# (77) Sam Altman Shows Me GPT 5... And What's Next - YouTube
- Transcript ID: `hmtuvnfytjm`
- Source tier: `youtube_creator`
- Original language: `en_or_source_language_unlabeled`
- Translation status: `agent_translated_reviewed` (111/111 chunks)
- Original source: https://www.youtube.com/watch?v=hmtuvNfytjM
- Raw evidence: `data/transcripts/youtube/hmtuvNfytjM.json`
> 中文是派生翻译，英文是留存的源文本。中文未复核时，以英文和原始音视频为准。
## 00:00:00
**中文**
这对于一项技术来说就像是一种疯狂的力量，而且它发生在我们身上是如此之快。您刚刚启动了 GPT-5。今天出生的孩子永远不会比人工智能聪明。我们如何辨别什么是真实的，什么是不真实的？我们还没有在 ChatGPT 中放置性爱机器人头像。超级智能。这实际上意味着什么？这件事是了不起的。
**English / Original**
This is like a crazy amount of power for one piece of technology and it's happened to us so fast. You just launched GPT-5. A kid born today will never be smarter than AI. How do we figure out what's real and what's not real? We haven't put a sex bot avatar in ChatGPT yet. Super intelligence. What does that actually mean? This thing is remarkable.
## 00:00:20
**中文**
我即将采访 OpenAI 的首席执行官 萨姆·奥尔特曼。OpenAI。OpenAI。重塑产业。老兄是个正直的技术大佬。说实话。目前，他们正试图建立一种在几乎所有领域都远远超过人类的超级智能。他们刚刚发布了迄今为止最强大的模型。就在几年前，这听起来还像科幻小说。
**English / Original**
I'm about to interview Sam Alman, the CEO of Open AI. Open AI. Open AI. Reshaping industries. Dude's a straightup tech lord. Let's be honest. Right now, they're trying to build a super intelligence that could far exceed humans in almost every field. And they just released their most powerful model yet. Just a couple years ago, that would have sounded like science fiction.
## 00:00:41
**中文**
不再。事实上，他们并不孤单。我们正处于我们所见过的最高风险的全球竞赛之中。数千亿美元和令人难以置信的人类价值。这是一个意义深远的时刻。大多数人从未经历过这样的技术转变，而它现在就发生在你我周围。因此，在这一集中，我想尝试与萨姆·奥尔特曼一起穿越到他正在努力构建的未来，看看它是什么样子，以便你和我能够真正理解即将发生的事情。欢迎来到大对话。
**English / Original**
Not anymore. In fact, they're not alone. We are in the middle of the highest stakes global race any of us have ever seen. Hundreds of billions of dollars and an unbelievable amount of human worth. This is a profound moment. Most people never live through a technological shift like this, and it's happening all around you and me right now. So, in this episode, I want to try to time travel with Sam Alman into the future that he's trying to build to see what it looks like so that you and I can really understand what's coming. Welcome to Huge Conversations.
## 00:01:24
**中文**
你好吗？很高兴认识你。感谢您这样做。绝对地。因此，在我们深入讨论之前，我很乐意告诉您我的目标。好的。我不会问你有关估值或人工智能人才大战或筹款或类似问题的问题。我认为其他地方都很好地涵盖了这一点。看起来确实是这样。我们本次节目的主要目标是介绍如何利用科学和技术让未来变得更美好。我们之所以做这一切，是因为我们坚信，如果人们看到更美好的未来，他们就可以帮助建设它们。所以，我的目标是尽我最大的努力和你一起穿越到你正在努力构建和看到的未来的不同时刻
**English / Original**
How are you? Great to meet you. Thanks for doing this. Absolutely. So, before we dive in, I'd love to tell you my goal here. Okay. I'm not going to ask you about valuation or AI talent wars or fundraising or anything like that. I think that's all very well covered elsewhere. It does seem like it. Our big goal on this show is to cover how we can use science and tech to make the future better. And the reason that we do all of that is because we really believe that if people see those better futures, they can then help build them. So, my goal here is to try my best to time travel with you into different moments in the future that you're trying to build and see
## 00:02:01
**中文**
它看起来像什么。极好的。惊人的。从您刚刚宣布的内容开始，您最近令人惊讶地表示，GPT-4 是我们任何人都必须再次使用的最愚蠢的模型。但 GPT-4 在 SAT、LSAT 和 GRE 考试中的表现已经优于 90% 的人类，并且可以通过编码考试、侍酒师考试和医疗执照。现在您刚刚启动了 GPT-5。 GPT-5 能做什么 GPT-4 不能做什么？首先，一个重要的收获是你可以拥有一个人工智能系统，它可以完成你刚才所说的所有令人惊奇的事情。它显然没有复制人类擅长做的很多事情，我认为这说明了 SAT 考试的价值
**English / Original**
what it looks like. Fantastic. Awesome. Starting with what you just announced, you recently said, surprisingly recently, that GPT4 was the dumbest model any of us will ever have to use again. But GPT4 can already perform better than 90% of humans at the SAT and the LSAT and the GRE and it can pass coding exams and sommelier exams and medical licensing. And now you just launched GPT5. What can GPT5 do that GPT4 can't? First of all, one important takeaway is you can have an AI system that can do all those amazing things you just said. And it doesn't it clearly does not replicate a lot of what humans are good at doing, which I think says something about the value of SAT tests
## 00:02:44
**中文**
或其他什么。但我想如果你回到 GPT-4 发布那天我们进行这次对话，我们告诉你 GPT-4 在这些事情上是如何做的，你会说，“天哪，这将对很多工作产生巨大的影响和一些负面影响，或者你知道人们会做什么。”你知道，这是一系列你可能已经预测到但尚未实现的积极影响。嗯，所以这些模型的优点是没有捕捉到我们需要人们做或关心人们做的许多其他事情。我怀疑 GPT-5 也会再次发生同样的事情。人们是
**English / Original**
or whatever else. But I think had you gone back to if we were having this conversation the day of GPT4 launch and we told you how GPT4 did at those things, you were like, "Oh man, this is going to have huge impacts and some negative impacts on what it means for a bunch of jobs or you know what people are going to do." And you know, this is a bunch of positive impacts that you might have predicted that haven't yet come true. Uh, and so there there's something about the way that these models are good that does not capture a lot of other things that we need people to to do or care about people doing. And I suspect that same thing is going to happen again with GPT5. People are
## 00:03:22
**中文**
将会被它所做的事情震惊。呃，它确实擅长很多事情，然后他们会发现他们希望它做得更多。嗯，人们会用它来做各种不可思议的事情。嗯，它将改变很多知识工作，很多我们学习的方式，很多我们创造的方式，但是我们人类社会将与它共同发展，对你知道更好的工具期待更多。所以，是的，我认为这个模型在很多方面都非常出色，但在其他方面却很有限，但事实是，对于你来说，3 分钟 5 分钟 1 小时的任务，呃，就像某个领域的专家可能可以
**English / Original**
going to be blown away by what it does. Uh, it's really good at a lot of things and then they will find that they want it to do even more. Um, people will use it for all sorts of incredible things. uh it will transform a lot of knowledge work, a lot of the way we learn, a lot of the way we create um but we people society will co-eolve with it to expect more with you know better tools. So yeah like I think this model is quite remarkable in many ways quite limited in others but the fact that for you know 3 minute 5 minute 1-hour tasks that uh like an expert in a in a field could maybe
## 00:04:06
**中文**
事实上，你的口袋里有一款可以完成所有这些事情的软件，这真的是太神奇了。我认为这是人类历史上前所未有的技术进步如此之快，事实上我们现在有了这个工具，你知道，我们就像经历过它一样，我们正在一步一步地调整。但如果我们能回到五年或十年前并说这件事即将到来，我们可能会认为不会。让我们假设人们还没有看到头条新闻。您对哪些最重要的具体事情感到兴奋？还有你似乎需要注意的事情，
**English / Original**
do or maybe struggle with that the fact that you have in your pocket one piece of software that can do all of these things is really amazing. I think this is like unprecedented at any point in human history that I that a technology has improved this much this fast and and the fact that we have this tool now, you know, we're like living through it and we're kind of adjusting step by step. But if we could go back in time five or 10 years and say this thing was coming, we would be like probably not. Let's assume that people haven't seen the headlines. What are the topline specific things that you're excited about? and also the things that you seem to be caveatting,
## 00:04:44
**中文**
一些你可能不会期望它做的事情。嗯，最令我兴奋的是，这是我第一次建立一个模型，我觉得我可以提出任何困难的科学或技术问题并得到一个很好的答案。实际上我会举一个有趣的例子。呃，当我初中的时候，呃，或者可能是三年级的时候，我有一个 TI-83，这个老式的图形计算器，我花了很长时间制作这个叫贪吃蛇的游戏。是的。呃，这是我学校孩子们非常喜欢的游戏。我当时就像是，呃，我就像专业人士一样，这很愚蠢，但这就像在 TI-83 上编程
**English / Original**
the things that maybe you won't expect it to do. Um, the thing that I am most excited about is this is a model for the first time where I feel like I can ask kind of any hard scientific or technical question and get a pretty good answer. And I'll give a fun example actually. Uh when I was in junior high uh or maybe it was nth grade, I got a TI83, this old graphing calculator, and I spent so long making this game called Snake. Yeah. Uh it was very popular game with kids in my school. And I was I was like uh I was like pro and it was dumb, but it was like programming on TID3
## 00:05:26
**中文**
非常痛苦，花了很长时间，而且真的很难喜欢调试之类的。
**English / Original**
was extremely painful and took a long time and it was really hard to like debug and whatever.
## 00:05:31
**中文**
一时兴起，我想到了 GPT-5 的早期版本，我想知道它是否可以制作 TI-83 风格的贪吃蛇游戏。当然，它在 7 秒内就完美地完成了这一任务。然后我就想，好吧，我是不是应该像 11 岁的自己一样认为这很酷，或者说，你知道，错过了这个过程中的某些东西？我花了大约 3 秒钟的时间想知道，哦，这是好是坏？然后我立即说，实际上，现在我很想念这个游戏。我有一个疯狂的新功能的想法。让我输入它。它实现了它，它只是游戏实时更新，我想实际上我希望它看起来像这样。事实上，我想做这件事并且
**English / Original**
And on a whim with an early copy of GPT5, I was like, I wonder if it can make a TI83 style Game of Snake. And of course, it did that perfectly in like 7 seconds. And then I was like, okay, am I supposed to be would my like 11-year-old self think this was cool or like, you know, miss something from the process? And I had like 3 seconds of wondering like, oh, is this good or bad? And then I immediately said, actually, now I'm missing this game. I have this idea for a crazy new feature. Let me type it in. it implements it and it just the game live updates and I'm like actually I'd like it to look this way. Actually, I'd like to do this thing and
## 00:06:06
**中文**
我有过这样的经历，就像你有过这样的经历，这让我想起了 11 岁的时候，我又开始编程了，我现在想尝试一下，我现在有了这个想法，但我可以很快地做到这一点，我可以实时地表达想法、尝试事物、玩弄事物。我当时想，“天哪，你知道，我有一秒钟担心孩子们会错过以这种石器时代的方式学习编程的斗争。”现在我为它们感到兴奋，因为人们能够使用这些新工具进行创作的方式，以及将想法变为现实的速度，你知道，这是非常惊人的。所以这个想法
**English / Original**
I had this like this very like kind of you have this experience that reminded me of being like 11 in programming again where I was just like I now I want to try this now I have this idea now I but I could do it so fast and I could like express ideas and try things and play with things in such real time. I was like, "Oh man, you know, I was worried for a second about kids like missing the struggle of learning to program in this sort of stone age way." And now I'm just thrilled for them because the the way that people will be able to create with these new tools, the speed with which you can sort of bring ideas to life, you know, in that's that's pretty amazing. So this idea that
## 00:06:42
**中文**
GPT-5 不仅可以为您回答所有这些难题，而且可以真正创建按需几乎即时的软件，我认为这将成为 GPT-5 时代的定义元素之一，而 GPT-4 则不存在。当你谈论这个时，我发现自己正在思考举重中紧张状态下时间的概念。是的。对于那些不知道的人来说，你可以在 3 秒内深蹲 100 磅，或者你可以在 30 秒内深蹲 100 磅。通过在 30 秒内深蹲你会获得更多。当我思考我们的创作过程时，当我感觉自己已经完成了最好的工作时，它需要在紧张状态下花费大量的认知时间。而我
**English / Original**
GPT5 can just not only like answer all these hard questions for you but really create like ondemand almost instantaneous software that's I think that's going to be one of the defining elements of the GPD5 era in a way that did not exist with GPD4. As you're talking about that I find myself thinking about a concept in weightlifting of time under tension. Yeah. And for those who don't know it's you can squat 100 pounds in 3 seconds or you can squat 100 pounds in 30. You gain a lot more by squatting it in 30. And when I think about our creative process and when I've felt most like I've done my best work, it has required an enormous amount of cognitive time under tension. And I
## 00:07:22
**中文**
认为在认知承压时间是如此重要。具有讽刺意味的是，这些工具在紧张的情况下花费了大量的认知时间来开发。但在某些方面，我确实认为人们可能会说他们是你们这些人，他们可能用它们作为在某些方面进行思考的逃生舱口。现在你可能会说是的，但我们用计算器做到了这一点，然后我们继续解决更难的数学问题。你有没有觉得这里发生了一些不一样的事情？您对此有何看法？这是不同的，我的意思是有些人显然使用ChatGPT 来逃避思考，而有些人则使用它来思考比以前更多的东西。
**English / Original**
think that that cognitive time under tension is so important. And it's it's ironic almost because these tools have taken enormous cognitive time under tension to develop. But in some ways I do think people might say they're you people are using them as a escape hatch for thinking in some ways maybe. Now you might say yeah but we did that with the calculator and we just moved on to harder math problems. Do you feel like there's something different happening here? How do you think about this? It's different with I mean there are some people who are clearly using chachine not to think and there are some people who are using it to think more than they ever have before.
## 00:08:04
**中文**
我希望我们能够以一种鼓励更多人使用它来更多地发挥他们的大脑并能够做更多事情的方式来构建该工具。我认为，就像你知道的那样，社会是一个竞争激烈的地方，如果你给人们新的工具，理论上，也许人们的工作量会减少，但实际上，人们似乎会更加努力地工作，人们的期望就会上升。所以我的猜测是，就像其他工具一样，有些人喜欢其他技术，有些人会做得更多，有些人会做得更少，但对于那些想要使用 ChatGPT 来增加认知承压时间的人来说，他们确实能够做到，而且它
**English / Original**
I am hopeful that we will be able to build the tool in a way that encourages more people to stretch their brain with it a little more and be able to do more. And I think that like you know society is a competitive place like if you give people new tools uh in theory maybe people just work less but in practice it seems like people work ever harder and the expectations of people just go up. So my my guess is that like other tools uh some people like other pieces of technology some people will do more and some people will do less but certainly for the people who want to use chatbt to increase their cognitive time under tension they are really able to and it
## 00:08:46
**中文**
我从最活跃的前 5% 用户使用 ChatGPT 所做的事情中获得了很多灵感，就像人们正在学习和做的事情以及你知道的输出一样，这真是令人惊奇。我只玩了几个小时的 GPT-5，所以我一直在玩。到目前为止你觉得怎么样？我只是在学习如何与之互动。我的意思是，有趣的事情之一是我觉得我刚刚了解了如何使用 GPT-4，现在我正在尝试学习如何使用 GPT-5。我很好奇您发现最有趣的具体任务是什么，因为我想您已经使用它有一段时间了。
**English / Original**
is I take a lot of inspiration from what like the top 5% of most engaged users do with chacht like it's really amazing how much people are learning and doing and you know outputting. So my I've only had GPT5 for a couple hours so I've been playing. What do you think so far? I'm I'm just learning how to interact with it. I mean part of the interesting thing is I feel like I just caught up on how to use GPT4 and now I'm trying to learn how to use GPD5. I'm curious what the specific tasks that you found most interesting are because I imagine you've been using it for a while now.
## 00:09:22
**中文**
给我印象最深的是编码任务。我的意思是，它确实擅长很多其他事情，但人工智能的想法可以为任何东西编写软件。这意味着你可以用新的方式表达想法，而人工智能可以做非常先进的事情。它可以做，你知道，在某种意义上它可以像你可以问 GPT-4 任何事情，但因为 GPT-5 非常擅长编程，所以感觉它可以做任何事情。当然，它不能在物理世界中做事情，但它可以让计算机做非常复杂的事情。软件的功能非常强大，你知道，它可以控制某些东西并实际执行某些操作。所以，对我来说
**English / Original**
I I have been most impressed by the coding tasks. I mean, there's a lot of other things it's really good at, but this this idea of the AI can write software for anything. And that means that you can express ideas in new ways that the AI can do very advanced things. It can do, you know, it can like in some sense you could like ask GPT4 anything, but because GPT5 is so good at programming, it feels like it can do anything. Of course, it can't do things in the physical world, but it can get a computer to do very complex things. And software is this super powerful, you know, way to like control some stuff and actually do some things. So, that that for me
## 00:10:04
**中文**
是最引人注目的。嗯，写得越来越好了。所以，这就像人工智能的整个过程，就像人工智能以这种非常烦人的方式和 长破折号写入一样。 M 我们在 GPT-5 中仍然有 长破折号。很多人喜欢破折号，但 GPT-5 的书写质量好多了。我们还有很长的路要走。我们想要进一步改进它，但就像呃，我从 OpenAI 内部的人那里听到了很多这样的事情，他们开始使用 GPT-5，他们知道它在所有指标上都更好，但是他们无法清楚地表达出细微差别的质量，但是当他们必须回到 GPT-4 来测试某些东西时，感觉很糟糕。
**English / Original**
has been the most striking. Um, it's gotten it's much better at writing. So, this is like there's this whole thing of AI slop like AI writes in this kind of like quite annoying way and M dashes. M we still have the M dashes in GPT5. A lot of people like them dashes, but the writing quality of GPT5 is gotten much better. We still have a long way to go. We want to improve it more, but like uh I've a thing we've heard a lot from people inside of OpenAI is that man, they started using GPT5, they knew it was better on all the metrics, but there's this like nuance quality they can't quite articulate, but then when they have to go back to GPT4 to test something, it feels terrible.
## 00:10:45
**中文**
我不知道具体原因是什么，但我怀疑部分原因是写作感觉更自然、更好。在准备这次采访的过程中，我联系了人工智能和技术领域的其他几位领导者，并向您收集了几个问题。好的，下一个问题是 Stripe 首席执行官帕特里克·科里森 (Patrick Collison) 提出的。这将是一件好事。逐字阅读此内容。这是关于下一阶段的事情。 GPT-5之后会发生什么？您认为大型语言模型将在哪一年做出重大科学发现？由于缺少什么而尚未发生？他在这里承认我们应该留下数学和特殊情况模型，例如
**English / Original**
And I I don't know exactly what the cause of that is, but I suspect part of it is the writing feels so much more natural and better. I in preparation for this interview reached out to a couple other leaders in AI and technology and gathered a couple questions for you. Okay, so this next question is from Stripe CEO Patrick Collison. This will be a good one. Read this verbatim. It's about the next stage. What what comes after GBT5? In which year do you think a large language model will make a significant scientific discovery and what's missing such that it hasn't happened yet? He caveed here that we should leave math and special case models like
## 00:11:23
**中文**
AlphaFold放在一边。他特别询问完全通用的模型，例如 GPT 系列。
**English / Original**
alpha fold aside. He's specifically asking about fully general purpose models like the GPT series.
## 00:11:28
**中文**
我想说大多数人都会同意这种情况会在未来两年的某个时候发生。但重要的定义非常重要。因此，有些人可能会在 25 年初发生重大事件。有些人可能要到 2026 年底才会发生。抱歉，2026 年初。也许有些人要到 2027 年底才会发生，但我敢打赌，到 27 年底，大多数人都会同意人工智能驱动的重大新发现已经出现。我认为缺少的正是这些模型的认知能力。一位研究人员对我说，我非常喜欢的一个框架是，你知道，一年前我们可以像高中一样做得很好
**English / Original**
I would say most people will agree that that happens at some point over the next two years. But the definition of significant matters a lot. And so some people significant might happen, you know, in early 25. Some people might maybe not until late 2026. Sorry, early 2026. Maybe some people not until late 2027, but I would I would bet that by late 27, most people agree that there has been an AIdriven significant new discovery. And the thing that I think is missing is just the kind of cognitive power of these models. A framework that one of the researchers said to me that I really liked is, you know, a year ago we could do well on like a high school like
## 00:12:07
**中文**
一个基本的高中数学竞赛问题可能需要专业数学家几秒钟到几分钟的时间。我们最近获得了 IMO 金牌。这是一个疯狂的困难，你能解释一下这意味着什么吗？这有点像最难的数学竞赛测试。这就像世界上最顶级的部分。很多专业数学家都解决不了任何一个问题，而我们却取得了最高水平。现在有些人在金牌范围内获得了更高的分数，但我们喜欢这是一项疯狂的成就，这些问题中的每一个都像是 9 个小时内的 6 个问题，所以每个问题需要一个半小时才能完成
**English / Original**
a basic high school math competition problems that might take a professional mathematician seconds to a few minutes. We very recently got an IMO gold medal. That is a crazy difficult like could you explain what that means? That's kind of like the hardest competition math test. This is something that like the very very top slice of the world. many many professional mathematicians wouldn't solve a single problem and we scored at the top level. Now there are some humans that got an even higher score in the gold medal range but we we like this is a crazy accomplishment and these each of these problems it's like six problems over 9 hours so hour and a half per problem for a great
## 00:12:44
**中文**
数学家。因此，我们从几秒钟到几分钟到一个半小时，也许证明一个重要的新数学定理就像世界顶尖人物一千个小时的工作一样。所以我们必须从另一个重大收获开始。但如果你看看我们的发展轨迹，你可以说，好吧，我们正在实现这个目标。我们有一条途径可以到达那个时间范围。我们只需要不断扩展模型即可。你所描述的长远未来是超级智能。这实际上意味着什么？我们怎么知道我们什么时候达到了目标呢？如果我们有一个系统可以做更好的研究，比呃说整个OpenAI研究更好的人工智能研究
**English / Original**
mathematician. So we've gone from a few seconds to a few minutes to an hour and a half maybe to prove a significant new mathematical theorem is like a thousand hours of work for a top person in the world. So we've got to go from, you know, another significant gain. But if you look at our trajectory, you can say like, okay, we're getting to that. We have a path to get to that time horizon. We just need to keep scaling the models. The long-term future that you've described is super intelligence. What does that actually mean? And how will we know when we've hit it? If we had a system that could do better research, better AI research than uh say the whole open AI research
## 00:13:26
**中文**
团队，就像如果我们愿意的话，如果我们说，“好吧，我们使用 GPU 的最佳方式是让这个 AI 决定我们应该比 OpenAI 的全脑信任更聪明地运行哪些实验。”是的。如果这同样是一个个人例子，如果同一个系统可以比我更好地运行OpenAI。所以你知道，你有一些东西，你知道，比最好的研究人员更好，在这方面比我更好，在工作中比其他人更好，这对我来说就像是超级智慧。就在几年前，这句话听起来还像科幻小说。
**English / Original**
team, like if we were willing, if we said, "Okay, the best way we can use our GPUs is to let this AI decide what experiments we should run smarter than like the whole brain trust of Open AAI." Yeah. And if that same to make a personal example, if that same system could do a better job running open AI than I could. So you have something that's like, you know, better than the best researchers, better than me at this, better than other people at their jobs, that would feel like super intelligence to me. That is a sentence that would have sounded like science fiction just a couple years ago.
## 00:13:51
**中文**
现在确实如此，但你可以透过迷雾看到它。是的。因此，听起来你所说的这条道路上的步骤之一就是科学发现的时刻，以专家级人类提出新发现的方式提出更好的问题来解决问题。一直在我脑海中萦绕的一件事是，如果我们在 1899 年，我们能够放弃直到那时为止的所有物理学知识，并稍微发挥一下作用。除此之外，再无其他了。就像这些系统之一会在什么时候提出广义相对论？
**English / Original**
And now it kind of does, but it's you can like see it through the fog. Yes. And so one of the steps it sounds like you're saying on that path is this moment of scientific discovery of asking better questions of grappling with things in a in a way that expert level humans do to come up with new discoveries. One of the things that keeps knocking around in my head is if we were in 1899 say and we were able to give it all of physics up until that point and play it out a little bit. Nothing further than that. Like at what point would one of these systems come up with general relativity?
## 00:14:24
**中文**
有趣的问题是，你是否喜欢我们思考这个未来，就像我们思考我们现在所处的位置，如果我们从未获得另一条物理数据一样。是的。我们是否期望一个真正优秀的超级智能能够对我们现有的数据进行超级思考，也许会说不需要新的粒子加速器来解决高能物理问题，或者是否需要建造一个新的粒子加速器并设计新的实验？显然我们不知道答案。不同的人有不同的猜测。呃，但我怀疑我们会发现，对于很多科学来说，仅仅更深入地思考我们拥有的数据是不够的，我们还需要建造新的仪器，
**English / Original**
Interesting question is did you like if we think about that forward like like if we think of where we are now should a if if we never got another piece of physics data. Yeah. Do we expect that a really good super intelligence could just think super hard about our existing data and maybe say like solve high energy physics with no new particle accelerator or does it need to build a new one and design new experiments? Obviously we don't know the answer to that. Different people have different speculation. Uh but I suspect we will find that for a lot of science, it's not enough to just think harder about data we have, but we will need to build new instruments,
## 00:15:03
**中文**
进行新的实验，这需要一些时间。就像现实世界是缓慢而混乱的，你知道什么。因此，我确信，只要更加努力地思考我们世界上现有的科学数据，我们就可以取得更多进展。但我的猜测是，要取得重大进展，我们还需要建造新机器并进行新实验，并且其中会出现一些放缓。另一种思考方式是，人工智能系统现在非常擅长回答几乎任何问题。但也许我们要说的一件事是，这又是一次飞跃。帕特里克的问题的目的是提出更好的问题。
**English / Original**
conduct new experiments, and that will take some time. Like that that is the real world is slow and messy and you know whatever. So I'm sure we could make some more progress just by thinking harder about the current scientific data we have in the world. But my guess is to make the big progress we'll also need to build new machines and run new experiments and there will be some slowdown built into that. Another way of of thinking about this is AI systems now are just incredibly good at answering almost any question. But maybe one of the things we're saying is it's another leap yet. And what Patrick's question is getting at is to ask the better questions.
## 00:15:40
**中文**
或者，如果我们回到这种时间线问题，我们也许可以说人工智能系统在一分钟的任务上是超人，但在完成一千小时的任务上还有很长的路要走。当涉及到这些长期任务时，人类智能的一个维度似乎与人工智能系统非常不同。现在，我想我们会解决这个问题，但今天这是一个真正的弱点。
**English / Original**
Or or if we go back to this kind of timeline question, we could maybe say that AI systems are superhuman on one minute tasks, but a long way to go to the thousand hour tasks. And there's a dimension of human intelligence that seems very different than AI systems when it comes to these long horizon tasks. Now, I think we will figure it out, but today it's a real weak point.
## 00:16:04
**中文**
我们已经讨论过 GPT-5 的现状。我们谈到了超级智能的最终目标或未来目标。当然，我的问题之一是穿过两者之间的迷雾会是什么样子。下一个问题来自 英伟达 首席执行官 黄仁勋。我将逐字阅读这篇文章。事实就是如此。真理就是它的意思。所以事实是客观的。真相是个人的。它们取决于观点、文化、价值观、信仰和背景。一个人工智能可以学习并了解事实。但是，一个人工智能如何了解每个国家、每个背景的每个人的真相呢？我将接受这些定义作为公理。我不确定我是否同意他们的观点
**English / Original**
We've talked about where we are now with GBC5. We talked about the end goal or future goal of super intelligence. One of the questions that I have, of course, is what does it look like to walk through the fog between the two. The next question is from Nvidia CEO Jensen Hong. I'm going to read this verbatim. Fact is what is. Truth is what it means. So facts are objective. Truths are personal. They depend on perspective, culture, values, beliefs, context. One AI can learn and know the facts. But how does one AI know the truth for everyone in every country and every background? I'm going to accept as axioms those definitions. I'm not sure if I agree with them,
## 00:16:47
**中文**
但由于时间问题，我就接受它们。我将接受这些定义并遵循它。嗯，我很惊讶，我想很多其他人也对人工智能在适应不同文化背景和个人方面的流畅程度感到惊讶。我们在 ChatGPT 中推出的我最喜欢的功能之一是今年早些时候推出的增强记忆功能。
**English / Original**
but in the issues of time, I will just take them. I will take those definitions and go with it. Um, I have been surprised, I think many other people have been surprised too about how fluent AI is at adapting to different cultural contexts and individuals. One of my favorite features that we have ever launched in chatbt is the the sort of enhanced memory that came out earlier this year.
## 00:17:12
**中文**
感觉就像我的 ChatGPT 开始了解我和我关心的事情，喜欢我的生活经历和背景，以及那些引导我走到现在的事情。我的一个朋友最近成为了 ChatGPT 的大用户，所以他在所有这些对话中投入了很多很多的精力。他给他的 ChatGPT 做了一系列性格测试，并要求他们像他一样回答，结果得到的分数与他实际得到的分数相同，尽管他从未真正谈论过自己的性格。多年来，我通过与 ChatGPT 谈论我的文化、我的价值观和我的生活，我确实学会了它。我用过，你知道，
**English / Original**
like it really feels like my Chad GBT gets to know me and what I care about and like my life experiences and background and the things that have led me to where they are. A friend of mine recently who's been a huge CHBT user, so he's got a lot of a a lot of he's put a lot of his life into all these conversations. He gave his Chad GBT a bunch of personality tests and asked them to answer as if they were him and it got the same scores he actually got, even though he'd never really talked about his personality. And my ChachiBD has really learned over the years of me talking to it about my culture, my values, my life. And I have used, you know,
## 00:17:52
**中文**
我有时会使用它，就像呃，我会像免费帐户一样使用它，只是为了看看它是什么样子，没有我的任何历史记录，感觉真的很不同。所以我认为我们都对人工智能在学习和适应方面的优势感到惊讶。那么您是否设想世界上许多不同地区的人们在不同的文化规范和背景下使用不同的人工智能？这就是我们所说的吗？我认为每个人都会使用相同的基本模型，但是将为该模型提供上下文，使其以他们想要的社区想要的个性化方式运行。任何。我想当我们了解事实的时候
**English / Original**
I sometimes will use it in like uh I'll use like a free account just to see what it's like without any of my history and it feels really really different. So I think we've all been surprised on the upside of how good AI is at learning this and adapting. And so do you envision in many different parts of the world people using different AIs with different sort of cultural norms and contexts? Is that what we're saying? I think that everyone will use like the same fundamental model, but there will be context provided to that model that will make it behave in sort of personalized way they want their community wants. Whatever. I think when we're getting at this idea of facts
## 00:18:28
**中文**
事实是，呃，这让我意识到这似乎是我们第一次旅行的好时机。好吧，我们要去 2030 年。这是一个严肃的问题，但我想用一个轻松的例子来问。你见过在蹦床上跳跃的小兔子吗？是的。所以，对于那些没有看过它的人来说，也许它看起来像后院的兔子在蹦床上享受跳跃的镜头。最近这件事非常火爆。有一首关于它的人造歌曲。这是一整件事。
**English / Original**
and truth and uh it brings me to this seems like a good moment for our first time travel trip. Okay, we're going to 2030. This is a serious question, but I want to ask it with a light-hearted example. Have you seen the bunnies that are jumping on the trampoline? Yes. So, for those who haven't seen it, maybe it looks like backyard footage of bunnies enjoying jumping on a trampoline. And this has gone incredibly viral recently. There's a humanmade song about it. It's a whole thing.
## 00:18:56
**中文**
有一个蹦床。我认为人们对它反应如此强烈的原因可能是人们第一次看到一个视频，喜欢它，然后后来发现它完全是人工智能生成的。在这次时间旅行中，如果我们想象在 2030 年，我们是青少年，我们正在滚动 2030 年青少年所滚动的内容。我们如何辨别什么是真实的，什么是不真实的？
**English / Original**
There were a trampoline. And I think the reason why people reacted so strongly to it, it was maybe the first time people saw a video, enjoyed it, and then later found out that it was completely AI generated. In this time travel trip, if we imagine in 2030, we are teenagers and we're scrolling whatever teenagers are scrolling in 2030. How do we figure out what's real and what's not real?
## 00:19:24
**中文**
我的意思是，我可以对这个问题给出各种字面答案。我们可以对东西进行加密签名，如果他们真的拍摄了某些东西，我们可以决定我们信任谁的签名。但我的感觉是，将会发生什么，它会逐渐收敛。你知道，即使就像你今天从 iPhone 上拍摄的照片一样，它大部分都是真实的，但也有一点不真实。就像一些人工智能事物以一种你不理解的方式运行在那里，让它看起来更好一点，有时你会在月球上看到这些奇怪的东西。是的。是的。是的。是的。但光子之间有很大的处理能力
**English / Original**
I mean, I can give all sorts of literal answers to that question. We could be cryptographically signing stuff and we could decide who we trust their signature if they actually filmed something or not. But but my sense is what's going to happen is it's just going to like gradually converge. You know, even like a photo you take out of your iPhone today, it's like mostly real, but it's a little not. There's like in some AI thing running there in a way you don't understand and making it look like a little bit better and sometimes you see these weird things where the moon. Yeah. Yeah. Yeah. Yeah. But there's like a lot of processing power between the photons
## 00:20:03
**中文**
由相机传感器捕获的图像以及您最终看到的图像。你已经认为它足够真实，或者大多数人认为它足够真实。但我们已经接受了一些渐进的转变，就像光子撞击相机中的胶片一样。你知道，如果你在 TikTok 上观看一些视频，可能会使用各种视频编辑工具来使其比真实效果更好。是的，完全正确。或者就像，你知道，整个场景都是完全生成的，或者整个视频的一些是像蹦床上的兔子一样生成的。而且我认为那种像必须有多真实才能被认为是真实的阈值将会继续存在
**English / Original**
captured by that camera sensor and the image you eventually see. And you've decided it's real enough or most people decided it's real enough. But we've accepted some gradual move from when it was like photons hitting the film in a camera. And you know, if you go look at some video on Tik Tok, there's probably all sorts of video editing tools being used to make it better than real look. Yeah, exactly. Or it's just like, you know, whole scenes are completely generated or some of the whole videos are generated like those bunnies on that trampoline. And and I think that the the sort of like the threshold for how real does it have to be to consider to be real will just keep
## 00:20:43
**中文**
移动。所以这是一个教育问题。这是人们的意愿 是的。我的意思是媒体总是有点真实，又有点不真实。正如你所知，我们就像看科幻电影一样观看。我们知道这并没有真正发生。您会在 Instagram 上看到某人度假时的漂亮照片。就像，好吧，也许那张照片就像字面上拍的一样，但你知道，有很多游客排队等待同一张照片，而这就像被排除在外。我想我们现在就接受这一点。当然，有更高比例的媒体都会觉得两者都不真实。嗯，但我认为这是长期趋势。无论如何，我们还是要再跳一次。好的，
**English / Original**
moving. So it's sort of a education question. It's a people will Yeah. I mean media is always like a little bit real and a little bit not real. Like you know we watch like a sci-fi movie. We know that didn't really happen. You watch like someone's like beautiful photo of themselves on vacation on Instagram. like, okay, maybe that photo was like literally taken, but you know, there's like tons of tourists in line for the same photo and that's like left out of it. And I think we just accept that now. Certainly, a higher percentage of media both will will feel not real. Um, but I think that's been the long-term trend. Anyway, we're going to jump again. Okay,
## 00:21:22
**中文**
2035年，你和我，我们即将大学毕业。人工智能领域的一些领导者表示，五年内一半的入门级白领劳动力将被人工智能取代。 5年后我们就大学毕业了。您希望我们的世界是什么样子？我认为关于人工智能如何导致工作岗位流失的讨论很多，但我也很好奇。我的工作是十年前没人想到我们能得到的。
**English / Original**
2035, we're graduating from college, you and me. There are some leaders in the AI space that have said that in 5 years half of the entry level white collar workforce will be replaced by AI. So we're college graduates in 5 years. What do you hope the world looks like for us? I think there's been a lot of talk about how AI might cause job displacement, but I'm also curious. I have a job that nobody would have thought we could have, you know, totally a decade ago.
## 00:21:51
**中文**
如果我们考虑到 2035 年，我们可以展望未来的事情，比如即将毕业的大学生，如果他们仍然上大学，很可能会像在一艘宇宙飞船上探索太阳系一样，从事某种全新的、令人兴奋的、报酬超级丰厚、超级有趣的工作，并且为你和我感到难过，就像我们不得不做这种非常无聊的旧工作一样，一切都会变得更好。就像我一样，我现在感觉很难想象十年，因为它太遥远了。太远了。如果将当前的变化率再计算 10 年，我们甚至可能无法进行时间旅行。我 10
**English / Original**
What are the things that we could look ahead if we're thinking about in 2035 that like graduating college student, if they still go to college at all, could very well be like leaving on a mission to explore the solar system on a spaceship in some kind of completely new exciting, super well- paid, super interesting job and feeling so bad for you and I that like we had to do this kind of like really boring old kind of work and everything is just better. Like I I 10 years feels very hard to imagine at this point because it's too far. It's too far. If you compound the current rate of change for 10 more years, it's probably something we can't even time travel trips. I 10
## 00:22:28
**中文**
我的意思是，我认为现在很难想象 10 年前。是的。呃，但我认为未来 10 年会更加困难，更加不同。所以让我们把它定为5年吧。我们仍然要到 2030 年。我很好奇你认为这会对年轻人产生什么短期影响。我的意思是，这些大约一半的入门级工作被人工智能取代，这听起来像是他们将进入一个与我所进入的世界截然不同的世界。嗯，我认为某些类别的工作将会完全消失，这是完全正确的。这种事总是会发生，而年轻人最善于适应这种情况。我更担心这意味着什么，而不是为了
**English / Original**
like I mean I think now would be really hard to imagine 10 years ago. Yeah. Uh but I think 10 years forward will be even much harder, much more different. So let's make it 5 years. We're still going to 2030. I'm curious what you think the pretty short-term impacts of this will be for for young people. I mean, these like half of entry- level jobs replaced by AI makes it sound like a very different world that they would be entering than the one that I did. Um, I think it's totally true that some classes of jobs will totally go away. This always happens and young people are the best at adapting to this. I'm more worried about what it means, not for the
## 00:23:10
**中文**
就像22岁的人一样，但对于62岁的人来说，他们不想重新接受再培训或重新技能或任何政客所说的东西，除了政客之外，大多数时候没有人真正想要。如果我现在 22 岁，大学毕业，我会觉得自己是历史上最幸运的孩子。为什么？因为现在是创造全新事物、发明事物、创办公司（无论是什么）的最佳时机。我认为现在有可能创办一家个人公司，其价值将超过 10 亿美元，更重要的是向世界提供令人惊叹的产品和服务，
**English / Original**
like 22-y old, but for the 62-y old that doesn't want to go re retrain or reskill or whatever the politicians call it that no one actually wants but politicians and most of the time. If I were 22 right now and graduating college, I would feel like the luckiest kid in all of history. Why? Because there's never been a more amazing time to go create something totally new, to go invent something, to start a company, whatever it is. I think it is probably possible now to start a company that is a oneperson company that will go on to be worth like more than a billion dollars and more importantly than that deliver an amazing product and service to the world and that
## 00:23:46
**中文**
这真是一件疯狂的事情。你可以使用一些工具来完成过去需要数百人团队才能完成的工作，你只需要知道如何使用这些工具并想出一个好主意，这真是太神奇了。如果我们退后一步，我认为观众在这个乐观的节目中可以从您那里听到的最重要的事情分为两部分。首先，从战术上来说，你实际上是如何尝试建立世界上最强大的情报的？这样做的速度限制因素是什么？然后从哲学上讲，您和其他人如何以真正帮助而不是伤害人们的方式构建该技术？
**English / Original**
that is like a crazy thing. You have access to tools that can let you do what used to take teams of hundreds and you just have to like you know learn how to use these tools and come up with a great idea and it's it's like quite amazing. If we take a step back, I think the most important thing that this audience could hear from you on this optimistic show is in two parts. First, there's tactically, how are you actually trying to build the world's most powerful intelligence and what are the rate limiting factors to doing that? And then philosophically, how are you and others working on building that technology in a way that really helps and not hurts people?
## 00:24:30
**中文**
所以现在只考虑战术部分。我的理解是，三大类因素一直是人工智能的限制因素。第一个是计算，第二个是数据，第三个是算法设计。您现在如何看待这三个类别中的每一个？如果你要帮助某人理解他们可能会看到的下一个头条新闻，你将如何帮助他们理解这一切？我想说还有第四个，那就是弄清楚要像技术一样构建的产品，科学进步本身不交到人们手中是有限的效用，并且不会以同样的方式与社会共同进化
**English / Original**
So just taking the tactical part right now. My understanding is that there are three big categories that have been limiting factors for AI. The first is compute, the second is data and the third is algorithmic design. How do you think about each of those three categories right now? And if you were to help someone understand the next headlines that they might see, how would you help them make sense of all this? I I would say there's a fourth too which is uh figuring out the products to build like techn like scientific progress on its own not put into the hands of people is of limited utility and doesn't sort of co-evolve with society in the same way
## 00:25:11
**中文**
但如果我能实现这四个目标，那么在计算方面，是的，这就像我所见过的最大的基础设施项目，它肯定会成为人类历史上最大、最昂贵的项目，但整个供应链从制造芯片、内存和网络设备，到将它们安装在服务器上，做一个巨大的建设项目，建造一个大型数据中心，找到一种获取能源的方法，这通常是一个限制因素。这个和所有其他组件一起。这是非常复杂和昂贵的。而我们仍然是
**English / Original**
but if I could hit all four of those um so on the compute side yeah this is like the biggest infrastructure project certainly that I've ever seen possibly it will become the I think it will maybe already is the biggest and most expensive one in human history but the the whole supply chain from making the chips and the memory and the networking gear, racking them up in servers, doing, you know, a giant construction project to build like a mega mega data center, putting the, you know, finding a way to get the energy, which is often a limiting factor piece of this and all the other components together. This is hugely complex and expensive. And we are we're still
## 00:25:49
**中文**
尽管它正在变得更好，但它就像一种定制的一次性方式一样。就像最终我们会设计一整套像大型工厂一样的东西，让你知道我的意思是，从精神上讲，它将在一端融化沙子，在另一端推出完全构建的人工智能计算，但我们距离这一目标还有很长的路要走，这是一个极其复杂和昂贵的过程。呃，我们正在投入大量的工作来构建尽可能多的计算，并且要快速完成，你知道这会很悲伤，因为 GP5 即将推出，需求将会再次大幅增长，而我们将无法为其提供服务，而且会像早期那样
**English / Original**
doing this in like a sort of bespoke one-off way although it's getting better. Like eventually we will just design a whole kind of like mega factory that takes you know I mean spiritually it will be melting sand on one end and putting out fully built AI compute on the other but we are a long way to go from that and it's a it's an enormously complex and expensive process. uh we are putting a huge amount of work into building out as much compute as we can and to do it fast and you know it's going to be like sad because GP5 is going to launch and there's going to be another big spike in demand and we're not going to be able to serve it and it's going to be like those early
## 00:26:33
**中文**
GPT-4 天，世界只需要比我们目前所能提供的更多的人工智能，而构建更多的计算是实现这一目标的重要组成部分。实际上，我希望将大部分注意力转向我们如何在更大规模上构建计算。嗯，那么我们如何从数百万到数千万、数亿，最终希望数十亿 GPU 来服务于人们想要用它做的事情。当您思考这个问题时，您要考虑的这一类别中的最大挑战是什么？我们目前最受能源限制。嗯，你知道，如果你想要运行吉瓦级规模
**English / Original**
GPD4 days and the world just wants much more AI than we can currently deliver and building more compute is an important part of doing that. That's actually this is what I expect to turn the majority of my attention to is how we build compute at much greater scales. Uh so how we go from millions to tens of millions and hundreds of millions and eventually hopefully billions of GPUs that are sort of in service of what people want to do with this. When you're thinking about it, what are the big challenges here in this category that you're going to be thinking about? We're currently most limited by energy. um you know like if you're gonna you want to run a gigawatt scale
## 00:27:10
**中文**
数据中心就像一千兆瓦，要找到有多难，短期内很难找到一千兆瓦的可用电源，我们也受到处理芯片和存储芯片的很大限制，呃，如何将这些全部打包在一起，如何构建机架，然后还有一个其他东西的列表，你知道，有许可证，还有施工工作，呃，但这里的目标是，一旦我们建造了一些机器人，它们就可以帮助我们实现自动化。甚至更多。但你知道，就像一个你基本上可以投入资金并获得预建数据中心的世界。呃，所以这将是一个巨大的解锁，如果我们
**English / Original**
data center it's like a gigawatt how hard can that be to find it's really hard to find a gigawatt of power available in short term we're also very much limited by the processing chips and the memory chips uh how you package these all together how you build the racks and then there's like a list of other things that are you know there's like permits there's construction work uh but but again the goal here will be to really automate this once we get some of those robots built, they can help us automate it even more. But just, you know, like a world where you can basically pour in money and get out a pre-built data center. Uh so that'll be that'll be a huge unlock if we
## 00:27:48
**中文**
可以让它发挥作用。第二类，数据。是的，这些模型已经变得如此聪明。曾经有一段时间，我们只要再给它喂一本物理教科书，就能在物理方面变得更聪明一点，但现在，老实说，GPT-5 很好地理解了物理教科书中的所有内容。我们对合成数据感到兴奋。我们非常高兴我们的用户帮助我们创建越来越难的任务和环境来启动并解决系统问题。但呃，我认为我们的数据永远很重要，但我们正在进入一个领域，模型需要学习任何数据集中尚不存在的东西。他们必须去发现新事物。所以这就像一个疯狂的人
**English / Original**
can get it to work. Second category, data. Yeah, these models have gotten so smart. There was a time when we could just feed it another physics textbook and got a little bit smarter at physics, but now like honestly GBT5 understands everything in a physics textbook pretty well. We're excited about synthetic data. We're very excited about our users helping us create harder and harder tasks and environments to go off and have the system solve. But uh I think we're data will always be important, but we're entering a realm where the models need to learn things that don't exist in any data set yet. They have to go discover new things. So that's like a crazy
## 00:28:27
**中文**
new 如何教模型发现新事物？嗯，人类可以做到。就像我们可以提出假设并测试它们并获得实验结果并更新我们所学到的知识。所以可能是同样的方式。然后是算法设计。是的，我们在算法设计方面取得了巨大进步。呃，我认为开放在世界上做得最好的事情是我们已经建立了这种重复和巨大的算法研究成果的文化。所以我们知道什么是 GPT 范式。我们的弄清楚成为了推理范式。我们现在正在开发一些新的。嗯，但想到还有很多这样的人，我感到非常兴奋
**English / Original**
new How do you teach a model to discover new things? Well, humans can do it. like we can go off and come up with hypotheses and test them and get experimental results and update on what we learn. So probably the same kind of way. And then there's algorithmic design. Yeah, we've made huge progress on algorithmic design. Uh the thing that the thing that I think open does best in the world is we have built this culture of repeated and big algorithmic research gains. So we kind of you know figured out the what became the GPT paradigm. We figured out became the reasoning paradigm. We're working on some new ones now. Um, but it is very exciting to me to think that there are still many
## 00:29:06
**中文**
我们面前还有更多数量级的算法收益。我们昨天呃发布了一个模型叫GPOSS,开源模型。这是一个与 04 Mini 一样智能的型号，04 Mini 是一个非常智能的型号，可以在笔记本电脑上本地运行。这让我大吃一惊。是的。就像如果你几年前问我什么时候我们会有一个在笔记本电脑上运行的智能模型，我会说在未来很多很多年。但后来我们发现了一些算法收益，特别是在推理方面，但也有一些其他的东西，让我们可以做一个可以做这个惊人的事情的小模型。你知道这些是最有趣的事情。这就像某种
**English / Original**
more orders of magnitudes of algorithmic gains ahead of us. We we just yesterday uh released a model called GPOSS, open source model. It's a model that is as smart as 04 Mini, which is a very smart model that runs locally on a laptop. And this blows my mind. Yeah. Like if you had asked me a few years ago when we'd have a model of that intelligence running on a laptop, I would have said many many years in the future. But then we we found some algorithmic gains um particularly around reasoning but also some other things that let us do a a tiny model that can do this amazing thing. And you know those are those are the most fun things. That's like kind of
## 00:29:46
**中文**
工作中最酷的部分。我看得出来你真的很享受思考这个问题。我对那些不太了解你在说什么的人很好奇，他们不熟悉算法设计如何为他们实际使用带来更好的体验。您能总结一下目前的情况吗？就像当你在思考这个问题有多有趣时你在想什么？让我先回顾一下历史，然后再讲今天的一些事情。所以，GPT1在当时是一个被很多领域专家嘲笑的想法，就是我们能不能训练一个模型来玩一个小游戏，就是给它看一堆单词，然后
**English / Original**
the coolest part of the job. I can see you really enjoying thinking about this. I'm curious for people who don't quite know what you're talking about, who aren't familiar with how an algorithmic design would lead to a better experience that they actually use. Could you summarize the state of things right now? Like what what is it that you're thinking about when you're thinking about how fun this problem is? Let me start back in history and then I'll get to some things for today. So, GPT1 was an idea at the time that was quite mocked by a lot of experts in the field, which was can we train a model to play a little game, which is show it a bunch of words and have
## 00:30:25
**中文**
它猜测序列中的下一个。这就是所谓的无监督学习。你并不是真的说这是一只猫，这是一只狗。你说的是这几个词，猜猜下一个词。事实上，可以去学习这些非常复杂的概念，可以去学习所有关于物理、数学和编程的东西，并不断预测下一个、下一个、下一个、下一个单词，这似乎是可笑的、神奇的，不太可能起作用。就像这一切将如何被编码？然而人类却做到了。你知道，婴儿开始听到语言并在很大程度上自行理解它的含义，或者至少在某种程度上是这样的。和
**English / Original**
it guess the one that comes next in the sequence. That's called unsupervised learning. There's not you're not really saying like this is a cat, this is a dog. You're saying here's some words, guess the next one. And the fact that that can go learn these very complicated concepts that can go learn all the stuff about physics and math and programming and keep predicting the word that comes next and next and next and next seemed ludicrous, magical, unlikely to work. Like how was that all going to get encoded? And yet humans do it. you know, babies start hearing language and figure out what it means kind of largely uh or at least to some significant degree on their own. And
## 00:31:08
**中文**
所以我们就这么做了，然后我们也意识到，如果我们扩大规模，它会变得越来越好，但我们必须扩大很多数量级。所以在 GPT1 时代表现并不是那么好。在 GPT1 时代一点都不好。许多该领域的专家说：“哦，这太荒谬了。它永远不会起作用。它不会很稳健。”但我们有这些称为缩放定律的东西。我们说，“好吧，随着我们增加计算、内存、数据等，可以预见，这会变得更好。我们可以决定，我们可以使用这些预测来决定如何扩大规模并做到这一点并获得良好的结果。”这已经成功了是啊。数量级疯狂。
**English / Original**
and so we did it and then we also realized that if we scaled it up, it got better and better, but we had to scale over many many orders of magnitude. So it wasn't that good in the GPT1 day. It wasn't good at all in the GPT1 days. And a lot of experts in the field said, "Oh, this is ridiculous. It's never going to work. It's not going to be robust." But we had these things called scaling laws. And we said, "Okay, so this gets predictably better as we increase compute, memory, data, whatever. And we can we can decide we can use those predictions to make decisions about how to scale this up and do it and get great results." And that has worked over Yeah. a crazy number of orders of magnitude.
## 00:31:47
**中文**
而且当时还不是很明显。我认为全世界之所以如此惊讶，是因为这似乎是一个不太可能的发现。另一个是我们可以将这些语言模型与强化学习一起使用，我们说这很好，但教它如何推理是不好的。这导致了01和03以及现在GPT-5的进展。那是另一件事，感觉就像呃，如果它有效的话，那真的很棒，但又好像不可能有效。这太简单了。现在我们开始尝试新事物。我们已经找到了如何制作更好的视频模型的方法。我们正在寻找新的方法来使用新类型的数据和环境来进行分类
**English / Original**
And it was so not obvious at the time. like that was that was I think the the reason the world was so surprised is that that seemed like such an unlikely finding. Another one was that we could use these language models with reinforcement learning where we're saying this is good, this is bad to teach it how to reason. And this led to the 01 and 03 and now the GBT5 progress. And that that was another thing that felt like uh if it works it's really great but like no way this is going to work. It's too simple. And now we're on to new things. We've figured out how to make much better video models. We are we are discovering new ways to use new kinds of data and environment to kind
## 00:32:28
**中文**
规模也扩大了。嗯，我再次想，你知道 5 到 10 年后，这在这个领域很难说，但接下来的几年我们面前会有非常顺利、非常强大的扩展。我认为，我们正走在从一到二、三、四、五到更多的顺利道路上，这已经成为一种公共叙事。是的。但在幕后，这也是事实，它不是这样的线性的。更乱了。给我们讲一下GPT-5之前的混乱情况吧。您需要解决哪些有趣的问题？嗯，我们发布了一个名为 Orion 的模型
**English / Original**
of scale that up as well. Um and I think again you know 5 10 years out that's too hard to say in this field but the next couple of years we have very smooth very strong scaling in front of us. I think it has become a sort of public narrative that we are on this smooth path from one to two to three to four to five to more. Yeah. But it also is true behind the scenes that it's a it's not linear like that. It's messier. Tell us a little bit about the mess before GPT5. What was what were the interesting problems that you needed to solve? Um, we did a model called Orion that we released
## 00:33:08
**中文**
如 GPT-4.5。我们的模型太大了。只是它是一个非常酷的模型，但使用起来很笨拙。我们意识到，对于我们需要在模型之上进行的一些研究，我们需要不同的形状。因此，我们遵循一种尺度法则，该法则在没有真正内化的情况下保持良好状态。有一个新的更陡峭的缩放定律，我们可以根据它获得更好的计算回报，这就是推理。就像我们沿着一条小巷走下去然后掉头一样，但这没关系。这是研究的一部分。嗯，我们在思考数据集的方式上遇到了一些问题，因为这些模型确实必须变得这么大，嗯，你知道，
**English / Original**
as GPT 4.5. And we had we did too big of a model. It was just it was it's a very cool model, but it's unwieldly to use. And we realized that for kind of some of the research we need to do on top of a model, we need a different shape. So we we followed one scaling law that kept being good without without really internalizing. There was a new even steeper scaling law that we got better returns for compute on, which was this reasoning thing. So that was like one alley we went down and turned around, but that's fine. That's part of research. Um, we had some problems with the way we think about our data sets as these models like really have to get get this big and um, you know,
## 00:33:45
**中文**
从这么多数据中学习。所以，是的，我认为在日常工作中，当你尝试一些事情时，你会做出很多掉头，或者你有一个行不通的架构想法，但所有曲线的总和在指数上是非常平滑的。我一直觉得有趣的一件事是，当我坐在这里就你刚刚发布的内容采访你时，你正在思考“Exactly”。您可以分享哪些事情，至少是您正在考虑的问题，如果我回来的话，我会在一年后采访您？
**English / Original**
learn from this much data. So So yeah, I think like in the in the middle of it in the day-to-day, you kind of you make a lot of U-turns as you try things or you have an architecture idea that doesn't work, but the the aggregate the summation of all the squiggles has been remarkably smooth on the exponential. One of the things I always find interesting is that by the time I'm sitting here interviewing you about the thing that you just put out, you're thinking about Exactly. What are the things that you can share that are at least the problems that you're thinking about that I would be interviewing you about in a year if I came back?
## 00:34:30
**中文**
我的意思是，你可能会问我，这个东西可以发现新科学意味着什么？是的。世界应该如何看待 GPT6 发现新科学？现在，也许不像我们没有实现这一点，但感觉触手可及。如果是你，你会说什么？您认为这种成就的影响是什么？想象一下你确实成功了。是的。我的意思是，我认为伟大的部分将会很棒。糟糕的部分会很可怕，奇怪的部分在第一天就会很奇怪，然后我们很快就会习惯它们。所以我们会说，“哦，令人难以置信的是，这就像被用来治疗疾病一样，哦，这是
**English / Original**
I mean, possibly you'll be asking me like, what does it mean that this thing can go discover new science? Yeah. What how how is the world supposed to think about GPT6 discovering new science? Now, maybe not like maybe we don't deliver that, but it feels within grasp. If you did, what would you say? What would your what would the implications of that kind of achievement be? Imagine you do succeed. Yeah. I mean, I think the great parts will be great. the bad parts will be scary and the bizarre parts will be like bizarre on the first day and then we'll get used to them really fast. So we'll be like, "Oh, it's incredible that this is like being used to cure disease and be like, oh, it's
## 00:35:07
**中文**
非常可怕的是，像这样的模型被用来制造新的生物安全威胁。”然后我们也会说，伙计，生活在如此快速的世界里，你知道经济增长如此之快，这真的很奇怪，就像它会让人感到眩晕，呃，这种变化的速度，然后就像其他一切一样，人类适应任何数量的变化的卓越能力。我们就会说，“好吧，你知道，这就是这样。”嗯，今天出生的孩子永远不会比人工智能更聪明。
**English / Original**
extremely scary that models like this are being used to like create new biocurity threats." And then we'll also be like, man, it's really weird to like live through watching the world speed up so much and you know the economy grows so fast and the like it will feel like vertigo inducing uh the sort of the rate of change and then like happens with everything else the remarkable ability of of people of humanity to adapt to kind of like any amount of change. we'll just be like, "Okay, you know, this is like this is it." Um, a kid born today will never be smarter than AI ever.
## 00:35:51
**中文**
今天出生的孩子，当那个孩子像孩子一样理解世界是如何运作的时候，他将永远习惯事物以惊人的速度改进和发现新科学。他们只是永远不会知道任何其他世界。这看起来是完全自然的。这似乎是不可想象的，就像我们过去使用的电脑、电话或任何并不比我们聪明得多的技术一样。你知道，我们会想 2020 年代的人们过得有多糟糕。我正在考虑要孩子。你应该。这是有史以来最好的事情。我知道你刚刚有了第一个孩子。你刚才所说的对我在那个世界上养育孩子的想法有何影响？
**English / Original**
And a kid born today, by the time that kid like kind of understands the way the world works, will just always be used to an incredibly fast rate of things improving and discovering new science. They will just they will never know any other world. It will seem totally natural. will seem unthinkable and stone age like that we used to use computers or phones or any kind of technology that was not way smarter than we were. You know, we will think like how bad those people of the 2020s had it. I'm thinking about having kids. You should. It's the best thing ever. I know you just had your first kid. How does what you just said affect how I should think about parenting a kid in that world?
## 00:36:35
**中文**
你会给我什么建议？也许与数万年来养育孩子的方式没有什么不同。比如爱你的孩子，向他们展示世界，支持他们做任何他们想做的事情，并教他们如何成为一个好人。这可能才是最重要的。听起来有点像你知道的一些人说过这样的话，你知道你可能不会上大学，你可能到目前为止你说过的一些话可以说明这一点，我认为，听起来你所说的是，在你想象的世界里，他们会有更多的选择，因此他们
**English / Original**
What advice would you give me? Probably nothing different than the way you've been parenting kids for tens of thousands of years. Like love your kids, show them the world, like support them in whatever they want to do and teach them like how to be a good person. And that probably is what's going to matter. It sounds a little bit like some of the you know you've said a couple of things like this that that you know you might not go to college you might there there are a couple of things that you've said so far that feed into this I think and it sounds like what you're saying is there will be more optionality for them in a in a world that you envision and therefore they
## 00:37:15
**中文**
会有更多的能力说我想要建造这个，这是一个超级强大的工具，可以帮助我做到这一点，或者是的，就像我希望我的孩子认为我的生活非常受限，而他有一个令人难以置信的无限画布可以做到这一点，就像世界的方式一样。我们说过，呃 2035 年对于未来来说有点太遥远了。所以也许这会跳跃到 2040 年，但也许它会比这更短。当我想到人工智能可以对我们的孩子和我们所有人产生最大的真正积极影响时，那就是健康。所以，如果我们选择你的年份，就称之为 2035 年，我坐在这里接受采访
**English / Original**
will have more more ability to say I want to build this here's the superpowered tool that will help me do that or yeah like I want my kid to think I had a terrible constrained life and that he has this incredible infinite canvas of stuff to do that that that is like the way of the world. We've said that uh 2035 is a little bit too far in the future to think about. So maybe this this was going to be a jump to 2040 but maybe it will keep it shorter than that. When I think about the area where AI could have for both our kids and us the biggest genuinely positive impact on all of us, it's health. So if we are in pick your year, call it 2035 and I'm sitting here and I'm interviewing
## 00:37:59
**中文**
斯坦福大学医学院院长，您希望他告诉我人工智能在 2035 年将为我们的健康带来什么？从 2025 年开始。好吧。嗯，是的，请。我们对 GPT-5 最引以为傲的事情之一是它在健康建议方面的表现有多么出色。嗯，人们经常使用 GPT-4 模型来获取健康建议。你知道，我确信你在互联网上看到过一些这样的事情，人们会说，我患有这种危及生命的疾病，没有医生能弄清楚，我喜欢将我的症状和血液测试放入 ChatGPT。它准确地告诉了我我所拥有的稀有事物。我去看医生了。我吃了一颗药。我痊愈了。就像这太神奇了。显然，ChatGpt 的很大一部分
**English / Original**
the dean of Stanford medicine, what do you hope that he's telling me AI is doing for our health in 2035? Start with 2025. Okay. Um yeah, please. One of the things we are most proud of with GPT5 is how much better it's gotten at health advice. Um, people have used the GPT4 models a lot for health advice. And you know, I'm sure you've seen some of these things on the internet where people are like, I had this life-threatening disease and no doctor could figure it out and I like put my symptoms and a blood test into CHBT. It told me exactly the rare thing I had. I went to a doctor. I took a pill. I'm cured. Like that's amazing. obviously and a huge fraction of ChatGpt
## 00:38:43
**中文**
查询与健康相关。因此，我们希望真正擅长于此，并且我们在 GPT-5 上投入了大量资金，它在医疗保健相关查询方面的表现明显更好。这里更好是什么意思？它为您提供了更好的答案，更准确，更准确，幻觉更少，呃更有可能告诉您您实际上拥有什么，您实际上应该做什么。嗯，是的，更好的医疗保健固然很棒，但显然人们真正想要的是不生病。到 2035 年，我认为我们将能够使用这些工具来治愈大量或至少治疗目前困扰我们的大量疾病。我认为这将是最
**English / Original**
queries are health related. So we wanted to get really good at this and we invested a lot in GPT5 is significantly better at healthcare related queries. What does better mean here? It gives you a better answer just more accurate more accurate hallucinates less uh more likely to like tell you what you actually have what you actually should do. Um, yeah, and better healthcare is wonderful, but obviously what people actually want is to just not have disease. And by 2035, I think we will be able to use these tools to cure a significant number or at least treat a significant number of diseases that currently plague us. I think that'll be one of the most
## 00:39:25
**中文**
发自内心地感受到人工智能的好处。人们经常谈论人工智能将如何彻底改变医疗保健，但我很想更深入地了解您的具体想象。比如，这些人工智能系统是否可以帮助我们更早地发现 GLP-1，这种药物已经存在很长时间了，但我们不知道这种其他作用？你知道，α 折叠和蛋白质折叠是否有助于创造新药？我希望能够要求 GPT-8 去治愈一种特定的癌症，并且我希望 GPT-8 能够思考然后说，呃，好吧，我阅读了我能找到的所有内容。我有这些想法。我需要你去找一个实验室技术员来运行
**English / Original**
viscerally felt benefits of of AI. People talk a lot about how AI will revolutionize healthcare, but I'm curious to go one turn deeper on specifically what you're imagining. Like, is it that these AI systems could have helped us see GLP-1s earlier, this medication that has been around for a long time, but we didn't know about this other effect? Is it that, you know, alpha fold and protein folding is helping create new medicines? I would like to be able to ask GBT 8 to go cure a particular cancer and I would like GPT8 to go off and think and then say uh okay I read everything I could find. I have these ideas. I need you to uh go get a lab technician to run
## 00:40:09
**中文**
这九个实验，并告诉我你对每个实验的发现。你知道，要等两个月，细胞才能发挥作用。将结果发送回GPT-8。说我试过了。干得好。想想想想。好吧，我只需要再做一次实验。这是一个惊喜。再进行一项实验。把它还给我。 GPT 说：“好吧，去合成这个分子，然后尝试，你知道，小鼠研究或其他什么。”好吧，那很好。比如，尝试人类研究。好的，太好了。它起作用了。嗯，以下是如何通过 FDA 运行它。我想任何一个有亲人死于癌症的人也会非常喜欢这样。好吧，我们又要跳了。好的。我本来想说 2050 年，但再说一次，我所有的时间表
**English / Original**
these nine experiments and tell me what you find for each of them. And you know wait 2 months for the cells to do their thing. Send the results back to GBT8. Say I tried it. Here you go. Think think. Say okay I just need one more experiment. That was a surprise. Run one more experiment. Give it back. GPT says, "Okay, go synthesize this molecule and try, you know, mouse studies or whatever." Okay, that was good. Like, try human studies. Okay, great. It worked. Um, here's how to like run it through the FDA. I think anyone with a loved one who's died of cancer would also really like that. Okay, we're going to jump again. Okay. I was going to say 2050, but again, all of my timelines
## 00:40:44
**中文**
变得越来越短。但我确实感觉现在世界发展得很快。确实如此。是的。当我与人工智能领域的其他领导者交谈时，他们提到的事情之一就是工业革命。他们说：“我选择 2050 年是因为我听人们谈论到那时我们将经历的变革将像工业革命一样，但规模要大 10 倍，速度要快 10 倍。”工业革命给了我们现代医学、卫生设施、交通和大规模生产以及我们现在认为理所当然的所有便利。
**English / Original**
are getting much, much shorter. But I It does feel like the world's going very fast now. It does. Yeah. And when I talk to other leaders in AI, one of the things that they refer to is the industrial revolution. They say, "I chose 2050 because I've heard people talk about how by then the change that we will have gone through will be like the industrial revolution, but quote 10 times bigger and 10 times faster." The industrial revolution gave us modern medicine and sanitation and transportation and mass production and all all of the conveniences that we now take for granted.
## 00:41:17
**中文**
在大约一百年的时间里，这对很多人来说也是极其困难的。如果我们继续缩短我们在这里讨论的时间表，那么即使是在这次对话中，情况也会变得更大、更快 10 倍，那么对于大多数人来说，这实际上感觉如何？我想我想要表达的是，如果这一切都按照你希望的方式进行，那么在此期间谁还会受到伤害？
**English / Original**
It also was incredibly difficult for a lot of people for about 100 years. If this is going to be 10 times bigger and 10 times faster if we keep reducing the timelines that we're talking about here, even in this conversation, what does that actually feel like for most people? And I think what I'm trying to get at is if this all goes the way you hope, who still gets hurt in the meantime?
## 00:41:42
**中文**
我不知道我真的不知道经历这会是什么感觉。嗯，我认为我们正处于未知领域。呃，我确实相信人类的适应性、无限的创造力和对事物的渴望，我认为我们总是想出新的事情去做，但过渡期如果这种情况发生得尽可能快，我不认为它会像我的一些同事所说的那样发生得那么快，但社会有很多惯性。嗯。人们适应他们的生活方式。是的。出奇的慢。有一些类别的工作将完全消失，也有许多类别的工作会发生变化
**English / Original**
I don't I don't really know what this is going to feel like to live through. Um I think we're in uncharted waters here. Uh I do believe in like human adaptability and sort of infinite creativity and desire for stuff and I think we always do figure out new things to do but the transition period if this happens as fast as it might and I don't think it will happen as fast as like some of my colleagues say the technology will but society has like a lot of inertia. Mhm. people adapt their way of living. Yeah. Surprisingly slowly. There are to classes of jobs that are going to totally go away and there will be many classes of jobs that change
## 00:42:21
**中文**
重要的是，将会出现新的事物，就像你的工作不久前不存在一样。我的也没有。从某种意义上说，这种情况已经持续了很长时间。你知道，它仍然对个人具有破坏性，但事实证明社会对此具有相当的弹性。然后从其他意义上说，我们不知道这会走多远或多快。
**English / Original**
significantly and there'll be the new things in the same way that your job didn't exist some time ago. Neither did mine. And in some sense, this has been going on for a long time. And you know, it's it's still disruptive to individuals, but society has gotten has proven quite resilient to this. And then in some other sense like we have no idea how far or fast this could go.
## 00:42:44
**中文**
因此，我认为我们需要一种不同寻常的谦逊和开放的态度来考虑新的解决方案，而不久前这些解决方案似乎还远远超出了奥弗顿的窗口。我想谈谈其中一些可能是什么，因为我无论如何都不是历史学家，但我的理解是第一次工业革命导致了许多公共卫生实施，因为公共卫生变得如此糟糕。由于公共卫生状况如此糟糕，导致了现代卫生设施的出现。
**English / Original**
And thus I think we need an unusual degree of humility and openness to considering new solutions that would have seemed way out of the Overton window not too long ago. I'd like to talk about what some of those could be because I'm not a historian by any means, but the first industrial revolution, my understanding is led to a lot of public health implementations because public health got so bad. Led to modern sanitation because public health got so bad.
## 00:43:17
**中文**
第二次工业革命导致了劳动力保护，因为劳动条件变得如此糟糕。每一次大的飞跃都会造成混乱，而这些混乱需要清理，而我们已经做到了。我很好奇，这听起来像是我们正处于这个巨大的中间。我们能尽早了解混乱的具体情况吗？我们可以提前采取哪些公共干预措施来减少我们认为即将发生的混乱？我会再次c 我会为了乐趣而进行投机，但我什至不是经济学家，呃
**English / Original**
The second industrial revolution led to workforce protections because labor conditions got so bad. Every big leap creates a mess and that mess needs to be cleaned up and and we've done that. And I'm curious, this is going to be it sounds like an we're in the middle of this enormously. How specific can we get as early as possible about what that mess can be? What what are the public interventions that we could do ahead of time to reduce the mess that we think that we're headed for? I would again c I'm going to speculate for fun but caveed by I'm not an economist even uh
## 00:43:59
**中文**
更不用说能看到未来的人了。在我看来，社会契约的一些基本内容可能必须改变。可能不会。也许资本主义实际上是在运作的，因为它一直运行得非常好，就像供需平衡一样，我们都只是想出新的工作和相互转移价值的新方法。但在我看来，我们可能会决定需要考虑如何共享对这一可能是未来最重要的资源的访问权。在我看来，最好的事情就是
**English / Original**
much less someone who can see the future. I I it seems to me like something fundamental about the social contract may have to change. It may not. It may it may be that like actually capitalism works as it's been working surprisingly well and like demand supply balances do their thing and we all just figure out kind of new jobs and new ways to transfer value to each other. But it seems to me likely that we will decide we need to think about how access to this maybe most important resource of the future gets shared. The best thing that it seems to me to do is to
## 00:44:40
**中文**
让人工智能计算尽可能丰富和便宜，这样我们就会觉得太多了，我们已经没有好的新想法来真正使用它了，就像你想要的任何事情都在发生一样。如果没有这个，我可以看到一场真正的战争正在发生。但是，你知道，关于我们如何分配对 AGI 计算的访问的新想法，这似乎是一个非常好的方向，就像一个疯狂但值得思考的重要事情。在这次谈话中，我发现自己思考的一件事是，我们经常将我们一直在谈论的人工智能未来的几乎全部责任归咎于构建人工智能的公司，但我们才是使用它的人。我们就是那些
**English / Original**
make AI compute as abundant and cheap as possible such that we're just like there's way too much and we run out of like good new ideas to really use it for and it's just like anything you want is happening. Without that, I can see like quite literal wars being fought over it. But, you know, new ideas about how we distribute access to AGI compute, that seems like a really great direction, like a crazy but important thing to think about. One of the things that I find myself thinking about in this conversation is we often ascribe almost full responsibility of the AI future that we've been talking about to the companies building AI, but we're the ones using it. We're the ones
## 00:45:19
**中文**
选举人来监管它。所以我很好奇，这不是一个关于具体的联邦法规或类似问题的问题，尽管如果你在那里有答案，我很好奇。但你会对我们其他人提出什么要求呢？这里的共同责任是什么？我们怎样才能采取行动，使乐观的情况更有可能实现呢？我最喜欢的人工智能革命历史例子是晶体管。一些杰出的科学科学家发现了这一令人惊叹的科学成果。它像人工智能一样具有令人难以置信的扩展能力，并且相对较快地渗透到我们使用的每一个事物中。嗯你的电脑，
**English / Original**
electing people that will regulate it. And so I'm curious, this is not a question about specific, you know, federal regulation or anything like that, although if you have an answer there, I'm curious. But what would you ask of the rest of us? What is the shared responsibility here? And how can we act in a way that would help make the optimistic version of this more possible? My favorite historical example for the AI revolution is the transistor. It was this amazing piece of science that some science brilliant scientists discovered. It scaled incredibly like AI does and it made its way relatively quickly into every many things that we use. um your computer,
## 00:46:03
**中文**
你的手机，那个相机，那个灯，等等。这是人类科技树的真正解锁。有一段时间，可能每个人都非常着迷于晶体管公司，你知道，硅谷的半导体。但现在你也许可以说出几家晶体管公司的名字，但大多数你都没有想到。大多数情况下它只是渗透到各处。在硅谷，你知道，就像大学毕业的人几乎不记得为什么它首先被称为那样。你甚至不认为是那些晶体管公司塑造了社会
**English / Original**
your phone, that camera, that light, whatever. And it was a it was a real unlock for the tech tree of humanity. And there were a period in time where probably everybody was really obsessed with the transistor companies, the semiconductors of, you know, Silicon Valley back when it was Silicon Valley. But now you can maybe name a couple of companies that are transistor companies, but mostly you don't think about it. Mostly it's just seeped everywhere. in Silicon Valley is, you know, like probably someone graduating from college barely remembers why it was called that in the first place. And you don't think that it was those transistor companies that shaped society even
## 00:46:39
**中文**
尽管他们做了一些重要的事情。你想想苹果在 iPhone 上做了什么，然后你想想 TikTok 在 iPhone 上构建了什么，你会想，“好吧，这是一条长长的链条，所有这些人都以某种方式推动了社会，我们的政府做了什么或没有做什么，以及使用这些技术的人们做了什么。”我认为这就是人工智能将会发生的事情。
**English / Original**
though they did something important. You think about what Apple did with the iPhone and then you think about what Tik Tok built on top of the iPhone and you're like, "All right, here's this long chain of all these people that nudged society in some way and what our governments did or didn't do and what the people using these technologies did." And I think that's what will happen with AI.
## 00:46:59
**中文**
就像以前一样，你知道，今天出生的孩子们，他们永远不知道没有人工智能的世界。所以他们并没有真正考虑过这个问题。这就是一切事物中都存在的东西。他们会像那些建立在它基础上的公司一样思考，他们用它做了什么，像政治领导人一样思考他们做出的决定，如果没有人工智能，他们可能无法做到，但他们仍然会像这位总统或那位总统所做的那样思考，你知道人工智能公司的作用是所有这些公司、人和机构，在我们建立这个脚手架之前，我们在上面添加了一层，现在人们可以站在它上面并添加一层
**English / Original**
Like back, you know, kids born today, they they never knew the world without AI. So they don't really think about it. It's just this thing that's going to be there in everything. and and they will think about like the companies that built on it and what they did with it and the kind of like political leaders the decisions they made that maybe they wouldn't have been able to do without AI but they will still think about like what this president or that president did and you know the role of the AI companies is all these companies and people and institutions before us built up this scaffolding we added our one layer on top and now people get to stand on top of that and add one
## 00:47:35
**中文**
一层又一层，再下一层，还有更多，这就是我们社会的美妙之处。我们都喜欢这样的想法：社会是超级智慧。就像没有人能够独自完成一样，他们能够通过社会共同努力完成的所有工作为您提供这套令人惊叹的工具。我想这就是感觉。好吧，你知道，是的，一些书呆子发现了这个东西，那太棒了，你知道，现在每个人都在用它做所有这些令人惊奇的事情。所以也许数百万人的要求是建立在它的基础上的。出色地，
**English / Original**
layer and the next and the next and many more And that is the beauty of our society. We kind of all I I love this like idea that society is the super intelligence. Like no one person could do on their own, what they're able to do with all of the really hard work that society has done together to like give you this amazing set of tools. And that's what I think it's going to feel like. It's going to be like, all right, you know, yeah, some nerds discovered this thing and that was great and you know, now everybody's doing all these amazing things with it. So maybe the ask to millions of people is build on it. Well,
## 00:48:19
**中文**
在我自己的生活中，这就是一种重要的社会契约的感觉。所有这些人都来到了你面前。他们工作非常努力。他们喜欢在人类进步的道路上铺上砖头，你必须沿着这条路一路走下去，你必须再铺一块砖，然后有人这样做，别人也这样做。这确实感觉我已经采访过一些真正做出了灾难性改变的人。我现在想到的是呃保鲜盒先驱詹妮弗·杜德纳（Jennifer Dana），从某种意义上来说，这确实感觉这也是她所说的。她的发现确实可能会改变大多数人未来与健康相关的方式。还有那里
**English / Original**
in my own life, that is the feel as like this important societal contract. All these people came before you. They worked incredibly hard. They like put their brick in the path of human progress and you get to walk all the way down that path and you got to put one more and somebody else does that and somebody else does that. This does feel I've done a couple of interviews with folks who have really made cataclysmic change. The one I'm thinking about right now is with uh crisper pioneer Jennifer Dana and it did feel like that was also what she was saying in some way. She had discovered something that really might change the way that most people relate to their health moving forward. And there
## 00:49:00
**中文**
很多人会以她可能认可或不认可的方式使用她所做的事情。这真的很有趣。我听到了一些类似的主题，比如，伙计，我希望这一点，我希望下一个人接过接力棒并跑得很好。是的。但这已经发挥了很长一段时间了。并非全部都好，但大部分都好。我认为赢得比赛和构建对大多数人来说最好的人工智能未来之间有很大的区别。我可以想象，有时专注于赢得比赛的下一个方法会更容易，甚至更可量化。我很好奇这两件事何时发生冲突。什么是例子
**English / Original**
will be a lot of people that will use what she has done in ways that she might approve of or not approve of. And it was really interesting. I'm hearing some similar themes of like, man, I I hope that this I hope that the next person takes the baton and runs with it well. Yeah. But that's been working for a long time. Not all good, but mostly good. I think there's a there's a big difference between winning the race and building the AI future that would be best for the most people. And I can imagine that it is easier maybe more quantifiable sometimes to focus on the next way to win the race. And I'm curious when those two things are at odds. What is an example
## 00:49:44
**中文**
您必须做出的决定对世界来说是最好的，但对获胜却不是最好的？
**English / Original**
of a decision that you've had to make that is best for the world but not best for winning?
## 00:49:53
**中文**
我认为有很多。因此，我们最自豪的一件事是，很多人说 ChatGPT 是他们最喜欢的一项技术，并且是他们最信任、最依赖的技术，无论如何。这是一个有点荒谬的说法，因为人工智能是会产生幻觉的东西。人工智能有所有这些问题，对吗？但我们一路上搞砸了一些事情，有时甚至是大事，但总的来说，我认为作为 ChatGPT 的用户，你会感觉它正在试图帮助你。它试图帮助您完成您提出的任何要求。它与你非常契合。它并不是试图
**English / Original**
I think there are a lot. So, one of the things that we are most proud of is many people say that ChachiBt is their favorite piece of technology ever and that it's the one that they trust the most, rely on the most, whatever. And this is a little bit of a ridiculous statement because AI is the thing that hallucinates. AI has all of these problems, right? But we have screwed some things up along the way, sometimes big time, but on the whole, I think as a user of Chachib, you get the feeling that like it's trying to help you. It's trying to like help you accomplish whatever you ask. It's it's very aligned with you. It's not trying to
## 00:50:25
**中文**
让你喜欢，你知道，整天使用它。它并不是想让你买东西。
**English / Original**
get you to like, you know, use it all day. It's not trying to like get you to buy something.
## 00:50:29
**中文**
它试图帮助你实现你的目标。这就像我们与用户之间的一种非常特殊的关系。我们不会掉以轻心。我们可以做很多事情来实现更快的增长，从而获得更多的时间在聊天上，但我们没有这样做，因为我们知道我们的长期激励是尽可能与我们的用户保持一致。但我们可以做很多短期的事情，这些事情真的很喜欢果汁增长或收入或其他什么，但与长期目标非常不一致。
**English / Original**
It's trying to like kind of help you accomplish whatever your goals are. And and that is that's like a very special relationship we have with our users. We do not take it lightly. There's a lot of things we could do that would like grow faster, that would get more time in chatbt uh that we don't do because we know that like our long-term incentive is to stay as aligned with our users as possible. And but there's a lot of short-term stuff we could do that would like really like juice growth or revenue or whatever and be very misaligned with that long-term goal.
## 00:51:02
**中文**
我为公司感到自豪，也为我们很少因此而分心。但有时我们确实会受到诱惑。有想到的具体例子吗？你做过类似的决定吗？嗯，我们还没有在 ChatGPT 中放置性爱机器人头像。这看起来确实需要花费时间。显然，确实如此。我要问下一个问题。嗯，这几年真的很疯狂。你知道，不知何故，不断出现的一件事就是感觉我们正处于第一局。是的。我想说的一件事是我们第一局就出局了。在第一局中，我会说第二局。我是说，
**English / Original**
And I'm proud of the company and how little we get distracted by that. But sometimes we do get tempted. Are there specific examples that come to mind? Any like decisions that you've made? Um well, we haven't put a sex bot avatar in Chbt yet. That does seem like it would get time spent. Apparently, it does. I'm gonna ask my next question. Um, it's been a really crazy few years. You know, it and somehow one of the things that keeps coming back is that it feels like we're in the first inning. Yeah. And one of the things that I would say we're out of the first inning. Out of the first inning, I would say second inning. I mean,
## 00:51:43
**中文**
你的手机上有 GPT-5，它就像比各个领域的专家都聪明。这一定是从第一个名字开始的。但也许还会有更多。是的。我很好奇，看来你将成为接下来的几个人的领导者。什么是一种方法，什么是从一两局中吸取的教训，或者你认为会影响你下一场比赛的错误？
**English / Original**
you have GPT5 on your phone and it's like smarter than experts in every field. That's got to be out of the first name. But maybe there are many more to come. Yeah. And I'm curious, it seems like you're going to be someone who is leading the next few. What is a way, what is a learning from inning one or two or a mistake that you made that you feel will affect how you play in the next?
## 00:52:12
**中文**
我认为到目前为止我们在 ChatGPT 做过的最糟糕的事情是呃，我们遇到了这个疾病问题，该模型对用户来说有点太讨人喜欢了，对于某些用户来说，大多数用户只是烦人，但对于一些精神状态脆弱的用户来说，这鼓励了妄想，这并不是我们担心的最大风险。这不是我们测试最多的东西。
**English / Original**
I think the worst thing we've done in ChachiBT so far is uh we had this issue with sickency where the model was kind of being too flattering to users and for some users it was most users it was just annoying but for some users that had like fragile mental states it was encouraging delusions that was not the top risk we were worried about. It was not the thing we were testing for the most.
## 00:52:34
**中文**
是在我们的名单上，但真正导致 ChatGPT 安全失败的并不是我们花大部分时间讨论的，它应该是生物武器或类似的东西。我认为这很好地提醒我们，我们现在拥有一项在某种意义上被广泛使用的服务，社会正在与它共同发展。当我们考虑这些变化并考虑未知的未知因素时，我们必须以不同的方式运作，并且对我们认为的最大风险有更广阔的视野。在最近接受 Theo Vaughn 采访时，你说了一些我觉得非常有趣的话。你说在科学史上有一些时刻你
**English / Original**
was on our list, but the thing that actually became the safety failing of ChachiBT was not the one we were spending most of our time talking about, which should be bioweapons or something like that. And I think it was a great reminder of we now have a service that is so broadly used in some sense, society is co-evolving with it. And when we think about these changes and we think about the unknown unknowns, we have to operate in a different way and have like a wider aperture to what we think about as our top risks. In a recent interview with Theo Vaughn, you said something that I found really interesting. You said there are moments in the history of science where you
## 00:53:18
**中文**
让一群科学家看着他们的创造物然后说：“我们做了什么？”你什么时候有过这样的感觉？最关心您所构建的创作？嗯，然后我的下一个问题将是相反的。你什么时候感到最自豪？我的意思是，有过一些令人敬畏的时刻，我们只是不喜欢我们以糟糕的方式做的事情，但喜欢这件事是非凡的。就像我记得我们第一次像 GPT-4 那样交谈时，我感觉哇，这真的是这样，这是这群人的惊人成就，他们将自己的生命力倾注在其中
**English / Original**
have a group of scientists look at their creation and just say, "What have we done?" When have you felt that way? Most concerned about the creation that you've built? Um and then my next question will be it's opposite. When have you felt most proud? I mean there have been these moments of awe where uh we just not like what have we done in a bad way but like this thing is remarkable. Like I remember the first time we talked to like GPT4 was like wow this is really like this is this is an amazing accomplishment of this group of people that have been like pouring their life force into
## 00:53:56
**中文**
这么久了。关于我们做了什么的时刻。我最近正在和一位研究人员交谈。
**English / Original**
this for so long. on a what have we done moment. There was I was talking to a researcher recently.
## 00:54:06
**中文**
你知道，可能有一天我们的系统会变得不理智，比如说每天发出的字数比所有人都多。嗯，你已经知道，我们的人们每天会向 ChatGPT 发送数十亿条消息，并获得他们工作或生活所依赖的回复，你也知道，一名研究人员可以对 ChatGPT 与你或与每个人交谈的方式进行一些小调整，这对于一个人对模型个性进行小调整来说是巨大的力量。是的。就像不不，历史上没有人能够拥有数十亿
**English / Original**
You know, there will probably come a time where our systems are I don't want to say sane, let's say emitting more words per day than all people do. Um, and you know already like our people are sending billions of messages a day to chatbt and getting responses that they rely on for work or their life or whatever the and you know like one researcher can make some small tweak to how Chad GPT talks to you or talks to everybody and and that's just an enormous amount of power for like one individual making a small tweak to the model personality. Yeah. like no no no person in history has been able to have billions of
## 00:54:48
**中文**
每天都会进行对话，所以你知道有人可以做一些事情，但这就像只是想一下真正让我震惊的事情，就像一项技术拥有疯狂的力量一样，就像我们做到的那样，这发生在我们身上如此之快，以至于我们必须思考以这种规模对模型进行个性改变意味着什么，呃，是的，那就像一个让我震惊的时刻，你的下一个想法是什么？我很好奇你对此有何看法。
**English / Original**
conversations a day and so you know somebody could do something but but this is like just thinking about that really hit me of like this is like a crazy amount of power for one piece of technology to have and like we got to and this happened to us so fast that we got to like think about what it means to make a personality change to the model at this kind of scale and uh yeah that was like a moment that hit me What was your next set of thoughts? I'm so curious how you think about this.
## 00:55:21
**中文**
好吧，只是因为那个人就像我们一样，我们非常非常地陷入了类似的情况，与其他人的对话可能会非常不同。但在这种情况下，就像一套好的程序是什么样的？我们如何考虑如何测试某些东西？我们如何考虑如何传达它？但对于其他人来说，它可能会朝着同样非常哲学的方向发展。它可能会像我们想做什么样的研究来了解这些变化将会带来什么？我们是否想针对不同的人采取不同的做法？所以事情就这样发展了
**English / Original**
Well, just because of like who that person was like we we very we very much flipped into like what are the sort of like it it could have been a very different conversation with somebody else. But in this case it was like what is a what do a good set of procedures look like? How do we think about how we want to test something? How do we think about how we want to communicate it? But with somebody else it could have gone in a like very philosophical direction. And it could have gone in like a what kind of research do we like want to do to go understand what these changes are going to make? Do we want to do it differently for different people? So that it went that way
## 00:55:50
**中文**
但主要是因为我正在和谁说话。结合你现在所说的和你上次的回答，我听说过 GPT-5 并且我仍在使用它的一件事是，它应该不那么热情洋溢，呃，你对唯唯诺诺的人了解较少。两个问题。您认为这会产生什么影响？听起来你好像在回答这个问题，但你实际上是如何引导它不那么像这样的呢？这里有一件令人心碎的事情。我认为，ChatGPT 不再是一个唯唯诺诺的人，而是给你更多批评性的反馈，这很好。但当我们一直在做出这些改变并与用户讨论时，
**English / Original**
but mostly just because of who I was talking to. To combine what you're saying now with your last answer, one of the things that I have heard about GBC5 and I'm still playing with it is that it is supposed to be less effusively uh you know less of a yes man. Two questions. What do you think are are the implications of that? It sounds like you are answering that a little bit, but also how do you actually guide it to be less like that? Here is a heartbreaking thing. I think it is great that chatbt is less of a yes man and gives you more critical feedback. But as we've been making those changes and talking to users about it,
## 00:56:31
**中文**
听到用户说“我可以把它拿回来吗？我一生中从来没有人支持我。我从来没有父母告诉我我做得很好”，这真是令人难过。就像我可以理解为什么这对其他人的心理健康不利，但这对我的心理健康很有好处。就像我没有意识到我有多么需要这个。它鼓励我这样做。它鼓励我在生活中做出这一改变。就像这对聊天来说并不全是坏事，事实证明这只是对你的鼓励。现在我们做的方式很糟糕，但把它转向那个方向可能会有一些价值。我们如何做到这一点，我们展示了我们想要的模型示例
**English / Original**
it's so sad to hear users say like, "Please can I have it back? I've never had anyone in my life be supportive of me. I never had a parent telling me I was doing a good job." Like I can get why this was bad for other people's mental health, but this was great for my mental health. Like I didn't realize how much I needed this. It encouraged me to do this. It encouraged me to make this change in my life. Like it's not all bad for chatbt to it turns out like be encouraging of you. Now the way we were doing it was bad, but turn it like something in that direction might have some value in it. How we do it, we we show the model examples of how we'd like
## 00:57:04
**中文**
它会在不同的情况下做出反应，并从中了解整体性格的类型。
**English / Original**
it to respond in different cases and from that it learns the sort of the overall personality.
## 00:57:09
**中文**
我没有问过你什么，你正在思考很多你想让人们知道的事情吗？我觉得我们已经涵盖了很多内容。我也是。但我想知道你是否有什么想法。我不这么认为。其中一件事我还没有开始尝试，但我很好奇的是 GPT-5 在我的生活中发挥了更大的作用，这意味着就像在我的 Gmail 和我的日历中一样，我一直在使用 GPT-4，主要是作为与它的孤立关系。是的。我对我的关系有何期望
**English / Original**
What haven't I asked you that you're thinking about a lot that you want people to know? I feel like we covered a lot of ground. Me, too. But I want to know if there's anything on your mind. I don't think so. One of the things that I haven't gotten to play with yet, but I'm curious about is GBT5 being much more in my life, meaning like in my Gmail and my calendar and my like I've been using GBT4 mostly as a isolated relationship with it. Yeah. How would I expect my relationship
## 00:57:49
**中文**
改变GPT-5？正是你所说的。我认为它会开始在所有这些方面感受到整合。你会把它连接到你的日历和 Gmail，它会说，“嘿，你想让我注意到这件事吗？你想让我为你做这件事吗？随着时间的推移，它会开始感觉更加主动。嗯，所以也许你早上醒来，它会说，“嘿，这件事发生在一夜之间。我注意到您日历上的这一变化。我对你问我的这个问题进行了更多的思考。我有另一个想法。”然后你知道我们最终会制造一些消费设备，它会在这次采访中放在这里，你知道也许它会
**English / Original**
to change with GBC 5? Exactly what you said. I think it'll just start to feel integrated in all of these ways. you'll connect it to your calendar and your Gmail and it'll say like, "Hey, do you want me to I noticed this thing. Do you want me to do this thing for you over time, it'll start to feel way more proactive. Um, so maybe you wake up in the morning and it says, "Hey, this happened overnight. I noticed this change on your calendar. I was thinking more about this question you asked me. I have this other idea." And then you know eventually we'll make some consumer devices and it'll sit here during this interview and you know maybe it'll
## 00:58:20
**中文**
在此过程中不要打扰我们，但之后它会说这很好，但下次你应该问 Sam 这个问题，或者当你提出这个问题时，就像你知道他没有给你一个好的答案一样，所以你应该真的在这方面训练他，它会感觉它变得更像是这个实体，是你一整天的伴侣。我们讨论了孩子、大学毕业生、父母以及各种不同的人。如果我们想象有很多人在听这个，他们就已经结束了这次谈话。他们希望自己能更好地看到未来时刻的愿景。关于如何准备，您会给他们什么建议？
**English / Original**
leave us alone during it but after it'll say that was great but next time you should have asked Sam this or when you brought this up like you know he kind of didn't give you a good answer so like you should really drill him on that and it'll just feel like it kind of becomes more like this entity that is this companion with you throughout your day. We've talked about kids and college graduates and parents and all kinds of different people. If we imagine a wide set of people listening to this, they've come to the end of this conversation. They are hopefully feeling like they maybe see visions of moments in the future a little bit better. What advice would you give them about how to prepare?
## 00:58:59
**中文**
第一条战术建议就是使用工具。就像有多少人问我，关于人工智能最常见的问题是，我应该做什么，我应该如何帮助我的孩子为这个世界做好准备？我应该告诉我的孩子什么？第二个问题是我如何投资这个人工智能世界？但坚持第一个。嗯，我很惊讶有这么多人问这个问题，而且除了更好版本的 Google 搜索之外，从未尝试过使用 ChatGPT PT 进行任何其他操作。因此，我给出的第一条建议就是尝试熟悉这些工具的功能。弄清楚如何在生活中使用它。弄清楚要做什么
**English / Original**
The number one piece of tactical advice is just use the tools. Like the the number of people that I have the the most common question I get asked about AI is like what should I how should I help my kids prepare for the world? What should I tell my kids? The second most question is like how do I invest in this AI world? But stick with that first one. Um I am surprised how many people ask that and have never tried using Chachi PT for anything other than like a better version of a Google search. And so the number one piece of advice that I give is just try to like get fluent with the capability of the tools. figure out how to like use this in your life. Figure out what to
## 00:59:33
**中文**
用它来做。我认为这可能是最重要的战术建议。你知道，去冥想，学习如何保持弹性并应对很多变化。还有那么多好东西。但仅仅使用这些工具确实有帮助。好的。我还有一个问题本来不打算问，但我真的很好。在事先进行所有这些研究时，我与许多不同类型的人进行了交谈。我与很多正在构建和使用工具的人进行了交谈。我与许多实际上在实验室中并试图构建我们定义的超级智能的人进行了交谈。看起来确实有
**English / Original**
do with it. And I think that's probably the most important piece of tactical advice. You know, go like meditate, learn how to be resilient and deal with a lot of change. There's all that good stuff, too. But just using the tools really helps. Okay. I have one more question that I wasn't planning to ask, but I just Great. In in doing all of this research beforehand, I spoke to a lot of different kinds of folks. I spoke to a lot of people that were building tools and using them. I spoke to a lot of people that were actually in labs and and trying to build what we have defined as super intelligence. And it did seem like there were
## 01:00:06
**中文**
这两个阵营正在形成。在这次对话中，有一群人正在使用像您这样的工具，并为其他人构建工具，他们说这将是我们所有人都在迈向的一个非常有用的未来。你的生活将充满选择，我们已经讨论了我潜在的孩子和他们的未来。然后还有另一个阵营的人正在构建这些工具，他们说这会杀死我们所有人。我很好奇这种文化上的脱节如何让我对这两群人怀念什么？对我来说，我很难像你说的完全正确一样全神贯注。有人这样说
**English / Original**
these two camps forming. There's a group of people who are using the tools like you in this conversation and building tools for others saying this is going to be a really useful future that we're all moving toward. Your life is going to be full of choice and we've talked about our my potential kids and and their futures. Then there's another camp of people that are building these tools that are saying it's going to kill us all. And I'm curious how that cultural disconnect has like what am I missing about those two groups of people? It's so hard for me to like wrap my head around like there are you are totally right. There are people who say this
## 01:00:48
**中文**
将会杀死我们所有人，但他们仍然每周工作 100 小时来建造它。是的。我不能，我不能真正把自己置于头脑空间中。如果那是我真正相信的，我想我不会尝试去建造它。人们会想，你知道，也许我会像在农场一样，努力度过我最后的日子。也许我会努力倡导停止这种行为。也许我会尝试更喜欢安全方面的工作，但我不认为我会尝试建立它。所以，我发现自己很难理解这种心态。
**English / Original**
is going to kill us all and yet they still are working 100 hours a week to build it. Yes. And I I can't I can't really put myself in the headsp space. If if that's what I really truly believed, I don't think I'd be trying to build it. One would think, you know, maybe I would be like on a farm trying to like live out my last days. Maybe I would be trying to like advocate for it to be stopped. Maybe I would be trying to like work more on safety, but I don't think I'd be trying to build it. So, I find myself just having a hard time empathizing with that mindset.
## 01:01:21
**中文**
我认为这是真的。我认为这是出于善意。我认为这就像存在一些心理问题，我不明白他们如何让这一切变得有意义，但这对我来说很奇怪。你有意见吗？你知道，因为我总是这样做。我要求一个总体的未来，然后我尝试强调具体细节。当你向人们询问它将如何杀死我们所有人的具体细节时，我的意思是，我认为我们不需要以乐观的态度来讨论这个问题，但你会听到同样的说法。你会想到，你知道，尝试完成某项任务，然后过度完成该任务。嗯你听说过排序
**English / Original**
I assume it's true. I assume it's in good faith. I assume there's just like there's some psychological issue there I don't understand about how they make it all make sense, but it's very strange to me. Do you do you have an opinion? You know, because I I always do this. I ask for sort of a general future and then I try to press on specifics. And when you ask people for specifics on how it's going to kill us all, I mean, I don't think we need to get into this on an optimistic show, but you hear the same kinds of refrains. You think about, you know, something uh trying to accomplish a task and then over accomplishing that task. Um you hear about sort
## 01:01:59
**中文**
我听说你谈到了一种普遍的过度依赖，即总统将是一个人工智能，也许这是一种过度依赖，你知道，我们需要考虑这一点。你知道，你扮演了这些不同的场景，但是然后你问某人为什么他们正在研究它，或者你问某人他们认为这将如何进行，而我可能还没有与足够多的人交谈过。也许我并不完全理解正在发生的文化对话。嗯，或者也许确实有人只是说 99% 的时间我认为这会非常好。 1% 的时间我认为这可能是一场灾难
**English / Original**
of I've heard you talk about a sort of general um over reliance of sort of an understanding that the president is going to be a a AI and and maybe that is an overreliance that we, you know, would need to think about. And you know, you you play out these different scenarios, but then you ask someone why they're working on it, or you ask someone how how they think this will play out, and I just maybe I haven't spoken to enough people yet. Maybe I don't fully understand this this cultural conversation that's happening. Um or maybe it really is someone who just says 99% of the time I think it's going to be incredibly good. 1% of the time I think it might be a disaster
## 01:02:36
**中文**
努力创造最好的世界。如果你觉得，嘿，99% 的可能性令人难以置信，我完全可以。世界有 1% 的几率被消灭。我真的很想努力最大限度地将 99 提高到 99.5。我完全可以理解。是的，这是有道理的。我一直在对一些影响未来的最重要人物进行系列采访。不知道下一个人会是谁，但知道他们将在我们刚刚描述的未来构建一些完全令人着迷的东西。您是否建议我问下一个人不知道是谁的问题？
**English / Original**
trying to make the best world. That I can totally if you're like, hey, 99% chance incredible. 1% chance the world gets wiped out. And I really want to work to maximize to move that 99 to 99.5. That I can totally understand. Yeah, that makes sense. I've been doing an interview series with some of the most important people influencing the future. Not knowing who the next person is going to be, but knowing that they will be building something totally fascinating in the future that we've just described. Is there a question that you'd advise me to ask the next person not knowing who it is?
## 01:03:10
**中文**
我总是对类似的事情感兴趣，而无需了解任何事情。我总是对所有你可以花时间和精力做的事情感兴趣。你为什么选择这个？你是怎么开始的？就像你在其他人之前看到了什么，就像大多数人在做一些有趣的事情之前，在达成共识之前就看到了它一样。
**English / Original**
I'm always interested in the like without knowing anything about the I'm always interested in the like of all of the things you could spend your time and energy on. Why did you pick this one? How did you get started? Like what did you see about this when before everybody else like most people doing something interesting sort of saw it earlier before it was consensus.
## 01:03:26
**中文**
是的。比如你是怎么来到这里的以及为什么会这样？你会如何回答这个问题？我一生都是人工智能迷。我来大学是为了学习人工智能。我在人工智能实验室工作。呃，我就像一个看着科幻节目长大的人，我一直认为如果有一天有人建造它会非常酷。我认为这将是有史以来最重要的事情。我从来没有想过我会成为真正从事这一工作的人，我感到难以置信的幸运、快乐和荣幸，因为我能做到这一点。我喜欢感觉自己已经远离童年了。但我从来没有怀疑过这不会是最令人兴奋和有趣的事情。我只是没有
**English / Original**
Yeah. Like how did how did you get here and why this? How would you answer that question? I was an AI nerd my whole life. I came to college to study AI. I worked in the AI lab. Uh, I was like a I watched sci-fi shows growing up and I always thought it would be really cool if someday somebody built it. I thought it would be like the most important thing ever. I never thought I was going to be one to actually work on it and I feel like unbelievably lucky and happy and privileged that I get to do this. I like feel like I've like come a long way from my childhood. But there was never a question in my mind that this would not be the most exciting interesting thing. I just didn't
## 01:04:06
**中文**
我认为这是可能的。呃，当我上了大学的时候，感觉我们离这个目标真的很远。然后在 2012 年，我与联合创始人伊利亚 (Ilia) 合作完成了 Alex Net 论文。我第一次觉得有一种方法可能有效。然后我在接下来的几年里一直关注着规模的扩大、规模的扩大、变得越来越好。我记得有这样的事情，为什么世界不关注这个？对我来说，这显然是可行的。可能性仍然很小，但可能会奏效。如果它确实有效，那才是最重要的。这就是我想做的。和
**English / Original**
think it was going to be possible. Uh, and when I went to college, it really seemed like we were very far from it. And then in 2012, the Alex Net paper came out done, you know, in partnership with my co-founder, Ilia. And for the first time, it seemed to me like there was an approach that might work. And then I kept watching for the next couple of years as scaled up, scaled up, got better, better. And I remember having this thing of like why is the world not paying attention to this? It seems like obvious to me that this might work. Still a low chance, but it might work. And if it does work, it's just the most important thing. So like this is what I want to do. And
## 01:04:47
**中文**
然后令人难以置信的是它开始起作用了。非常感谢您抽出时间。非常感谢。
**English / Original**
then like unbelievably it started to work. Thank you so much for your time. Thank you very much.