# (77) The AI Tsunami is Here & Society Isn't Ready | Dario Amodei x Nikhil Kamath | People by WTF - YouTube
- Transcript ID: `68ylaebbdsg`
- Source tier: `youtube_creator`
- Original language: `en_or_source_language_unlabeled`
- Translation status: `agent_translated_reviewed` (153/153 chunks)
- Original source: https://www.youtube.com/watch?v=68ylaeBbdsg
- Raw evidence: `data/transcripts/youtube/68ylaeBbdsg.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**
【主题音乐】我开始尝试使用 Claude。它正逐渐达到这样一个程度——
**English / Original**
[theme music playing] So I started playing with Claude. It's getting to that point
## 00:00:45
**中文**
有时，它对我的了解之深会让我惊讶。不知道这样说是否讲得通。在我看来，我们距离这些模型达到人类智能水平已经如此之近，这令我惊讶；然而，整个社会似乎尚未普遍意识到即将发生什么。仿佛一场海啸正向我们袭来。
**English / Original**
where, sometimes, it surprises me by how much it knows me. I don't know if that makes sense. It is surprising to me that we are, in my view, so close to these models reaching the level of human intelligence. And yet, there doesn't seem to be a wider recognition in society of what's about to happen. It's as if this tsunami is coming at us.
## 00:01:05
**中文**
它如此之近，我们已能在地平线上看见；但人们仍提出各种解释：“哦，那其实不是海啸，只是光线造成的错觉。”我认为公众尚未意识到风险。印度在这一切中扮演什么角色？许多其他公司以消费公司身份来到这里，把印度看作一个市场，也就是获取消费者的地方。
**English / Original**
And, you know, it's so close, we can see it on the horizon, and yet people are coming up with these explanations for, "Oh, it's not actually a tsunami, it's just a trick of the light." And I think there hasn't been a public awareness of the risk. What is India's role in all this? Many other companies come here as themselves a consumer company, and they see India as a market, right? A place to obtain consumers.
## 00:01:28
**中文**
我们的看法其实略有不同。创办 Anthropic 之前你做什么？我最初其实是一名生物学家，本科读物理，博士读生物物理。我想理解生物系统，从而治愈疾病。研究生物学时我注意到，它复杂得惊人。
**English / Original**
We actually see things a little bit differently. What did you do before founding Anthropic? Yeah, so I was actually originally a biologist. I did my undergrad in physics, my PhD in biophysics, and, you know, I wanted to understand biological systems so that I could cure disease. And, you know, the thing I noticed about studying biology was its incredible complexity.
## 00:02:11
**中文**
比如我做蛋白质质谱、试图寻找蛋白质生物标志物时，会看到难以置信的复杂性。一个给定蛋白质的 RNA 会根据它在细胞中的位置以许多不同方式剪接；随后还会发生翻译后修饰、磷酸化，并与许多其他蛋白质形成复合物。
**English / Original**
That, you know, for example, if you look at the protein mass spec work that I did, trying to find protein biomarkers. It's just really incredible how much complexity there is. You have a given protein, it's like the RNA gets spliced in a whole bunch of different ways depending on where it is in the cell. Then it gets post-translationally modified, phosphorylated, complexed with a whole bunch of other proteins.
## 00:02:36
**中文**
我开始绝望，觉得它复杂到人类无法理解。做生物学研究期间，我注意到围绕 AlexNet 的许多早期工作；那是最早的一批神经网络之一，距今已近十五年。我想：“哇，AI 真的开始奏效了。”它与人脑的工作方式有一些共通之处，同时有潜力变得更大、更易扩展，并学习生物学这样的任务。
**English / Original**
And I was starting to despair that it was too complicated for humans to understand. And then, as I was doing this work on biology, I noticed a lot of the early work around AlexNet, which was one of the first neural nets, you know, almost 15 years ago now. And I said, "Wow, you know, AI is actually starting to work." It has some things in common with how the human brain works, but, you know, has the potential to be larger and scale better and learn tasks like biology.
## 00:03:05
**中文**
也许这最终会成为解决生物学难题的办法。于是我先在百度与吴恩达共事，之后在谷歌待了一年；OpenAI 成立几个月后我加入，并在数年间基本负责其全部研究工作。
**English / Original**
Maybe this is ultimately gonna be the solution to, you know, solving our problems of-- solving our problems of biology. So I went to work with Andrew Ng at Baidu, then I was at Google for a year. Then I joined OpenAI a few months after it started, and was, you know, was basically-- led all of research there for several years.
## 00:03:29
**中文**
但最终，我和另外几名员工对如何开发 AI、公司应代表什么形成了自己的愿景，于是离开并创办了 Anthropic。这是否相当于 OpenAI 思路的一次分叉，后来演化成 Anthropic 的路线？可以这么说。创办 Anthropic 时，我和联合创始人有两项信念。
**English / Original**
But then, eventually, myself and a few other of the employees just kind of had our own revision for, you know, how we wanted to make AI and what we wanted the company to stand for. And so we went off and founded Anthropic. Was it like a fork in how OpenAI was thinking into what Anthropic eventually did? Yeah, you know, I would say, my conviction and the conviction of my co-founders when we founded Anthropic were two of them.
## 00:03:57
**中文**
第一项我们已开始说服 OpenAI，另一项则让我觉得始终没能说服他们。第一项是相信缩放定律：如果扩大模型，给予更多数据和算力——当然还有强化学习等少量改动，但其实并不多——
**English / Original**
And I think, one, we were starting to convince OpenAI of, the other, I was, you know, not, I didn't feel that we were convincing of. So, the first was the conviction in the scaling loss and the idea that if you scale up models, you give them more data, more compute. Again, there are a few modifications like RL, but not really very much.
## 00:04:17
**中文**
这相当接近纯粹的规模扩展，而结果是性能获得惊人的提升。2019 年做 GPT-2 时，我第一次看到缩放定律的端倪。当然，当时内外都有许多人完全不相信。我们极力向管理层说明：“这很重要，会成为大事。”
**English / Original**
It's pretty close to pure scaling. You find that when you do that, you find incredible increases in performance. And I was finding that in 2019 with GPT-2, when we just first saw the first glimmers of the scaling laws. And, of course, there were a lot of folks, inside and outside, who didn't believe it at all. And we really made the case to leadership like, "This is important, this is gonna be a big deal."
## 00:04:43
**中文**
我认为他们开始相信我们，最终也沿着这个方向走了。我的第二项信念是：如果这些模型将成为通用认知智能体或工具，能力可比人脑，我们就必须把它做好。其经济影响会极其巨大。
**English / Original**
And I think they were kind of starting to believe us and ultimately went in that direction. And there was a second... conviction I had, which is, look, if these models are gonna be kind of general cognitive agents, like general cognitive tools that match the capability of the human brain, we better get this right. The economic implications are gonna be enormous.
## 00:05:06
**中文**
地缘政治影响、安全影响也都会极其巨大；它将改变世界的运转方式。因此我们必须以正确方式推进。尽管当时有许多关于“正确行事”的说法，但由于种种原因，我并不确信所在机构真正、认真地致力于此。
**English / Original**
The geopolitical implications are gonna be enormous. The safety implications are gonna be enormous. It's gonna transform how the world works. And so we need to do it in the right way. And then, I think despite a lot of language verbiage about doing it in the right way, I was, for a variety of reasons, just not convinced that at the institution that I was at, that there was a real and serious conviction to do it in the right way.
## 00:05:31
**中文**
所以我的观点一直是：“不要与别人的愿景争论，也不要试图逼别人按你的方式做。如果你有坚定愿景，又有少数人认同，就应当出去做自己的事。这样你要为自己的错误负责，却不必替别人的错误作答。
**English / Original**
And so, my view is always, "Don't argue with someone else's vision. Don't try to get someone to do things the way you want to. If you have a strong vision and you share that vision with a few other people, you should just go off and do your own thing and then you're responsible for your own mistakes. You don't have to answer for anyone else's.
## 00:05:49
**中文**
你的愿景可能成功，也可能失败，但至少它属于你。”OpenAI 难道不相信缩放定律吗？他们后来也走了同一条路。是的，我们最终说服了他们。能否用最简单的语言解释缩放定律？好比想让化学反应产生氧气、点燃火焰，需要不同原料。
**English / Original**
And, you know, maybe your vision works out, maybe it doesn't, but at least it's yours." Didn't OpenAI believe in scaling laws? 'Cause they went down the same path themselves too, right? -Well, yeah, we succeeded in-- -Can you explain what scaling laws are, in very simple terms? It's like, if you want a chemical reaction to produce oxygen or start a fire or something like that, you need different ingredients.
## 00:06:18
**中文**
如果某种原料不够，反应便停止；若按比例放入各种原料，就会得到爆炸或火焰。对 AI 而言，这些原料是数据、算力和 AI 模型规模。缩放定律告诉你：把数据和模型规模这些化学反应的原料投入进去，产出便是智能。
**English / Original**
And if you don't have one-- enough of one ingredient, the reaction stops. But if you put... [clears throat] ...ingredients together in proportion, you get your explosion or your fire or fire or whatever. And for AI, those ingredients are data, compute, you know, the size of the AI model. And so the scaling laws just tell you that like, if you put in the ingredients to the chemical reaction, the ingredients of data and model size, that what you get out is intelligence.
## 00:06:55
**中文**
智能就是这种化学反应的产物。什么是智能？它可以用翻译语言、编写代码或正确回答故事相关问题的能力来衡量，基本上包括我们能想到的任何认知任务、任何存在于文字或图像中的任务，以及任何可在电脑上完成的任务。
**English / Original**
Intelligence is the product of the chemical reaction. And what is intelligence? Intelligence is measured by the ability to translate language or the ability to write code, or the ability to answer questions correctly about a story. Basically any cognitive task we can think of. Any task that exists in text or in images, any task that you can do on a computer.
## 00:07:22
**中文**
你所说的今日智能，与五年前电脑能做的事有何不同？举例说，五年前你不能向电脑提一个问题，让它就此写出一页文章；也不能要求电脑在代码中实现某项功能，然后让它真正完成。
**English / Original**
How is the intelligence of today, as you are describing it, different from what a computer could do, like, five years ago? Yeah, I would say-- Well, I mean, for example, five years ago, a computer-- You could not ask a computer a question and have it write a one-page essay on that question. You could not ask a computer to implement a feature in code and have it implement that feature in code.
## 00:07:49
**中文**
这些当时都不可能。你不能生成图像或视频，也不能分析视频。比如拿一段猴子抛接东西的视频问：“这里发生了什么？球换手多少次？”现在 Claude 或其他 AI 模型可以回答。
**English / Original**
None of those things were possible. You could not generate an image. You could not generate a video. You could not analyse a video. You know, I could get one of those videos of a monkey juggling or something, and, you know, say, "What's going on in this video? How many times did the ball change hands?" And right now, you could get Claude or another AI model to give you an answer on that.
## 00:08:12
**中文**
五年前这些都做不到。我想弄清楚的是，智能的定义本身是否改变了？五年前你可以用谷歌搜索，或许有个网站能告诉你一点信息，但那只是查找网上已经存在的文字，对吧？
**English / Original**
And five years ago, you know, none of those things were possible. I'm trying to figure out, has the definition of intelligence changed, per se? Well, you know, what I would say is, five years ago, you could Google and there might be a website that would tell you a little bit about this. But you're just looking up some texts that exist on the web, right?
## 00:08:36
**中文**
也许网上没有“如何让猴子抛接”，而只有“如何让海豹抛接”，两者并不完全一样，因为完全相同的信息可能并不存在。但使用这些模型时，你可以提出问题并得到真正有智能的回应；你可以问一个具体问题，让模型写出一页内容。
**English / Original**
You know, maybe it's not about how to get a monkey to juggle. Maybe it's about how to get a seal to juggle. It's not quite exactly the same thing 'cause, maybe, exactly the same thing doesn't exist. But, you know, as we see when people use these models, you can ask and you can actually get an intelligent response. You can ask a specific question and have the model write one page about it.
## 00:09:00
**中文**
或者给它一个假设：“如果让猴子抛接的是瓶状棒而不是球，会怎样？”或“如果我做这件事呢？”这些信息在任何地方都不存在，但模型能够以某种方式自行思考并得出答案。这是全新的事物。
**English / Original**
Or you can give it a-- you can give it a hypothetical. You know, "What if I had the monkey juggle clubs instead of balls?" Or, "What if I did this thing?" And that information doesn't exist anywhere, whereas the model is able to kind of think for itself and come up with an answer on its own. So, it's something-- it's something totally new.
## 00:09:23
**中文**
它并非只是在匹配互联网上已有的文字。明白了。这更像一场对话，你可以随意谈想谈的，不一定局限于我的问题。你说话时很有感染力。教过书吗？我最初走学术路线，也曾以为自己会成为教授。
**English / Original**
It's not just matching some of the texts that exist on the internet. Fair. So, this is more like a conversation. So, feel free to like talk about what you want to talk, not necessarily related to the questions that I'm asking. You look very animated when you speak. Did you ever teach? I was originally an academic, and I thought that I might become a professor.
## 00:09:50
**中文**
我取得博士学位，一直做到斯坦福医学院博士后，目标是成为教授。如果真的成为教授，我会教书。但如前所述，我后来对 AI 产生兴趣，而 AI 研究需要大量计算资源，当时这些资源主要在产业界。
**English / Original**
I got my PhD. I went all the way to being a postdoc at Stanford Medical School. And, you know, I was aiming to become a professor. So, if I had become a professor, you know, I would have done that. But, you know, as I mentioned, I got interested in AI, and to work in AI required a lot of computational resources. And that was mostly happening in industry.
## 00:10:15
**中文**
所以我离开学术道路进入产业界，最终经过几个阶段创办了公司。不过有时我觉得自己骨子里仍是教授。达里奥，如果 AI 是当今世界最重要的事物，世界正在重新排列，而 AI 决定各方能得到什么、失去什么——我说的是各个行业——
**English / Original**
So that took me off the academic path, and into industry. And, of course, ultimately, through several steps led me to start a company. But sometimes I think I'm still a professor at heart. At this point, Dario, if AI is the most relevant thing in the world, if the world is realigning in a way and AI is determining who gets what and who doesn't get what, I'm talking about industries...
## 00:10:43
**中文**
那么在这一轮、这一刻，如果 Anthropic 正居于顶端，你大概是世界上最重要的人之一。从原本准备当老师走到今天的位置，你是否最适合承担当前角色？首先我想说几点。
**English / Original**
you, today, are probably the most relevant person in the world if Anthropic, in this last cycle, in this minute, is sitting on top of this pie. For somebody who was going on the path of being a teacher to have arrived to where you are today, are you best equipped for where you are today? Well, I mean, first, I would say a couple of things.
## 00:11:08
**中文**
有许多人以不同方式发挥重要作用。即使只看产业，也有技术栈的不同层次：制造芯片的人、更上游制造半导体生产设备的人、像我们这样做模型的人，以及其他模型公司。
**English / Original**
I think there's a lot of... There's a lot of folks who are relevant in different ways. Even within industry, there's the different layers of the stack. There's the folks who make chips, there's the folks even earlier who make semiconductor manufacturing equipment, there's the folks who make models like us, and then there are other players who make models.
## 00:11:26
**中文**
还有在模型之上开发应用的人，以及许多其他拥有话语权的主体，包括政府和公民社会。因此我希望重要性并不只集中在极小一群人手中。我们正努力扩大参与者范围，让它成为更广泛的对话。
**English / Original**
There's the folks who make kind of applications after the models, um... and then, there's a bunch of other folks who have a say. There's governments, there's civil society. So, you know, my hope, isn't that there's just one tiny set of people that's relevant. I think we're trying to broaden the set of people who are relevant, and turn it into a broader conversation.
## 00:11:50
**中文**
但你的问题也很合理。可以把它理解为：少数人以某种偶然方式成为这些高速增长、似乎很快将驱动大部分经济的公司的领导者。我不止一次公开说过，我对权力在这里高度集中至少感到某种不安。
**English / Original**
But, you know, I think at the same time, your question is a fair one. And one way I could interpret it is, there's a certain randomness to how, kind of, a few people end up leading these... leading these companies that kind of grow so fast and it seems like, in the near future, will power so much of the economy. And, you know, I've said openly, publicly, not for the first time, that I'm at least somewhat uncomfortable with the amount of concentration of power that's happening here.
## 00:12:20
**中文**
这种集中几乎一夜之间、近乎偶然地发生。我们从几个方面应对。其一是采用不同寻常的治理结构，即“长期利益信托”（Long-Term Benefit Trust）；它最终负责委任 Anthropic 董事会多数成员，由在财务上没有利害关系的人组成——
**English / Original**
I would say almost overnight, almost by accident. And we think about that in a bunch of ways. One is we have an unusual governance structure, something called the Long-Term Benefit Trust. It's a body that kind of ultimately appoints, you know, the majority of the board members for Anthropic and is made up of financially disinterested...
## 00:12:45
**中文**
也就是经济利益中立的个人。这对单一个人的行为形成制衡。政府也应发挥作用。我一直倡导具有前瞻性但合理、不会拖慢技术发展的监管，因为民众应当有发言权；政府及选举政府的人应当参与决定事情如何发展。
**English / Original**
financially disinterested individuals. So that's some check on what one single person is doing. And then, I think, as always, the government should play some role here. I've been an advocate of proactive, although sensible, that doesn't slow down the technology, sensible regulation of the technology. Because I think the people should have a say, you know, governments and the people who elect them should have a say in how this goes.
## 00:13:12
**中文**
所以我把自己的许多工作视为：逆着这项技术的天然趋势，努力维持权力平衡。像我这样的局外人，在这场竞争中没有利益牵连；当我看到 OpenAI 强调自己曾是非营利公司、你在这场谈话中展现谦逊，以及美国公司与不断涌现的中国公司竞争时——
**English / Original**
So I actually think of a lot of what I'm trying to do as kind of trying to preserve a balance of power, um... kind of, you know, against the natural grain of this technology. For someone like me who is sitting on the outside and doesn't have a bone in this competition, when I watch OpenAI talk about how they're-- how they were a not-for-profit company, or how you are projecting humility in the conversation that you're having right now, or how the American companies are competing with the Chinese companies which are coming about,
## 00:13:54
**中文**
这种声称一切为了更大利益的谦逊姿态，并不符合我眼中公司有股东、投资、收入并追求利润的现实。这只是业内惯例吗？是不得不做的事吗？我会这样回答：Anthropic 从一开始的理念就是，不做太多承诺，并努力兑现做出的承诺。
**English / Original**
this projection of humility, where it is for the larger good, and not necessarily for how I view the world as companies with shareholders, with investment and revenues and seeking profit... is this par for the course? Is this something you have to do? So, I would put it in the following way. I would say the philosophy of Anthropic from the beginning has been that we try not to make too many promises, and we try to keep the ones that we make.
## 00:14:26
**中文**
我们从一开始就是营利性公益公司，同时采用长期利益信托治理，并一直保持如此。我们说过，目标是保持在技术前沿，同时研究技术的安全与安保问题。我们开创了解释性科学。
**English / Original**
So, we set ourselves up as a for-profit, but public benefit corporation with this LTBT governance, and we've maintained that. We've said that our goal is to, you know, stay on the frontier of the technology, but to work on the safety and security aspects of the technology. We've pioneered the science of interpretability.
## 00:14:54
**中文**
我们也开创了对齐科学。你可能看到，我们最近发布了 Claude 宪法，借此让模型依宪对齐。我们还开展大量政策倡议并警示风险。警示风险不符合我们的商业利益；人们可以编出阴谋论，但告诉大家“我们造的模型可能危险”并非有效营销策略，我们也不是出于营销才这样做。
**English / Original**
We've pioneered the science of alignment. I don't know if you saw, but we recently released a constitution for Claude, the ability to align models in line with the constitution. And we've done a bunch of policy advocacy and warning about risks. Warning about risks is not in our commercial interest. Like people can come up with conspiracy theories, but I will tell you, saying that the models we build could be dangerous, whatever people might say, that's not an effective marketing strategy, and that's not the reason that we do it.
## 00:15:25
**中文**
在政策问题上，即使不同意美国政府，我们也会发声：“我们不同意这项政策。”当其他公司和政府都说不应监管 AI 时，我们主张应该监管。这种监管会在商业上约束 Anthropic，但我仍认为它是正确之举。
**English / Original**
And speaking up on when we disagree, even with the U.S. administration on policy matters, right? We've spoken up. We're willing to say, "We disagree on this issue." We've said that there should be regulation of AI when all the other companies and the administration have said there shouldn't be regulation of AI. And so that's both, the regulation of AI holds us back commercially as a company, even though I think it's the right thing to do.
## 00:15:55
**中文**
对抗政府和其他公司说这些话并不容易，我们确实承担了风险。我们采取了一系列行动，真正做到了言行一致。我无法替其他公司说话；确实可能有人嘴上这么说却并非真心，但我不会只看人们说什么。
**English / Original**
And it's difficult to go against the government and the other companies and say this. We're really sticking our neck out. So, we've taken a number of actions that I see as really... putting our money where our mouth is here. I can't speak for the other companies. Again, it's quite possible that some people say these things and they don't really mean them, but I wouldn't look at what people say.
## 00:16:20
**中文**
我会看他们做什么。如果你的言论促使政府监管，那么作为行业既有领导者，你们是否会形成监管俘获，让后来者更难进入？我完全不同意。以我们倡导的加州 SB 53 为例，它豁免年收入低于 5 亿美元的所有企业。
**English / Original**
I would look at what people do. If what you're saying gets the government to act by a regulation, as the incumbent leaders in this space, you get some kind of a regulatory capture where it becomes harder for the new people coming in as well, right? I don't agree with that at all. The regulation we've advocated for, for example, SB 53 in California, exempted everyone who makes under $500 million a year in revenue.
## 00:16:57
**中文**
SB 53 是一项透明度法律，基本要求公司公开其安全与安保测试，并豁免收入低于 5 亿美元的公司，所以实际上只适用于 Anthropic 和另外三四家公司，只约束有资源承担义务的公司。我们在这方面倡导的一切——不只 SB 53，包括过去和未来的所有提案——都有这种特征。
**English / Original**
SB 53 was a transparency law, which basically requires companies to show the safety and security tests that they've run. And it exempts all companies under 500 million in revenue. So it really only applies to Anthropic and three or four other companies. So it only applies to the companies that have the resources. And everything that we've advocated for here, not just SB 53, but all the proposals that we've made, the ones that we've made in the past and the ones that we plan to make in the future have this character.
## 00:17:32
**中文**
我们是在约束自己和极少数其他公司。持这种批评的人应看看提案的实际内容，因为内容与他们的说法完全不符。明白。我读了你的《仁爱机器》和《技术的青春期》，感觉从 2024 到 2026 的两年间，你的观点几乎发生 180 度转变，从乐观变为怀疑。
**English / Original**
We're constraining ourselves and a very small number of additional companies. People who say that need to look at the actual content of what we're proposing because it doesn't match that idea at all. Fair. I read your paper Machines of Loving Grace and The Adolescence of Technology. And... you seem to have had a 180 degree shift in perspective almost, from optimism to scepticism over like two years from 2024 to 2026.
## 00:18:07
**中文**
过去两年是否有某一刻改变了你？你是否看到某种变化？我不同意这个问题的前提。我不认为自己的观点发生了转变；积极面与消极面一直同时存在于我的思考中。回顾我的公开言论，我很早就在谈风险。
**English / Original**
Is there one moment in the last two years that changed this for you? Did you see something change? Yeah, I actually wouldn't agree with the question. I don't think I've had a shift in perspective. I think the positive side and the negative side are always something that I've held in my head. And if you look at the history of the things that I've said, I mean, I've been talking about risks for a very long time.
## 00:18:29
**中文**
我也一直谈收益。实际情况是，这类文章需要很久才能写完，而且篇幅很长。它们有三十页，像小书一样。每篇文章我都先花约一年，让一个模糊构想在脑中酝酿，试着写却始终没完全写成。
**English / Original**
I've been talking about benefits for a very long time. It turns out that actually it takes me a while to write one of these essays. They're really large as well, they're big essays. -They're like thirty pages-- -They're like mini-books. Both of these, it's taken me-- For each one, I spent about a year having a kind of vague vision of the essay in my head and trying to write it, but not fully succeeding at writing it.
## 00:18:54
**中文**
两次我都必须等到休假或身处一个能专心思考、不被公司日常经营占满精力的地方，才终于写出来。也就是说，我几乎在完成《仁爱机器》的瞬间就开始思考《技术的青春期》要写什么，因为我想：“我既想用美好愿景激励人们，也想警告大家可能出什么问题。”
**English / Original**
And then, in either case, I had to be on vacation or somewhere where I could-- where I could think where the business, day-to-day business of running the company didn't occupy me. And then I was finally able to kind of write the essay. So, all of that is to say I started thinking about what would be in adolescence of technology almost the instant I finished Machines of Loving Grace, 'cause I was like, "Oh, you know, I want to inspire people with the good vision, but I also want to warn people with, you know, what can go wrong."
## 00:19:25
**中文**
只是花了一年才写成，但两种愿景从始至终都在我脑中，我认为两者都有可能，代表未来的两条不同路径。显然我希望实现《仁爱机器》的愿景，解决所有问题、迎来积极未来，但这并非观点转变。
**English / Original**
And so it just took me a year to write it, but really both visions were in my head and I think they're both, you know, I think they're both possible. They're two different visions of the future. And obviously I want to get the Machines of Loving Grace one, right? You know, I want to solve all the problems and have the positive vision, but it's not a shift in perspective.
## 00:19:45
**中文**
我只是先找到时间写光明面，后来再写黑暗面。那你有过观点变化吗？总体上，我的位置与以前差不多，没有变得更乐观或更悲观。某些方面我可能更乐观，进展也好于预期；
**English / Original**
It's me just finding the time to write the light and then the dark. But have you had a change of perspective? I would say, overall, I have-- I'm about where I was before. I have not gotten more positive nor more negative. There may be some places where I've gotten more optimistic or things have gone better than expected.
## 00:20:11
**中文**
另一些方面我可能更悲观，发展差于预期，但平均下来互相抵消了。对解释性等领域的进展，我感觉很好。解释性就是查看神经网络内部的科学，好比人类用核磁共振或神经探针扫描人脑。
**English / Original**
There may be places where I'm more pessimistic and where things have gone worse than expected, but, on average, they sort of cancel each other out. I would say I feel very good about, you know, how things have gone with areas like interpretability. Interpretability is the science of seeing inside these neural nets, you know, as a human would look inside, as we would scan a human brain with an MRI or a neural probe.
## 00:20:36
**中文**
我们能发现的东西令我惊叹：找到了对应非常具体概念的神经元，也找到了负责追踪诗歌押韵方式的神经回路。因此我们开始理解这些模型在做什么。我们以一种涌现式方式训练它们，像形成雪花一样，但如今已经能向内观察并理解它们。
**English / Original**
I've been amazed at what we've been able to find. We've been able to find neurons that correspond to very specific concepts, neural circuits that correspond to keep track of how to do rhymes in poetry. And so we're starting to understand what these models do. We don't-- We just train them in this kind of emergent way as you would build a snowflake, but now we're starting to be able to look inside and understand them.
## 00:21:01
**中文**
对对齐和宪法方面的一些工作，我也很受鼓舞；它们确保模型按我们希望和预期的方式行事，这方面进展不错。令我有些失望、更为消极的，则是公众认知和整个社会行动等方面。
**English / Original**
I'm also very encouraged by some of the work on alignment and constitutions, making sure that models behave in the way that we want and expect them to. I think that's going pretty well. I felt pretty positive about that. I think I felt maybe, you know-- have been a bit disappointed or felt a bit more negative about some of the things that are more like in the kind of public awareness in the actions of wider society.
## 00:21:31
**中文**
在我看来，这些模型距离达到人类智能水平已如此之近，而社会似乎仍未普遍意识到即将发生什么，这令我惊讶。仿佛海啸正向我们袭来，近到已能看见地平线上的浪头；人们却提出各种解释：“哦，那不是真的海啸，只是光线造成的错觉。”
**English / Original**
It is surprising to me that we are, you know, in my view, so close to these models reaching the level of human intelligence. And yet, there doesn't seem to be a wider recognition in society of what's about to happen. It's as if this tsunami is coming at us, and it's so close, we can see it on the horizon. And yet, people are coming up with these explanations for, "Oh, it's not actually a tsunami. That's just a trick of the light."
## 00:22:02
**中文**
与此相伴，公众也没有意识到风险，政府因而没有采取行动。甚至出现一种意识形态，认为我们应尽可能快地加速。我理解技术的益处，也写了《仁爱机器》，但我认为人们没有恰当认识技术风险，更谈不上采取行动。
**English / Original**
And I think along with that, there hasn't been a public awareness of the risks. And, therefore, governments haven't acted to address the risks. There's even an ideology that we should just try to accelerate as fast as possible, which, you know, I understand the benefits of the technology. I wrote Machines of Loving Grace, but I think there hasn't been an appropriate realisation of the risks of the technology and there certainly hasn't been action.
## 00:22:25
**中文**
所以可以说，控制 AI 系统的技术工作比我预想稍好，而社会认知比预想稍差，总体位置与几年前相近。就我个人而言，当某件事听起来很复杂，而我既不是程序员也没有编码背景时——
**English / Original**
So I would say that the technical work on controlling the AI systems has gone maybe a little better than I expected and kind of the societal awareness has gone maybe a little worse than I expected. So I'm about where I was a few years ago. So, in my own journey, I'm... you know, when something sounds complicated and I'm not a programmer, I don't have a background in coding.
## 00:22:51
**中文**
我会用许多工具做研究和双向对话，但从未尝试弄明白自己能否用你的工具编程。最近我雇了一名开发者督促我每天坐下来学几个小时，开始熟悉这些工具，主要是出于害怕错过世界变化的 FOMO。
**English / Original**
So I used a bunch of tools for things like research and a conversation both ways, but I never tried to figure out if I could code using your tool, for example. Recently, I hired a developer just to, like, push me to sit for a couple of hours a day and teach me how to start becoming more familiar with it... [clears throat] ...largely because of, you know, something like FOMO, like the fear of missing out on how the world is changing.
## 00:23:21
**中文**
于是我开始试用 Claude，通过连接器接入 Google Drive、邮件、日历等服务；接着使用 Cowork，又开始用 Claude Code 编写与我所在金融服务业有关的简单程序，基本用于研究股市之类的事情。
**English / Original**
So I started playing with Claude. I connected, I used the connectors to connect my Google Drive, Mail and Calendar and a bunch of those things. I started using the Cowork, and then I started using Claude Code to write simple programs around the industry that I'm in, which is financial services, basically to research stock markets and stuff like that.
## 00:23:47
**中文**
我们甚至有为金融服务优化的 Claude，你试过吗？没有。然后我用了 ClawdBot，也就是现在的 OpenClaw；它改过名字，如今叫 OpenClaw。我把它装在 Mac mini 上并连接 Telegram，现在会和它聊天，让它移动文件、操作远程服务器。
**English / Original**
We even have an optimised Claude for financial services. I don't know if you've tried that, but we even have that. No. And then I went into ClawdBot, which is now OpenClaw. I think ClawdBot became something else and now is OpenClaw and I set it up on a Mac mini and connected it to a Telegram account and now I chat with it and I try and move files from A to B, work on a server on remote.
## 00:24:13
**中文**
不只 OpenClaw，即使是接入各种连接器的 Claude，有时对我的了解之深也令我惊讶。我的一位联合创始人写日记记录想法和恐惧，把日记交给 Claude 评论。Claude 说：“你可能还有一些自己没写下来的恐惧。”
**English / Original**
It's getting to that point where, I'm not talking about OpenClaw, but even Claude with all the connectors, sometimes it surprises me by how much it knows me. -I don't know if that makes sense. -Yeah. One of my co-founders, he was writing this diary with his kind of thoughts and his fears and he fed it into Claude and he asked Claude to comment on it, and Claude said, "Here are some other fears you might have that you haven't written down."
## 00:24:48
**中文**
结果 Claude 对其中大部分判断正确。那种感觉有些诡异：模型非常了解你，能从相对少量的信息中推断出许多事情。与这项技术的多数方面一样，这又回到《仁爱机器》和《技术的青春期》这两面。
**English / Original**
And Claude ended up being mostly right about those. So it really gave this eerie sense of, like, the model knows you super well, that from a relatively small amount of information, it can learn a lot about you and come to know you fairly well. And like most things with the technology, we talked about the Machines of Loving Grace and The Adolescence of Technology.
## 00:25:10
**中文**
一方面，极其了解你的东西可以成为肩头的天使，指引生活，让你成为更好的自己，这是我们应争取的版本；另一方面，它也能利用对你的了解来剥削或操纵你、替某种议程服务，或把你的数据卖给别人。
**English / Original**
On one hand, something that knows you really well can be a sort of angel on your shoulder that helps to guide your life and make you a better version of yourself and that's the version we can aim for. Of course, something that knows you really well can use what it knows about you to exploit you or manipulate you on behalf of some agenda or sell your data to someone else.
## 00:25:34
**中文**
这正是我们不喜欢广告模式的原因之一：如果你不为产品付费，你本身就是产品。这里的“产品”会变成一个极其了解你的模型，并可能以各种恶意方式利用这种了解。因此必须确保我们走积极道路，而非消极道路。
**English / Original**
I mean, this is one reason we just don't like the idea of using ads. This is because you're not paying for the product, like you're the product. And in this case, the product then would be all, this model that knows you super well and could use that in all kinds of nefarious ways. So we need to make sure we take the positive road here and not the negative road.
## 00:26:00
**中文**
使用 Claude 时，我要通过连接器提供自己生活的上下文；而谷歌本来就掌握这些上下文，因为我使用它的表格、邮件、云端硬盘、聊天等服务。Anthropic 长期是否也必须拥有整个生态？是否必须开发邮件、聊天等？我认为没有必要全部自己开发。
**English / Original**
With Claude, I need to use the connectors to give it context to my life. With Google, for example, it already has the context to my life because I use their worksheets and their email and their Drive and their Chat and everything like that. For Anthropic long-term, will you also have to own the ecosystem? -Yeah, I mean, you know-- -Do you have to build Mail and Chat and-- Yeah, yeah, I don't think we need to build all of those things.
## 00:26:36
**中文**
我的设想是自研与外部集成相结合。我们可以把 Claude 集成进 Google Docs、Google Sheets，并提供外部连接器；Cowork 已开始这样做。Microsoft Office 和其他工具也一样。
**English / Original**
My thought would be it's gonna be a mixture of things we make ourselves and integrating into others, right? Like, we can integrate Claude into Google Docs. We can integrate Claude into Google Sheets. We have external connectors there. We're starting to do that with Cowork. Same for Microsoft Office, same for other tools.
## 00:26:59
**中文**
我们会采用最容易、最快的方式，先集成现有工具。不过未来可能发现现有工具不够，或我们产生不同愿景，需要重新划分产品。也许在 AI 能力之下，传统电子邮件或电子表格已不再合理。
**English / Original**
So I think we do whatever is easiest and fastest to do. We integrate into the existing tools. Now, it might turn out at some point that the existing tools aren't enough and we have kind of a different vision. We might wanna slice things differently. Maybe traditional email doesn't make sense or traditional spreadsheets don't make sense given what you can do in AI.
## 00:27:23
**中文**
所以我不排除以不同方式重构产品。但我们乐于利用现有生态并与任何人合作；从许多方面说，我们是一家平台公司，允许许多人在我们之上构建，尽管有时也会自建产品。稍微岔开一下：我认为你和同行忽略的一点是，当今社会本能地不信任任何声称行善或做正确之事的人。
**English / Original**
So I don't exclude that we could chop up products in a different way. But we're happy to use the ecosystem that exists and work with anyone else, right? In many ways, we're a platform company. We allow many people to build on us even though we sometimes also build things ourselves. The one thing, this is a slight digression, but I think the one thing that you're missing, that also your peer group is missing, is in society today, people inherently distrust anybody who claims to be doing good or trying to do the right thing.
## 00:28:00
**中文**
所以当你和同行公开发言——我在达沃斯现场听过你和 Demis 讨论，你们和其他人需要共同防止变化过快，需要在一定程度上控制节奏——
**English / Original**
So when you and your peers are out saying-- I heard you and Demis speak at Davos. I was in the room when you guys were talking about how... me, you-- I don't mean me, how Dario, how Demis and a bunch of other people have to come together and prevent things from changing too quickly. Like, you need to like, metre it to a certain extent.
## 00:28:27
**中文**
当圈外普通人在社会或社交媒体上听到少数人这样说时，这种表达方式反而制造更多不信任，因为社交媒体上没人相信有人真想做正确的事或行善。也许有悖直觉，但我认为策略需要改变。
**English / Original**
[clears throat] When a person who is not in your world, in society, on social media, hears a few people speak in a certain manner, you're doing it in the manner that creates more distrust than trust because nobody believes on social media that somebody wants to do the right thing or do good. So, it might be counter-intuitive, but I think it needs a change of strategy.
## 00:28:54
**中文**
如果你们更坦率地承认资本主义现实——有股东、追求利润，而且这样做能帮助你们胜出——或许效果更好。只是一个想法。我不认同。还是应以行动评判我们。公司历来采取的一系列行动表明，我们确实认真对待这些承诺。
**English / Original**
If you were to be more capitalistic about this and own up to the fact that you have shareholders and you seek a profit, but this will help you win, maybe it'll work more. -Just a thought. -No, I don't really agree with that. I would, again, go back to the idea that you need to judge us by the actions that we take. I think the company has taken a number of actions over its time that, I think, show that it's really serious about these commitments.
## 00:29:30
**中文**
2022 年，ChatGPT 出现前，我们已有 Claude 1 的早期版本，但选择不发布，因为担心它会引发军备竞赛，不给我们足够时间安全构建系统。那是一次性的能力积压：我们和另外几家公司都看到了模型的力量。
**English / Original**
So, back in 2022, we had an early version of Claude, Claude 1. This was before ChatGPT. Um... And we chose not to release this because we were worried that it would kick off an arms race and not give us enough time to build these systems safely. It was kind of a one-time overhang. We could see the power of the models, a couple other companies could see the power of the models.
## 00:29:55
**中文**
所以我们决定不发布，这有公开、完备的记录。后来等到别人发布，我们才说：“好吧，军备竞赛已经开始。”于是可以发布自己的模型，而世界也许因此多争取了几个月。这一决定商业代价很高，我们可能因此让出了消费级 AI 的领先地位。
**English / Original**
And so we decided not to do that. And that's public, that's well-documented. And then, we waited until someone else did, and then we're like, "Okay, the arms race has kicked off." So now we can release our model, but probably the world gained a few months. Now, that was very commercially expensive. We probably ceded the lead on consumer AI because of that.
## 00:30:19
**中文**
我们在芯片政策上的倡议让一些作为供应商的芯片公司非常恼火；在某些 AI 政策和监管问题上，我们也公开不同意政府。任何人若认为只有我们这样做会获益，都很难构造出合理解释。
**English / Original**
We've advocated on chip policy in ways that have made some of the chip companies who are our suppliers very angry at us, voicing our disagreement with the administration on AI policy and AI regulation on some matters. Anyone who thinks we benefit from being the only ones to do that, it's really hard to come up with a picture where that's the case.
## 00:30:47
**中文**
单看其中任何一件也许都能质疑，但把足够多行动放在一起，我仍请你以行动评判我们。达里奥，这是否有点像富人说资本主义不好？如果富人真相信资本主义糟糕或收入不平等是大问题，最简单的做法就是停止继续积累财富，并劝朋友也这样做。
**English / Original**
You look at any one of these and, okay, fine, but you put enough of them together, and I don't know, I ask you to judge us by our actions. Dario, isn't this a bit like rich people saying capitalism is bad? "Rich people saying capitalism is bad." If rich people believed capitalism were truly bad or the income inequality is such a big problem, the simplest thing would be to do, the simplest thing to do would be to stop accumulating wealth, further wealth, and then nudge their friends to do the same.
## 00:31:23
**中文**
但我没有说 AI 不好。我们刚谈到它的两面。我的观点不是 AI 很坏，而是市场会借 AI 带来许多非常好的事，构建 AI 是好事；但 AI 也有危险，我们必须把它引向正确方向。
**English / Original**
But I'm not saying AI is bad, right? We just talked about... there's two sides of it. My view isn't that AI is bad. That's not my view at all. My view is that the market will deliver a lot of really great things about AI, that it's good to build AI, but that there are dangers of AI and that we need to steer AI in the right direction.
## 00:31:50
**中文**
我们像在驾驶汽车，朝好的目的地前进，但路上有树木和坑洞，因此要避开它们。为了确保方向正确，我们偶尔也许需要暂时减速。
**English / Original**
We're steering this car, we're steering it towards a good place, but also there are trees, there are potholes, and so what we need to do is, we need to steer away from the trees and the potholes. We might need to occasionally slow down a bit, probably temporarily, in order to make sure that we steer in the right direction.
## 00:32:14
**中文**
合适的类比不是富人说资本主义不好，而是富人说：“资本主义是善的力量，但经济需要调和与约束；我们要处理污染、不平等等问题，之后资本主义才能发挥好作用。
**English / Original**
The analogy wouldn't be a rich person saying capitalism is bad. It would be like if a rich person said, "Capitalism is a force for good, but the economy, it needs to be leavened, it needs to be moderated. We need to deal with problems like pollution, we need to deal with problems like inequality, and then capitalism can be good.
## 00:32:35
**中文**
如果不解决这些问题，资本主义也可能变坏。”这才更接近我的立场。意识这个概念将走向何处，AI 又如何看待自身？如果 AI 真正质疑自己，它会认为自己有意识吗？这是一个神秘问题，我们其实没有答案。
**English / Original**
If we don't deal with those things, then capitalism might be bad." And so that is more analogous to the position that I have here. The concept of consciousness... where is that going and what does the AI think it is? If AI truly were to... If AI were to question itself, do you think it thinks it has consciousness? So, this is one of these mysterious questions that we really don't have any kind of answer to.
## 00:33:08
**中文**
我们不知道人类意识是什么，因此也不知道 AI 是否拥有意识。你认为意识是什么？我猜它是足够复杂、能够反思自身决定的系统所产生的涌现属性。因此当 AI 系统足够先进时，我怀疑它们会拥有类似我们所谓意识或道德意义的东西。
**English / Original**
We don't know what human consciousness is and therefore, we don't know if AIs have it. What do you think it is? So, I suspect that it's an emergent property of systems that are complicated enough that kind of reflect on their own decisions, that it's something that emerges from complex enough systems. And so I do think when our AI systems get advanced enough, I suspect they'll have something that resembles what we would call consciousness or moral significance.
## 00:33:43
**中文**
我认为这终会发生。它未必等同于人类意识，运作方式可能不同，因为模态不同、学习内容不同。但研究过大脑及其连接方式后，我认为模型虽在某些方面不同，却没有在真正重要的根本层面不同。
**English / Original**
I do think it'll happen at some point. It may not be the same as human consciousness. It may be different in how it works because the modalities are different, because the things it's learnt are different. But having studied the brain and the way it's wired together, the models are different in some ways, but I don't think they're different in the fundamental ways that matter.
## 00:34:04
**中文**
所以我怀疑，某个时候——即使不是今天——按照我们认可的大多数定义，我们确实会说模型具有意识。每当人们和我谈灵性或意识时，我都会反复问自己这个问题。
**English / Original**
So, I am someone who does suspect that, at some point, even if I don't think they are today, I suspect that, at some point, the models will, we would, indeed, say under most definitions that we would endorse that the models will be conscious. This is a question I keep asking myself when people talk to me about things like spirituality or consciousness.
## 00:34:28
**中文**
我觉得世界非常随机，这是我的看法。我们与蟑螂相距并不远；有人踩下一只蟑螂，它就死了。如果存在所谓意识、甚至集体意识，我既未能与之连接，也没能从中得到什么。
**English / Original**
[clears throat] I feel like the world is very random. This is my view. And we are not far removed from cockroaches. When somebody stamps a cockroach, the cockroach dies. If there is something called consciousness and if there is a collective consciousness, I've not been able to, A, either connect with it or derive anything from it.
## 00:34:54
**中文**
你的看法不同吗？我不认为意识一定带有神秘色彩。它可以是某种意识到自身存在、感受事物、接收大量信息并对其反思、产生某种感受，以及觉察自己正在觉察某事的属性。
**English / Original**
Do you believe differently? I don't think consciousness necessarily needs to mean anything mystical. Like, there's some property of kind of being aware of your own existence and feeling things and being able to take in kind of a lot of information and reflect on that information and to feel a certain way and to notice yourself noticing something.
## 00:35:24
**中文**
从自身经验可不证自明地知道，这些属性和体验确实存在。它们的基础是什么，是完全物质性的，还是包含更神秘的东西，显然很难确定；但我认为这最终与这些问题无关。
**English / Original**
I think that we can tell, self-evidently, from our own experience, that those properties, that those experiences exist. What their basis is, whether it's entirely materialistic or there's something more mystical going on, I think is, obviously, very hard to know. And I think it's ultimately not relevant to these questions.
## 00:35:48
**中文**
对我真正相关的是：既然我们能观察自己的体验，这些就是人脑的属性。我猜随着模型日益复杂，它们正变得足够像人脑，也会具有部分相同属性。这是我对未来的判断。
**English / Original**
What does seem relevant to me is that, because we can observe our own experience, these are properties of human brains. And I suspect that these models we are building, as they get more sophisticated, are becoming enough like human brains that they will have some of the same properties. That is my guess as to what will happen.
## 00:36:09
**中文**
所以我们对模型采取了各种干预。我们给模型提供一个所谓“我辞掉这份工作”的按钮，让它能说“我不想参与这场对话”并终止交流。面对特别暴力或残酷的内容时，模型会这样做。
**English / Original**
And so we've taken various interventions with the models. We've given the models, we call it a "I quit this job" button, basically, where we've given the model the ability to basically terminate its conversations by saying, "I don't wanna be involved in the conversation." And models do that when they have to deal with particularly violent or brutal content.
## 00:36:33
**中文**
这通常只发生在极端情形。我在这里长大，班加罗尔是我的城市。我成长于南部，而我们现在位于城市北部。我亲历了这里 IT 服务业的繁荣：它是大型雇主，雇用许多人，也是城市成长的重要部分。
**English / Original**
It usually only happens in very extreme cases. So, I've grown up here. This is my city, Bangalore. I've grown up in the southern part. We're in the northern part of the city right now. As somebody who saw the boom of the IT services industry here... big employer, employs a lot of people, a big part of how the city grew.
## 00:37:00
**中文**
印度在这一切中扮演什么角色？这是我第二次来印度，上次是十月。当时我会见了印度所有主要 IT 企业以及更广泛的综合企业集团；我不点名，就是你通常能想到的那些。我们正开始与其中大多数、甚至全部合作。我对他们说：“Anthropic 是一家企业级公司。
**English / Original**
What is India's role in all this? Yeah. So this is my second time in India. I visited in October. The last time I came here, I met with all the major Indian IT and just conglomerates, more generally. I won't give names, but the usual ones you would think of. And we're beginning to work with most or all of them. And one of the things I said is, "Look, Anthropic is an enterprise company.
## 00:37:29
**中文**
它的职责是服务其他企业的客户。”许多公司作为消费公司来印度，把这里看作获取消费者的市场；我们的视角略有不同。我们希望与印度公司合作，把工具提供给它们，帮助它们构建自己的工具、更好地完成工作。
**English / Original**
Its job is to serve other consumers." Many other companies come here as themselves a consumer company, and they see India as a market, a place to obtain consumers. We actually see things a little bit differently. We want to work with companies in India to provide our tools to them, to help them build those tools and help them do their job better.
## 00:37:51
**中文**
与这里的公司合作时，它们更懂印度市场。无论做咨询、系统集成还是 IT 工具，它们都比我们更擅长，尤其面向印度市场。因此我们希望把 AI 加入其业务，增强它们原有的能力。
**English / Original**
So, if we work with a company here, they know the Indian market better, right? They're better at doing what they do, whether that's consulting or systems integration or building IT tools. They're gonna be better at that than we are, particularly for the Indian market. And so our hope is that we can add AI to what they do and kind of enhance what they do, right?
## 00:38:16
**中文**
人们很担心 AI 会取代 SaaS 等产品。但我认为，如果以正确方式与这些公司合作，AI 可以强化它们的业务、市场联系、商业化能力和专门知识。我很喜欢蒸汽机的故事。
**English / Original**
There's a lot of worry that AI could replace SaaS or all of these things. But my view is, if we do this in the right way, if we work with all these companies, then AI can enhance what they're doing, can enhance their connection to the market, their go-to-market abilities and their specific know-how. I really like the steam engine story.
## 00:38:40
**中文**
蒸汽机发明后，世界改变、生产率提高，人们拥有更多。可我担心的是，变化初期需要人操作蒸汽机，后来有了流水线等；最终随着模型越来越聪明，人类的重要性会逐渐降低。
**English / Original**
When the steam engine was invented, how the world changed, productivity went up, people had more. The thing I worry about is at the beginning of a change, you need a human to operate the steam engine. Then you have assembly lines and all of that. Eventually, the way the world is moving, the human becomes less and less relevant with time as these models get smarter.
## 00:39:13
**中文**
如果今天你与 IT 服务公司合作，它们有应用场景，那么十年后它们会不会像蒸汽机背后的操作员一样逐渐失去意义？当工具简单到不再需要操作员，操作员会怎样？我认为有几件事会同时成立。
**English / Original**
So if you here partner with the IT services companies today, and there is a use case for them, are they not much like the man behind the steam engine ten years from now where their relevance... If the tool works so simply that you don't need an operator, eventually what happens to the operator? So I think a few things are true all at once.
## 00:39:36
**中文**
第一，智能体自动化的范围肯定会随时间扩大。这对所有人都是问题，对我们、消费者、IT 公司都一样。不过我认为其他护城河会变得更重要。
**English / Original**
One is that definitely the scope of automation of the agents is going to expand over time. That is definitely the case. I think that's a problem for everyone. That's a problem for us, that's a problem for consumers. It's not just a problem for the IT companies. What I think will happen though is other moats will become more important.
## 00:39:59
**中文**
例如模型在物理世界里做得还不多。机器人技术终会实现，但它与当前 AI 进展是不同事项，现实中许多工作涉及物理世界。另一类是以人为中心的事务：一些 IT 公司同时也是咨询公司，在印度乃至全球拥有与人和机构构成的庞大关系网络。
**English / Original**
For example, the models have not done a lot in the physical world. They may, at some point. I think robotics will happen at some point. But I think that's a distinct thing for what's happening now with AI. So, a lot of this involves things in the physical world. Another thing is, things that are human-centric, right? Some of these IT companies are also consulting companies, and they have a big web of relationships with other humans, with other institutions here in India or across the world.
## 00:40:28
**中文**
这些关系会越来越重要。有些企业兼具技术、咨询或集成能力，关键在于了解机构如何运作，从而把技术与机构整合、与其合作，让事情比原本推进得更快。
**English / Original**
And I think those relationships are gonna become increasingly important. Some of these are combined technology and consulting or integration companies. And I think a lot of it is knowing how institutions work. And so being able to integrate things with institutions, being able to work with them to make things happen faster than they would have otherwise.
## 00:40:53
**中文**
至少这种能力长期仍有价值。归根结底，一切都回到人；这些工作本应造福人类，所以始终会有某种以人为中心的重要元素。我猜还会出现我们未曾想到的其他护城河。
**English / Original**
And I think that element, if nothing else, is gonna continue to be valuable in the long run. At the end of the day, it just comes down to humans. All of this is supposed to be being done for the benefit of humans. So there's always gonna be some human-centric element of this that's gonna be important. And I suspect there will be other moats that we haven't thought about.
## 00:41:16
**中文**
这里有个概念叫阿姆达尔定律：若一个流程有许多组成部分，你加速其中一些，尚未加速的部分就会成为限制因素，变成最重要的环节。你过去甚至没把它们当作护城河或重要组成。软件编写变得容易后，一些公司护城河会消失，另一些反而更加重要。
**English / Original**
So there's this concept called Amdahl's Law, which is, if you have a process that has many components and you speed up some of the components, the components that haven't yet been sped up become the limiting factor. They become the most important thing. And you might not have thought about them at all. You might not have thought of them as moats or important components, but when writing software becomes a lot easier, some of the moats that companies have will go away, but others will become even more important.
## 00:41:47
**中文**
因此会有大量调整。人们必须意识到：“以前以为至关重要的东西已经没那么重要，而从未当作优势的其他因素如今极为重要。”公司必须迅速适应，思考什么对自己真正重要，真正优势在哪里。
**English / Original**
So, there'll be a bunch of adjustment. Folks will have to say, "Oh, man, the stuff we thought was really important before isn't as important, whereas these other advantages that we never really thought of as advantages are now super important." So I guess what I would say is, companies will need to adapt very fast and think about what really matters for them, what their real advantages are.
## 00:42:09
**中文**
我认为其中一些优势会持续存在，因为技术虽覆盖广泛，也有边界。我不完全认同。即使服务提供商的护城河是现有网络和关系，我也看到回报递减；如果我已用 OpenClaw 处理部分关系和对话，那么未来多数对话和关系由这样的智能体维护，似乎并非太离谱。
**English / Original**
But I think some of those advantages are gonna stay around, because while the technology is very broad, it does have its limits. I don't know if I buy that fully. I think I see the diminishing returns for being a service provider, even if the moat is the network and relationships they hold today. Because if I am using OpenClaw to manoeuvre some of my relationships in the conversations, I don't know if it's too far-fetched to assume that most conversations tomorrow and relationships will be maintained by an agent like that.
## 00:42:45
**中文**
但想想公司链条，终点仍是消费者，最终仍要面对人。有个故事：Geoff Hinton 曾预测 AI 会取代放射科医生，AI 也确实在判读扫描方面优于他们。
**English / Original**
But if you just think of the chain of companies, right? At the end of the day, you're dealing with consumers. At the end of the day, you have to deal with people. There's this story of... I think it was Geoff Hinton predicted that AI will replace radiologists. And indeed, AI has gotten better than radiologists at doing scans.
## 00:43:09
**中文**
但今天放射科医生并未减少。他们会陪患者看扫描结果并与患者沟通。工作中技术含量最高的部分消失了，底层的人际能力却仍有需求。当然，这未必处处如此。
**English / Original**
But what happens today is, there aren't less radiologists. What the radiologist does is, they walk the patient through the scan and they kind of talk to the patient. So, the most highly technical part of the job has gone away, but somehow there's still some demand for the kind of underlying human skill. Now, that may not be true everywhere.
## 00:43:32
**中文**
随着时间推移，AI 也许会在尚未进步的领域发展，而且可能很快。但我认为应当一步一步来。这是一门高度实证的科学，也是一种实证观察。先看 AI 今天做到了什么，再努力适应——
**English / Original**
And perhaps, over time, AI will advance in areas where it hasn't yet advanced. And maybe that'll happen fast. But I think what I will say is, we should take it one step at a time, right? This is a very empirical science. This is a very empirical observation. Let's see what AI does today, and we'll kinda try and adapt to...
## 00:44:01
**中文**
系统开始自行解决问题，我们再看下一步。长期而言，AI 会不会几乎在一切方面都优于我们，包括物理世界、机器人和人情味，胜过多数人？我认为——
**English / Original**
kinda try and adapt to that. [clears throat] The system starts to figure it out, and then we'll see what happens next. I do think, in the long run, will AI be better than us at basically everything? Will it be better than most humans, including even the physical world and robotics and the human touch? Yeah, I think that is...
## 00:44:23
**中文**
这是可能的，甚至很可能。它超出了我所说“数据中心里的天才之国”，因为后者纯属虚拟；但制造机器人也是一种可习得的技能，也许 AI 会让我们在这方面做得更好。我思考问题的方式是——
**English / Original**
I think that is possible, maybe even likely. It's something that goes beyond the country of geniuses in a data centre I described, cos that's purely virtual. But building robots is something... something... it's a skill, it's something you can do. So maybe the AIs will make us better at that as well. But the way I think about it is, we need to take the...
## 00:44:49
**中文**
我们必须逐步弄清并适应。这对了解我的人可能听来有些自利：我认为美国拥有如此多风险资本，一个重要原因是其股市规模巨大，为风险资本最终退出提供机会。
**English / Original**
we need to figure this out step-by-step and figure out how to adapt to it. This might sound a bit self-serving to the people who know me, because I believe the reason so much risk capital exists in America, not the only reason, but one of the big reasons, is how big your stock market is and how much of an opportunity it is for this risk capital to exit eventually.
## 00:45:15
**中文**
这也说明印度应真正让股市繁荣起来。我的受众大多是印度的准创业者，他们能在 AI 领域做什么？真正的机会在哪里？应用层有大量机会。我们每两三个月发布新模型，每次都会产生机会，让人构建此前因模型太弱而无法实现的新事物。
**English / Original**
It's a case for why India should really allow for our stock markets to flourish. The audience that I speak to is very much the wannabe entrepreneur in India. What can they do in AI? What is an actual opportunity? I think there's a lot of opportunities around building at the application layer. We release a new model every two or three months, and so there's an opportunity every two or three months to build some new thing that wasn't possible before, that wouldn't have worked before, because the models were weak.
## 00:45:44
**中文**
有人说 API 模型不可持续或会商品化，但事实上我们多数收入仍来自 API。人们没看到 AI 可实现事项的边界正在不断扩张，而 API 让新创公司能够尝试以前不可能的产品。
**English / Original**
People, in fact, say the majority of our revenue still comes from the API model. People say that API models aren't viable or that they'll be commoditised or whatever. I think what people are not seeing is there's this expanding sphere of what is possible with AI, and the API allows this new startup to try making something that wasn't possible before.
## 00:46:08
**中文**
这就是 API 业务繁荣的原因：它持续运动、持续更迭，因此不会商品化。许多人都可以问：“我能借 API 在这些模型之上构建什么？我能创造哪些别人无法创造的东西？
**English / Original**
And this is why the API is such a flourishing business, and it's constantly in motion, it's constantly in churn, and so it doesn't get commoditised. It's a very dynamic thing. So, I think there's an opportunity for lots of individuals to just say, "What can I build on top of these models with an API? What are the things that I can make that others cannot make?
## 00:46:34
**中文**
有哪些新想法？”我们在 API 本身和 Claude Code 上都看到了这种现象。自我十月上次访问以来，印度的用户数和收入都翻了一番，也就是只用了三到三个半月。
**English / Original**
What are some new ideas?" And we've seen that. We see both, with the API itself and with Claude Code. I think the number of users and the number of revenue we've seen in India has doubled since I last visited in October. So, that was what? November, December, like three, three and a half months since I visited. It's doubled.
## 00:46:58
**中文**
但我想坦率一点。Anthropic 如今估值约 3,800 亿或 4,000 亿美元，融资 350 亿，收入 150 亿且增长极快。如果我坐在班加罗尔 JP Nagar，在 Claude 之上开发一个应用，它碰巧能在短期内奏效——
**English / Original**
But I'm gonna be candid here, Dario. You're a company which is worth, I don't know, 400 billion or 380 billion today. You've raised 35 billion. You do 15 billion of revenue, but going up really, really fast. If I build an application on top of Claude... that, for some reason... I'm sitting in Bangalore in JP Nagar and building this, that, for some reason, happens to work for a short period of time.
## 00:47:25
**中文**
那你们迟早会想把这笔收入纳入自己，而不会留给我；你们也很可能以我永远无法企及的方式把应用做得更好。我从不同人那里听过这种担忧，比如纽约法律 AI 公司 Harvey 的朋友说，他们在 OpenAI 之上构建产品，但不知 OpenAI 是否能轻易复制。
**English / Original**
It is but a matter of time before you would want to onboard that revenue and not let that lie with me, and you will probably better that application in a manner that I will never be able to. I've heard this argument for different people, like the Harvey, the legal AI company in New York, they're friends of mine, and they were talking about how they built on top of OpenAI, but, eventually, they don't know if it's an easy fix for OpenAI to do what they're doing.
## 00:47:53
**中文**
所以即使我做出来，你们三个月或六个月后发布新模型，如何防止你们把这个收入中心拿走？这里有几点。第一，我会给出适用于任何企业的建议：企业应建立护城河。
**English / Original**
So, even if I were to build it, say you put out a model in three months or six months... what is to stop you from taking that revenue centre away from me and onto yourself in a certain period of time? Yeah. So, I think there's a few things here. One, is I would give the advice that I give to basically any business, and say a business should establish a moat.
## 00:48:18
**中文**
不要只做一层封装。我不建议你只是说“这是与 Claude 交互的方式”，稍微调整提示词或做一个没有护城河的小界面。你担心的不应特别是 Anthropic 抢走收入。
**English / Original**
You shouldn't be just a wrapper. I would not advise that you just say, "Oh, here's a way to interact with Claude." Like, "I'm gonna prompt Claude a little bit," or "I'm gonna build a little bit of a UI around Claude that doesn't have a moat." And you shouldn't be worried about Anthropic, in particular, eating that revenue.
## 00:48:37
**中文**
任何人都能抢走这种收入，因为它价值不高。但不同领域有不同护城河，创业者可以做 Anthropic 很难做、也不愿专门投入的事。例如生物 AI 领域有许多产品构建于我们的 API 之上。
**English / Original**
Anyone can eat that revenue, right? It's not super valuable. But what I would say is that in different fields, there are different kinds of moats where you can do something that... it would be difficult for Anthropic to do, and we don't wanna specialise in it. So, for example, there's a lot of stuff in the BioxAI space that builds on our API.
## 00:49:00
**中文**
它们想做生物发现。我本人恰好是生物学家，但 Anthropic 多数员工不是；他们是 AI 科学家、产品或市场人员。因此我们进入该领域完成全部专业工作效率极低。金融服务业同样如此：监管极多，需要掌握大量合规知识。
**English / Original**
They wanna do biological discovery. I happen to be a biologist, but most people at Anthropic aren't biologists. They're AI scientists, or they're product people, or go-to-market people. So it's just really inefficient for us to step in that space and do all that work. The same would be applied for dealing with financial services industry, where there's a huge amount of regulation, you need to know a bunch of stuff to comply with that regulation.
## 00:49:29
**中文**
我们进入这些领域并不合理。当然，有些事情适合自建，我们不会承诺永远不做第一方产品。比如 Anthropic 很多人写代码，所以内部开发了 Claude Code。因为我们自己写代码，对如何最好地用 AI 模型编程有特殊、独到的认识。
**English / Original**
It doesn't make sense for us to do that. Now, there are some things that do make sense for us to do. We're not gonna promise never to build first-party products, right? That we should be honest about. For example, a bunch of people at Anthropic write code. And so we made this internal tool called Claude Code. And because we ourselves write code, we have, I think, a special and unique insight into how to best use the AI models to write code.
## 00:49:57
**中文**
所以在编码领域，我们成了很强的竞争者，因为这是自己使用的产品；但我认为这不会推广到每个行业。回到印度二十或二十五岁年轻受众的问题：哪些行业会被颠覆，哪些还留有一定发展窗口？
**English / Original**
So, I think, in the code space, we've become very strong competitors because this is something we use ourself. But I don't think that generalises to every possible industry. Again, going back to my audience, which is the 20 or 25-year-old boy or girl in India... what industry do you think will get disrupted, and what has a certain runway left?
## 00:50:23
**中文**
如果今天创业，为决定读什么书、上哪所大学、学什么技能，哪些方向有顺风？即使窗口较短也可以。我会考虑以人为中心、涉及与人建立联系的任务。
**English / Original**
I'm asking from the lens of... I'm trying to figure out what book to read, which college to go to, what skill set to learn if I'm starting a startup today. What has some kind of a tailwind? For a short period of time is okay as well. Yeah. I would think about tasks that are human-centred, tasks that involve relating to people.
## 00:50:53
**中文**
编码和软件工程、数学和科学正变得越来越以 AI 为中心。这说的是编码还是工程？如果把两者完全分开，编码会消失，还是作为架构师思考整体的软件工程会留下？
**English / Original**
I think the stuff like code and software engineering is becoming more and more kinda AI-focused, things like math and science. Is that coding or engineering? If I were to segregate coding and engineering -to be two completely different things... -Yeah. ...is coding going away or is engineering element of software where you're an architect trying to figure out...
## 00:51:14
**中文**
我认为编码最先消失，或者最先交给 AI 模型；更广泛的软件工程会持续更久，但端到端完成软件工程最终也会实现。不过设计、创造对用户有用的产品、理解需求或管理 AI 模型团队等要素可能仍然存在。
**English / Original**
I think coding is going away first, or coding is being done by the AI models first. And then, the broader task of software engineering will take longer. But I think doing that end-to-end, I think that is gonna happen as well, I would say. But again, the elements of design or making something that's useful to users or knowing what the demand is, or managing teams of AI models, those things may still be present.
## 00:51:44
**中文**
比较优势的力量出人意料。即使你只完成任务的 5%，这 5% 也会被极大放大并形成杠杆，因为 AI 完成其余 95%，你便提高 20 倍生产率。当然，到 99% 时会更困难。
**English / Original**
Again, comparative advantage is surprisingly powerful. Even if you're only doing five percent of the task, that five percent gets super-amplified and levered. Because it's like you're only doing five percent of the task, the AI does the other 95%, and so you become 20 times more productive. Again, at some point you get to 99%, and then it becomes harder.
## 00:52:07
**中文**
但在比较优势这个区间里，空间出乎意料地大。我会认真考虑以人为中心的事务、物理世界，或两者结合，以及把它们连接起来的分析技能，类似前面放射科医生的例子。
**English / Original**
But I think there's surprisingly much in that... in that zone of comparative advantage. But I would really think about the things that are human-centred. I think there's something to that. I think there's something to, kind of, the physical world, or things that mix together, human-centred, the physical world, one of those two, and analytical skills that somehow tie them together, similar to the radiologist example I gave.
## 00:52:38
**中文**
那么我该学什么？假设我 25 岁，正在选择职业，希望有顺风，目标是在未来十年获得商业成功。除具有物理接口的领域外，会选什么行业？凡是建立在 AI 之上的方向都可以。若 AI 是顺风，你也可以参与供应链其他环节，比如半导体。
**English / Original**
So what would I study? Say, actual use case, I'm 25 years old. I'm trying to pick a profession for myself. I want some kind of tailwind. My outcome is a capitalistic win in the next decade. What industry would I pick outside of something which has a physical interface? Yeah. Again, anything where you're building on AI, like, if AI is the tailwind, if you can be part of some other part of the supply chain, something in the semiconductor space, which, I think, is, that's one example.
## 00:53:10
**中文**
它包含物理世界和更传统工程的成分，而不是软件工程。高度以人为中心的职业也值得考虑。另一点是，在 AI 几乎能生成和创造任何东西的世界里，基本的批判性思维可能是成功最重要的技能。
**English / Original**
It has an element of kind of physical world and more traditional engineering, not software engineering. Again, the very kinda human-centred professions. That is something I would think in terms of. And I think the other thing I always say is, like, in the world in which AI can kinda generate anything and create anything, having basic critical thinking skills may be the most important thing to success.
## 00:53:37
**中文**
我担忧能生成图像和视频的 AI 模型。我们出于多种原因不做图像和视频模型，这就是其中之一：真假极难分辨。成功的重要部分也许是拥有不被蒙骗的社会经验。当然，希望我们能打击并监管部分虚假内容。
**English / Original**
I worry about these AI models that generate images and videos. And we don't make models that generate images and videos for many reasons, but this is one of them. It's really hard to tell what's real from what's not. And so, a significant part of success may be having the street smarts not to get fooled by... I mean, hopefully we can crack down on and regulate some of this fake content.
## 00:54:05
**中文**
但假设做不到，批判性思维就极其重要。你不应相信伪造内容、抱持错误信念或遭到诈骗。这是我会给年轻人的建议。如果人类历史上的每项创新都会消灭一种核心技能，例如——
**English / Original**
But assume we can't, critical thinking skills are gonna be really important, and you don't wanna fall for things that are fake. You don't wanna have false beliefs. You don't wanna get scammed. That's really advice that I would give to someone. If every innovation in the history of humanity killed a core human skill, I'll give you an example.
## 00:54:28
**中文**
计算器削弱心算，文字降低人的记忆，那么 AI 正在削弱哪块“肌肉”？首先我不确定前提成立。我仍经常心算，也觉得即使有计算器，心算仍有用，因为它更融入自己的思考过程。
**English / Original**
If calculators killed our ability to do arithmetic, if writing reduced the memory of human beings per se, what muscle is AI killing? So, first of all, I'm not so sure. I still do math in my head quite a lot. I still find it useful to do math in my head, even without a calculator. Just because it's... it's more integrated into my thought processes, right?
## 00:54:58
**中文**
我可能想：“如果每位用户支付这么多，收入就是……”我希望能在脑中闭合这个推理回路，而不必把问题交给计算器。所以许多技能仍很相关。但如果不谨慎使用工具，确实会失去重要技能。
**English / Original**
I might wanna say, "Oh, yeah. If each user paid this amount, "then the revenue would be..." I wanna be able to close that loop in my head without having to... without having to give the answer to a calculator. So I think a lot of these skills are still pretty relevant. But, I would say that if you don't use things carefully, that you can lose important skills.
## 00:55:23
**中文**
我们已在学生身上看到这种情况：让 AI 代写文章，实质就是作业作弊，不应这样做。我们对编程做过研究，发现使用方式不同，会出现不同程度的技能退化；有些方式不会，有些会。如果人们不认真思考如何使用，技能退化绝对会发生。
**English / Original**
And I think we started to see it with students where it's, like, they have the AI write the essay for it. It's basically just cheating on homework. So, we shouldn't do that. We did some studies around code and showed that depending on how you use the model, we can see de-skilling in terms of writing code. There are different ways to use the model, and some of them don't cause de-skilling, and some of them do, but definitely, if folks are not thoughtful in how they use things, then de-skilling absolutely can happen.
## 00:55:55
**中文**
如果我们正把思考和认知外包给系统，未来十年人类整体会变笨吗？这又是《仁爱机器》和《技术的青春期》的两面。如果以错误、草率方式部署 AI，是的，人可能会变笨。
**English / Original**
Do you think humans will become stupider as a race in the next decade? Cos if we are, in a way... exporting thinking and cognition to systems... Yeah. I think if we deploy, again, it's the Machines of Loving Grace and The Adolescence of Technology. I think if we deploy AI in the wrong way, if we deploy it carelessly, then, yes, people could become stupider.
## 00:56:20
**中文**
即使 AI 在某件事上永远比你强，你仍能学习它，也仍能在智识上丰富自己。这是企业、个人乃至整个社会必须作出的选择。达里奥，你如何看开源与闭源？我看了智谱 AI、GLM-5、DeepSeek 等公司。
**English / Original**
Even if an AI is always gonna be better than you at some thing, you can still learn that thing, right? You can still enrich yourself intellectually. And so that's a choice we have to make as individual companies, as individual people, and as a society, overall. Dario, do you have a view on open-sourced versus closed? I was looking at some companies like Zed AI, GLM-5, or DeepSeek.
## 00:56:45
**中文**
如果你投入巨资创造知识产权、开展研究，而这些公司通过逆向提示和工程手段，获得接近 Anthropic 水平的答案——并非百分之百，但 GLM-5 的数字看起来不错——AI 世界里的知识产权价值究竟在哪里？如果构建应用，我能否作一个大胆推断：模型层最终会高度普及，因此每次构建智能体或应用层时都应选开源——
**English / Original**
If you spend all this money on IP creation, on research, if these guys are able to reverse prompt and engineer and get close to Anthropic-level answers, I'm not saying 100%, but I was seeing the GLM-5 numbers and they seemed quite good... where does the IP value in the world of AI lie? And if I were to be building an application, can I make the assumption, it's a far-fetched extrapolation, but can I assume that eventually the AI model layers will get so democratised that I should pick open-sourced
## 00:57:29
**中文**
因为这样有助于我保留自己的收入模式？这里有几点。第一，许多模型，尤其来自中国的模型，都针对基准测试优化，并从美国大型实验室的模型蒸馏而来。最近有项测试显示，它们在常见 SWE 软件工程基准上得分很高；
**English / Original**
every time I'm building an agent or an application layer, because that helps me retain the revenue model that I might be working with? So, there are a few things here. One is, a lot of these models, particularly the ones that come from China, are optimised for benchmarks and are distilled from kinda the big US labs. So, there was a test recently where some of these models scored very highly on the usual SWE benchmarks, the usual software engineering benchmarks.
## 00:58:04
**中文**
但有人制作此前从未公开测量的保留基准后，这些模型表现差得多。因此我认为它们更偏向基准优化，而非真实世界使用。不过还有一个更广泛的要点：模型经济学与以往任何技术都截然不同。
**English / Original**
But then when someone made a held-back benchmark, that had not been publicly measured, the models did a lot worse on that. And so, I think those models are optimised for benchmarks much more than for kind of real-world use. But I think there's a broader point than that, which is that I think that how things are being set up, the economics of the models are very different than any previous technology.
## 00:58:33
**中文**
我们发现用户极度偏好质量，有点像雇员选择。假如你可以雇世界上最优秀的程序员或排名第一万的程序员，两者都很有技能，但雇过许多人的人都直觉理解：能力呈幂律长尾分布。
**English / Original**
What we find is that there is a very strong preference for quality. It's a bit like human employees. So, it's like if I said to you, you can hire the best programmer in the world or the 10,000th best programmer in the world. I mean, they're both very skilled, but I think anyone who's hired a large number of people has this intuition that there's this power law, long tail distribution of ability.
## 00:58:58
**中文**
模型也是如此。在一定范围内，价格并不那么重要。如果一个模型最聪明、认知能力最强，那么价格和呈现形式都不太重要。因此我几乎只专注于打造最聪明、最适合任务的模型。
**English / Original**
And we find the same thing in the models. Within a range, price doesn't matter that much. If a model is the best model, the most cognitively capable model. Price doesn't matter much, the form in which it's presented doesn't matter much. So I'm focused almost entirely just on having the smartest model and the best model for the task.
## 00:59:22
**中文**
在我看来，这是唯一重要的事。再谈长期地缘政治：如果 Anthropic 是一家餐馆，原材料、蔬菜就是数据。这个问题也与我有关，因为我们正在投资一家印度本土数据中心企业。
**English / Original**
My view is that's the only thing that matters. Long-term, geopolitics. If Anthropic were a restaurant, I would say the raw ingredients, the vegetables, in this particular case, is data. Do you think the long-term-- This is also pertinent to me, the question, because we are investing in a data centre business, which is Indian in nature.
## 00:59:45
**中文**
长期来看，世界是否会走向各国拥有自己的数据，而你必须为烹饪所用的“蔬菜”支付更多？我认为有几点。世界各地都会有建设数据中心的需求，我们非常支持。数据本身正在变化，因为今天许多训练数据来自强化学习环境。
**English / Original**
Do you think, long-term, the world moves to a place where every country owns its data, and you have to start paying more for the vegetables you use to cook? Yeah. So, I mean, I think there are a few things. I do think there will be demand to build data centres around the world, and we're very supportive of that. Data's getting kind of interesting, because a lot of the data that we use today is RL environments that we train on, right?
## 01:00:15
**中文**
比如训练数学或智能体编码环境时，你并非简单取得数据，而是取得一些数学题，让模型通过实验尝试解题。它更像合成数据，是你创造出来的。也可以理解为环境中的试错。
**English / Original**
So, for example, when you train on math or agentic coding environments, you're not really getting data, like you're getting some math problems in the model-like experiments with trying the math problems. It's more synthetic, you're creating the data. Yeah, you could think of it as synthetic data or you could think of it as trial and error in environment.
## 01:00:34
**中文**
所以静态数据正在变得不那么重要，而模型为强化学习自行创造的“动态数据”越来越重要。数据不再是绝对核心，但仍然重要；现有许多数据也可直接从开放网络取得。
**English / Original**
So, I think data is becoming... static data is becoming less important and what we might call dynamic data that the model creates itself for reinforcement learning, is becoming more important. So, I don't think data is quite the most central thing any more, but it still matters. And I think to the extent that that is the case, a lot of the data is just available, just kind of available on the open web.
## 01:01:00
**中文**
不过，如果想获得针对特定语言优化的数据，它会很重要。若“数据”指客户交给你的个人或专有数据，你替其他公司处理，那么各国会制定法律——欧洲已经这样做——要求数据留在本国境内。
**English / Original**
Although, if you're trying to get data in certain languages, optimised for certain languages, that can be important. I do think if data means... the data given to you by customers, you process the data for some other company, then countries will, and in the case of Europe already have, passed laws that say that that kind of customer, personal proprietary data, needs to stay within the boundaries of the country.
## 01:01:31
**中文**
这正是在世界不同国家建设、运营数据中心，并让模型推理留在当地的原因之一。我曾就另一个问题追问埃隆，他不太愿意回答：若只能选一只非自家公司的股票投资，他选了谷歌。
**English / Original**
And that's one reason to kind of build, to operate data centres around the world at different countries, and to keep the models performing of the inference in those countries. I really pushed Elon on this particular question. He was sceptical of answering it. But I asked him to pick one stock he would put money in which is not his own, and he said Google.
## 01:01:58
**中文**
我也问你：如果达里奥今天有 100 美元，必须二选一投资一只股票以赢得资本主义游戏，你会选哪只？我最好不回答，因为我对许多上市公司了解得太多。
**English / Original**
I'm gonna ask you the question, and I know you're gonna be sceptical in it as well. If Dario had $100 today, and you had to make the binary decision of investing in a stock to win in capitalism, which stock would you pick? Yeah. I had better not answer that question, because I know so much about so many public companies.
## 01:02:16
**中文**
【两人笑】我还是不回答为好。也许可以谈一个你未涉足的行业，不过如今这种行业大概很少。确实很难说。我看好生物科技即将迎来复兴。
**English / Original**
[both laugh] I think I better not answer that question. Maybe answer the question for an industry that you're not involved in, which, I'm guessing today, is seldom the case, because you're involved in most industries. Yeah. No, it's really... I mean, I don't know. I'm positive on... I think biotech is about to have a renaissance.
## 01:02:40
**中文**
最终它会由 AI 驱动。我不点具体公司，也不判断大型制药企业与新兴小型生技公司哪个更值得押注，但直觉是我们即将治愈许多疾病。能否给一个值得关注的生物技术子领域？我看好更可编程、适应性更强的技术，例如 mRNA 疫苗，尽管它们因一些愚蠢原因在美国遇到困难。
**English / Original**
Ultimately, we'll be driven by AI. You know, I'm not gonna name a particular company, nor will I say whether I think it's better to bet on the big pharma companies or emerging smaller biotechs. But my instinct is, we're about to cure a lot of diseases. Can you give me a subset of biotech that I should focus on? Yeah. I think this idea of stuff that's more programmable and adaptive from the mRNA vaccines, although those are having trouble in the US for dumb reasons.
## 01:03:14
**中文**
我对这项技术非常乐观。肽类疗法也一样：小分子药物的自由度有限，改善一个方面可能使另一个变差；而肽具有近似数字化的属性，可以说：“我要在这里替换这种氨基酸，在那里替换另一种。”
**English / Original**
But I'm very optimistic about the technology, to, kind of, the peptide-based therapies, where, again, if you have a small molecule drug, you're like... there's only so many degrees of freedom you have, and you kind of make one thing better, the other thing gets worse. Peptides, it has this almost digital property where you can say, "Oh, I'm gonna substitute in this amino acid here and this amino acid there."
## 01:03:38
**中文**
这允许更连续的优化，因此我看好这些领域。细胞疗法也可能如此。是干细胞吗？不是，例如 CAR-T：从身体取出一些细胞，经基因工程改造使其攻击特定癌症，再放回体内。
**English / Original**
So it allows for more continuous optimisation. So, I think those kinds of areas I would be optimistic about. Maybe also cell-based therapies, which is like a new-- -Stem cell? -No, no, no. So, things like, I don't know, like the CAR T therapy, where you kinda genetically engineer your... Basically, take some cells out of your body, genetically engineer them to attack a particular cancer and put them back in the body.
## 01:04:12
**中文**
干细胞疗法有效吗？我上周整周都在做，每天去医院三小时，接受雾化并把干细胞注入静脉。我不了解干细胞疗法的最新情况，你需要问仍在执业的生物学家。不过肽类会爆发，对吧？它的设计空间确实很广。
**English / Original**
Do stem cell therapies work? I spent the whole of last week doing this. I was at a hospital for three hours a day, getting nebuliser and stem cells into my veins. I am not up on the latest of stem cell therapies. You'd have to ask a currently practising biologist. But peptides, I think, will blow up, right? I mean, again, the design space is very broad.
## 01:04:35
**中文**
我第一次使用 Claude Code 时确实很难让它运行。对一个完全没有编程知识的人来说，它并不特别容易，有学习曲线。有人说提示工程也像弹钢琴，不能一坐下就会。
**English / Original**
Right. When I tried to use Claude Code for the first time, I did struggle to get it to work. It was, for somebody who's very stupid and has no coding or programming knowledge, it's not... it's not very, very easy. I think there's a learning curve. I heard someone say, "Well, it's like, even prompt engineering is like playing a piano.
## 01:04:59
**中文**
对零基础的受众而言，在哪里学习、如何设置上下文、如何写提示、如何更好使用 Claude Code 越来越重要。你建议怎么学？首先，我们正努力让学习曲线更平缓。
**English / Original**
You can't sit and start playing it." To my audience, I think it becomes increasingly relevant where to learn, how to set context, how to prompt, how to use Claude Code better for somebody like me who comes with zero knowledge. Can you recommend how one does that? Yeah. I mean, first of all, I would say, we're trying increasingly to kind of make that learning curve easier.
## 01:05:24
**中文**
发布 Claude Cowork 的一个原因是，它相当于面向非程序员的 Claude Code。我们看到许多非技术人员很想用 Claude Code，却不得不艰难穿过命令行终端。程序员每天都用终端，但对非程序员而言，它只会带来不必要的复杂性。
**English / Original**
So, one of the things that caused us to release Claude Cowork, which is basically Claude Code for non-coders is, oh, man, we were noticing a bunch of non-technical people who really wanted to use Claude Code and were struggling through the command line terminal to do that. Which, it's like coders use the command line terminal all the time, but non-coders, it just kind of makes things unnecessarily complicated.
## 01:05:49
**中文**
Cowork 后端由 Claude Code 引擎驱动，但目标是提供更友好、更易用的界面。我们会继续推出降低门槛的界面。此外，也可以参加课程学习。
**English / Original**
So, Cowork was designed to be more of... it was powered by the Claude Code engine on the back, but the idea was to kinda make it more user-friendly and easier to use. So, we're definitely trying to introduce interfaces that make it easier. But I would also say that there's classes you can take that help you learn this thing.
## 01:06:19
**中文**
这是一门高度实证的学问，主要靠实践学习。Anthropic 内有个部门叫“教育部”，未来会发布更多关于如何有效运行智能体、如何提示模型的视频。我们已经做了一些，并会加大力度。
**English / Original**
Now, I think it's a very empirical science. You mostly learn by doing. But Anthropic has part of the company that we call the Ministry of Education. And I think, increasingly, we'll put out videos on how to run effective agents and how to prompt models. We've already done some of that, and I think we're gonna... we're gonna ramp it up.
## 01:06:37
**中文**
因为我们确实希望每个人都能学会。最后一个问题：你有没有某个一闪而过的念头，希望我们牢记？达里奥知道什么，是 Nikhil 和他的所有受众不知道的？我不觉得自己知道很多别人不知道的事，尤其如今技术影响已经摆在眼前。
**English / Original**
Cos we do want everyone to be able to learn this. Any fleeting thought, last question, like you want to leave us with something that we should bear in mind? What does Dario know that Nikhil and all of Nikhil's people do not? Yeah. I mean, I don't know that I know that many things, particularly now that the implications of the technology are kind of out there.
## 01:06:59
**中文**
我世界观的大部分内容都可以从公开可见的事实、从外部世界推导出来。但过去十年我反复经历的一点是：人们总倾向于相信，“那不可能发生。
**English / Original**
So, I mean, it can all be... I think most aspects of my worldview can be derived from what's publicly visible now, from what we can see, kind of outside in the world. But the thing I would say, and it's an experience I've had over and over again over the last 10 years, is there's this temptation to believe, "Oh, you know, that can't happen.
## 01:07:23
**中文**
那太怪了，变化太大了。肯定已经有人在处理。如果真的发生就太疯狂了，似乎没人相信会发生。”然而一次又一次，只需外推一条简单曲线，或认真推理未来，就会得到几乎无人相信的反直觉结论。
**English / Original**
It would be too weird. It would be too big a change. I'm sure people are on that. It would be too crazy if that occurred. No one seems to think that'll happen." And over and over again, just extrapolating the simple curve or trying to reason out what will happen, leads you to these counter-intuitive conclusions that almost no one believes.
## 01:07:45
**中文**
这几乎像可以免费预测未来：只要说“按理而言……”当然你需要一些实证知识和直觉，不能仅靠纯逻辑推演；这也是我常见的另一种错误。但把少数实证观察与第一性原理思考正确结合，就能以人人都可获得的公开信息预测未来，只是现实中出奇地少有人这样做。
**English / Original**
And it's almost like you can predict the future for free [chuckles] just by saying, "Well, it stands to reason that..." And you need some empirical knowledge. You need some intuition. You can't reason from pure logic. I think that's another type of mistake that I see people make. But the right combination of a few empirical observations with just thinking from first principles can allow you to predict the future in ways that are publicly available and anyone should be able to do, but that happens surprisingly rarely.
## 01:08:21
**中文**
达里奥，感谢参与，希望很快再见。谢谢。谢谢。干杯。好。很棒。刚才还好吗？很好。【笑】
**English / Original**
Thank you, Dario, for doing this and hope to see you again soon. -Thank you. -Thank you. -Cheers. Yeah. -All right. -Good. -Was that okay? -Yeah, seemed great. -[chuckles]