Sam Altman：如何打造 OpenAI，并押注那些看似不可能的事

简要说明Brief Description

David Senra 与 Sam Altman 探讨了 AI 如何改变产品、公司和个人工作流程；OpenAI 为何专注于研究和算力；非共识押注、安全、公众信任和商业战略如何塑造这家公司；以及 Altman 从创业者、YC 和 OpenAI 早期充满不确定性的岁月中学到了什么。David Senra speaks with Sam Altman about how AI changes products, companies, and personal workflows; why OpenAI concentrates on research and compute; how non-consensus bets, safety, public trust, and business strategy shape the company; and what Altman learned from founders, YC, and OpenAI’s uncertain early years.

目录Table of Contents

• AI 采用、习惯与产品设计
  AI Adoption, Habits, and Product Design
• 研究、计算与非共识押注
  Research, Compute, and Non-Consensus Bets
• 从投资者重回创始人角色
  From Investor Back to Founder
• AI 应该释放什么可能性
  What AI Should Unlock
• 安全、权力与迭代式部署
  Safety, Power, and Iterative Deployment
• 公众信任与人工智能的解释
  Public Trust and Explaining AI
• OpenAI 的平台与商业战略
  OpenAI’s Platform and Business Strategy
• 导师、YC 与创始人的经验教训
  Mentors, YC, and Founder Lessons
• 在没有客户信号的情况下构建 OpenAI
  Building OpenAI Without Customer Signals

AI 采用、使用习惯与产品设计AI Adoption, Habits, and Product Design

David Senra：我刚才提到了 Toby Lu，以及我之前和他一起录过节目。你为什么会说他是当下最有意思的 CEO 之一？David Senra: I just brought up Toby Lu and the fact that I recorded with him previously. Why' you say that you think he's one of the most interesting CEOs right now?

萨姆·奥特曼：托比最让我印象深刻的一点是，从 AI 发展的早期开始，在它一路演进的每个阶段，他都是最积极进取、最愿意走在前沿的 CEO。他会亲自上手编写软件，亲自进行试验，还会就产品提供的服务和模型的能力，给我们发送极其详细的反馈。Sam Altman: 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 it's developed, he has been the most forwardleaning 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.

早在其他任何人这么说之前，他就说：“我们不是一家 NPC 公司，所以我们要采用智能体；不然的话，你知道，我们就彻底完蛋了。我们要自己把它建出来。”每次我跟他交谈，他都处在所有人——不管是不是 CEO——所做事情的最前沿。他亲自构建。He was before anybody else is 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 ourself. Every time I talk to him he is at the edge of what anyone CEO or not is doing. He builds himself.

他明白自己有着非常敏锐深刻的判断力，而且总是比其他 CEO 领先六到八个月。你还记得他写那封信的时候吗？大概是一年半前，也许是 2024 年。他在信里说，你首先要做的就是看看 AI 能不能解决你的问题。甚至在那时候，也就是 18 或 24 个月前，人们都觉得这话荒唐，反应非常激烈。这就是我的意思：他一直都走在前面，而且判断正确，也积极拥抱 AI。他非常务实，完全没有炒作；他只会说，现在它到底能做什么、我觉得它很快能做到什么，以及我打算如何推动公司前进。他对 AI 发展到了什么阶段，有着极其深刻的理解。He understands that he has like a great deep feel and he is always six 8 months ahead of like any other CEO. Do you remember when he wrote this is 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 I don't know 18 months 24 months ago people went crazy they thought it was ridiculous this is my point like he's just consistently been ahead he's 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 how I'm going to push the company here and just like extremely deep understanding of where it's at.

David Senra：我以前从没想过，对于你这样的人来说，有这么一个人给你提供强烈、直接而明确的产品反馈，能带来多大的好处。很多人都会提供产品反馈，但他是唯一一个兼具大型公司 CEO 身份，并且能给出极其精准、详细、处于前沿的反馈的人。对，他跟我说过，我不确定是在我们那期节目里说的，还是节目之后说的，但他说得非常坚决。David Senra: 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. 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. Yeah, he told me I don't know if it was on the episode that we if it was in the episode or if it was after, but he said he was very adamant.

他就像是在说：“我们会在2026年回顾这一切。”其实我想听听你的看法。我之前甚至都没想到要和你聊这个。他说，回顾2026年时，我们会发现那是一个所有企业都面临变革的年份。他还说，会有人打造出 Shopify 的 AI 原生版本。He's like, "We're going to look back in 2026." And 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 is a year that every business was up for grabs. He said somebody was going to build the AI native version of Shopify.

他说：“而那个人会是我。”于是到了晚上，他真的在努力重建。And he said, "And it's going to be me." And so at night he literally trying to rebuild.

Sam Altman：如果从头开始，你会用现有技术做什么？我本来还想说他的另一点：他会亲自上手。他自己在用这些工具，也自己写软件。Sam Altman: If you started from scratch, what would you do with the current technology? That was the other thing I was gonna say about him is he does it himself. Like he is using these tools himself. He's writing software himself.

他自己在尝试这些模型，也在尝试重新构想自己的工作流程。大多数 CEO 到了那个层级，手下都有一层层的团队在负责落实这件事，而这些人会努力让你满意，也会努力把各种不顺的地方打磨平顺。我觉得，如果你不亲自做这件事，就很难真正体会到其中的感觉。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. I think it's very hard to get the feel if you're not actually doing the thing.

据我所知，他整晚都这么亲力亲为。我不确定2026年会不会成为每个行业都觉得随时可能被人抢占的一年。我在这点上可能和他有些不同看法，但我明白他的意思，也理解为什么会让人觉得事情确实正在发生。And 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. but I I get the spirit of that and I do understand that it feels like that's happening.

你觉得这真的有可能吗？比如说，不管是2026年还是2046年？我的意思是，显然不是字面意义上的每一家企业。我觉得有些事情非常反AII。Do you think that's even possible? Like whether it's 2026 or 2046? I mean, obviously not literally every business. I think there are some things that are very anti-AII.

比如，随着 AI 越来越强，我觉得有些跟 AI 毫无关系的行业反而会变得更难竞争，因为我们会特别渴望这种真实、非科技的体验，或者会更在意体育队之类的东西。所以，不是所有行业都会如此，但我觉得很多软件行业都还有很大的变数。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.

David Senra：那么，你会不同意这个时间安排吗？你会怎么……David Senra: Would you disagree on the timeline then? What do you

萨姆·奥特曼：我对时间安排有不同看法。我认为还需要再多花一点时间。Sam Altman: I disagree on the timeline. I think it's going to take a little bit longer.

David Senra：好。你能多说一点吗？我很喜欢初创公司。我觉得初创公司是经济中最酷的东西，而我的整个职业生涯都在努力真正理解初创公司。我原以为，等我们迎来 GPT-4——那是在 2023 年——之后很快，软件行业就会出现更大的颠覆，整个行业也会立刻变得人人都有机会去争夺。但事实证明并非如此。David Senra: Okay. Can you say more about that? I love startups. Like I think startups are the coolest thing in the economy and I've spent my career trying to like really understand startups and I thought when we got to GBT4 which was back in 20 23 I think that very quickly after that there was going to be much more disruption in software business being up for grabs right away than it turned out to be.

而且我觉得，有几件事我之前判断错了，其中一件是关于速度的，另一件是经济本身有着巨大的惯性。人们会继续做自己一直在做的事，继续从同一家——你知道——公司购买产品，也会继续以同样的方式使用他们的工具。And the thing that I think I was wrong about a few things 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 you know company. They keep sort of wanting to use their tools in the same way.

我认为这实际上在很多方面都是件好事，会让眼前这场重大转型推进得更平稳、更缓慢。我对此心怀感激。但我认为，这也意味着我们所有人对时间安排都过于乐观了。即使有了这项令人难以置信的技术，我仍然认为，人工智能是人类有史以来发明的最非凡的技术之一。I think this actually a positive in many ways and it's going to make this big transition in front of us go smoother and slower. 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 has ever invented.

社会和经济的适应速度会更慢。Society and the economy will adapt more slowly.

萨姆·奥特曼：是啊，这挺有意思的。开始录制前我们还聊到，历史上有很多类似之处。显然，我平时就是以读历史为生的。Sam Altman: Yeah. It's funny. We were talking before we started recording that there's all these parallels to history. Obviously, I read history for a living.

你刚才说话的时候，我根本没在想 OpenAI、人工智能和萨姆·奥特曼。我想到的是读拉里·埃里森的传记，讲到 80 年代时，他当时就说：“伙计们，这不是软件问题，而是人的问题。”When you were just talking, I wasn't even thinking about open AI and AI and Sam Alman. I was thinking of like reading this biography of Larry Ellison and in like the 80s. He was just like, "Guys, this isn't a software problem. It's a people problem.

我们得让他们相信我们能够安装软件。他们并没有在使用它。我们必须改变他们的行为。技术已经具备了。We have to convince them like we can install software. They're not using it. We have to change their behavior. The technology is there.

这就像现在我们必须让人类适应这项技术，让他们真正开始使用它。我自己的例子是，Netflix 刚推出时，先开始邮寄 DVD，后来才开始提供流媒体服务。让我惊讶的是，人们居然还去百视达租碟。我简直不敢相信。It's like we have to now adapt humans so they actually start using the technology. My own example of this was 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.

我当时就会看着这件事，因为我上学和放学的路上会开车经过一家百视达。让我觉得很不可思议的是，人们居然还在这么做。你知道，这就是一个让我一直记在脑子里的例子，说明了习惯的力量，以及人们做事的方式——改变行为要难得多，远超那些科技迷的想象。所以，回到托比写那封公开信，或者说写给公司内部员工的那封信所引发的轩然大波，你们采纳这些东西的速度比任何人都快，因为某种程度上，你们自己也在发明它们，对吧？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 and the way people do things 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 that letter to the people inside of his company, you're adopting this faster than anybody else because you're partially inventing them, right?

所以，有没有过这种时候，你会真的被自己的行为吓到，或者心想：“我知道有更好的办法。”我甚至正在打造一个本可以做得更好的产品，可我还是改不了这个习惯，这种根深蒂固的习惯。So, like, 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. 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.

David Senra：百分之百。David Senra: 100%.

萨姆·奥特曼：好的。Sam Altman: Okay.

David Senra：我很喜欢你之前问过我这个问题。我一直在等这个问题。对我来说，自己最让人觉得心理上前后不一致的一点是，20年来我一直用同一种方式使用电脑。现在我有了一个叫编解码器的神奇东西。David Senra: I love asked me this before. I have 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 codecs.

你也是，大家都是。这意味着我应该彻底换一种方式使用电脑，而不是到处点击，在一个聊天应用里复制再粘贴到另一个应用里。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 you know pasting from one messaging app to another.

我不应该漫无目的地刷邮件，在自己根本不想处理的时候，还要琢磨哪封邮件打开并回复起来最不让人难受。我不应该像这么多年来一直做的那样，列个待办清单，然后做这些机械重复的电脑任务。可我脑子里好像还是刻下了这样一种观念：做这类事情才叫工作，才叫有生产力。要是你问我，我绝不会说我喜欢这样做。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. And if you asked me I would never say I like doing it that way.

事实上，我反而会说相反的话。而且我想我是真心这么认为的。不过从显示性偏好来看，我现在有更好的办法，也能做得更快。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. I can do it faster.

我可以更多地用 Codeex 来处理日常事务，比如清理这一堆邮件、完成待办清单上的事情，还有各种杂事。但我还是照旧用老办法做。这完全说不通，除非我其实是暗地里喜欢这么做，或者觉得这样做很舒服。你觉得要发生什么变化，你才会真正更深入地使用自己的产品？I can be using codeex for more of just like my dayto-day like got to get through this stack of emails, got to do the 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 it or feel good about it. What do you think is going to has to change for you to actually adopt your own product in a more deep way?

我也不太清楚。我的意思是，这件事正在逐步发生，而这可能就是正确答案：这些事情必须循序渐进地发生，要彻底改变一个人根深蒂固的习惯和工作流程很难。我觉得我们可以用这项技术打造更好的产品，让这种转变更加顺畅。但现在感觉我们都在这两个世界之间摇摆：一方面，我们还有一台可以照旧使用的电脑；另一方面，我们也有一些编解码器，能以这种令人惊叹的新方式使用电脑，而我们不确定什么时候该用哪种方式、做什么事。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. 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 codecs that can use our computer in this amazing new way and we're like not sure which to use when for what.

我觉得这主要是产品层面的失败。我们现在所处的阶段让我想起 iPhone 出现前的智能手机。我算是个早期用户。大概在 2003 年还是 2004 年什么的，我就有一台 Palm Trio。And I think this is mostly a product failure. 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 four or whatever.

Sam Altman：你有搭档吗？我从来没有过。我觉得他们特别酷，也想要一个。Sam Altman: You have a sidekick? I never had a I thought they were super cool. I wanted one.

David Senra：很多技术其实都已经具备了。比如当时还没有多点触控，但更重要的是，缺少那些让 iPhone 成为 iPhone 的产品创意。我觉得我们现在也处于这样一个阶段：所有技术要素都齐备了，但还没有出现 iPhone 时刻，也就是彻底改变人们与技术交互方式的时刻。我们刚才聊到 Toby，Toby 现在就在亲自打造这些东西，对吧？David Senra: 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. We were talking about Toby's like Toby's out here building these himself, right?

我们有一个共同的朋友，乔什·库什纳。他说，史蒂夫·乔布斯的思维方式和经营公司的方式，与你做事的方式有很大的可比性。乔布斯显然不是那个写代码的人，也不是打造硬件的人，但他就像是说：“我是零号病人。”we have a mutual friend in Josh Kushner. He says he's like there's there's a big comparison to be made between the way that Steve Jobs thought and the way he ran his company to the way that he thinks that you do. He wasn't the one obviously writing the code. He wasn't building the hardware, but he's like I am patient zero.

我做的是我自己也想用的产品。基本上，我们看到苹果做的一切，都是他想要的。有本书里讲了一个很棒的故事：他们本来要开个会，我想是讨论某款 MacBook，也就是新款 MacBook 笔记本电脑。团队为史蒂夫准备了一场很长的演示，他们很紧张，因为他气场很强。他走进来时，他们以为这会是个一小时的会议。结果他走进来，给他看了看笔记本电脑，然后说：“开，关。”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. There's this great story in one of the books where he they he they were supposed to have a meeting on 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 they think it's going to be like an hour meeting. walks in and he shows him the laptop and he's like on off.

他按下按钮，它就亮了。马上按下关闭，然后他接着试着打开 MacBook。中间好像有一段延迟。他就把这个弄成这样（指的是 MacBook），然后走出房间，然后就……He presses the button, it comes on. Press off like immediately and then he then tries to open up 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

研究、计算与非共识押注Research, Compute, and Non-Consensus Bets

David Senra：整体意思就是这样。苹果的历史上有很多这样的例子。你会怎么做？比如说，你如何改进产品？David Senra: the whole meaning like that. There's a lot of examples in the history of Apple like that. How do you approach it? Like how do you improve the product?

你做这件事主要是从自身需求出发吗？你怎么看这个问题？我现在大部分精力都放在研究和算力上。我很希望能把更多时间花在产品上。Like are you just doing it through your own needs? Like how do you think about this? Most of my effort right now is on research and compute. I would love to be able to spend more time on product.

这里有很多优秀的人在思考产品，但我们能做的最重要的事，就是打造智能模型，并能够高效、大规模地为很多人运行这些模型。如果我们能把这件事做好，我相信其他一切都会水到渠成。从理念上说，我很倾向于去寻找那种高杠杆、难度很大的问题，让指数级增长得以延续；对我们来说，这就是模型和算力。我也觉得，这些问题恰好很适合我。为什么它们恰好适合你？按照我们现在的方式扩展算力，需要应对一条复杂的供应链，还要理清许多有意思的合作关系，而我喜欢做这些事；此外还有一些有趣的财务挑战，比如如何为这个可能已经是、或者至少正在迅速成为史上最昂贵的基础设施项目筹集资金。要把算力扩展到这样的规模，还涉及许多技术问题：从设计自己的芯片，到与晶圆厂及机架制造商相关的供应链，再到这些设施的供电系统。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. 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 of compute I also just think those are like problems that naturally suit me why do they naturally suit you 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 to figure out which I like doing there's like interesting financial challenges of how you're going to finance what is probably already or at least rapidly becoming the most expensive infrastructure project in history. the technology questions that go into building out comput at this scale from you know designing your own chip to the supply chain of fabs and people that make racks to sort of the power systems for these things.

我一直对能源领域中各种因素如何汇聚很感兴趣。因此，围绕着以这种规模建设算力，技术、商业、政策、供应链和物流等方面都有很多有趣的问题。我以前做过初创企业投资人，而在我的职业生涯中，我发现与初创投资最接近的事情就是管理一个研究项目。不过，两者也有很多截然不同之处。I've always been interested in energy all come together. So there are a lot of problems that are interesting across technology, business, policy, supply chain, logistics altogether around building compute at this kind of scale. 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.

就像你知道的，我认为普通研究人员和普通创始人表面上看起来显然很不一样，但在很多方面其实很相似：比如如何找到非共识的投资机会，如何决定该对什么抱有信念，如何理解指数级增长是什么样的，如何管理那些离群的顶尖人才，以及如何识别他们。我们现在就在这栋研究楼里，我也坐在这里。很好，说说你在初创公司投资中学到的东西，与从事研究之间有哪些相似之处。Like you know the average researcher and the average founder have I think on the surface look different for obvious reasons but there's like a lot of similarities about how you find the non-conensus 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 it even more. This is the research building that we're in and it's where I sit. Great. say more about why the parallels between what you learned at startup investing with doing research.

萨姆·奥特曼：一个重要概念是幂律。投资领域的人总是会谈到这一点：你得在某种程度上重新训练自己的大脑，因为我们似乎天生就不太擅长用这种方式思考。也就是说，你最好的那笔投资，回报会超过你其他所有投资的总和；第二好的那笔投资，回报则会超过除此之外所有其他投资的总和。Sam Altman: One big one is the power law. So 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. 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.

至少，AI研究也是如此。我们刚开始时，人们认为 AGR 完全不可能实现，或者说几乎不可能实现。这是哪一年？And AI research at least is like that as well. When we started, people thought it was totally unlikely or almost impossible that AGR was possible. What year is this?

David Senra：2015年。2015年。我的意思是，我们刚刚因为说要追求 AGI，被这个领域所有的思想巨擘狠狠批了一顿。然后，当我们开始真正专注于大型语言模型时，又再次遭到痛批，他们说这完全荒谬。David Senra: 2015. 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.

我们理解到——至少我从自己那种创业背景出发是这么理解的，我想其他人也从不同角度理解了——高风险下注是可以的，只要你选择的是那种一旦成功就极具价值的项目，而研究就是这样。那些能成为优秀研究者的人，往往是不随大流、思路新鲜、精力充沛、不太循规蹈矩的人；“不循规蹈矩”这个词一直浮现在我脑海里。你得多说说“不循规蹈矩”是什么意思。能不能具体一点？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 looks this way. The kind of people that make great researchers are sort of non-conensus fresh approach high energy sort of non-standard is the word that keeps coming to mind. people you got to say more about non-standard. Can you be more specific?

他们够有棱角吗？你不会想投资这样一位创始人：他对同一个点子只有一点点不同的看法，而你之前聊过的上千个人都试图说服你——或许也说服他们自己——相信他们有多么与众不同、做的事有多么新颖。但他们大多只是在努力融入群体，跟大家走同一条路，做大家认为他们该做的事，也就是创办一家初创公司。你知道，他们听彼得·蒂尔说过太多次，说他们应该做些与众不同的事，于是便试着模仿这种做法，但其实并非真心如此。Are they spiky? 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 talk 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 Teal 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.

比如说，当你遇到一个思维方式和大多数人截然不同的人，而且他愿意坚持那些极不受欢迎的信念时，我就看得很清楚：这些信念可能是错的，但如果是对的，那他们至少会对得非常彻底；这和那些只是在大家都持有的同一个观点上薄薄地覆了一层的人不一样。2015年末，我们开始创办 OpenAI 时，世界上致力于 AGI 的项目还寥寥无几。我能想到的只有 DeepMind 和另外一两个。这是一件非常不符合共识的事。Like it's it's very clear to me when you have someone who just thinks differently than most other people and has 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 late 2015 when we were starting open AI there were very few AGI efforts in the world. There was Deep Mind, one or two others that I can think of. It was like a very non-conensus thing to do.

同一年里，可能有——我就拿它来说吧，只是因为刚好想到——不过也还有其他类别。那时候大概有成千上万的创始人在做照片分享应用。你知道，那可能不是那么好的选择。如今，很多人都想创办 AI 实验室。In that same year, there were probably I'll 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.

有那么一小群人，你知道的，两三个之类的，在做一些全新的事情。这件事直到我做到这么好那天之前，实际上都不可能实现，但目前看起来还不像是个好主意。而这正是我作为一名创业投资人一直想资助的事情，也是对我来说大多时候行得通的事情。对研究人员来说也有类似的情况：有很多研究人员会追逐上一个奏效的东西，而只有少数研究人员对一个新想法抱有坚定信念。我认为我们过去是、现在也仍然是最适合这类人的研究实验室。几个月前我记得和 Deus 谈过这件事。他觉得，就你们这种做法而言，资金和资本所要求的那种格局里有三大玩家，你们不可能成为第四个更大的玩家。不过他说，还有这么一类十……我忘了具体数字，就随便编一个吧。There are some handful of people, you know, two, three, whatever, doing something completely new. that actually wasn't possible until the day I got this good but doesn't seem like a good idea yet and like that is the thing that as a startup funer I always wanted to fund and the thing that mostly worked for me there's a similar thing for researchers there were a lot of researchers that would chase whatever the last thing was that worked and there were a small number of researchers that had high conviction towards a new idea and I think we were and are the best research lab for those people. I remember talking to Deus about this a few months ago and he thought, you know, in terms of like chasing after the way that you guys are, it's like, you know, there's the big three players that the money the capital requires 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.

比如说，有 10% 的可能，会有某位僧侣研究者从一个我们从未考虑过的角度来研究它。Say 10% chance that there's just some monk researcher that's going to approach it in a way that just this angle we've never even considered.

萨姆·奥特曼：没错。我不知道该怎么量化，但确实有一定概率。我不觉得这个数字是我瞎编的，不过大概是个很小的百分比。Sam Altman: Totally. I don't know how to put a number on it, but there is some chance. I don't think I'm making the number up, but it was like a small percentage.

David Senra：确实有这种可能，肯定的，David Senra: There is some chance of that for sure,

从投资人回归创始人From Investor Back to Founder

David Senra：好。让我困惑的是，你从创始人转为投资人，又回去当创始人。但为什么是在2015年？最初是什么让你对人工智能感兴趣，以至于你会说：“嘿，这是一件如此不符合共识的事情。”David Senra: Okay. So, what is confusing to me? You went from founder to investor to back to founder. 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-conensus thing.

人们觉得我疯了。反正我还是要做。”People think I'm crazy. I'm going to do it anyways."

萨姆·奥特曼：嗯，我这一生都对人工智能很感兴趣。我小时候是个特别书呆子的孩子。就是，你知道，我是那种周五晚上会玩电脑、看科幻片、读科幻小说的孩子。我一直觉得人工智能会是最不可思议、最疯狂的东西。我从没想过自己真的有机会参与其中，但我一直、一直都很喜欢它。Sam Altman: 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 like the most amazing kind of craziest thing. I never thought I would actually get to work on it, but I always I always like loved it.

我甚至可以说是为了研究它才上大学的。我大一升大二的那个暑假在人工智能实验室工作，但什么都行不通。事实上，我印象特别深的是，一位教授告诉我可以试试所有这些办法，还有这么多不同的方向。I even came to college sort of to study it. I worked in the AI lab the summer between my freshman and sophomore year and nothing was working. In fact, I very memorably a professor told me could try all of these things. There's all these directions.

我们知道唯一行不通的就是深度学习。我们试了很长时间。你知道，这是那种最能确保职业生涯走下坡路的做法。我当时就像个容易受影响的大一新生，诸如此类。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 most guaranteed way to have a bad career. And I was like an impressionable freshman in college, whatever.

我当时想，我以为那是真的。所以，你知道，我就去做了其他这些事情。那时候我很清楚——大概是2005年——AI行不通。我碰巧是无意间进入了创业领域，但后来真的爱上了它。I like I assumed that was true. So, you know, pursued 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 happened to like accidentally get into startups, but then very much fell in love with it.

所以我甚至不会把它称作职业上的绕道，因为它真的很有帮助。回头看，后来成为一名初创公司投资人是件很棒的事。硅谷比较常见的职业道路是，你会成为——或者说，常见的一条路是先做创始人，然后差不多半退休，转而成为投资人。And so I wouldn't even call it a career detour cuz it was super helpful. looking back and becoming like a startup investor was great. The sort of normal career path in Silicon Valley is you're like a or not a a common path is that you're a founder and then you like sort of semi-retire and you become an investor.

David Senra：我们不想要那个。我听你说，你打算在职业生涯剩下的时间里一直做这件事。是啊，希望这只是个开始。我们还会多次来上节目。David Senra: We don't want that. I heard you say that you're going to work on this for the rest of your career. Yeah, I'm hopefully we're starting. We're going to come on the show multiple times.

我会要求你说到做到。我们不需要更多退休后转去投资的创始人。我们已经有了……I'm going to hold you to this. We don't need more founders that retire and invest. We have

萨姆·奥特曼：我觉得这件事的投资者并不算太多。Sam Altman: I don't we have too many investors in this.

David Senra：但我想说的是，我有机会走了另一条路。我先做投资人，然后才经营公司。这挺不寻常的。David Senra: But what I was going to say is I the fact that I got to go in the other direction. I was like an investor first and then I ran a company. It's pretty unusual.

萨姆·奥特曼：非常罕见。Sam Altman: Very unusual.

David Senra：我对此非常感激。因为，如果你以投资者的身份真正去研究和观察公司，就能获得一套不可思议的经验和模式识别能力，这对我经营 OpenAI 帮助很大。但这和通常的路径恰恰相反，所以这是一件非常罕见的事，我强烈推荐这么做。为什么有帮助？如果你在经营一家公司，过去肯定做过一些类似的决策，比如一些关键决策，也见识过哪些做法奏效，哪些不奏效。David Senra: And I'm super grateful for it. 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 it's like it's the opposite normal direction so it's just like a very rare thing and I strongly recommend it. Why is it helpful? 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.

而且如果你不得不做出高风险的战略调整，或者以一种非常棘手的方式解雇一位高管，你能依靠的也就是你过去五年或十年里积累的有限经验。但作为投资人，你基本上能见证所有关键时刻。你不会像每天亲自经营一家公司那样积累运营经验，但你会反复见证许多重大的关键时刻，几乎每天都能看到。所以，我在那里获得的丰富数据集真是太棒了。And if you have to like, you know, make a highstake 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 5 or 10 years that you've been doing it. But as an investor, you kind of watch all the crux moments. 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 that the wealth of the data set that I had there was awesome.

萨姆·奥特曼：所以当你需要做决定时，脑海里就会浮现出这句话。Sam Altman: So that plays in your head when you have a decision to make.

David Senra：对。我就会想：“哦，这就是那家公司遇到类似情况时发生的事，或者我看到这位创始人犯了这个错误，又或者那位创始人做得特别对。”David Senra: 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."

Sam Altman：我们刚才在聊你研究过工业革命。我们还聊了我们俩之前都读过的一些很棒的传记。我的朋友 Daniel X 是这么评价我的，因为我觉得，我在另一个名为 Founders 的播客上做这个项目做了 10 年，带来的好处是……Sam Altman: We were talking about that you studied the industrial revolution. We were talking about some great biographies that we both read earlier. my friend Daniel X says this about me cuz like I think the benefit of me doing this project on my other podcast called Founders for 10 years

David Senra：就像David Senra: is like

萨姆·奥特曼：所以他就说，你就像一个用历史上最伟大的企业家训练出来的大语言模型，只不过把温度调高了，因为你很疯。我对这件事特别狂热，狂热得有点奇怪，简直痴迷于已经去世的企业家。不过这确实有帮助。比如，我和一位创始人聊天，他们会讲自己遇到的某件事，我就会说：“哦，卡内基当年是这么做的，洛克菲勒是那么做的，你也许可以试试这个。”就像是，Sam Altman: so he's like you're like an LLM train on history's greatest 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. but it is helpful. 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." It's like,

David Senra：你会不会觉得这一切归结起来就一个大的洞见？还是说，具体到每种情境，你脑子里都会想到这些人分别做了什么，以及这些事是如何串联起来的？我觉得这取决于创始人的性格，对吧？我读你的博客好多年了，我觉得你是个很棒的作家。David Senra: and do you find that you have like one big insight all of that or it's just like for any given scenario, you have like what all these people did and how it comes together. I think it's dependent 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.

你表达得非常简洁，这种简练真的很吸引我，而且我很喜欢编号列表。挺奇妙的，我们俩写作风格竟然一样。我读你的博客时会想，这正是我读了这么多之后会得出的结论；而且，虽然有那么几条原则可以应用，但具体情况真的取决于创始人是谁、他们想做什么。这正是我想弄明白的。咱们还是回到刚才聊的话题吧。You're very succinct 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 and like there's this handful of principles that could be applied but it's like really depends on like who the founders is and what they want to do. This is what I'm trying to understand. It's like let's go back to what we were talking about.

我还是觉得，你这是一个很大的跨越，因为据我所知，你是硅谷有史以来最优秀的投资人之一。你本来可以就这么当个有钱人，没必要真的工作，毕竟投资人多少有点懒。I still like you're you're making a big jump cuz you know you're one of 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 investor kind of lazy.

Sam Altman：顺便说一句，我只是在开玩笑。也不完全是。Sam Altman: I'm just kidding by the way. kind of not.

不，确实……我两种都做过，我想我可以说，经营一家公司比在公司里工作要难得多得多。David Senra: no, it's pretty I having done both, I think I can say it's like much much harder to run a company than being in.

萨姆·奥特曼：没错。我认为人们就该这么做。然后你就会想：“去他妈的。我才不走容易的路。”Sam Altman: Exactly. And that's what people should be doing in my opinion. So then you're like, "Fuck that. I'm going to not take the easy route.

“我要去做有史以来最难的事。”那件人们认为不可能的事。那件我会被嘲笑的事。I'm going to do the hardest thing ever." The thing that people think is impossible. The thing I'm going to be made fun of.

David Senra：是的。David Senra: Yeah.

我还是得弄明白。好吧，所以你喜欢这个，孩子。它到底为什么会吸引孩子呢？Sam Altman: I still need to understand. Okay. So you're into it kid. Like why would it appeal to a kid?

当时你住在圣路易斯。You were living in St. Louis at the time.

David Senra：我当时住在圣路易斯。David Senra: I was living in St. Louis.

萨姆·奥特曼：那时候，AI 为什么会吸引你？嗯，我觉得它吸引了各种各样的电脑迷。我不觉得自己有什么特别的。它当时就是让人觉得不可能实现。Sam Altman: Why would AI appeal to you back then? 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.

我觉得大多数人会说，当然啦，那肯定是有史以来最酷的事，但完全不可能。我觉得我比较奇怪的地方就是会想：行，那我们试试吧。不过我觉得大家都觉得——每个人都会觉得这很棒，是值得去、值得去争取的事情。I think most people would say like of course that'd be the coolest thing ever, but it's totally impossible. I think that 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.

David Senra：等等，所以那是你小时候的一种性格特质，它告诉你……David Senra: So wait, that was a personality trait of yours as a kid that told you

萨姆·奥特曼：你不能做类似的事情吗？你的最初反应是抗拒？也不是抗拒，更像是“你确定吗？为什么不试试？我们试试看。”Sam Altman: that you couldn't do something like your initial response was resistance? not resistance, but like are you sure? Like why not? Let's try.

我们看看会发生什么。也许我能做到，也许我们都能做到。我以前是个特别乐观的孩子。而且一件事看起来越是不可能，我就越感兴趣。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.

我们能够发明一种技术，让我们做成其他所有事情；这种技术能以其他任何单一技术都做不到的方式赋予人们力量。这个想法一直让我觉得天生就极其吸引人。就像，我想要那样的东西。我想要能够做成其他所有事情。我觉得还有一点，从我记事起，这就有点像是我的一种性格特质：你知道，真正让人们拥有更多力量、更多能力，这件事很有意思。从某种意义上说，这就是技术发展的整个历程。我当然一直都是个技术迷，但人工智能是我所能想象到的、最强大的这种技术。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. 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.

David Senra：你当时觉得它能让你做到什么？比如你还是个孩子的时候，觉得这项技术很酷。我想做X。除非有AI，否则我做不了X。David Senra: What did you think that it would enable back then? Like when you were a kid like this seems like a cool technology. I want to do X. I can't do X unless AI

萨姆·奥特曼：是虚构的。Sam Altman: is invented.

David Senra：要分清有多少是我当时真正这么想的，有多少是你现在正试图打造的东西，总是很难。David Senra: It's always hard to remember like how much of this is the stuff that I actually thought at the time versus like what you're trying to build right now.

萨姆·奥特曼：是啊。比如说，我现在的工作在多大程度上影响了我对它的记忆。肯定有影响。Sam Altman: Yeah. Like how much my current work has like colored my memories of it. For sure

AI 应该释放的潜力What AI Should Unlock

萨姆·奥特曼：我小时候特别迷机器人。你知道，我们学校有个机器人俱乐部。当时的机器人简直幼稚得让人发笑。我甚至还记得，夏令营里有一只小乌龟，可以通过电脑控制它在地板上或桌面上移动，我觉得那简直酷毙了。电脑控制的实体东西动起来，总让我觉得特别神奇。如今，我对人工智能如何推动科学发现极为感兴趣。Sam Altman: as a kid I was like very into robots, 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.

在我成年后的记忆里，我觉得自己小时候也认为那很酷。但现在想来，这似乎实在有点不可信。我猜这就是一种记忆被后来添上了更多色彩的例子。不过如今，AI 可以去发现新的物理规律、治愈疾病，而且它已经在数学领域发挥作用。对此我认为，这将会是最重要的领域之一，甚至比 AI 自动化其他任务更重要，因为它能帮助我们理解更多事物。In my memory 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.

我们之前聊过这本书，《无穷的开始》。从今天的视角重新读这本书，我就会想，天哪，AI真的会帮助我们做好这件重要的事——理解一切，或者尽可能多地理解一切。我确实对那种星际迷航式的巨大繁荣与富足，以及AI能如何推动这一切很感兴趣。也许，回忆起自己曾经对科学感兴趣这件事，更有真实感。We were talking earlier about this book, The Beginning of Infinity. And rereading that book from today's vantage point, I'm like, man, AI is 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 what AI could do to drive that. Maybe the memory of being interested in science is more real.

也喜欢科学，也喜欢这样一个想法：因为我们足够聪明，所以能够弄明白如何理解世界、做出预测，并做到那些没有这种深刻理解就无法做到的事。我不知道，这感觉天生就很棒。人类一直以来对 AI 的期待竟然如此一致，这很有意思，因为你描述的某些东西就和这一点很相似。我刚刚第二次重读了克劳德·香农的传记。我都忘了这件事了，因为我可能有五年没读过这本书：香农和艾伦·图灵当年都在贝尔实验室时，每天都会一起喝咖啡。else loved science 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 innately awesome. 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 because 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 Bill Labs.

这就像是发生在20世纪40年代，他们会谈论人工智能，而且他们俩都对此着迷。他们当时认为这件事是不可避免的，还觉得大概再过15年就会实现。也就是说，他们认为到了1955年，我们就会有电脑——那时候电脑还不存在，对吧？他们有的是模拟计算机，而他们觉得这些机器会比人类更聪明；谁要是认为这不会发生，他们就觉得那简直荒唐至极。他们还会问：“你想让电脑做什么？”他会说：“解数学题、写诗，比如治愈疾病。”类似的话你会一遍又一遍地听到。This is like 1940s and they would just talk about AI and they were both obsessed with there is 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 that are that are going to be smarter than humans and that anybody that thought that wasn't going to occur, they thought was absolutely ridiculous. And they're like, "Well, what would you want the computer to do?" He's like, "Solve math problems, write poetry, like sol cure diseases." Like you hear this over and over again.

我读过当年那些人写的很多东西，想到他们没能活着看到这一切，我真的很难过，因为他们说的一切都太对了。我们终于到了 AI 能解决新颖数学问题的时刻了。它还在发现其他东西。你知道，关于它到底有多厉害可以争论；我会说不怎么样。但它写诗也已经到了这种程度，就像这些人——我觉得他们会说：“好了，你做到了，就是这样，我们成功了。”I have read a bunch of things that those guys wrote at the time and I am so sad they are not here to see it cuz they were so right about everything. We're finally at the moment where AI is solving novel math problems. It is discovering other stuff. It is you know you can argue about how good or not I would say not very good but it is writing poetry 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.

那会很酷。是啊。这事挺奇怪的，大家都只会说：“哦，它永远做不到 X。”比如我跟音乐行业的人聊过，他们会说：“它永远创作不出好音乐。”然后他们又会问：“那你觉得它会做播客吗？”我就说：“它当然会啊。”and that would have been so cool. Yeah. This is the weird thing where everybody's just like, "Oh, it'll never do X." Like, I talked to people in the music industry. It's like, "It's never going to make great music." 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.

“它将会做到我们能做的一切，至少我想说，甚至现在就能做得比我们更好，像是比我们做得还好。”这是一件非常奇怪的事：它永远不会超越此时此刻正在发生的事情，而我碰巧还活在这个时刻。这里面有一种深层的人类心理缺陷。不过我觉得，这里有个更有意思的问题。假设它真的做出了一档很棒的播客。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. There's a deep human psychological flaw there. But here is, I think, a more interesting question. Let's say it does make a great podcast.

你知道吗，两个 AI 之间的对话，比你我之间的对话有意思多了。你觉得人们会在意吗？还是他们会想看有真人参与的那个，因为我们都对人着迷？而且这又不是真人。是啊，因为这个好像更有意思。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.

就像，哦，这两个人可能本来就让我倾向于喜欢或讨厌，但他们正在聊一场让我感兴趣的对话。我觉得，严格来说，比如说我另一个播客，我只是会说：“嘿，这是我在这本书里读到的一些有意思的观点。”这种内容或许会受到冲击吧，不管怎么说。尤其是那些在这件事发生之前出生的人，可能跟你儿子的情况不一样，你懂吧？但对我来说，我觉得人类永远都会被人类吸引。It's like, oh, these two people that I may be predisposed to like or dislike are having conversation that's interesting to me. I think for like strict like reference, like maybe my other podcast where I'm just saying, hey, this is some interesting ideas I read in this book. that could maybe get disrupted, whatever the case is. But especially for people that were born before this happened, maybe it's different for your son, you know, but for me it's just like I think humans are going to always be drawn to humans.

我真的非常相信这一点。我觉得还有很多其他工作可能会经历重大转变，但那些与人有关的事、与人与人之间的联系有关的事——人与人建立联系、彼此喜欢——在后数字化时代似乎会变得更有价值，而不是更没价值。不过，也许我其实不太适合谈这个，因为尽管我做的所有工作都是数字化的，你知道，向全世界传播，我内心深处还是非常渴望过一种更模拟、更贴近现实的生活。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, connection to people and people liking other people, that stuff feels like it gets more valuable in the post world, not less. I may be actually the wrong person to talk about this though because I kind of deeply desire even though my entire work is digital, you know, broadcast all over the world. It's just like I deeply desire like more like more of an analog life.

我喜欢看纸质书。比如我跟凯莉聊天时，我就说：“我不想上 Zoom。给我打电话，或者我们当面聊。”就是，我喜欢实体的，我不喜欢……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

David Senra：我也一样。我不看电子书。David Senra: I'm like that too. I don't read ebooks.

萨姆·奥特曼：是的。Sam Altman: Yeah.

David Senra：我不喜欢开 Zoom 会议。我喜欢和现实生活中的人待在一起。我确实觉得，有一小撮怪人——而且这座城市里可能有不少这样的人——他们不喜欢和人打交道，只想跟电脑交流。但我觉得，这只占人类中的极小一部分。David Senra: I don't like Zoom meetings. I like to be like with people in the real world. 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.

我觉得这只占人类中极小的一部分。我之所以这么想，是因为即使出现超级智能，整个世界总体上也不会有那么大的不同。人们的本性依然会让他们在根本上关心他人，想和他人待在一起、与他人互动。当然，有些人会沉迷于模型，觉得人类挡了路，或者是需要应对的危险之类的；但对大多数人来说，与他人相处才是最重要的。I think it's a tiny percentage of humanity. I This is why I think like the world is on the whole not going to be that different even with super intelligence. Like people are still going to be very fundamentally wired to care about other people, to want to be around other people, to interact with other people. 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 and for most people it'll be the whole point.

我认为这非常重要；一旦发现这样的人，就应该公开揭露他们，并确保他们无法获得权力。I think it's very important and when we do find people like that to them be called out and make sure they don't acquire power.

萨姆·奥特曼：我当然同意这一点。关于人工智能，我最担心的两大风险，可能在某种程度上都与意图有关。一个是失去控制：你知道，人工智能可能会变得过于强大，以至于我们无法确保它处于我们希望的控制之下。另一个是权力过度集中：你知道，某一家公司、某个模型或某个人掌握了太多权力。而这两种情况的根本问题在于，我认为无论哪一种发生，都是一种非常反人类的立场。正确的做法应该是：我们希望人们能够深度掌控未来，也希望人们能够充分赋权。人本身就是这一切的意义所在。我们不会坐在这里，眼看着自己逐渐把控制权交给一个人工智能模型，因为我们不信任人，也不喜欢人。你知道，把所有信任都交给这个模型，让它掌握世界上的全部权力和决策权，这是一种非常厌恶人类的想法。Sam Altman: I certainly agree with that. Maybe the two big risks that I'm most worried about with AI which are a little bit intention one is like 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 and in both of these the fundamental thing is like I think it's a very antihuman 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 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 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-m over the world.

但我觉得，世界上有些人认为那就是正确的结果。这件事还有另一种说法：因为我们不信任人们，所以必须限制谁能接触这项技术、以及他们能如何使用它；可能会发生种种可怕的事情，你懂的。出于对这些事情的恐惧，我们就要把权力集中到少数几家公司手里，然后呢，我们不让其他人使用这项技术，但会给他们一些好处。对这件事，我的漫画式概括是：我觉得 AI 领域有些人实际上是在说，我们会给全世界一种治愈所有疾病的方法，也会让各种东西变得非常便宜，作为交换，人们必须放弃自主权、对未来的影响力和权力；而且这也是为了安全着想，同时还会造成彻头彻尾、肆无忌惮的不平等。也就是说，有些人会拥有巨额财富和权力，而其他人得到的，不过是方方面面都还算不错的生活。But I think there are some people in the world who think that's the right outcome. 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 these terrible things could happen 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. Like my caricature of this is I think there are some people in the AI field 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. Like there will be people that have access to huge amounts of wealth and power and other people just get a pretty good everything.

这就像一段糟糕透顶的销售话术，是一种极其不近人情、却不知为何有人愿意采用的销售话术。And this is like a terrible sales pitch. This is a very anti-human sales pitch that somehow people feel willing to make.

大卫·森拉：你觉得他们为什么愿意做那件事？David Senra: Why do you think they feel willing to make that?

萨姆·奥特曼：我觉得这就像是恐惧和权力。我觉得，当人们谈论 AI 的风险时，有很多人会对这些风险的巨大程度感到非常紧张，深受其影响，觉得自己有必要保护世界免受这些风险的威胁，于是就会说，你知道，为了安全，我们应该在很大程度上牺牲自由，因为这和我们见过的其他风险都不一样。但我觉得，这最终也会变成一种为许多追求权力的行为辩护的方式。我读到的内容——比如我刚才提到的克劳德·沙……克劳德·香农说过的话，或者至少我读过的书里艾伦·图灵说过的话——更多体现的是一种乐观态度：我们会发明出能让生活变得更好、能替我们做事的东西。Sam Altman: I think it's like fear and power. 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 a need to protect the world from 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 a way to justify a lot of power seeking behavior. Everything when I read like when I was just saying Claude Ch 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.

你说得完全正确。如果回到 Claude Chen 和 Alan Tarian 的时代，他们谈论过 AGI 会有多么美好，以及它能做到的一切。我们刚起步时，确实承受了末日论者带来的很大压力。我赞同末日论者的一点是，这是一项强大的技术，我们应该宁可偏向安全一侧，并在技术发展的每个阶段都谨慎行事。我不赞同末日论者的一点是，他们认为这是一个无解的问题。You are totally right that if you go back to the Claude Chen and Alan Tarian era they talked about how wonderful AGI would be and all the things that it would do. 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 air on the side of side of safety and we should act with caution at each level of technology. The part of the doomers that I don't agree with is that it's an unsolvable problem.

如果你回顾 OpenAI 创立之初，我觉得当时有两种广泛持有的看法。第一，绝不可能——至少未来 10 年内绝不可能——造出一个非常像通用人工智能的东西；而且，即便我们真做到了，也肯定没法确保它安全。你知道，如果有一种 AI 在很多方面都比许多最聪明的人、比绝大多数最聪明的人还聪明，那么灾难论者就会说，到了那一步，世界肯定已经毁灭了。对齐工作会失败，而且当时人们对十年后会发生什么，都抱着这些极其笃定的看法。If you go back to the beginning of OpenAI, 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. 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 there were just these very confidently held positions about what would have happened a decade on.

我们已经打造出了一些东西，我想当时大多数人都会说，这让我们看起来非常接近 AGI。你知道，很多好事都发生了，而那些关于世界末日的疯狂糟糕预言并没有成真。所以我认为，人们应该据此调整对未来的预测。我们面前仍然有一些风险更高的挑战需要解决。但我们采取的方法——这是我从创业公司身上学到的另一件事——就是把东西推向世界，从真实客户那里获取反馈，看看它们会在哪里出问题，又会在哪里安然无恙。we have built something that I think most people would say at the time would have set us very AGI like 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.

这就是打造优质产品的方式，也是打造安全产品的方式。而我们在人工智能方面已经取得了更大的进展。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

安全、权力与迭代式部署Safety, Power, and Iterative Deployment

山姆·奥特曼：安全性比我认为我们刚开始时大多数人预想的要高。Sam Altman: safety than I think most people thought we would when we started.

David Senra：为什么？因为有十亿人每周都在使用你们的产品。每当模型能力提升一个层级，我们就把它发布到现实世界中，看看哪些有效、哪些无效；看看人们在哪些方面希望我们放宽安全护栏，因为他们有很好的用途；也看看我们在哪些地方出现了对齐失效，或安全系统失效。ChatGPT 上线还不到四年，就已经有十亿人在使用它，而且用它处理敏感而重要的事情。考虑到时间这么短、技术又这么强大，我们竟能交付一个普遍被认为安全的产品——当然，它也存在一些问题。我认为，我们绝不可能在象牙塔里做到这一点。你知道，我相信这就是打造优质、安全、稳健且实用的技术和产品的方式。我觉得这是 Y Combinator 的一个很棒的经验。对大多数 AI 安全领域的人来说，达到现在这个阶段、同时仍然拥有我们如今这样的安全保障，似乎完全不可能。我确实认为，从现在起会越来越难，但我不认为脱离现实就能解决问题。David Senra: Why? because so many people there's billion people using your products on a weekly basis 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 we have safety systems failures chatbt has only been out like less than 4 years billion people use it and sensitive important stuff 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 ivory tower and you know this is how I believe you build good safe robust useful technology and products and I think is a great a great learning of y cominator 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 gonna solve it by disconnecting yourself from reality.

萨姆·奥特曼：为什么从现在开始会变得更难？Sam Altman: Why does it get harder from here?

David Senra：因为我们当中最聪明的人，差不多也就和世界上最聪明的模型一样聪明。而这种情况现在就要反转了。David Senra: Because 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.

萨姆·奥特曼：是的，这是一个方向。我觉得没错。我认为这些模型的能力实在太强，而且正沿着如此陡峭的轨迹不断进步，以至于那些未知的未知或许相对而言并没有变得更难，但从绝对角度看，它们似乎更难应对。我想我们将不得不做出许多艰难决定，比如什么时候推迟开发，什么时候说：“好吧，你知道吗，咱们现在就让它接受现实检验”，或者再多等一段时间，深入研究一下。Sam Altman: Yeah. A direction. I think that's right. I think that the models are just so incredibly capable and improving on such a steep trajectory that the unknown unknowns maybe they don't get harder relatively but from an absolute perspective 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 let's contact with reality now or let's let's wait longer to really study this more.

最近和人聊天时，有件事一直让我印象很深：你知道，FAA 帮助让飞行变得极其安全。乍看之下，飞行似乎是件极其危险的事。可你大概上飞机时不会多想。当然，你知道，从人类历史的漫长历程来看，飞机出现的时间还不算长。Talking to someone recently and something that stuck in my mind is that the you know the FAA has helped make flying incredibly safe. Flying on the surface seems like this extremely dangerous thing. 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 trajectory of human history.

当然，在飞机刚出现之初，情况肯定不是这样。航空业的事故报告机制极其健全，也非常客观清醒。他们绝不会试图——你知道的——把事情轻描淡写地带过。他们想尽可能多地提取信息。And this was certainly not the case at the beginning of airplanes. They have extremely robust accident reporting, extremely cleareyed. You're never they never try to like, you know, handwave over something. They want to extract as much information as possible.

从某种意义上说，我认为，面对任何新技术，采用这种做法都很有效，而且往往没有得到足够重视。因此，当我们开始部署模型、说要把 ch 推向世界时，我们知道模型并不完美。我们知道它会产生幻觉，也知道它可能会做出其他这些事情，但我们也知道，世界必须亲身体验这项技术。我们必须学会如何让它变得安全。And in some sense I think with any new technology an approach like that works very well and is often underappreciated. So when we started deploying our models when we said we're going to put ch in the world we know the model's imperfect. we know it hallucinates we know it can do these other things but we also know that the world's got to experience this technology. We've got to learn how to make it safe.

我们必须把权力交到人们手中。我们不能只是利用它来强加我们的世界观，也不能躲进实验室里，试图想清楚所有影响——反正那也行不通，因为社会和模型会共同演进。我们必须一起参与，把它作为一个共同的成果来打造。And we got to put the power in people's hands. 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-eolve. Like we have to all do this together as this as this joint product.

然后我们会做好事故记录。出现问题时，我们会进行研究，并发布一份非常清晰的事后复盘。我们会尽可能多地吸取经验。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.

我们不仅会改进自己的技术和产品，还会努力与其他开发 AI 的人分享这些经验。我认为到目前为止，效果出乎意料地好。这也体现了科技发展史和创业公司中的一些优秀案例。关键在于，最优秀的创始人如何将全世界都变成他们的人才库。We will not only improve our own technology and products, but 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 the history of technology, good examples from startups. Deal is how the best founders turn the world into their talent pool.

十年来，我一直在研究历史上最杰出的创始人是如何做事的。他们有一个共同点：他们明白，招募和聘用最优秀的人才是最重要的优先事项。A 级人才善于识别其他 A 级人才，这也是 Ramp、Shopify、11 Labs、Uber 和 DoorDash 等顶尖公司都在使用 Deel 的原因。我认识的许多顶尖创始人都在使用 Deel 的产品后亲自投资了这家公司；他们发现，Deel 是全球最擅长为全球招聘打造基础设施的公司。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, 11 Labs, Uber and Door Dash all use deal. Many of the top founders I know have personally invested in Deal after using their product and what they discovered is that deal is the best company in the world at building infrastructure for global hiring.

Deal 将帮助您的企业在世界任何地方雇用、支付薪酬并管理员工。这样，您就能留住各地最优秀的人才，并把其余时间用于专注于自己最擅长的事：为客户创造价值。11 Labs 的创始人很好地阐述了 Deal 能为您的公司带来的价值。他说：“我们创立 11 Labs，旨在打破语言和沟通障碍。Deal 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. The founder of 11 Labs has a great description of the value deal can give your company. He said, "We built 11 Labs to break down language and communication barriers.

有了 Deal 的助力，我们就能在任何地方招聘并支持杰出人才，从而加速创新，让更多声音、故事和想法传遍世界的每个角落。超过 40,000 家企业信赖 Deal。立即访问 deal.com/enra，了解他们如何帮助你的企业。”那就是 deal.comra。对你来说，有一件事可能会让你觉得很困惑，因为我自己也觉得这完全说不通。你知道，我基本上关注的就是创业者和创业，对吧？所以我制作的所有播客都是为了帮助创业者。我很高兴其他人也会收听，但它的重点确实就是尽力服务……With deal 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. Deal is trusted by over 40,000 businesses. Learn how they can help your business today by going to deal.com/enra." that is deal.comra. One thing that has to be disorienting for you because it doesn't make any sense to me like you know essentially what I focus on is just entrepreneurs and entrepreneurship right so all the podcasts I make are for the benefit of entrepreneurs I'm glad other people listen but it's like heavily focused on just trying to serve

David Senra：我一直在努力寻找有用的信息，无论是从已故企业家的传记里，还是通过和像你这样的人交谈，让其他创业者也能从这段对话中受益，对吧？或者从我做的任何播客中获取信息。所以，很多创业者喜欢 AI 这件事倒不是重点；我想弄明白的是——你能不能帮我理清一下：人人都在用 AI，人人都讨厌 AI。这到底是怎么回事？嗯，人们总是会害怕快速的社会经济变革。David Senra: trying 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 entrepreneurs love AI but like what I'm trying to figure out like if you can help me reconcile is Everybody uses AI. Everybody hates AI. What the hell is going on there? Well, people are always afraid of like rapid socioeconomic change.

之前聊过工业革命。我喜欢，我喜欢读有关过去那些技术革命的内容。而且，人们对工业革命期间发生的变化，并不都是满怀热情、欣然接受的。我觉得，人类社会有某种内在惯性，可能是件好事。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. I think it's probably a good feature of human society that we have some built-in inertia.

我们对快速变化抱有一些怀疑。我认为，在社会动荡时期，或者出现局部混乱之类的情况时，这种态度可能会对社会有所帮助。所以，这种怀疑大概有其积极的一面。我也认为，这是人类生物特性的一部分，而我相信我们不应该总是竭力与之对抗。 我还觉得，很多从事 AI 开发的人一直在外面宣称，我们有 25% 的概率会毁灭世界；但我们还是会一马当先地推进下去，因为否则那些坏人就会先这么做。又或者，他们会说：“这东西会变得非常糟糕，明年就会有 50% 的工作岗位消失。希望你们都能挺过去。”听起来实在很可怕。作为一个领域，我们一直没能很好地向人们解释 AI 有什么好处，以及如何减轻它带来的负面影响；当然，我们也没有做好其他方面的沟通。即便有人给出过一些说法，比如“会有全民基本收入”“工作将成为可选项”之类，人们也很少讨论，为什么人们在这个世界上应该拥有更多而非更少的权力和个人自由，以及这为什么如此重要。对大多数人来说，人们能够影响自己的未来，并共同决定社会的发展方向，以及由此带来的自主权，都非常重要。我觉得 AI 领域的很多人自己能感受到这一点，但他们很少花时间思考、反省或承认这对其他人有多重要。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. 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. I also think a lot of the people building AI you know have been off saying there's a 25% chance we're going to destroy the world and yeah 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 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 personal freedom in the world not less 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 I think a lot of people in the AI field, they feel it for themselves, but they don't spend much time thinking about or reflecting on or acknowledging how important that is to other people.

所以，回到之前那个……像是 Jason 这个角色对销售推介话术的刻画——我甚至不知道之前用的那个词算不算一个词。And so to go back to that like character Jason of the sales p characterization of this characterization of the sales pitch, I don't even know if that's a word from earlier.

萨姆·奥特曼：没错。就像是：“亲爱的农民们，我们将把这些礼物赐予你们：治愈癌症的方法、物质财富，还有一些别的东西，你们懂的，还有精彩的娱乐。你们就别抱怨了。未来的所有决定都由我们来做，你们只要相信我们就好。我们会有点像独裁者。”不行，不行。Sam Altman: It is. 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 and you stop complaining and we'll make all the decisions about the future and just trust us you know we'll be bit dictators. Not good. Not good.

作为一个热爱创业者的人，也算是研究近几个世纪以来这场非凡经济奇迹如何运作的人，我认为，真正赋能人们去尝试新事物、坚持自己相信的事情，让他们有自由创办公司、发明技术、追求各种想法，并建立起促成这一切的体系，这一点我坚信不疑。即使人们从未觉得自己是创业者，也可能永远不想创办一家大公司，他们也明白这有多重要。然后，当你听到有人或明或暗地说，随着 AI 的发展，这类事情会变少，因为权力会掌握在少数人手里，但他们会做出很好的决定，让所有人都安全，我觉得这会让他们非常害怕。我还觉得，即使大多数人可能不想创办规模很大的公司，也有很多人想创办小一些的公司，而这一直都很难。as a lover of entrepreneurs and sort of like a student of what has made this incredible economic miracle of recent centuries work. 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 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 may never want to start a big company they do understand how important that is and then when you hear people kind of implicitly or explicitly saying there's going to be less of that with AI cuz a small 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.

过去要做到这一点，需要相当多的特权、运气和资源，而我们即将迎来有史以来规模最大的一波小型创业热潮。我认为 AI 正在赋能这件事。奇怪的是，不知为什么，整个行业——包括我们自己——都没有充分谈论这一点，尽管我们看到了种种迹象。这确实很棒，但我们还没有开发出足够多能推动这股浪潮的产品，不过我认为未来会看到更多这样的情况。挺有意思的，我们之前在对话快结束时谈到了托比·卢克，我想这段内容会放进这一集里。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. Now, for some reason, the field, including us, has 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. It's funny, we talked about Toby Luke earlier at the end of the conversation, and I think that's in the episode.

他说了一件我之前没想到的事。他说：“哦，对，你和我做的是同一行。”他说：“我们都在努力培养更多创业者。他在为创业者搭建基础设施，而我在为他们制作兼具教育性和启发性的播客。”你刚才说的那件事也很不可思议，我觉得在所有新兴行业中，人工智能行业可能是我见过做得最差的一个。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 podcasts for them." And the crazy thing with what you just said, it's like not only I think out of any new industry, it's not that as an industry, the AI industry, which it's doing the worst job I've probably ever seen.

我觉得其中一部分就是你们有能力走出去，谈谈自己看到的事情，并向大家普及相关知识。有一本很棒的书叫《英特尔三位一体》，讲述了英特尔的故事。之所以叫这个名字，是因为书中的三位主角是鲍勃·诺伊斯、安迪·格鲁夫和戈登·摩尔。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 this great book called the Intel Trinity. And it talks the story of Intel. And it's called Trinity because the three main players are Bob Noise, Andy Grove, and Gordon Moore.

而且他们……书里有个很棒的故事，我一直没忘。他们从发明——我想是集成电路——开始。And when they there's a great story in the book that I never forgot. they go from inventing I think the integrated circuit

公众信任与人工智能的解释说明Public Trust and Explaining AI

萨姆·奥特曼：……微处理器，他们意识到这项技术非常重要，可能会吓跑潜在客户。所以他们走了出去——那三个人停下手头的工作，走出去开始做科普。Sam Altman: to the microp processor and they realized that technology was so important and it would scare their potential customers. So they went out they stopped those three people stopped doing what they're doing and went out and started educating

David Senra：潜在客户、投资者，还有全国各地的人。他们曾经开设的课程，比当地社区大学整个课程目录里的课程还多。这就说明他们把这件事放在多么优先的位置：我们要走出去，向人们普及这项新技术。那为什么 AI 领域没人这么做呢？我是说，别找借口。David Senra: 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 top priority like we're going to get out and educate about this new technology. It's just like why isn't anybody in AI doing that? I mean, no excuses.

我们应该做得更多。我觉得我们已经尝试过类似的方案，但还没有完全做好。We should be doing more. I think we've like tried versions of this. We haven't gotten it quite right.

萨姆·奥特曼：嗯，你现在就在这么做。这就是我想跟你聊的几个原因中的第一点，因为我一直在用人工智能。我觉得它很迷人，但你的视野如此开阔，会让我的视野显得像蚂蚁的视野。你脑子里有那么多东西，我真想把它们都挖出来。就像，嘿，你掌握了这么多背景信息。Sam Altman: Well, you're doing it right now. Like, this is point 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 the view of an ant. Like you there's so much stuff in your head that I want to like get out and like, hey, you have all this context.

就像是，你在创造这种令人惊叹的技术。我很想知道其他人是怎么使用它的。其实，在聊其他人之前，我听到你刚才说了件挺有意思的事。我觉得这和你刚才说的、我们好像正在创造技术这件事有关。It's like and you're inventing this incredible technology. I would love to know how other people are using it. Actually, before we even get to other people, I heard you say something that was interesting. I think ties what you just said about kind of like we're inventing technology.

技术发展得很快，但采用它应该慢一些、深思熟虑。还有，我听你在另一个播客里说：“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？对于最新一代模型，我不想说它们已经聪明到足够了，因为我觉得我们应该始终希望它们变得更聪明，但它们确实相当聪明。而我觉得此刻更限制我的，是 AI 掌握的关于我的有用背景信息还不够多。The techn 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? With the latest generation of models, I don't want to say 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 AI has on me.

比如，我希望 AI 尽可能多地了解情况，好帮到我。我希望它能替我做那些我做不到或不想自己做的事。比如，我不会去读我们内部 Slack 上的每一条帖子，也不会去读每个客户讲述的故事，了解 Chad GBT 在哪些方面帮到了他们，或者让他们失望了。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'm not going to read every post on our internal Slack. I'm not going to go read every story a customer has to tell about where Chad GBT worked for them or failed them.

我做不到。然后还有其他一些事情，比如，我只是，你知道，我读的研究论文可能本来可以比现在多，但这很耗费脑力，你知道。不过我很希望能有一个 AI 代理，它一直在努力帮我，可以查看并理解比我能理解的更多的上下文，或者比我自己有时间或精力去处理的更多的上下文，并能运用这些背景信息，在我必须做决定时给我好的建议。所以我觉得，我们如此专注于模型智能是正确的，但在产品层面，我们还没有充分思考，给模型提供比任何人都更多的上下文，并让它为那个人的重要决策提供建议，意味着什么。我的感觉是，我们正处在一个临界点，即将看到一种与 AI 合作的截然不同的方式——在某个方面，人类就是做不到这么好。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, 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. So I think we've 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 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.

有很多非常聪明的人，但没有人能在短短几秒钟内读完数万页背景资料，还能真正准确地加以运用。而这是 AI 能做到的事情，会成为一种全新的、极好的补充。你读过所有这些传记。可能有些时候，你会隐约记得某件事；如果你能想起其中某本传记里的一个具体轶事，在你和某位创业者交谈时，恰好能帮到他，那就真的很有用了。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. 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 were talking to them.

但也许你忘了，或者记得不太准确。我自己开发了一个 AI 工具，所以我在内部使用它。你知道它是什么吗？But maybe you forgot it or maybe you don't remember it exactly right. I built my own AI tool. So I use it internally. So you know what it is?

它只用 2018 年以来的内容进行训练。我把自己用过的每一本书里的每一条笔记和每一处划线都保存到了这个数据库里，需要的时候就会搜索它。后来，你们做的那项工作发布了，我就把它也加了进去。所以它现在也用那项工作进行训练，还有我的每一条笔记、每一处划线，以及《Founders》每期节目的所有文字稿。我每天都会用这个东西来制作每一期节目。It's only trained on since 2018. I've kept every single note and highlight from every single book that I've ever used into 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 for my episodes of founders. I use this thing every single day to make every single episode.

所以我在用一个叫 Shannon 的 Claude，对吧？关于克劳德·香农的那期节目几周前出了，我记不清了，大概两三周前吧。然后我就问它各种问题，比如：“嘿，鲍勃·诺伊斯当时对此说了什么？”或者“洛克菲勒对此做了什么？”我做过那期节目，也读过那本书，还做了笔记，但我不记得了，毕竟那都是七年前的事了。太不可思议了。这就是我的意思。So I'm working on Claude called Shannon right the call 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 noise say about this or what did Rockefeller do about this and I made the episode I read the book. I took the note I don't remember because it was like seven years ago. It's incredible. This is what I mean.

我当时觉得这太棒了，真酷。I was like it's awesome. That is so cool.

David Senra：我们来聊聊你如何看待公司的运营，对吧？也就是说，你把时间都花在哪些事情上。你说你目前最关注的是获取更多算力，然后是研究，对吧？好。David Senra: Let's get into like how you think about running the company, right? So you're spending your time. You said your main focus is getting more compute and then research, right? Okay.

Sam Altman：所以，你们希望模型做到全球最好。但你怎么看，比如说，你们必须自己开发产品吗？你们现在开发了编解码器，对吧？我甚至都不清楚你们的产品线是什么样的——收入都来自哪里？Sam Altman: 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? Now you built codecs, right? What I don't even know the product lines like where's all the revenue coming from?

David Senra：其实，我觉得我们应该更像一家平台型公司，而不是产品型公司。当然，我们会开发产品，但你们有多少款产品？我们先退一步说，你们现在有多少款产品？David Senra: Actually, I think we should be more of a platform company than a product company. like we will build products of course, but how many products you have? Let's let's back up. How many products you have now?

Sam Altman：我们刚刚把 Chad GBT 和 Codex 合并到一起了。以前我们大概有 Chadbt、Codex 和 API。Sam Altman: We just merged Chad GBT and Codex together. So we used to have like Chadbt, Codex and the API.

David Senra：你知道，Codex 这个名字起得有点不太好，但它做的并不只是编程。它基本上什么工作都能做，这让人们感到困惑。David Senra: you know and Codex sort of unfortunately named but and that was not just coding. It could kind of do any kind of work which confused people.

萨姆·奥特曼：我对此感到困惑。Sam Altman: I'm confused by that.

David Senra：是的。David Senra: Yes.

Sam Altman：好的。Sam Altman: Okay.

David Senra：很多其他人也一样。我认为大多数人想要的是某种通往自己个人……的单一界面。David Senra: As were many other people. What I think most people want is the sort of like single interface to their own personal

OpenAI 的平台与商业战略OpenAI’s Platform and Business Strategy

大卫·森拉：或者他们公司的 AGI，可以在他们有任何需求时提供帮助，然后还能通过 API 在它的基础上构建他们想要的任何东西。这就是我们应该提供给全世界的平台。我们会在成本曲线、成本性能曲线上的每一个——每一个点，都提供出色的 AI，并做到最好。你知道，如果你想要非常高端的 AI 来发现科学规律，那很好。David Senra: 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. You know, you want really high-end AI to discover science, that's great.

如果你真的想要一种非常便宜的 AI，来处理海量工作——这些工作可能不需要天才级的智能——我们也能满足你。你知道，人们会从不同角度谈论这件事：一种新的公用事业、新的商品，或者你想怎么称呼都行。人们想大量使用 AI，而且希望成本低、速度快、效果好，有上下文，使用起来也顺畅。我们都能满足你。 然后还有一种单一产品，就是“我总有一天得问 AI 点什么”。也许 AI 应该主动给我提供一些东西。不过，你会拥有这样一个界面：它最初是聊天机器人，现在也有了编程智能体。我想，到了某个时候，它会让人觉得这是一个运行在你需要它运行的平台上的、更加持久的 AI 智能体。就这些。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 as a sort of people talk about different ways a new utility a new commodity whatever you want to call it like people want to use a lot of AI and they want it at a low cost and they want to be fast and to work well and have their context and be smooth we got you and then there's like a single product which is I need to ask the AI something 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.

我觉得我们不应该去打造每一种产品类别。我觉得我们不应该去尝试和所有客户竞争。我觉得我们不应该试图把整个经济都纳入囊中。我认为我们应该提供这个平台，让一亿家新企业和八十亿人以各种新方式使用它。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. 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.

所以，一种是直接面向产品的界面，另一种是 API，让人们可以随心所欲地使用它。这两者最终也会越来越融合。然后，一切都取决于人们会用它做什么、在它的基础上构建什么，等等。你犯过什么错误，才学会这一点的？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. What mistakes did you make to have to learn that?

我感觉你也不得不扼杀一些不错的想法，牺牲它们，全力以赴、专注地去追求伟大的想法。是啊，我觉得，为了追求伟大的想法而牺牲不错的想法，大概是每个创业者或企业最难学会的一课。扼杀好想法真让人难受。不管你觉得自己多么能做到这一点，大家似乎都做得很糟糕——可能这就是选择创业的人天生如此吧。I feel like you've had to kill some good ideas to and sacrifice going after the great with your full like intensity and focus. Yeah, I I think killing the good ideas, like sacrificing the good ideas to go after the great ideas 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 people, everyone like kind of maybe just by the nature of who chooses to be an entrepreneur seems to do terrible at this.

我在这方面很差劲。我知道自己做得不好。不过举例来说，去年我们停掉了 Sora。它是个不错、有趣又酷的产品，但消耗了大量算力，而且没有我们投入算力的 codeex 那么重要。我们还停掉了名为 Atlas 的网络浏览器。I'm terrible at this. I know I'm bad at this. But last year for example, we killed Sora which was you know good product and fun and cool but used a lot of compute and not as important as codeex where we put the compute. we killed our web browser called Atlas.

再说一次，我认为那是一款很棒的产品，也是最好的网页浏览器，但对我们来说，它并不像把人才投入其他领域那么重要。在算力、人力和资源都有限的情况下，我们认真权衡后得出结论：你知道吗，面向知识工作的通用智能，以及最终用于科学研究的通用智能，是我们能做的最重要的事。凡是有助于从上游构建这种智能的工作——打造我们自己的芯片、建设自己的数据中心、编写优秀的基础设施软件，当然还有训练模型——都非常重要。但接下来，我们不妨把这种 AI 作为一项服务提供出去，让人们用它来进行智力探索、开展工作、推动科学发现，也让他们在个人生活中更高效。我们应该打造一个灵活、通用的平台，而不是去做许多其他事情。which again I think it was a great product and it was the best web browser but not as important for us to focus on as somewhere else we could put that talent. in a world of limited compute, limited people, limited resources, we thought really hard and we said, you know what, the general intelligence for knowledge work and eventually for science is 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, you know, writing good infrastructure software, certainly training models, obviously that's all really important, but then let's just offer this AI 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.

任何人只要从事复杂的工作——你知道，你得是那种顶尖人物，算得上顶尖中的顶尖——如今活着的任何人都需要有人帮忙梳理思路，对吧？这非常有益。每一篇传记里都能看到这一点。回顾历史也是如此：你需要有人可以倾诉。Anybody engage in complicated work and you're got to be the, you know, top of sorts top of the list of anybody alive right now needs somebody to help organize their thoughts, right? It's extremely beneficial. You see this in every single biography. You see this history like you need somebody to talk to.

实际上有个挺有趣的故事，讲的就是这种情况能有多极端。查理·芒格有个所谓的“猩猩理论”。你听说过吗？他说，一个相当聪明的人可以走进去，坐在猩猩旁边，把自己所有的问题都告诉它，把自己心里想的所有事情都告诉它，然后你知道，猩猩显然什么也不会说，也不会说别的什么。There's there's actually a funny story of how extreme this can be. Charlie Mer has a thing called a rangutang theory. You've ever heard of this? where he said a relatively smart human could go in sit down with the regang, tell him all his problems, tell him everything's mind, and then you know the rectang obviously says nothing about nothing else.

人离开了，反而过得更好了。光是被迫把自己的想法——你知道——整理成某种结构这一点，就很有意义。显然，芒格是一位非常聪明的搭档，他在巴菲特身上发挥了这种作用。巴菲特是有史以来最聪明的人之一。The human leaves and the human's better off. Just the idea of just being forced to put your thoughts into, you know, into some kind of structure. Now, obviously with a very intelligent partner, Mer played this role for Buffett. Buffett's one of the most intelligent people ever lived.

有史以来最伟大的投资者。他仍然需要向别人梳理自己的想法。你正在经历的这些，我想不出……你，你几乎有着一种独一无二的人生经历，尤其是对你这么年轻的人来说。所以我很好奇，在你的生活中，谁扮演着这样的角色？你会去找谁，哪怕只是稍微能够体会你每天到底在经历些什么？Greatest investor of all time. Still needed to organize his thoughts to somebody else. you are going through I can't think you're you're you have almost like a singular lived experience especially for 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 remotely empathize with what the hell you're dealing with on a day-to-day basis?

这里大致分成三类。第一，很多一直在这里的研究人员，我们基本上是一起经历了这一切，并形成了一套共同的语言、直觉、标准，随便你怎么称呼它吧；而这种默契，我没能在公司外的任何人身上复制出来。谈到正在发生的事情是什么样、接下来可能会发生什么，以及技术可能会走向何方——也就是商业和世界这些问题——在我职业生涯的很长一段时间里，保罗·格雷厄姆和彼得·蒂尔一直是我学到最多东西的两个人，关于……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. when it comes to like the shape of what's happening and what might happen next and where the technology is likely to go in terms of questions of just like you know business and the world for a long time in my career Paul Graham and Peter Teal have been two of the people that I have learned the most from about

导师、YC 与创始人的经验教训Mentors, YC, and Founder Lessons

大卫·森拉：在我职业生涯的许多不同阶段，他们一直都是那两位——每当我真的遇到一个非常棘手、自己卡住了的问题时，我就会去找他们。找了很久之后，我还是没发现有其他人也具备这种能力，能够以一种极其非线性的方式思考。你知道，如果说大语言模型做的事情是预测下一个词，那么这两个人就是我最难预测下一个词会是什么的人。这是一项非常宝贵的能力。David Senra: lots of different phases 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 there I have not found anyone else after a lot of looking that has the same kind of ability to just to like think in a super nonlinear way. Like you know if what LLM 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.

你会说类似：“哦，天哪，我真的觉得自己卡住了，而且我也差不多把这些选项都想了一遍。”然后有人告诉你：“我觉得这些选项都不太好。这里有个现在看来完全显而易见、也完全正确的办法，只是你没想到——一个你在别的任何地方都没听过的全新视角。”这更像是在启发你自己思考，而不是给你明确的建议，比如“你就这么做”，对吗？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 I think none of those options are good. 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. Is this like more of like a prompt for your own thinking as opposed to like explicit advice do X for example?

Sam Altman：通常就像是，这里有一件具体的事情。Sam Altman: It's often like here is a specific thing

David Senra：真的。David Senra: really.

萨姆·奥特曼：是啊。那你能分享一个彼得的例子吗？我觉得彼得非常有意思。Sam Altman: Yeah. So what would be an example that you could share from like Peter? Peter's very fascinating to me.

David Senra：他非常引人入胜。David Senra: He is very fascinating

萨姆·奥特曼：而我，我其实想到的就是他。我刚才之所以想到这个问题，是因为你说：“我们不得不为了伟大的想法，舍弃这些好点子。我们要砍掉 Atlas。我们被计算了。”Sam Altman: and I it's it's actually who I thought of. The reason I thought of this question just now is because you're like we had to kill these good ideas for the great. We're cutting Atlas. We're computed.

我们必须专注。专注这一点，在你听他谈论专注的重要性时就显而易见。如果你有件事已经奏效，那就让它做得更好，沿着这条路继续走；抽出一小时去探索别的东西，代价太高了。你应该在已经奏效的事情上继续深入。极端之处往往蕴藏着巨大的价值。We have to focus focus is 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.

推出 Chacha BT 后，情况变得有点奇怪，因为人们其实不太清楚它能用来做什么。它的增长速度非常快，但感觉很不稳定，或者说几乎是低价值增长。人们使用它，只是因为他们对和它聊天、以及它能做些什么感兴趣。所以公司里有很多人都在说：“我们得想点别的办法，这种价值不可持续。”After we launched Chacha BT sort of 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 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 this is you know we got to figure out something else. this is not sustainable value.

我还记得和他聊过这件事，还列出了五六个我们可以转而关注的其他方向。那大概是教会成立两个月后之类的。然后他说，除了这件事正在增长——这很罕见，也很棒——以外，采取任何行动都是个明显的错误。那时它的增长速度还没有后来那么快。And remember talking to him about this like list of five or six other things that we could focus on instead. This is like maybe 2 months after church launch something like that. And he was like it's an obvious mistake to do anything about this besides the fact that it's growing which is rare and great. It was not growing as fast then as it did start after.

他就说，这东西的力量，就在于它拥有谷歌文本框那样的力量。它就像一个文本框，你可以在里面输入任何内容，它都会做对的事。而且，它并不符合硅谷当下的那套认知——你知道，你得有信息流，得有网络效应，还得有……因为我们当时这些都没有，所以大家才会担心。你知道，你得有一种……能让人们不断积累更多东西的方式。这还是在我们有记忆功能之前。He's like the power of this is the power of the Google text box. 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. This is before we had memory.

人们会积累更多上下文。人们会被锁定在里面吗？人们会拥有所有那些……他说的那些东西吗？人们追逐谷歌的商业模式已经 20 年了，而这是第一个冒出来的东西。你知道，显然，那个空白文本框对谷歌奏效了，所以你们为什么不在这方面加倍投入呢？它正在成长，非常灵活，而且你知道，除了不符合当前硅谷的主流观念之外，它具备所有的迹象。我当时就想，好吧，于是我们全力投入其中，结果非常棒。People are going to build up more context. people going to get locked in? Are people going to have all the he's 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 and I was like okay and so we went super hard ont and it was great.

他刚才说的简直是朴素的天才。有时候表达会更复杂，但刚才那就是一个非常重要的朴素天才的例子。David Senra: He's like a simple genius to what he just said. Sometimes there's like more complexness, but that was an example of very important simple genius.

Sam Altman：Paul Graham 有没有给过你什么建议、指导，或者把你往某个方向上引导？Sam Altman: What about some advice that Paul Graham or some guidance or a direction he kind of pushed you in

David Senra：你刚才说，这对很多 YC 创始人来说就像个梗：你去找他参加办公时间，他就会说：“你知道你该做什么吗？”然后像这样晃着手指。“你知道你该做什么吗？你知道你该做什么吗？”有时候，他接下来给出的建议确实很棒。David Senra: when you just said that the thing this is like a meme for many YC founders 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.

有时候，后来出现的东西很糟糕。但重要的是，那种创造力、开放的空间，还有那种“我们多尝试些东西吧”的劲头。我们谈到了迭代式部署的精神，也谈到了他如何像对待初创公司那样，推动整个初创生态进入这样一种状态：你得尽早发布 V1，早到甚至会觉得有点不好意思；就算它还有很大的改进空间也没关系，你会根据客户的反馈把它做得好得多。我甚至不记得在发布之前有没有问过他：“嘿，你觉得我们应该发布这个东西吗？”但我知道他会怎么说。我知道那时候还为时尚早。Sometimes the thing that came after that was terrible. But the important thing was there was a kind of there is a creativity and open landscape and just a you know let's try a lot of things. We talked about the spirit of iterative deployment and we talked about you know 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 v1 you're embarrass early and it doesn't matter if it's you know it could be much better you'll you'll you'll get it much better because of the feedback to customers I don't even think I asked him before we launched like hey do you think we should launch this thing but I knew what he would say. I knew it was still early.

我知道这事还是挺让人尴尬的。我也知道，正确的做法就是把它拿出来，摆到大家面前。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.

Sam Altman：等等。你对 Paul Graham 的心智模型已经完整到连这种情况都考虑到了吗？Sam Altman: So, wait. Your mental model of Paul Graham is so complete you don't even have this one case.

David Senra：对，就是那种你会说很确定的情况。David Senra: That's that's the one where you would say like there's certainty.

萨姆·奥特曼：我给你讲件好笑的事。他去世前不久，也就是去世前几个月，我去了查理·芒格家里，和他一起吃了顿饭。我问他：“你多久跟巴菲特聊一次？”他说：“从来不聊。”我说：“什么？”他说：“我们以前每天都聊，一聊就是好几个小时。巴菲特甚至只要假装拿起电话要打给我，就已经知道我要说什么了。”这当然是两人密切合作了65年之后才有的默契，不过我觉得这事特别好笑。Sam Altman: Let me tell you something funny. Right before he died, a few months before he died, I went to Charlie Monger's house and had dinner with him. And I was like, "How often do you talk to Buffet?" He goes, "Never." I go, "What?" 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.

David Senra：这太好笑了。这真是个有趣的故事。David Senra: That is hilarious. That is really a funny story.

萨姆·奥特曼：不，有很多时候我都猜不到他会说什么，这正是我认为这很有价值的原因。不过说到产品发布，比如你对自己的产品感到不好意思的时候，我知道他会说什么。那条建议……我不会说它是 YC 战术建议里最有价值的一条，但也算得上名列前茅。回顾这些年来我接触过的 YC 创始人，看看所有这些数据点，我很惊讶地发现，行动迅速、不断迭代的能力与成功的相关性竟然这么高。Sam Altman: 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 that that has been like I won't say the most valuable piece of Y of tactical YC advice, but it's been up there. I'm astonished looking back at all of my data points at YC Founders over the years how much the ability the like moving fast and being iterative correlates with success.

David Senra：好吧，你在这段对话里提 YC 提得实在太多了。我得深入聊聊这个，因为我们之前谈过。听着，我不是记者，我只是个爱好者。David Senra: Okay, you've mentioned YC way many too many times in this conversation. I have to explore this because we talked before. It's like listen, I'm not a journalist. I'm an enthusiast.

我没有一份问题清单。我就是觉得，眼前坐着一位世界级的创始人，我想知道这人脑子里到底在想什么，也想自私地从你这里挖点信息。所以说，为什么呢？我只是很惊讶，你在聊天中提到它的次数这么多。比如，去 YC 创业，然后又执掌 YC——也就是说，和他们有这样的联系——显然对你的人生产生了很大的影响。I don't have a list of questions. 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 like how impactful going through YC and then running YC so being you know affiliate with them has is clearly on your life.

你能不能详细展开说说？有支乐队当时并不算成功，专辑也没卖出去多少。但他们影响了之后所有的音乐人。Can you like you expound on this? 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 after.

萨姆·奥特曼：我想它叫乐队。Sam Altman: I think it's called the band.

David Senra：Rick Rubin确实讲过这个故事。我想，可能说的是地下丝绒乐队吧，不过你知道我想表达的意思，不管它是……David Senra: Literally the Rick Rubin told this story. I think is it might be the Velvet Underground, but you know the idea I'm getting at whether it's

Sam Altman：用这种方式谈论 YC 不太公平，因为如果按照传统指标来衡量，比如创造的市值之类的，它会是最有价值的几家科技公司之一。但 YC 对过去 20 年科技行业、初创企业和创业活动中发生的一切所产生的巨大影响，我觉得人们还只是有些了解而已。OpenAI 就是一个例子。这种影响不仅体现在我们如何将产品推向世界，也体现在我们运营研究实验室的理念上。Sam Altman: not fair to talk about YC in this way cuz YC measured by like traditional metrics and market cap created or whatever is one of the hand would be one of the handful of most valuable tech companies. 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 is only like sort of understood. Open eye 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.

我想，如果你去和许多经营这一代大型科技公司的人聊聊，即使他们没参加过 YC，他们也会讲类似的故事。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 similar stories even if they didn't go through YC.

David Senra：但那里面到底是怎么回事？YC 给你的是一套操作系统吗？因为你听到的就是，你知道，做这五件事之类的？还是说它更像是一种创建公司的理念？作为局外人，这部分让我很困惑。David Senra: But 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.

萨姆·奥特曼：我认为，我认为主要有两件事。一方面，有一些关于该做什么的操作层面的方法；但我认为，更重要的是经营公司的理念：迭代式部署、由技术人员掌舵，以及愿意在公司各个层级押注于精力充沛、雄心勃勃但经验可能较少的年轻人。另一方面，整个生态系统也发生了变化，也就是科技生态系统中的相关变化。所以，如果我们把时钟拨回2004年，再推演技术发展到2016年……Sam Altman: I think I think it's two major things. I mean 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 ambition but maybe less experience throughout all levels of the company and then it was also the change the related change to the whole ecosystem that happened in the preyc tech ecosystem. So if we, you know, ran the clock back to 2004 and then projected technology forward to 2016.

但创业生态系统的其他方面并没有改变，比如创业者意味着什么、资本如何流动、谁能经营公司，诸如此类。我认为，OpenAI 就不可能诞生。我认为，YC 给整个生态系统带来的变化——比如创始人拥有更多主动权，年轻的技术型创始人能够筹集大量资金，也能够在没有经过充分验证的履历的情况下，去做一些雄心勃勃的事情——是 OpenAI 得以诞生的关键。我认为，OpenAI 原本是不可能诞生的。but not anything else about the shape of startup ecosystem, what it meant to be an entrepreneur, how capital flowed, all of the, you know, who got to run companies, all of those things. I do not think opening would have been possible. 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, the ability to sort of like work on ambitious things without a very proven resume. I don't think opening would have been possible.

所以，这算是一个挺大的转变。这一切是否都和你认为自己从创始人转型为投资人、经过很长一段时间后又回到创始人角色有所裨益有关？这些当然也都是好处。不过我不会说自己真的经历了从创始人到投资人再到创始人的转变，因为我第一次当创始人时，结果并不太理想。就像……So, this is kind of like a big change. 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? There are all those benefits too and I wouldn't say I really went from founder to investor to founder because like the first time I was founder didn't really work out that well. It's like

David Senra：有家公司，你从失败中吸取了一些教训，但我觉得你从成功中学到的要多得多。David Senra: a company you learned some lessons from failure but I think you learned way more from success.

萨姆·奥特曼：哦，你等一下，我们不能就这么略过这个。你得再多说说这个。Sam Altman: Oh you got hold on we're not moving on from that. You got to say more about that.

David Senra：有一本……我简直不敢相信，我想那是一本伟大的俄罗斯小说。我真不好意思，竟然不知道这本书。开头大概是这么说的：所有不幸的家庭，各有各的不幸。所有幸福的家庭都一样。David Senra: There's some I can't believe I think it's an 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 the same.

山姆·奥特曼：是的。Sam Altman: Yeah.

David Senra：这就解释了为什么这个想法突然冒了出来。但我觉得这确实是真的。比如回顾自己在哪些事情上失败过，我学到了一些关于毅力和决心的普遍道理，也知道了哪些事不该做。但大多数事情都行不通。David Senra: That explains why it jumped into my mind. 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.

所以，事情行不通的原因有很多。我觉得，要理清正确的因果关系更难。当我真正做成一件事时，当我明白 Y Combinator 哪些方面确实起了作用，或者 OpenAI 哪些方面确实起了作用时，把这些经验运用到今后的事情上，对我的帮助远远大于试图从失败中吸取反面教训。所以，你当然应该尽可能多地从每一个数据点中学习。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. And when I've had something really work, when I understand like what parts of Y cominator really worked or what parts of open air really worked, trying to apply those lessons going forward has been much more helpful to me than trying to apply the anti-lesssons of what didn't work. And so, you know, you should of course learn as much as you can from every data point.

所以，要从失败中学习，也要从成功中学习。但根据我自己的经验，在尝试应用这些经验教训时，我发现从成功中学到的教训非常有用，我本该更多地运用它们。而从失败中学到的教训，要么相当笼统、其实我早就知道了，要么会妨碍其他事情。我觉得很多人大体上都是这样。So learn from the failures, learn from the successes. But in my own experience, 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.

萨姆·奥特曼：是啊。但我们不是多少已经知道该做什么、该避免什么了吗？可关键在于提醒，不断地提醒。所以，我听过的对我的另一档播客中创业者们最好的描述，就是说它是创业者的教会。仔细想想，我以前会在周日发布节目，应该重新这么做。Sam Altman: Yeah. But isn't it like we already kind of know what we should do or should we avoid, but it's like the reminder, the constant reminder. So like the best description of my other podcast founders I 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.

但说真的，我只是在说同一回事：这种性格类型贯穿历史一直都存在。只不过现在这个人在造船，而那个人以前创造了技术，他们生活在不同的时代。性格是一样的，这一点肯定没错。But it's like really I'm just telling the same it's the same personality type has appeared throughout history. It's just like now this person happens to be building ships and this person built technology but like and they live different times. Same personality. That's for sure.

我有点痴迷于那些能够长时间持续下去的事物这种想法。而且，像是……I'm kind of obsessed with this idea of things that last for a long period of time. And like

David Senra：你知道，公司——那些最好的公司——可以长盛不衰，但还是没有城市那么长久；而城市的存续时间又不如宗教长。我就在想，人造的事物里，还有什么能比宗教存在得更久呢？我想不出别的了，也许宗教就是其中之一。于是我开始研究起来。David Senra: you know companies the best companies can last a long time but not as long as cities and cities don't last cities and countries don't last as long as like religions. And I'm 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 another. So then I start studying.

我从小在一个基要派基督徒妈妈身边长大，所以一辈子都被迫去教会，后来我就开始分析：世界上的主要宗教到底有什么共同点？就像，哦，我们有一套共同的知识基础，通常是某种书籍，I grew up my mom was fundamentalist Christian. So I was forced to go to church my entire life and I just start 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,

萨姆·奥特曼：对吧？我们会定期和志同道合的信徒们见面。Sam Altman: right? We meet with like-minded fellow believers at regular intervals.

David Senra：而且我又不是每周日都去教堂。也不是说，好吧，上周我们聊了耶稣，这周咱们聊聊另一个人。不，我们会一遍又一遍地回到这些相同的书和故事上。所以，我读了你的博客，你甚至提到过 YC 结束时的某件事。David Senra: 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. It's like, no, we go back to these same books and the same stories over and over again. So, I read your blog and you even said this something about like when YC ended.

就像你一直在重复同一件事。你总是在跟他们说，然后他们就离开教会了，你知道，就这个比喻来说。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

Sam Altman：然后他们就不再做同样的事情了。就像……Sam Altman: and then they stop doing the same stuff. It's like

David Senra：重要的甚至不是这些经验教训，而是不断提醒自己这件事很重要。David Senra: it's not even the lessons. It's like the constant reminder that this is important.

萨姆·奥特曼：我非常非常赞同这一点。不过我觉得，还是应该多提醒自己去做这些事，比如多和用户交流、早点发布产品、收集更多反馈、提高招募和招聘的标准，并且加快进程。但我觉得这些积极的方面是好的。Sam Altman: I extremely strongly agree with that. 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, hold a higher bar for who you recruit and who you hire and more quickly. But it's the positives that I think are good.

大卫·森拉：你有一条推文，是我对着手机念出来的最棒的推文之一。你大概是这么说的：别去参加会议、晚宴之类的，别管其他事情。基本上就是把产品做出来，或者去卖产品。你要是不做产品，就卖不了产品。David Senra: You have one of the greatest tweets 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.

就像这就是你真正需要做的全部事情。我觉得这又回到了那种朴素的天才。所以接下来是另一件我觉得最有意思的事，因为昨天有人问我，他们说：「你通常会给我认识的每位创始人找一个历史上的对应人物。比如，哦，那家伙有点像范德比尔特；那家伙像洛克菲勒、路维格，或者这些人中的任何一个。」然后我就说：「那你觉得萨姆在历史上对应谁？」Like that's all you actually have to do. And I think it's like again it goes back to like that simple genius. 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 Vanderbilt. That guy's like Rockefeller Lewig or any of these people and I was like what's your historical equivalent for Sam?

我当时就想，没有吧，我想不出一个，因为我还不太了解他，也还不知道他是怎么想的。I was like there isn't I can't think of one cuz like I don't know him enough well like I don't understand how he thinks yet.

Sam Altman：你现在怎么看？Sam Altman: What do you think now?

David Senra：好吧，这只是八场对话中的第一场，希望我们能聊满八场。等聊到第七场时，我会告诉你，David Senra: Well this is the first of hopefully eight conversations. So I'll tell you on conversation 7,

Sam Altman：但这种情况非常罕见。我刚和 Doug Leone 聊过，他提到自己曾雇过一个人，那人后来成了 New Bank 的创始人。当时他还是一家风投公司的助理，后来离职创办了一家极为成功的公司。我当时就想：我从没听说过这种事。Doug，你听说过吗？Sam Altman: but this is very rare. I just talked to Doug Leone and he talked about one dude that he hired is the founder of New Bank and he was a like an associate and VC and then leaves and founds one of the most successful companies. I'm like I've never heard of that. Doug, have you?

他把自己的一生都奉献给了这件事。他说：“不，那是唯一的一个。”所以，这种情况确实非常罕见。大多数人会先做创始人，然后卖掉自己的公司，转而做投资者；遗憾的是，他们不会一直经营公司直到去世，而这才是我更喜欢的做法。And he dedicated his life to this. He goes, no, that's the only one. So again, 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.

我好奇的是，你刚才说自己从成功中学到的更多，对吧？你接触过那么多成功案例——在那十年，或者说十年多的时间里，你接触了多少家公司？一万家？显然，其中可能有六七家，或者十来家，是世界上最优秀的。所以，你也会把他们的成功当作学习借鉴的对象吗？不，不，当然会。我觉得人们确实会这么做。我的意思是，你是个非常出色的学习者，不过研究创业的人里也有很多相当优秀的。人们往往会试着去寻找那些真正奏效的经验，就像你说的，其实来来回回就是同一套东西，只不过出现在不同的行业里。但你得经常提醒自己这一点，而且它并不光鲜。What I'm curious about this is like when you just said I learned more from successes right? 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 were the best in the world. So like are you taking their successes as well as like instructive? No, no, to totally the and I think people do I mean you're a 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 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.

开始这次谈话时，我对这件事一无所知。我觉得现在总算稍微了解了一点。开始之前我就告诉过你，这只是为了满足我自己的求知欲。不过，哪怕是影响过你的人，比如彼得·泰勒，他肯定会说：“别犯傻了，这明明行得通，你为什么还要做别的，不继续做这件行得通的事呢？”所以肯定也有这样的例子：你会想，“嘿，我已经把这条建议给过其他创业者无数次了”，然后突然意识到：“哦，我现在根本就没在听从自己的建议。”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 where it's just like Peter Taylor saying no dummy he obviously would say no dummy this is working 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

David Senra：完全是，没错，我会举很多这方面的例子。我觉得这也很有启发性，比如，新的是什么？你当时没有得到关于什么的建议？David Senra: totally yeah I'll give many examples of that I I think it's also instructive to like what was the new What didn't you have the advice for?

萨姆·奥特曼：OpenAI 真正与我之前见过的任何事物都不同的一点是，它是 4，而且……Sam Altman: And the thing that was really different about OpenAI than anything that I had pattern matching before is it was 4 and

在没有客户信号的情况下构建 OpenAIBuilding OpenAI Without Customer Signals

萨姆·奥特曼：从我们创办公司到推出首款产品，花了1/2年的时间。Sam Altman: 1/2 years from when we started the company till we launched our first product.

David Senra：这跟 YC 的建议正好相反，对吧？David Senra: The opposite of YC advice, right?

Sam Altman：是的。Sam Altman: Yes.

David Senra：好的。David Senra: Okay.

Sam Altman：是的。管理研究团队与挑选和指导创始人有很多相似之处。我们从中学到了多少，就看我们学到了多少吧，因为我觉得我们做得非常完美。比如，在这个领域里，你没有来自客户的外部信号，只能想办法管理团队；你通常会给初创公司提出灾难性的建议——四年半都不发布产品——而你现在做的就是这个。这非常困难。我们尝试了各种办法，想找到某种信号来替代“客户到底喜不喜欢这个产品”，用来判断我们的研究是否真的奏效。其实，有一种办法确实管用：在《Dota 2》那段时间，我们尝试用强化学习来打败电子游戏中的玩家时，做了一个排行榜，人们可以看到不同想法的表现。排行榜上的数据是客观、真实的，人们也想努力往上爬。为了模拟终端用户，我们不得不尝试各种办法。这是个全新的、很有意思的问题，我完全没有处理这类问题的经验。Sam Altman: 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 cuz I 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 shipping a product for 4 and a half years. 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. One of the things that worked actually is during the 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 that was like objective and real and people wanted to like go up that but we had to try all of these things to basically like simulate end users and that was a totally interesting new problem I had no pattern matching for.

你是怎么一步步搞定的？当时是怎么想的？比如，你是怎么做到的？How did you work your way through that? What was your thinking? Like, how'd you do this?

David Senra：我们采访了不少曾在过去那些杰出的研究实验室工作过的人。你知道，Open 最初兴起时，硅谷的每个人都想创办一家研究实验室，把它当作自己的虚荣项目，我也不例外。关于贝尔实验室或施乐帕克全盛时期的书当时都很流行。人人都在谈论这件事，讨论非常热烈。David Senra: We asked a bunch of people who had been at great research labs of the past and it had been, you know, open started as sort of a time when everybody in Silicon Valley as their vanity project, including me, wanted to start a research lab. And there were all these books about the heyday of Bell Labs or Xerox Park that were very popular. Everybody was talking about this. There was a huge amount of discussion.

事实上，我甚至还看到那边有一本关于贝尔实验室的书。但真正亲身经历过、知道该怎么做的人并不多。所以我们跟 Alan K 聊了很多，也跟其他几个人聊过，听取了他们的一些建议，了解怎样才能办好一所研究实验室，其中有些建议确实非常不错。In fact, I even see one of the books over there 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 K. We talked to a handful of other people and we got some advice from them about, you know, what made a really good research lab and some of it was really good.

其中有些内容不太适用于当下。Some of it didn't translate as well to the current moment.

萨姆·奥特曼：嗯，而且你们也没有像贝尔实验室那样独立分拆出来的、巨大的垄断性印钞机。宝丽来在基本垄断了摄影领域时，做了更多研究。我刚读了本田创始人的传记，对吧？H，那家伙造出了有史以来最成功的机动车。Sam Altman: Well, you also didn't have this giant monopolistic profit printing machine like Bell Labs was spun out independently. Polaroid did a lot more research when they had essentially like a monopoly on its photography. I just read the biography of the founder of Honda, right? H the guy created the most successful motor vehicle of all time.

本田 Cub 连续销售了大约 60 年，销量达数百万辆。而他的核心观点是，他得出了与比尔实验室相同的结论：研发必须真正分离出来。它从公司中分拆出去，并由独立主体持有，就像比尔实验室一样。The Honda Cub has sold uninterrupted for like 60 years, millions of vehicles. And his whole thing he arrived the same conclusion Bill 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 Bill Labs did.

David Senra：我们没有那个。不，你没有。David Senra: We did not have that. No, you did not have

萨姆·奥特曼：回想那些早期日子，我最主要的感受就是，我一直在努力筹钱，却屡屡失败。这几乎就是我对 OpenAI 早期最深刻的记忆。那实在太费劲了，令人沮丧。我真希望我们当时也有那样一台提款机。Sam Altman: the 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 OpenAI. It so much effort, so frustrating. I wish we had some sort of cash machine like that.

David Senra：我记得，关于整个 OpenAI，我最清晰的记忆之一是，它是在2015年年底宣布成立的。但第一天是在2016年新年刚过的时候，我们12个人，或者说11个人，来到了 Greg Brockman 的公寓。那天大概是周一或周二早上9点半，差不多就是这样。就当是1月4日吧，大家都到了。这件事筹备了很久，所有人走进来时都兴奋不已。David Senra: I remember like one of my clearest memories of all of Open AI. announced coming out of 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 9:30 on a Monday or Tuesday morning, something like that. Let's say it's January 4th, and everybody's there, and it had been this like big effort, and everybody walks in with a lot of excitement.

感觉就像开学第一天之类的。然后很快，大家就环顾房间，心里大概在想，好吧，我们现在该做什么？有人说：“好，我们应该弄块白板。”你知道，格雷格就让人去找白板。白板拿来了。It feels like the first day of school, whatever. And then very quickly, people like look around the room, and they're sort of like, well, what do we do now? Someone says, "Okay, we should get a whiteboard." Greg, you know, gets someone to go off and find a whiteboard. Whiteboard comes.

再环顾一下。你知道，我们现在该怎么办？你只觉得房间里的气氛一下子垮了下来。我们谁都不知道该怎么办。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.

这并不像是要创办一家产品初创公司，也不是说“我们来打造这个产品，跟客户聊聊”。而是说，好吧，我们说过想要实现通用人工智能（AGI）。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. It's like, okay, we said we want to make AGI.

也许我们该写几篇论文。好，那就写几篇论文吧。也许我们该想些点子。好，那就想些点子吧。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.

你知道，每个人都会有那种“我完全不知道自己在干什么”的时刻。那就是我的其中一次。就是，我……你知道，我们刚刚推出了这个东西。我们谁都不知道接下来要怎么办。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 have any idea what we're going to do.

所以，我们就做了自己知道该怎么做的事，最终发现很多事情都行不通。后来，我们逐渐摸索出了一种节奏，用来做出研究方面的押注并评估这些押注。当然，我显然远非完美。但我们确实找到了一个可以逐步推进的方向，也弄清楚了如何为非常聪明的人提供他们所需的资源，以及如何确保我们不会彻底迷失方向。So, we did what we know 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. And I'll far from perfect obviously. 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.

在若干年里，经过大多混乱的摸索，我们最终取得了大部分重要发现。你知道，最初纸面上的无监督情感分析，后来变成了 GPT-1，再后来变成了 GPT，不管是多少代。关于缩放定律的研究，不仅让我们对算力有了信心，也让我们明白该如何扩大模型规模；这些认识逐渐汇聚起来，当然还有许多其他事情也是如此。在这个过程中，我们学到了诸如排行榜这种行之有效的理念。And over some number of years, mostly chaotic stumbling, we eventually made most of the big discoveries. You know, what started as the unsupervised sentiment on paper turned into GPT1 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. through this process we learned things like that idea of leaderboards that worked.

我们还了解到，外部演示的作用有多么惊人，比如向一位研究人员特别想打动的知名人士做演示。然后我们也学到了不少行不通的做法，比如设定虚假的截止日期。We also learned the incredible power of external demos 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.

Sam Altman：亲身经历那样的事情，一定会让人感到非常茫然。你们当时12个人待在一套公寓里，连白板都没有，也不知道该做什么。快进十年，如今有十亿人在使用。Sam Altman: That has to 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.

David Senra：非常奇怪的体验。David Senra: Very strange experience.

萨姆·奥特曼：你会写日记吗？Sam Altman: Do you keep a journal?

David Senra：我的第一个孩子出生时，我每天结束后回到家，就会抱着他摇着哄他入睡，跟他聊聊天什么的。所以我就得想些话题来聊。我会跟他说说我这一天过得怎么样，我们遇到了什么难题，我有点担心什么，以及发生了什么事。这样做对我来说还挺有意思的，我当时就想，这还蛮有趣的，等他长大以后，听这些也会觉得有意思。David Senra: When my kid was born, my first kid, I would like, you know, get home at the end of the day and be rocking to sleep and just like talk to a kid or whatever. So, I was just like need to come up with things to 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. It was kind of like fun for me to do and I was like this is sort of interesting and someday it'll be like interesting for him to have this.

所以我就开始给他写信，差不多每个星期天都会给他写一封。我会聊聊天，就只是说说话，然后把说的写下来。我总共也就写了八封左右吧。你有几个孩子？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. How many kids do you have?

萨姆·奥特曼：两个。Sam Altman: Two.

David Senra：好。贝索斯有一句关于创建亚马逊的精彩话语，大意是：我们努力做一些以后能讲给孙辈听、并为之自豪的事，对吧？而这些事都很难。David Senra: Okay. Bezos has this great line about building Amazon. It'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.

你当时正在给儿子写信这一事实，The fact that you were writing to your son,

萨姆·奥特曼：哎呀，Sam Altman: oh man,

大卫·森拉：继续写信。还有，如果你不这么做，我简单说一下，因为我读过不少这方面的书。通常情况下，猜猜怎么着？创始人不会在40岁时写自传。David Senra: 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.

他们到了70岁，回首往事时写下这些话，盼着自己能重来一次。太多东西都已湮没在时间的长河里。他们说来说去都是这些：“真希望我当年写过日记。”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 this. They're like, I wish I journaled.

所以，即使你不这么做，你也有足够的资源。我会写一本书，或者找人写一本书，哪怕只是供内部使用。你读过迈克尔·莫里茨的《小王国》吗？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 Mortz?

Sam Altman：我从不看书。Sam Altman: I never read.

David Senra：哦，你一定得读读。那本书讲的是苹果公司最初六年的历史，作者是迈克尔·莫茨。他居然写了那本书，是不是很不可思议？David Senra: Oh, you have to. It's like the first six year history of Apple written by Michael Mortz. Isn't it crazy that he wrote that book?

萨姆·奥特曼：他是一位才华横溢的作家。Sam Altman: He's a phenomenal writer.

戴维·森拉：一个疯狂的作家，最后竟成了有史以来最优秀的风险投资家之一，我想是这样。不过，呃，重点就是让那本书在这里结束。史蒂夫甚至还没被苹果赶出去。所以，你看到的就是实际发生的事情。David Senra: Crazy writer winds up being one of the best venture capitalists of all time, I guess. But like the you just the point is to have that book ends. Steve hasn't even been kicked out of Apple yet. So, you get like what actually happened.

你会想要这个的。你现在也许不想要，但等你到了六七十岁，肯定会想要。最有意思的是那种写给孩子的心态。你真的没法躲在任何东西后面。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. The thing that was so interesting was like the mindset of writing to your kid. Like you really can't hide behind anything.

就像，我真的很在乎孩子们会怎么看我，所以这件事发生了，你知道，感觉不太好。下周最好换种做法。这是一个非常有趣、极其有趣的心理框架。也许我会想办法再做一次。Like you're like I really care what my kids 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 interest extremely interesting mental framework. Maybe I'll find some way to do it again.

萨姆·奥特曼：哦，也许你会去做这件事。Sam Altman: Oh maybe you're going to do it.

David Senra：好，Sam，感谢你抽出时间。这次聊得太棒了，兄弟。非常感谢。David Senra: Okay Sam thanks for taking the time. This was awesome man. Appreciate it.