential customers. So they went out they stopped those three people stopped doing what they're doing and went out and started educating 它之所以叫 Trinity，是因为三个主要人物是 Bob Noyce、Andy Grove 和 Gordon Moore。书里有一个我从未忘记的故事。他们从发明集成电路走到微处理器，然后意识到这项技术太重要了，会吓到他们的潜在客户。于是他们走出去，这三个人停下手里的事，开始去做教育。

嘉宾 Yeah. 对。

主持人 potential customers, investors, the entire country. And they said at one time they were putting on more classes than like the local community college had in their entire course catalog. That's how much they made it a top priority like we're going to get out and educate about this new technology. It's just like why is anyone in AI doing that? 教育潜在客户、投资人、整个国家。他们说，有一段时间他们开的课比当地社区大学整个课程目录还多。他们就是把这件事当成最高优先级：我们要走出去，教育这项新技术。为什么 AI 领域就没人这么做？

嘉宾 I mean no excuse we should be doing more. I think we've like tried versions of this we haven't gotten any quite right. We're doing it right now. 没有借口，我们应该做得更多。我觉得我们试过这个的一些版本，还没有哪个完全做对。我们现在就在做。

主持人 We're like this is the point of one of the points of reason I wanted to talk to you about because like I use AI all the time I think it's fascinating but you have such like this you have a view that makes mine look like like the the view of an ant. Like you have there's so much stuff in your head that I want to like get out and be like hey you have all this context. It's like and you're inventing this incredible technology I would love to know how other people are using it. 我们… …这也是我之。所以想跟你聊的原因之一，因为我自己一直在用 AI，我觉得它很迷人，但你有一个视角，会让我的视角看起来像蚂蚁的视角。你脑子里有那么多东西，我想。把它们掏出来，说：嘿，你有这么多上下文。而且你在发明这项惊人的技术，我很想知道其他人在怎么用它。

Actually before you even get to other people I heard you say something that was interesting I think ties to what you just said about kind of like we're inventing technology the technology is increasing rapidly but the adoption should be slow and deliberate. And I heard you on another podcast saying, "Hey, I'm even considering like how much should I let AI see every single thing that's on my computer?" You want to talk about that? 其实在讲到其他人之前，我听你说过一件有意思的事，我觉得它正好连上你刚才说的：我们在发明技术，技术在快速增强，但采用应该缓慢而审慎。我听你在另一档播客里说：嘿，我甚至在考虑，我该让 AI 看到我电脑上的每一件事多少。你想聊聊这个吗？

嘉宾 With the latest generation of models, I don't want to say they they feel smart enough cuz I think we should always aspire for them to get smarter, but they are pretty smart. And I feel more limited at this point by the amount of useful context the AI has on me. Like I want the AI to know as much as it can to help me. I want it to be doing things I can't or don't want to do on my own. Like I I'm not going to read every post on our internal Slack. 到了最新一代模型，我不想说它们。已经够聪明了，因为我觉得我们应该永远渴望它们变得更聪明，但它们已经相当聪明。我现在感觉更受限的是，AI 关于我的有用上下文有多少。我想让 AI 知道尽可能多的东西来帮我。我想让它去做我自己不能做、或不想做的事。

I'm not going to go read every story a customer has to tell about where ChatGPT works for them or failed them. I can't. And then there's like other stuff of like I just you know, I probably could read more research papers than I do, but like oh, it's like takes a lot of mental energy and you know. 我不会去读我们内部 Slack 上的每一条帖子。我不会去读客户讲的每一个关于 ChatGPT 在他们那里奏效或让他们失望的故事。我做不到。然后还有其他事，比如我大概可以比现在读更多研究论文，但那会消耗很多心力。

But I would love to have an AI agent that is constantly trying to be helpful to me and that can look at and understand more context than I can or that I have time for or energy for to do on my own and can help bring that context to bear and give me good advice when I have to make a decision. 可我会很想有一个 AI agent，不断试图对我有帮助，能够查看并理解比我更多的上下文，比我自己有时间或有精力去做的更多，并能把那些上下文用上，在我必须做决策时给我好的建议。

So, I think we focused correctly so much on model intelligence that on the product side we have not yet thought enough about what it means to give a model more context than any person could have and help advise that person on on their big decisions. My sense is we are just on the precipice of being able to see a very different way of working with AI on a on a on an axis where people just can't get this good. 所以我觉得我们正确地在模型智力上投入了。那么多，以至于在产品这边，我们还没有足够多地去想：给一个模型比任何人都多的上下文、并帮助建议那个人做重大决策，意味着什么。

There are plenty of like very smart people, but there is no one that can read like you know, tens of thousands of pages of context in some small number of seconds. And really like use that accurately. And this is something that AI can do that just is going to be very new and an incredible supplement. You've read all these biographies. 我的感觉是，我们正站在能够看到一种非常不同的与 AI 共事方式的边缘，那是在一个人们永远无法变得这么好的轴上。有很多非常聪明的人，但没有任何人能在几秒钟内读完几万页。上下文，并且真正准确地用上它。而这正是 AI 能做的事，这会非常新，会是一种不可思议的补充。

There are probably times where you vaguely remember something that if you could remember a specific anecdote from one of them, it would like really help an entrepreneur in one moment for that particular entrepreneur right when you're talking to them. But maybe you forgot it or maybe you don't remember it exactly right. 你读过这么多传记。大概会有些时候你模模糊糊记得某件事，如果你能记起其中一个具体轶事，它会在那一刻真正帮到某一个创业者，就在你跟他谈话的时候。但也许你忘了，或者记得不够准。

主持人 I built my own AI tools. I use it internally. So, you know what it is? It's only trained on since 2018 I've kept every single note and highlight from every single book that I've ever used in this database. And I would search it for that. And then when your the work that you guys do came out, then I added So, I have it trained on that then every note, every highlight, and then all the transcripts from my episodes of Founders. I use this thing every single day. 我给自己做了 AI 工具。我在内部用。你知道它是什么吗？它只训练在：从 2018 年以来，我把每一本书的每一条笔记和高亮都放进了这个数据库。我会去搜索它。然后当你们做的工作出来之后，我又加了进去。所以它训练在那些上面，然后是每一条笔记、每一个高亮，再加上我 Founders 每一集的逐字稿。我每天都在用这个东西。

嘉宾 That's awesome. 那太棒了。

主持人 To to make every single episode. So, I'm working on Claude Shannon, right? The Claude Shannon episode came out I don't know, two or three weeks ago whenever it was. And I'm asking questions about all I was like, "Hey, what did Bob Noyce say about this? Or what did Rockefeller do about this?" And I I I made the episode. I read the book. I took the note. I don't remember it cuz it was like 7 years ago. It's incredible. This is what I mean. I was like, "AI's awesome." 去做每一集。所以我在做 Claude Shannon，对吧？Claude Shannon 那一集大概两三个星期前出来，不管具体什么时候。我在问各种问题，比如：嘿，Bob Noyce 对这件事说了什么？或者 Rockefeller 对这件事做了什么？然后我做了那一集。我读过那本书，我做过笔记，我不记得了，因为那是大概七年前。这太不可思议了。这就是我的意思。我说：AI 太棒了。

嘉宾 That is so cool. Let's get into like how you think about running the company, right? So, you're spending your time you said your your main focus is getting more compute and then research, right? Okay. So, you want the models to be the best in the world. But how do you think about like do you have to build your own products? And you built Codex, right? What I don't even know the the product lines. Like where's all the revenue coming from? Like 那真的太酷了。我们来聊你怎么想经营这家公司，对吧？你说你把时间花在……你的主要焦点是拿到更多算力，然后是研究，对吧？好。所以你想让模型成为世界上最好的。但你怎么想，你必须做自己的产品吗？你们做了 Codex，对吧？我甚至不知道产品线。收入都从哪里来？

主持人 Actually, I be more of a platform company than a product company. 其实，我更希望做一家平台公司，而不是产品公司。

嘉宾 Okay. 好。

主持人 we will build products, of course. 我们当然会做产品。

嘉宾 Well, how many products you have Let's back up. How many products you have now? 那你们现在有多少产品？我们往回一点。你们现在有多少产品？

主持人 We just merged ChatGPT and Codex together. So, we used to have like ChatGPT, Codex, and the API. 我们刚把 ChatGPT 和 Codex 合并到一起。所以以前我们大概有 ChatGPT、Codex 和 API。

嘉宾 Okay. 好。

主持人 You know, and Codex sort of unfortunately named, but it was not just coding. It could kind of do any kind of work, which confused people. Codex 这个名字有点不幸，但它不只是编程。它几乎能做任何一种工作，这把人搞糊涂了。

嘉宾 I'm confused by that. 我就被搞糊涂了。

主持人 Yes. 是的。

嘉宾 Okay. 好。

主持人 As were many other people. What I think most people want is the sort of like single interface to their own personal or their company's AGI that can kind of help them with whatever they need. And then the ability with an API to build anything they want on top of it. And that is the platform that we should offer to the world. We're going to sell great AI at every at every point on the cost curve cost performance curve, we will be the best. 很多其他人也是。我觉得大多数人想要的，是一种单一界面，通向他们自己的、或他们公司的 AGI，能在他们需要的任何事上帮他们。然后是用 API 在它上面建造任何他们想要的东西的能力。而这就是我们应该提供给世界的平台。我们会在成本曲线、成本性能曲线上的每一个点出售很棒的 AI，我们会是最好的。

You know, you want a really high-end AI to discover science,that's great. You want really like inexpensive AI to do like, you know, a massive amount of volume of work that maybe doesn't require genius level intelligence. We got you covered there, too. And you know, thinking about this is a sort of people talk about different ways in the utility and new commodity, whatever you want to call it. 你想要一个非常高端的 AI 去发现科学，那很好。你想要非常便宜的 AI 去做海量工作，也许并不需要天才级的智力。那里我们也覆盖了。人们用不同方式谈论这个，效用、新商品，随便你怎么叫。人们想用很多 AI，想要低成本，想要它快、好用、有他们的上下文、顺滑。

Like people want to use a lot of AI and they want it at a low cost and they want it to be fast and to work well and have their context and be smooth. We we got you. And then there's like a single product which is I need to ask AI something. 我们能给你。然后还有一个单一产品：我需要问 AI 某件事。

Eventually, maybe it's the AI should proactively offer me things, but you will have this interface, which started as a chatbot and now also has coding agents and I think at some point will feel like a more persistent agent to this AI that is running on whatever you need it to run on. But that's it. I don't think we should go build every product category. I don't think we should like go try to compete with all our customers. 最终，也许是 AI 应该主动给我提供东西，但你会有这个界面，它开始是一个聊天机器人，现在也有了编程 agents，我觉得到某个时点会感觉更像一个持久的 agent，连着这个 AI，运行在你需要它运行的任何东西上。但就是这些。我不觉得我们应该去建每一个产品品类。我不觉得我们应该去试着和我们所有客户竞争。我不觉得我们应该试图吞掉整个经济。

I don't think we should try to like subsume the entire economy. I think we should offer this platform and try to have 100 million new businesses and 8 billion people use it in all kinds of new ways. So, one kind of direct interface to the product, one API for people to use it however they want. Those eventually come more and more together, too. And then it's all about what people do with it, build on top of it, whatever else. 我觉得我们应该提供这个平台，试着让一亿家新企业和 80 亿人用各种各样的新方式使用它。所以，一种直接通向产品的界面，一个让人们按自己想要的方式使用它的 API。这两者最终也会越来越合在一起。然后一切都关乎人们用它做什么、在它上面建造什么，以及其他。

嘉宾 What mistakes did you make to have to learn that? I feel like um you've had to kill some good ideas to and sacrifice and going after the great with your full like intensity and focus. 你们犯过什么错，才学到这一点？我觉得你必须杀掉一些好主意，去牺牲，才能用全部的强度和焦点去追伟大的那些。

主持人 Yeah, I I I think killing the good ideas, like sacrificing the good ideas to go after the great ideas is is kind of the hardest lesson for any entrepreneur or business to learn. It sucks to kill good ideas. And no matter how much you think you're going to do it, you you people everyone like kind of maybe just by the nature of who chooses to be an entrepreneur seems to do terrible at this. I'm terrible at this. I know I'm bad at this. But last year for example, we killed Sora. 对，我觉得杀掉好主意，牺牲好主意去追伟大的主意，大概是任何创业者或企业要学的最难的一课。杀掉好主意很糟糕。无论你觉得自己会做多少次，人们，每个选择成为创业者的人，好像天生就在这件事上做得极差。我在这件事上极差。我知道我很差。但比如去年，我们杀掉了 Sora。

Which was you know, good product and fun and cool, but used a lot of compute and not as important as Codex where we put the compute. Um we killed our web browser called Atlas, uh which again, I think it was a great product. I think it was the best web browser, but not as important for us to focus on it. Somewhere else we could put that talent. Um in a world of limited compute, limited people, limited resources,we thought really hard and we said, you know what? 那是一个好产品，好玩，也很酷，但用了很多算力，没有 Codex 重要，于是我们把算力放在了 Codex 上。我们杀掉了叫 Atlas 的浏览器，同样，我觉得它是一个很棒的产品。我觉得它是最好的网页浏览器，但对我们来说聚焦它没有那么重要。

The general intelligence for knowledge work and eventually for science, most important thing we can do. Anything that goes into making that upstream of generating that intelligence, building our own chip, building our own data centers, um you know, writing good infrastructure software, certainly training models, obviously. That's all really important. 那些人才可以放到别处。在一个算力有限、人有限、资源有限的世界里，我们想得很认真，然后说：你知道吗，面向知识工作、最终面向科学的通用智能，是我们能做的最重要的事。任何进入生成这种智能上游的事：做自己的芯片，建自己的数据中心，写好的基础设施软件，当然还有训练模型，显然。

But then let's just offer this AI as as a service and get people to use it for intellectual pursuit, for work, for scientific discovery, to be more productive in their personal life. And let's have the kind of flexible general platform and not do a lot of other things. 这些都非常重要。但然后我们就只把这个 AI 作为服务提供出去，让人们把它用于智识追求、用于工作、用于科学发现、用于在个人生活里更有生产力。让我们拥有这种灵活的通用平台，而不去做很多其他事情。

嘉宾 Anybody come engage in complicated work and you're going to be the, you know, top of the sort top of the list of anybody alive right now, needs somebody to help organize their thoughts. All right? It's extremely beneficial. You see this in every single biography. You see this in histories. Like you need somebody to talk to. There's there's actually a funny story of how extreme this can be. Uh Charlie Munger has a saying called the orangutan theory. You've ever heard of this? 任何要做复杂工作的人，而你大概会是现在活着的人里最靠前的那一串名单上的人，都需要有人帮他整理思路。好吗？这极其有益。你在每一本传记里都能看到这一点。你在历史里也能看到。你需要有人可以说话。其实有一个有趣的故事，说明这件事可以极端到什么程度。Charlie Munger 有一个说法叫猩猩理论。你听过吗？

主持人 No. 没有。

嘉宾 Where he said uh relatively smart human could go in uh sit down with the orangutan tell him all his problems tell him everything that's on his mind and then you know the orangutan obviously knows nothing about nothing else the human leaves and the human is better off just the idea of just being forced to put your thoughts into you know into into some kind of structure. Now obviously with a very intelligent partner. Munger played this role for Buffett. 他说，一个相对聪明的人可以走进去，坐在猩猩对面，把自己所有的问题、脑子里所有的事都告诉它，然后猩猩显然对其他什么都不知道，这个人离开时已经更好了，只是因为被迫把自己的想法放进某种结构里。当然，如果是一个非常聪明的搭档就更是如此。 Munger 对 Buffett 扮演的就是这个角色。

Buffett is one of the most intelligent people ever lived greatest investor of all time still needed to organize his stuff to somebody else. You are going through I can't think you're you're you have almost like a singular lived experience if you are somebody as young as you are. So I'm curious like who plays this role in your life? Like who do you go to that can even yeah remotely empathize with what the hell you're dealing with on a day-to-day basis? Buffett 是有史以来最聪明的人之一，有史以来最伟大的投资人，仍然需要把自己的东西整理给另一个人听。你正在经历的，我想不到… …你几乎有一种独一无二的生活经验，尤其你还这么年轻。所以我很好奇，谁在你生活里扮演这个角色？你会去找谁，哪怕能稍微共情你每天到底在对付什么？

主持人 Kind of three categories here. One a lot of the researchers that have been here forever we've kind of like all been through it together and we've developed this set of like shared language intuition standards whatever you want to call it and that I have not been able to replicate with anybody outside of the company. Um when it comes to like the shape of what's happening and what might happen next and where the technology is likely to go. 大概有三类。一类是很多一直在这里的研究者，我们有点一起经历过这一切，发展出了一套共享的语言、直觉、标准，随便你怎么叫，这是我没能和公司以外的任何人复制出来的。当问题涉及正在发生的事情的形状、接下来可能发生什么、技术可能走向哪里。

In in terms of questions of just like you know business and the world for a long time in my career Paul Graham and Peter Thiel have been two of the people that I have learned the most from about lots of different faces of my career and are still the two people that I go to if I really have like a very non-obvious problem that I'm stuck on and they're I have not found anyone else after a lot of looking that has the same kind of ability to to just to like think in a super non-linear way. 至于只是关于商业和世界的问题，在我职业生涯很长一段时间里，Paul Graham 和 Peter Thiel 是。我从他们那里学到最多的两个人，关于我职业生涯的很多不同阶段，而且如果我真的卡在一个非常非显而易见的问题上，我仍然会去找这两个人。我找了很久，还没有找到其他任何人有同样那种以超级非线性方式思考的能力。

Like you know if what LLMs do are predicting what word comes next those are two of the people that I can predict the least what word is going to come next. And that is a super valuable skill. You go with like a oh man I feel really stuck and I've kind of thought through all these options and someone that can tell you like, eh "Eh, I think none of those options are good. 就像，如果 LLM 做的是预测下一个词是什么，这两个人是我最无法预测下一个词会是什么的人。而这是一种超级有价值的技能。你带着一种「天哪我真的卡住了，这些选项我都想过了」进去，有人能告诉你：「嗯，我觉得这些选项都不好。

Here's this thing that now seems totally obvious and correct that you didn't think of." Just a completely different view that you haven't heard anywhere else. 这里有这个东西，现在看起来完全显而易见而且正确，而你没想到。 」就是一种你在别处完全没听过的不同视角。

嘉宾 Is this like more of like a prompt for your own thinking as a as opposed to like explicit advice do X, for example? 这更像是对你自己思考的一种提示，。而不是那种明确的建议，比如去做 X？

主持人 Yeah, it's often like here is a specific thing. 对，常常是：这里有一件具体的事。

嘉宾 Really? 真的？

主持人 Yeah. 对。

嘉宾 So, what would be an example that you could share from like Peter? Peter's very fascinating to me. 那你能分享一个来自 Peter 的例子吗？Peter 让我觉得非常迷人。

主持人 He is very fascinating. 他非常迷人。

嘉宾 And I it's it's actually who I thought of. The reason I thought of this question just now is cuz you're like we had to kill these good ideas for the great. We're cutting Atlas. We're compute constrained. We have to focus, focus. 我其实就是想到了他。我刚才想到这个问题，是因为你说我们必须为了伟大的主意杀掉这些好主意。我们在砍 Atlas。我们算力受限。

It's like that's something that is very obvious when you listen to him talk about the importance of focus and like if you have something that's working, making it work better and going down this line, like taking an hour away from that to like explore something else is too expensive. You should just go deeper on what's already working. Like there's a lot of value at the extremes. 我们必须聚焦、聚焦。这就像听他讲聚焦的重要性时非常显而易见的东西。如果你有正在奏效的东西，就让它更好地奏效，沿着这条线走下去。从那上面拿开一个小时去探索别的东西太昂贵了。你应该在已经奏效的事情上走得更深。极端处有很多价值。

主持人 After we launched ChatGPT, it was this weird thing cuz people didn't really know what to use it for. And it was growing super fast, but it felt like very unstable or kind of almost like a low-value growth. Like people were using it to just cuz they were like interested in talking to it and what they could do. And so, there were a lot of people in the company who were like, "Uh, this is you know, we got to figure out something else. 我们推出 ChatGPT 之后，有一件很怪的事，因为人们其实不太知道拿它来做什么。它增长得超级快，但感觉非常不稳定，或者说几乎像低价值增长。人们用它，只是因为他们对跟它说话、对它能做什么感兴趣。所以公司里很多人说：呃，这个… …我们必须想点别的。这不是可持续的价值。

This is not sustainable value." And we were talking to him about this like list of five or six other things that we could focus on. Instead, this is like maybe two months after ChatGPT launched, something like that. And he was like, "It's an obvious mistake to do anything but this. Besides the fact that it's growing, which is rare and great." And it was not growing this fast then and it did start after. He's like, "The power of this is the power of the Google text box. 我们当时在跟他聊另外五六件我们可以聚焦的事。那大概是 ChatGPT 推出后两个月左右。然后他说：「除了这件事以外再做任何事，都是明显的错误。更何况它还在增长，而这既罕见又很棒。 」当时它还没有增长得这么快，那是之后才开始的。他说：「这件事的力量就是 Google 那个文本框的力量。

It's like a text box you can type anything into and it does the right thing. And the fact that it doesn't match the current Silicon Valley wisdom of, you know, you got to have like feeds and you have to have like a network effect and you have to have cuz we had none of these things and that's why everyone was worried. You know, you have to have like a you know, way that people are going to build up more con- this before we had memory. People are going to build more contacts. 就是一个你可以打进任何东西的文本框，然后它做对的事。而它不符合当下硅谷的智慧：你必须有信息流，必须有网络效应，必须有… … 」因为我们这些都没有，所以每个人都在担心。你必须有一种让人们积累更多上下文的方式——那是在我们有记忆之前——人们会建立更多上下文，人们会被锁定，人们会拥有所有这些东西。

People are going to get locked in or people are going to have all of these like all that stuff. Like people have just been chasing the Google business model for 20 years and this is the first thing that's come up and, you know, clearly the empty text box worked for Google so why don't you just double down on that? It's growing like it's very flexible and, you know, it has all of the signs other than it doesn't fit the current Silicon Valley wisdom. 人们追了 Google 的商业模式二十年，而这是出现的第一件这样的东西。空文本框对 Google 奏效了，你为什么不就加倍押在那上面？它在增长，它非常灵活，它有所有那些迹象，除了它不符合当下硅谷的智慧。

And I was like, "Okay." And so we went super hard on ChatGPT uh and it was great. It's like a simple genius to what he just said. Sometimes there's like more complexity to this but that was an example of very important simple genius. 我就说：好。于是我们在 ChatGPT 上押得非常重，结果很棒。他刚才说的那种东西，有一种简单的天才。有时这会有更多复杂性，但那是一个非常重要的、简单天才的例子。

嘉宾 What about some advice that Paul Graham or some guidance or a direction he kind of pushed you in? 那 Paul Graham 的一些建议，或者他推你去的某种指引或方向呢？

主持人 When you just said that, the thing this is like a meme for many YC founders uh where you would go see him for office hours and he would say, "You know what you should do." And he would like shake his hand his finger like this. "You know what you should do. You know what you should do." And sometimes the thing that came after that was great. Sometimes the thing that came after that was terrible. 你刚才那么说的时候，我想起的是对很多 YC 创始人来说像一个梗的东西：你会去他的 office。 hours，然后他会说：「你知道你该做什么。 」他会像这样晃着手指。 「你知道你该做什么。你知道你该做什么。 」有时那句话后面出来的东西很棒。

But the important thing was there was a kind of there is a creativity and open landscape and just uh you know, let's try a lot of things. We talked about the spirit of iterative deployment. And we talked about you know, what what how like in the same way startups he really I think pushed the startup ecosystem into this world of you got to like get ship a a a V1 you're embarrassed of early and it doesn't matter if it's, you know, it could be much better. 有时那句话后面出来的东西很糟。但重要的是，那里有一种创造力、开放的地貌，以及：让我们试很多东西。我们聊过迭代部署的精神。我们也聊过，就像创业公司一样，他真的把创业生态系统推进到了这个世界：你必须尽早发布一个让你自己都感到尴尬的 V1，它现在好不好并不重要，它可以好得多。

You'll you'll you'll get it much much better because of the feedback to customers. I don't even think I asked him before we launched ChatGPT like, "Hey, do you think we should launch this thing?" But I knew what he would say. I knew it was still early. I knew it was still embarrassing, and I knew the right thing was to like get it out and get it in front of people. 你会因为它来自客户的反馈而把它做得好得多。我甚至觉得，在我们推出ChatGPT 之前，我都没有问他：嘿，你觉得我们该不该推出这个东西？但我知道他会说什么。我知道它还早。我知道它仍然让人尴尬。我知道正确的事就是把它拿出去，放到人们面前。

嘉宾 So, wait. Wait. Your mental model of Paul Graham is so complete, you don't even have to call him up. 所以等一下。你对 Paul Graham 的心智模型已经完整到，你甚至不必给他打电话。

主持人 one case. That's That's the one where you would say like there's certainty. 一种情况。那就是你会说有确定性的那种。

嘉宾 Let me tell you something funny. Right before he died, a few months before he died, I went to Charlie Munger's house and had uh dinner with him, and I was like, "How often do you talk to Buffett?" He goes, "Never." I go, "What?" 我跟你讲一件有意思的事。就在他去世前，去世前几个月，我去了 Charlie Munger 家里和他吃晚饭。我问：你多久跟 Buffett 聊一次？他说：从不。我说：什么？

主持人 He goes, "We talked every day for hours and hours. Buffett can just pretend to pick up the phone call to call me, and he already knows what I'm going to say." That's obviously comes after 65 years of working closely together, but I thought it was hilarious. 他说：我们曾经每天聊好几个小时。Buffett 可以只是假装拿起电话要打给我，而他已经知道我会说什么。那当然是 65 年紧密合作之后才会有的，但我觉得这太好笑了。

嘉宾 That is hilarious. That is really a funny story. 那是很好笑。那真的是一个很好笑的故事。

主持人 No, there's many times that I couldn't predict what he's going to say, which is That's why I think it's valuable. But in terms of the like launch when you're embarrassed of a product, I know what he's going to say there. Like that one uh That That That has been like I won't say the most valuable piece of YC of tactical YC advice, but it's been up there. 不，有很多次我无法预测他会说什么，而这正是我觉得它有价值的原因。但就「在你对产品感到尴尬的时候发布」这一点，我知道他会说什么。那一条，我不会说它是最有价值的一条YC 战术建议，但它排在很前面。

I'm astonished looking back at all of my data points of YC founders over the years how much the ability the like moving fast and being iterative correlates with success. 回头看这些年我所有关于 YC 创始人的数据点，我震惊于行动快、能迭代，和成功有多相关。

嘉宾 Okay, you've mentioned YC way many too many times in this conversation. I I have to explore this because we talked before. It's like, "Listen, I'm not a journalist. I'm an enthusiast. I don't have a list of questions." And I'm like, "I have a world-class founder across from me. I want to know what the hell is in this person's mind, and I want to like extract information out selfishly for me." So, like why like I just I'm shocked at how much you reference it in conversations. 好，你在这次谈话里提到 YC 的次数太多了。我必须挖一下这个，因为我们之前聊过。就像：听着，我不是记者，我是爱好者。我没有一份问题清单。我面前坐着一位世界级创始人，我想知道这个人脑子里到底有什么，我想自私地为我自己把信息抽出来。所以为什么… …我只是震惊于你在谈话里引用它的次数有多少。

Like how impactful going through YC and then running Y through YC, being, you know, affiliated with them has is is it clearly on your life. Can you like you expound on this? 经历 YC、然后经营 YC、和他们有关联，对你的生活显然有多大影响。你能展开讲讲吗？

主持人 There is some band that wasn't that successful. They didn't sell that many albums, I mean, but they like influenced all of the musicians that came out of college. 有一支乐队并没有那么成功。他们专辑卖得并不多，但我的意思是，他们影响了后来从大学里出来的所有音乐人。

嘉宾 The Band. Literally that. The Band。字面上就是那个。

主持人 Rick Rubin told this story. I think it's Is it might be The Velvet Underground. But, but you know the idea I'm getting at, whether it's called The Band or whatever. Yeah. It's not fair to talk about YC in this way cuz YC, measured by like traditional metrics and market cap created whatever, is one of the hand would be one of the handful of most valuable tech companies. Rick Rubin 讲过这个故事。我想也许是 The Velvet Underground。但你知道我在说的那个意思，不管它叫 The Band 还是什么。对。这样谈 YC 并不公平，因为用传统指标和市场价值来衡量，YC 会是少数几家最有价值的科技公司之一。

But, the degree to which YC totally influenced everything that has happened in the last 20 years of the tech industry and startups, entrepreneurship, whatever, I think it's is only like sort of understood. OpenAI is an example of that. Not just from like how we have shipped our products in the world, but like the philosophy of how we run our research lab. 但是，YC 在过去 20 年彻底影响了科技行业、创业公司、企业家精神里发生的一切，这种程度我觉得只是被部分理解了。 OpenAI 就是一个例子。不只是我们如何把产品发到世界上，也包括我们经营研究实验室的哲学。

I think if you go talk to like many of the other people running like this generation of large tech companies, they would tell you so much stories, even if they didn't go through YC. 我觉得如果你去问很多经营这一代大型科技公司的其他人，他们会告诉你非常多这样的故事，即便他们没有经历过 YC。

嘉宾 Well, what's happening there? Is it an operating system that YC is giving you because you hear, you know, do these five things or whatever, or is it more like a philosophy of building companies? This is the confusing part for me as an outsider. 那那里发生的是什么？是 YC 在给你一个操作系统，因为你听到要做这五件事之类的，还是更像一种建造公司的哲学？作为局外人，这是让我困惑的部分。

主持人 I think it's two major things. I mean, there there is there is some of the operating system of what to do. But, I think it was the philosophy of how to run companies. The idea of iterative deployment and technical people in charge and sort of being willing to bet on young people with a lot of energy and ambition, but maybe less experience throughout all levels of a company. And then it was also the change the related change to the whole ecosystem that happened. 我觉得主要是两件大事。我的意思是，确实有一些关于该做什么的操作系统。但我觉得它是如何经营公司的哲学。迭代部署的想法，技术出身的人掌权，以及愿意在各个层级押注那些能量和野心很大、但经验也许更少的年轻人。然后它也是发生在整个生态系统上的、与此相关的改变。

In the pre-YC tech ecosystem, so if you, you know, ran the clock back to 2004 and then projected technology forward to 2016, um but not anything else about the shape of startup ecosystem, what it meant be an entrepreneur, how capital flowed, all of the you know, who got to run companies, all of those things. I do not think OpenAI would have been impossible. 在 YC 之前的科技生态系统里，所以如果你把时钟拨回 2004 年，然后只把技术投影到 2016 年，但不投影创业生态系统的形状、成为创业者意味着什么、资本如何流动、谁能经营公司，所有这些事情。我不觉得 OpenAI 会是不可能的。

主持人 I think the changes that YC induced in the whole ecosystem, you know, more leverage going to founders, young technical founders having the ability to raise lots of capital, um the ability to sort of like work on ambitious things without a very proven resume. I don't think OpenAI would have been possible. So, this is kind of like a big change. 我觉得 YC 在整个生态系统里引发的那些变化，更多杠杆给到创始人，年轻的技术创始人有能力融到大量资本，能够在没有非常被验证过的履历的情况下去做雄心勃勃的事。我不觉得 OpenAI 会成为可能。所以这是一种很大的变化。

嘉宾 Is this all tied to the fact that you think there was a benefit in you going from founder to investor for a long period of time back to founder? 这是不是都连着你觉得，从创始人变成投资人很长一段时间再变回创始人，对你有好处？

主持人 There are all those benefits, too. And I wouldn't say I really went from founder to investor to founder cuz like the first time I was founder didn't really work out that well. So, like 那些好处也有。而且我不会说我真的是从创始人变成投资人再变成创始人，因为第一次当创始人并没有那么成功。所以

嘉宾 You still started a company. You you learned some lessons from failure, but I think you learn way more from success. 你还是创办了一家公司。你从失败里学到了一些教训，但我觉得你从成功里学到的要多得多。

主持人 No, you got to hold on. You We're not moving on from that. You got to say more about that. 不，你得等一下。我们不从这里跳走。你得再多说一点。

嘉宾 There's some I can't believe I think it's Anna Karenina. Some great Russian novel. I'm very embarrassed not to know this. Starts with like all unhappy families are unhappy in their own way. All happy families are alike. 有一句，我不敢相信，我想是《Anna Karenina》。某部伟大的俄国小说。我很尴尬自己不确定。开头大概是：所有不幸的家庭都各有各的不幸。所有幸福的家庭都相似。

主持人 Yeah. 对。

嘉宾 That explains why I jumped into YC. Um but I think this is really true. Like when I look at the lessons of where I have failed at something, I learned something generic about grit and determination and something not to do. But there's most things don't work. So, there's like a lot of reasons why things don't work and there's I think it's like harder to put together the correct causation. 这就解释了我为什么跳进了 YC。但我觉得这真的很对。当我看自己在哪些地方失败过的教训，我学到一些关于韧性和决心的很泛的东西，以及一些不该做的事。但大多数事情都不奏效。所以事情不奏效有很多原因，我觉得更难拼出正确的因果。

And when I've had something really work, when I understand like what parts of Y Combinator really worked or what parts of OpenAI really worked, trying to apply those lessons going forward has been much more helpful to me than trying to apply the anti-lessons of what didn't work. And so, you know, you you should of course learn as much as you can from every data point. So, learn from the failures, learn from the successes. 而当我有某件事真正奏效，当我理解 Y Combinator 真正奏效的是哪些部分，或者OpenAI 真正奏效的是哪些部分，试着把那些教训应用到往后，对我的帮助要比应用那些「什么不奏效」的反教训大得多。所以，你当然应该从每一个数据点学习尽可能多的东西。

But in my own experience, uh I have when I have tried to apply those lessons, the lessons I learned from success were very good, and I should have applied those more. And the lessons I learned from failure were either fairly generic, and I kind of already knew them, or got in the way of something else. And I think this is like generally true for a lot of people. 从失败中学，从成功中学。但以我自己的经验，当我试着应用那些教训时，我从成功中学到的教训非常好，我本该更多地应用它们。我从失败中学到的教训，要么相当泛，我其实已经知道，要么会挡到别的东西。我觉得这对很多人来说普遍成立。

主持人 Yeah, but isn't it like we already kind of know what we should do or what we should avoid? But it's like the reminder, the constant reminder. So,like the the best description of my other podcast Founders I've ever heard is like it's church for entrepreneurs. If you really think about it, I used to drop it on Sundays, and I should go back to doing that. But it's like really I'm just telling the same It's the same personality type as if you're throughout history. 对，但难道不是我们已经大概知道该做什么、该避免什么？只是需要提醒，不断的提醒。所以对我另一个播客 Founders 最好的描述，我听过的，就是：它是创业者的教堂。你要是真想一想，我以前在星期天发布，我应该回到那种做法。但就像我真的只是在讲同一件事。这是同一种性格类型，贯穿历史。

嘉宾 Yeah. 对。

主持人 It's just like now this person happens to be building ships, and this person built technology, but like and they live in different 只是现在这个人碰巧在造船，那个人在做技术，但他们生活在不同的。

嘉宾 same It's the same personality. 一样。就是同一种性格。

主持人 That's for sure. I I'm kind of obsessed with this idea of things that last for a long period of time. And like uh you know, companies The best companies can last a long time, but not as long as cities. And uh cities don't last Cities and countries don't last as long as like religions. You know, like so out of all the man-made things, what has lasted longer? I would say I can't think of anything other than religion might be an asset. So, then I started studying. 那是肯定的。我对那种能持续很长时间的事物有点着迷。最好的公司可以持续很长时间，但没有城市那么长。而城市不会持续… …城市和国家持续的时间没有宗教那么长。所以在所有人造的东西里，什么持续得更久？我想不出任何东西，也许宗教可能是一种资产。

I grew up My mom was fundamentalist Christian. So, I was forced to go to church my entire life. And I just started analyzing like what do all the main religions in the world have in common? It's like oh, we have a shared base of knowledge. Usually some kind of book, right? We meet with like-minded fellow believers at regular intervals. And it's not like I go to church on Sunday. It's like okay, we talked about Jesus last week, but let's talk about this other guy. 于是我开始研究。我长大的时候，我妈妈是基要派基督徒。所以我这辈子被迫去教堂。我开始分析：世界上所有主要宗教有什么共同点？哦，我们有一份共享的知识基础。通常是某种书，对吧？我们定期和志同道合的信徒见面。而且不是我星期天去教堂，就像：好，上周我们聊了耶稣，这周我们聊另一个人。

It's like no, I go back to the same books and same stories over and over again. So, I read your blog, and you even said this uh something about like when YC end ended. It's like you're repeating the same thing. You're telling it to them all the time, and then they leave the church, you know, to for this analogy, and then they stop doing the same thing. It's like 不是的，我一遍又一遍回到同一批书和同一批故事。所以我读你的博客，你甚至说过这个，关于 YC 结束的时候。就像你在重复同一件事，你一直在告诉他们，然后他们离开教堂，就这个比喻来说，然后他们就不再做同一件事。就像

嘉宾 100%. 百分之百。

主持人 even the lessons. It's like the constant reminder that this This important. 即便是那些教训。就像不断提醒：这件事重要。

嘉宾 I extremely strongly agree with that. 我极其强烈地同意这一点。

But I think it is better to be reminded of the thing like talk to your users more. You know, ship products earlier, get more feedback, um hold a higher bar for who you recruit and who you hire and more quickly suddenly. But it's the positives that I think are good. 但我觉得更好的是被提醒那些正面的事：更多地和用户聊。更早地发布产品，拿到更多反馈，对你招募和雇佣谁持有更高标准，并且更快地突然……但我觉得好的是那些正面的东西。

主持人 You have one of the greatest tweets. I have I say to my phone, you're like, you know, skip the conferences, the dinners, everything else. Just like essentially make the product or sell and sell the product. If you're not making it, you're not selling it, like that's all you actually have to do. And I think it's like there again it goes back to like that simple genius. 你有一条最伟大的推文。我对着手机说，你就像：跳过那些会议、那些晚餐、其他一切。本质上就是做产品，或者卖、再卖产品。如果你不是在做它，也不是在卖它，那其实你只需要做那些。我觉得这又回到那种简单的天才。

So then this is the other part that I find most fascinating cuz somebody asked me yesterday, they're like, "What's your Usually there's some kind of historical equivalent for every founder I meet that I can like, 'Oh, that guy's kind of like Verner Cole. 然后这是我觉得最迷人的另一部分，因为昨天有人问我：你通常对每个见到的创始人都会有某种历史对应，比如那个人有点像 Verner Cole，那个人有点像 Rockefeller、Ludwig，或这些人里的任何一个。

That guy's kind of like Rockefeller, Ludwig, or any of these people.'" And I was like, "What's your historical equivalent for Sam?" I was like, "There isn't I can't think of one cuz like I don't know him enough well I don't understand how he thinks yet." What do you think now? Well, we This is the first of hopefully eight conversations so we'll I'll tell you in conversation summary. But this is very rare. I just talked to Doug Leone and he talked about one dude that he hired. 然后他们问：Sam 的历史对应是谁？我说：没有。我想不出来，因为我还不够了解他，我还不理解他怎么想。你现在怎么想？我们这是希望中的八次对话的第一次，所以我会在对话总结里告诉你。但这非常罕见。我刚和 Doug Leone 聊过，他谈到他雇过的一个人。

It's the founder of Nubank and he was a like an associate in VC and then leaves and founds one of the most successful companies. I'm like, "I've never heard of that. Doug, have you?" And he dedicated his life to this. He goes, "No, that's the only one." So again, it's very rare. Mostly people go from founder, sell their business unfortunately, and then investor as opposed to run the business till you die, which is my preferred method of things. 那是 Nubank 的创始人，他当时像是 VC 里的一个 associate，然后离开，创办了最成功的公司之一。我说：我从没听说过这种事。 Doug，你呢？他把一生都献给了这件事。他说：没有，就这一个。所以这再次非常罕见。大多数人是从创始人，不幸地卖掉公司，然后变成投资人，而不是把公司经营到死，而那才是我更偏好的方式。

嘉宾 What I'm curious about this is like when you just said I learned more from successes, right? 我好奇的是，你刚才说你从成功中学到的更多，对吧？

主持人 Well, it's the successes cuz you were exposed to what? 10,000 different companies in that decade or decade and a half that you were doing this. And you saw obviously maybe the half a dozen or the dozen or were the best in the world. So like are you taking their successes as well as like instructive to No, no, okay. 是那些成功，因为你在那十年或十五年里接触了什么，一万家不同的公司。你显然看到了也许那六家或十几家世界上最好的。所以你是在把他们的成功也当成有教益的吗？不，不，好。

嘉宾 To- to- totally. Uh the And I think people do I mean, you're incredible student but there's a lot of pretty good students of entrepreneurialism and entrepreneurism and people I think often try to go look for those lessons of the things that that really worked. And as you said, it's kind of the same thing over and over again, like done in different industries. But you have to be reminded of it a lot and it's unglamorous. 完完全全是。而且我觉得人们确实……我的意思是，你是不可思议的学生，但也有很多相当好的企业家精神和创业的学生，我觉得人们常常试图去寻找那些真正奏效的事情的教训。正如你所说，它基本上一遍又一遍是同一件事，只是在不同行业里做。但你必须被提醒很多次，而且它并不光鲜。

主持人 I had no understanding going into this conversation. I think I was slightly better understanding going into this. I told you before we started this is just for my own edification. But like even the people that influenced you or it's just like Peter Thiel saying, "No,dummy." He's obviously going to say he's like, "No, dummy, this is working. 进入这次谈话时我完全不理解。我想进入这次谈话时我理解得稍好一点。我开录前就告诉过你，这只是为了我自己的启发。但即便是影响你的那些人，也只是像 Peter Thiel 说：不，笨蛋。他显然会说：不，笨蛋，这正在奏效。

Why are you doing anything else but the thing that is working?" So there's got to be examples where you're like, "Hey, I've given this advice to other founders a million times." And then you catch yourself, "Oh I'm not even applying my own advice at this point in time." 除了正在奏效的这件事，你为什么还要做别的？所以一定会有这样的例子：嘿，我把这条建议给其他创始人说过一百万次。然后你抓住自己：哦，我这个时点甚至没有在应用自己的建议。

嘉宾 Totally. Yeah, I'll give many examples of that. I I I I think it's also instructive to like what what was the new thing? What didn't you have the advice for? 完全是。对，我会给很多那样的例子。我觉得同样有教益的是：新的事情是什么？你没有建议可给的是什么？

主持人 Mhm. 嗯。

嘉宾 And the thing that was really different about OpenAI than anything that I had pattern matching with is it was four and a half years from when we started the company till when we launched our first product. 而真正不同的那件事。关于 OpenAI，和我有过模式匹配的任何事情相比，是从我们创办公司到推出第一个产品，过了四年半。

主持人 The opposite of YC advice, right? 正好和 YC 建议相反，对吧？

嘉宾 Yes. 是。

主持人 Okay. 好。

嘉宾 Yes. And although there were all these ways which managing a research team was similar to selecting and advising founders learning what it to whatever degree we learned it cuz I don't think we did it perfectly. Like how you manage through this part of the world where you don't have the external signal from customers and you're just trying to like you know, do what would normally be the catastrophic startup advice of not uh not shipping a product for four and a half years. 是。尽管管理一个研究团队和挑选、建议创始人有这么多相似之处，我们学到了它，学到了什么程度我不敢说，因为我不觉得我们做得完美。比如你如何在世界的这个部分里管理下去：你没有来自客户的外部信号，你只是在试图做那种通常会是灾难性创业建议的事，四年半不发布产品。

That was very difficult and we tried all of these things about how we like had a how we replaced the signal of do customers actually like the product for is our research actually working. 那非常困难，我们试了所有这些办法，关于我们如何有一个我们如何用「我们的研究是否真的在奏效」来替换「客户是否真的喜欢这个产品」这个信号。

One of the things that worked actually is during the um Dota 2 days when we were trying to use RL to beat this video beat people at a video game, we put up like a leaderboard and people could just see how different ideas were performing and what was, you know, if that was like objective and real and people wanted to like go off that. But we had to try all of these things to uh basically like simulate end users. 真正奏效的一件事，其实是在 Dota 2 那些日子，我们试图用 RL 在一个电子游戏里打败人的时候，我们挂上了一块排行榜，人们可以直接看到不同想法表现如何，那是否客观、真实，人们也想据此行动。但我们必须试所有这些办法，来。

And that was a totally interesting new problem I had no pattern matching for. 基本上模拟终端用户。那是一个我完全没有模式匹配的、非常有意思的新问题。

主持人 How did you work your way through that? What were you thinking? Like how did you do this? 你是怎么走过来的？你当时在想什么？你是怎么做的？

嘉宾 We asked a bunch of people who had been at great research labs of the past. And if it had been, you know, OpenAI started at sort of a time when everybody in Silicon Valley as their vanity project, including me, uh wanted to start a research lab. And there were all these books about the heyday of Bell Labs or Xerox PARC that were very popular. Everybody was talking about this. It was a huge amount of discussion. 我们问了一堆曾在过去那些伟大研究实验室待过的人。而且，OpenAI 创办的时候，某种意义上正是硅谷每个人都把创办一个研究实验室当成自己的虚荣项目的时候，包括我。当时有很多关于Bell Labs 或 Xerox PARC 鼎盛时期的书非常流行。每个人都在谈这个。有大量讨论。

In fact, I even see one of the books over there about uh about Bell Labs. But there was not a ton of people that had like in living memory how to actually do it. So we talked a lot to Alan Kay. We talked to a handful of other people. And we got some advice from them about, you know, what made a really good research research lab and some of it was really good. Some of it didn't translate as well to the current moment. 事实上我甚至在那边看到其中一本关于 Bell Labs 的书。但没有多少人在仍可记忆的范围内真正知道该怎么做。所以我们跟 Alan Kay 聊了很多。我们跟另外几个人聊。我们从他们那里得到一些建议，关于是什么造就一个真正好的研究实验室，其中一些真的很好。有一些不太能翻译到当下这个时刻。

主持人 Well, you also didn't have this giant monopolistic profit profit printing machine like Bell Labs was spun out independently. Uh Polaroid did a lot more research when they had uh essentially like a monopoly on its photography. I just read the biography of the founder of Honda, right? Ho- The guy created the most successful uh motor vehicle of all time. The Honda Cub has sold uninterrupted for like 60 years, millions of yeah, vehicles. 而且你们也没有那种巨大的垄断式利润。 【笑声】印钞机，像 Bell Labs 是独立分拆出来的。 Polaroid 在他们基本上拥有垄断的时候做了多得多的研究，在摄影上。我刚读了 Honda 创始人的传记，对吧？那个人创造了有史以来最成功的机动车。 Honda Cub 连续卖了大概 60 年，数百万辆。

And his whole thing and he he arrived at the same conclusion Bell Labs did, that he thought the research and development had to actually be separate. It was a it was spun out of the company and had separate ownership, just like Bell Labs did. 而他整件事，他得出了和 Bell Labs 一样的结论：他认为研发必须真正分开。它是从公司分拆出去的，有单独的所有权，就像 Bell Labs 一样。

嘉宾 We did not have that. 我们没有那个。

主持人 No, you did not have the 不，你们没有

嘉宾 When I think back to those early days, I mostly feel like I was trying and failing to raise money. That's like my dominant memory of the early days of Open AI. So much effort, so frustrating. I wish we had some sort of cash machine like that. 当我回想那些早期日子，我最多的感觉是我在试图融资，并且失败。那就是我对 OpenAI 早期最主导的记忆。那么多努力，那么令人沮丧。我希望我们当时有某种那样的印钞机。

I remember like one of my clearest memories of all of Open AI, so announced coming in 2015, but the first day was right after New Year's in 2016. And 12 of us or 11 of us showed up at Greg Brockman's apartment, you know, like 9:00, 9:30 on a Monday or Tuesday morning, something like that. Let's say it's January 4th. And everybody's there and it'd been this like big effort and everybody walks in with a lot of excitement. It feels like the first day of school, whatever. 我记得我对整个 OpenAI 最清晰的记忆之一： 2015 年宣布即将到来，但第一天是 2016 年新年刚过。我们 12 个人，或者 11 个人，出现在 Greg Brockman 的公寓里，大概早上 9 点、9 点半，星期一或星期二早上之类的。就当它是 1 月 4 日。每个人都在，这是一场很大的努力，每个人走进来都带着很多兴奋。

And then very quickly people like look around the room and they're sort of like, "Well, what do we do now?" 感觉像开学第一天，诸如此类。然后很快人们环顾房间，有点像在说：「那我们现在做什么？ 」

Someone says, "Okay, we should get a whiteboard." Greg, you know, gets someone to go off and find a whiteboard. Whiteboard comes. Um look around again, you know, what are we supposed to do now? And you just feel the energy in the room collapse. And none of us know what to do. Like there's no It was not like building a product startup. It was not like let's build this product. Let's talk to customers. 有人说：「好，我们应该弄一块白板。 」Greg 就让人出去找一块白板。白板来了。然后再环顾四周，我们现在该做什么？然后你就感觉房间里的能量塌下去。我们谁都不知道该做什么。那不像在做一家产品创业公司。不是「让我们做这个产品，让我们去跟客户聊」。

It's like, "Okay, we said we want to make AGI." Maybe we should write some papers. Okay, let's write some papers. Maybe we should think about some ideas. Okay, let's think about some ideas. You know, everybody's got their like moments of I have no idea what I'm doing. That was one of mine. Like I have, you know, we have just launched this thing. None of us had any idea what we're going to do. 而是：「好，我们说我们想做 AGI。 」也许我们应该写一些论文。好，让我们写一些论文。也许我们应该想一些想法。好，让我们想一些想法。每个人都有那种「我完全不知道自己在做什么」的时刻。那是我的其中一个。就像，我们刚刚推出了这个东西。我们谁都不知道接下来要做什么。

So we did what we knew how to do and eventually we figured out a lot of things didn't work. Eventually we figured out a kind of like rhythm for making and then evaluating research bets. 所以我们做了我们知道怎么做的事，最终我们发现很多事情不奏效。最终我们找到了一种做出、然后评估研究赌注的节奏。

And all far from perfect, obviously, uh but we did find a gradient that we could kind of progress along. And we figured out how to get, you know, the resources that very smart people needed and how to make sure that we were like not completely getting lost in the wilderness. And over some number of years mostly chaotic stumbling we eventually made most of the big discoveries. 当然远谈不上完美，但我们确实找到了一条可以沿着往前走的梯度。我们搞清楚了如何拿到非常聪明的人需要的资源，以及如何确保我们不会完全迷失在荒野里。然后在若干年里，多半是混乱的跌跌撞撞，我们最终做出了大多数重大发现。

You know, what started as the unsupervised sentiment neuron paper uh turned into GPT-1 and then eventually GPT whatever. The scaling laws work that gave us the confidence not only by the compute but the understanding about how to scale up our models sort of came together. And through and many other things, too. Um through this process we learned things like that idea of leaderboards that worked. 从无监督情感神经元那篇论文开始，变成了 GPT-1，然后最终变成 GPT 不管第几代。 scaling laws 的工作给了我们信心，不只是靠算力，还有关于如何放大模型的理解，这些慢慢合在一起。而且还有很多其他事情。通过这个过程，我们学到了像排行榜那种奏效的想法。

We also learned the incredible power of external demos uh for like an eminent person that the researchers really wanted to impress. And then we learned a bunch of things that like didn't work like fake deadlines. 我们也学到了外部演示的惊人力量，比如对着一位研究者非常想打动的重要人物做演示。然后我们还学到了一堆不奏效的事，比如假截止日期。

主持人 It must be so disorienting to live through that experience. You're at 12 people in an apartment, don't even have a whiteboard, don't know what to do. Fast forward a decade, you have a billion people using 活过那种经历一定非常让人迷失方向。你们 12 个人在一间公寓里，连白板都没有，不知道该做什么。快进十年，你有十亿人在用

嘉宾 experience. 这段经历。

主持人 Do you keep a journal? 你写日记吗？

嘉宾 When my kid was born, my first kid, I would like, you know, get home at the end of the day and be rocking him to sleep and just like talk to a kid or whatever. So I was just like need to come up with a talk about. So I would like just tell him about my day and what we were struggling with and kind of like what I was worried about and what was happening. 我的孩子出生时，我的第一个孩子，我会在一天结束回家，摇着他睡觉，然后就跟小孩说话之类的。所以我需要找点可说的。于是我就跟他讲我的一天，我们在挣扎什么，我在担心什么，正在发生什么。

It was kind of like fun for me to do and I was like, this is sort of interesting and someday I'll be like interesting for him to have this. So I started writing him like every Sunday I would like write him a letter. I would like talk just to talk and then I would like write it down. I only ever did like eight of them or something. 对我来说这有点好玩，然后我想：这有点意思，有一天对他来说拥有这些也会有意思。于是我开始每个星期天给他写信。我会先说，只是说，然后再写下来。我大概只写了八封之类的。

主持人 How many kids do you have? 你有几个孩子？

嘉宾 Two. 两个。

主持人 Okay. Bezos has this great line about building Amazon. He's like, we're trying to do stuff that we can tell our grandkids about that we're proud of, right? And those things are hard. The fact that you were writing to your son 好。Bezos 有一句关于建造 Amazon 的很棒的话。他说，我们在试图做那些我们可以告诉孙子、并且为之骄傲的事，对吧？那些事很难。你当时在给你儿子写信这个事实

嘉宾 Oh, man. 天哪。

主持人 Keep writing the letters. And if you don't do that, this is real quick. Just because I've read enough books about this. Most time, guess what? Founders don't write autobiographies when they're 40. They write them when they're 70 and they're looking back and they wish they could do it again and so much has been lost to the sands of time. They all repeat that. 继续写信。如果你不那么做，就很快说一句。只是因为我读过足够多关于这个的书。大多数时候，你猜怎么着？创始人不会在 40 岁写自传。他们在 70 岁写，回头看，希望能再来一次，而太多东西已经消失在时间的沙子里。他们都重复那句话。他们说：「我希望我当时写了日记。

They're like, "I wish I journaled." So, even if you don't do it, you have enough resources, what I would do, write have a book written, even if it's for internal purposes only. You ever read The Little Kingdom by Michael Moritz? 」所以即便你自己不写，你有足够的资源，我会做的是：让人写成一本书，即便只供内部使用。你读过 Michael Moritz 的《The Little Kingdom》吗？

嘉宾 I never read it. I have 我没读过。我有

主持人 Oh, you have to. It's like the first 6-year history of Apple written by Michael Moritz. 哦，你必须读。那是 Apple 最初六年的历史，由Michael Moritz 写的。

嘉宾 Isn't it crazy that he wrote that book? 他写了那本书，这不疯狂吗？

主持人 He's a phenomenal writer. Like, crazy writer. Winds up being one of the best venture capitalists of all time, I guess. But, like the you just The point is that have That book ends Steve hasn't even been kicked out of Apple yet. So, you get like what actually happened. You're going to want this. You might not want it now, but you're damn sure going to want it when you're 60 or 70. 他是一个非凡的写作者。疯狂的写作者。后来大概成为有史以来最好的风险投资人之一。但重点是要有这个。那本书结束的时候，Steve 甚至还没有被踢出 Apple。所以你得到的是实际发生了什么。你会想要这个。你现在也许不想要，但你 60 岁或 70 岁的时候，你他妈一定会想要。

嘉宾 The thing that was so interesting was like the mindset of writing to your kid. Like, you really can't hide behind anything. Like I like I don't really care what my kid's going to think about me. So, like this thing happened. Like,you know, didn't feel great about it. Better do it differently next week. Like, it was a very interesting extremely interesting mental framework. Maybe I'll find some way to do it again. No, maybe you're going to do it. 当时那么有意思的是写信给孩子的心态。你真的没法躲在任何东西后面。我其实不太在乎我的孩子会怎么看我。所以，这件事发生了。就像，感觉不太好。下周最好换一种做法。那是一种非常有意思、极其有意思的心智框架。也许我会找到某种方式再做一次。不，也许你会去做。好。 Sam，谢谢你抽出时间。

Okay. Sam, thanks for taking the time. This is awesome, man. Thank you. Appreciate it. I hope you enjoyed this episode. Please remember to subscribe wherever you're listening and leave a review. And make sure you listen to my other podcast Founders. For almost a decade, I've obsessively read over 400 biographies of history's greatest entrepreneurs searching for ideas that you can use in your work. Most of the guests you hear on this show first found me through Founders. 这太棒了。谢谢。感谢。希望你喜欢这一集。请记得在你收听的地方订阅并留下评价。也请一定去听我的另一个播客 Founders。将近十年里，我痴迷地读了 400 多本历史上最伟大企业家的传记，寻找你可以用于你工作的想法。你在这档节目里听到的大多数嘉宾，最初都是通过 Founders 找到我的。