# (77) A Conversation with Dario Amodei and Marc Benioff | Dreamforce 2025 - YouTube
- Transcript ID: `wuojtr1511m`
- Source tier: `youtube_auto`
- Original language: `en_or_source_language_unlabeled`
- Translation status: `agent_translated_reviewed` (73/73 chunks)
- Original source: https://www.youtube.com/watch?v=wUOjTR1511M
- Raw evidence: `data/transcripts/youtube/wUOjTR1511M.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。
## 00:00:07
**中文**
好了，各位下午好。大家玩得开心吗？——太棒了，精彩极了。准备好看 Metallica 了吗？——准备好看 Benson Boone 了吗？要去看 Metallica 的请举手。太好了。期待 Benson Boone 的有谁？——好吧，看来两边都有，我也说不准。下面有请 Dario。
**English / Original**
All right. Good afternoon, everybody. Are you all having a good time? >> Oh, fantastic. Amazing. Are you ready for Metallica? >> Are you ready for Benson Boone? >> Raise your hand if you're going to Metallica. Awesome. Who's looking forward to Benson Boon? >> All right. Well, so we got a It's kind of a mix. I don't know. Um, please welcome Daario.
## 00:00:39
**中文**
——嗨，Marc，谢谢你邀请我。Dario，很高兴你来，欢迎。——谢谢。——我们非常高兴邀请 Dario 来，把他介绍给现场各位。我们一直有很棒的合作，多次交流，一起服务客户，也共同开发了一些技术。能在 Slack 的新 Slackbot 中使用你们的模型，令人兴奋。我常向许多朋友谈起你；我们已经彼此熟悉，但很多人还不了解你。也许你可以先给大家讲讲……
**English / Original**
>> Hey, Mark. Thanks for having me. Great to have you, Dario. Welcome. >> Thank you. >> Uh, we're really excited to have you, Daario, and introduce you to the audience and everybody here. And, you know, we've had such a great partnership. We've had an opportunity to speak so many times and um you know work with some customers together and uh also build some technology together. It's been exciting to use your model inside Slack with our new Slackbot. But you know, as I've talked to so many of my friends about you, we've gotten to know each other, but a lot of people don't know you. So maybe you could tell a
## 00:01:20
**中文**
……你自己，包括早年的经历和来自哪里。我也会穿插问几个核心问题，不过先从头说起。——当然。我就是在旧金山长大的。起初我感兴趣的是科学，而不是技术本身。我读研时研究神经科学，后来在斯坦福做计算生物学博士后。当时我努力解决生物学问题，试图理解癌症等人类面临的疾病，也试图……
**English / Original**
little folks about a little about yourself, kind of your beginnings, where you're from, you know, and also kind of uh I'll ask you a couple of the core questions along the way, but to take it from the start. Yeah, absolutely. So I grew up right here in uh in I grew up right here in San Francisco. I was uh originally interested in science, not in uh not in tech per se. So you know I did my did my uh uh graduate work in uh neuroscience as a posttock in computational biology at at Stanford and you know as I was working hard on solving the problems of biology you know trying to understand the diseases we we we face like uh like cancer and to
## 00:02:02
**中文**
……理解生物学。我注意到，生物学的复杂程度似乎超出了人类能够把握的尺度。看过人类代谢图的人就会明白，那种复杂性远超人力，我甚至开始担心我们是否还能以任何像样的速度取得进展。几乎就在我思考这个问题时，Google 和多伦多大学出现了最早一批深度神经网络研究。我看过之后亲自复现了一些结果，心想：天哪，这东西真的有效，而且一定会大有发展。于是我转入 AI，后来去了……
**English / Original**
understand biology one of the things I noticed is that the complexity of biology felt like it was beyond human scale you know and I was starting to despair a little bit that that we would be able to make progress at any speed just because of you know if you've ever seen one of these diagrams of human metabolism it's just it's just beyond human scale but almost exactly at the time that I was wondering about this out of Google out of University of Toronto came the first work on deep neural networks uh and I looked at it you know I I replicated some of the results myself I said my god this stuff really works this stuff's really going to go there so I went into AI ended up working
## 00:02:40
**中文**
……Google；OpenAI 创立初期我加入了那里，并领导研究工作多年。我也是记录这项技术指数级扩展趋势的人之一。后来成为 Anthropic 联合创始人的同事和我，是最早研究技术规模化规律的一批人。到 2019 或 2020 年前后，我有了两个认识。第一，AI 的规模真的会一飞冲天，整件事会重塑经济。虽然要花几年，但它确实会重塑……
**English / Original**
at um uh Google I joined open AI I in the early days I led research there for for for several years um uh and and and you know was one of the people who kind of documented this trend of exponential scaling of the technology um you know myself and the folks who eventually became the anthropic co-founders were among the first to uh study the scaling of the technology and so you know around 2019 or 2020 had really two realizations one was wow AI is is really going to you know it's going to It's going to scale to the moon and it's really going to be you know this whole thing is going to reshape the economy. It'll take a few years but it's going to reshape the
## 00:03:20
**中文**
……经济，而现在我们几乎已经走到那里。第二，这些系统不同于普通软件。普通软件的每一行代码都是人写的；构建它像盖摩天大楼，要画蓝图、设计每一个部分。AI 反而更像生物系统，是有机生长的：你是在培育模型。
**English / Original**
economy and you know they are almost there now. Um uh and and the second was look there's you know these systems are different from ordinary software. You don't write every line of code right building ordinary software it's like building a skyscraper or something. You make the blueprint you make everything to design. This is ironically a bit more like biological. It's organic or something. You're growing these models.
## 00:03:43
**中文**
你设定的是一套高层配方，就像种植物或烤蛋糕。这种不可预测性，再加上巨大的经济影响，意味着安全与责任至关重要。我们既要让模型表现得可预测，也要在部署模型、让它们对世界产生巨大影响时确保负责任。因此，这两点构成了我和另外七位离开 OpenAI、创办 Anthropic 的联合创始人的基本理念。之后的事大家都知道了。Anthropic 到现在已经……
**English / Original**
You set a high level recipe. It's like growing a plant or baking a cake or something like that. And that unpredictability combined with the incredible economic impact means that safety and responsibility are going to be very important to make sure that the models behave predictably as well as as we deploy them and they have enormous impact on the world. We you know we we need to make sure that we deploy them responsibly. And so those were kind of the two pillars on which myself and the seven co-founders um who left OpenAI to to found Enthropic um you know generally generally based our generally based our view uh and you know the the the rest is history. Enthropic has been um you know
## 00:04:22
**中文**
……成立四年半，发展非常快。按收入衡量，我们目前在企业客户和企业收入上至少占有相对多数，甚至可能已占过半，而其他多数参与者更专注于消费市场。正如你这位企业型公司的管理者所了解的，信任与责任这些价值观和服务企业其实相辅相成：它们帮助我们服务企业，而以企业为中心的商业模式又强化了我们的价值观。
**English / Original**
around for 4 and 1/2 years. Um we're growing very quickly. um you know I think we're we're at this point um by revenue have at least a plurality perhaps the majority of uh um you know enterprise enterprise customers and enterprise revenue while most of the other players are are focused on the consumer side and we find that you know as as you know I think you would know from running an enterprise focused company these these values of trust and responsibility you know are really are synergistic with serving the enterprises right these values help us to serve the enterprise and Having a business model that serves the enterprise helps to reinforce our values.
## 00:05:01
**中文**
——有一件事：你很快讲完了创办公司的过程，仿佛一路从 Google、OpenAI 飞奔到 Anthropic，但你没有提到你妹妹。我们刚认识时，最令我惊讶的一点，就是你和妹妹一起经营这家公司。能讲讲这段创业故事吗？
**English / Original**
>> One of the one of the things um and you went pretty fast into kind of starting the company and kind of shot out of uh uh uh shot through uh Google and API to Anthropic, but you didn't mention your sister and that was like one of the things that first really shocked me when we started to get to know you was you and your sister together are working on this company and can you kind of tell us the origin story?
## 00:05:25
**中文**
——可以。公司有七位联合创始人，Daniela 和我是其中两位。刚才说过，我们都在旧金山长大，也都上过 Lowell 高中。很早的时候，我们就认定自己想要做……——我妈妈也上过 Lowell，她就坐在那里，听到这个一定会很高兴。
**English / Original**
>> Yeah. Yeah. So, you know, there are seven co-founders and me and Daniela are are two of them. As I mentioned, we both, you know, we both grew up in San Francisco. We went to to LOL High School and, you know, even even very early on, we really figured that we wanted to do >> My mom went to LOL and she's sitting right there. So, she's going to be very happy about that.
## 00:05:43
**中文**
——太巧了。那里确实是一所很棒的学校。Daniela 比我小四岁，所以我们从未同年在校。我在那里读了四年，接下来的四年她在那里。我们很早就怀有一种愿望：想做成一件事，做些对世界有益的事，完成某种宏大的事业，而且要一起做。
**English / Original**
>> Amazing. Um, uh, no, no, it was it was it was a great place. I actually didn't over Daniela was four years younger than me, so we were never there at the same year, but I was there for four and then, you know, the next four years she was she was there. So um uh yeah you know very early on you know we we we had these you know these ambitions to you know to to do something to do something good for the world to have some kind of grand project and and to work together.
## 00:06:06
**中文**
我想很多人——或者说很多兄弟姐妹——都有这种愿望，但不知怎么，机缘最终让我们真的做到了。她在 2018 年加入我所在的 OpenAI。后来，我们两人和一些共事过的人——其中许多也是多年的朋友——决定创办 Anthropic。我和 Daniela 实际上共同管理公司。她负责公司的日常运营。
**English / Original**
I think I think many many people you know kind of or many siblings I guess have these have these ambitions but you know some somehow things found their way to us actually actually being able to do it. So um uh you know she joined me at at she joined me at OpenAI in uh uh 2018 um and then the two of us along with some folks we worked with many of whom had been longtime uh uh friends decided to start Anthropic. So me and Daniela essentially essentially run the company together. You know she's responsible for the dayto-day running of the company.
## 00:06:41
**中文**
她负责公司如何搭建、组织如何运转、采用什么流程，也承担了相当多业务架构方面的工作。没有她、没有她处理这些事情，我根本无法管理公司。我则更侧重战略：研究走向何方，公司的战略规划是什么，如何看待安全、公司在世界上的角色以及愿景。我认为这是一种非常好的……
**English / Original**
you know, kind of operate, you know, how how the company is put put together, how the org runs, what its processes are, does, you know, kind of kind of a fair amount of the the the, you know, kind of the business on the on the the business on the structural side. Um, uh, you know, I I I I just, you know, couldn't couldn't run the company without her and without her without her doing all those things. Um you know I tend to think about the strategic side where the where the research is going what our kind of you know plans are as a company strategically how we think about safety how we think about the company's uh uh role in the world and and the vision and and I find that's a very good um that's
## 00:07:22
**中文**
……分工和职责划分。我们两个人都能做这两部分，但在运营模式和愿景模式之间切换很困难；分开负责，双方都能更高效。——谢谢你让我重新问到这一点。这是公司、文化和你们合作方式中很精彩的一部分。去年 Daniela 来到这里，今年则是你。我们从一开始就认识你们。Salesforce 似乎还持有 Anthropic 一点点股份，所以我们很高兴能成为投资者。
**English / Original**
a very good split that's a very good separation um because both of us can do both pieces but it's it's really hard to switch between a kind of operational mode and a vision mode and I think both people can be more effective if you if you split. >> Thanks for allowing me to come back to that because I think it's such a great part of the company and the culture and how you're working and last year she was here and now this year you're here. Um and we've known you all from the beginning. I mean I think Salesforce owns like a some little point or something of anthropics. So we're very happy to be an investor.
## 00:07:53
**中文**
——非常早期的投资者。——对，非常早，我们相信你们。——我记得你们投资时估值是 40 亿美元，对吗？——我不记得了，但不论多少，当时都太高。——我还没说完呢。——在说太高之前，你应该算算从那以后翻了多少倍。——好吧，到目前为止我们赚到钱了。
**English / Original**
>> Very early investor. Very >> very early investor. Believe in you. >> I think you I think you invested when the valuation was 4 billion. Is that correct? >> I I don't know but it was too high. whatever it was. >> I haven't. >> Before you say it's too high, you should calculate how many times it's gone up since then. >> Okay. We made money so far.
## 00:08:10
**中文**
——显然，我们非常高兴能参与你们的旅程，也非常喜欢与你和 Daniela 合作。回到你和妹妹及朋友在旧金山创业的故事：当时我们正整合这里的一些办公地产，后来谈到由你们接手 Slack 大楼；我们刚刚收购 Slack。——而我们确实接手了。
**English / Original**
>> Well, um, no, I I'm thrilled obviously that we're part of your journey and, uh, you know, we love working with you. We love working with Daniela, um, so much. And you know, I think kind of getting back to this story of you and your sister and your friends, you know, starting this company here in San Francisco and then you came to us, we were starting to consolidate some of our real estate here and then you, you know, we had a conversation about you taking over the Slack building. We had just bought Slack, >> which we have done.
## 00:08:37
**中文**
——现在你们就在 Slack 大楼里，和我们一样临着公园，从窗户还能看到 Salesforce Tower。——据说我的办公室以前是 Stewart 的。——以前是 Stewart 的办公室，很好。想到这一点很有意思：你是土生土长的旧金山人，和我们一起就在公园旁、塔楼旁；我们又是公司的投资者。如今你们的模型显然已成为 Slack 的关键组成部分，没有它几乎无法使用 Slack；同时你们又站在模型发展的最前沿，真的很了不起。
**English / Original**
>> And now you're in the Slack building. So, you're right on the park with us looking at the tower from your window. >> I I believe my office is what I I was told it was formerly Steuart's office. >> Formerly Steuart's office. Very good. And I would just, you know, it just just occurred to me like here you are. You're the San Franciscan. Um, you're right on you're right on the park with us. You're right on the tower with us. We're an investor in the company. Um, it's, you know, obviously a critical part of Slack today, right? In terms of how you couldn't use Slack without it, but you're at the very bleeding edge of these models. It's really incredible.
## 00:09:12
**中文**
而且你从一开始就极具远见。你在 OpenAI 时我还不认识你，是你创办公司后我们才相识。谈谈你的预期吧：从你走出那扇门、向 Sam 告别，然后对 Daniela 说“我们要把这件事做起来”，到现在不过四年半、五年，什么最出乎你的意料？——有太多这样的时刻了，因为过去四年半整体上都充满惊喜。
**English / Original**
And you've really been visionary uh, right from the very beginning. And when I didn't know you when you were at OpenAI, I only met you after you started the company. So just now kind of take us through your expectation. What has been your biggest surprise, you know, since it's only been what, four and a half, 5 years since you kind of walked out the door, said goodbye to Sam, right? And then you just said, "Okay, Daniela, we're going to we're going to get this going." What what was your biggest shock right there? Yeah, I mean, you know, there were there were so many moments because I think that, you know, the last four and a half years were were just so surprising overall.
## 00:09:49
**中文**
从宏观上说，这里有一种反差：一方面，过去四年半发生的一切，某种意义上都已被我用扩展定律画出的那些直线预测过——巨型数据中心的建设、收入每年增长十倍、AI 在整个经济中的应用，都能从纸上的几笔线条里看出来。但亲眼看到它真的发生，仍然非常震撼。
**English / Original**
Um, you know, I think I think at a high level there's a dichotomy where on one hand, everything we've seen over the last 4 and 1/2 years was in some sense predicted by those straight lines on graphs that I made with the scaling laws, right? these enormous data center buildouts, the way that our revenue is going up, you know, 10x per year, the the use across the economy. You could you you know, you could see it all in these scribbles on the page. But actually seeing it play out is is wild.
## 00:10:18
**中文**
而许多具体发生的事情，是我从未料到的。如果只能选一件最意外的，那就是：我们离开一家公司，创办了另一家公司。随着公司发展，你会从招聘的人以及公司作出的选择中，真正看到两条道路逐渐分岔、形成差异。OpenAI 明显走向了消费市场。
**English / Original**
And and a lot of the individual things that that I'm seeing happening, I just I just never would have I never would have expected. I guess if I were to pick one most surprising thing, it is, you know, we left one company and started another company. And uh something you see over time is that is that as you build a company, you really do see through the people you hire, through the choices that the company makes, you kind of see the paths diverge and you see differentiation, right? OpenAI has gone very much in the consumer direction.
## 00:10:52
**中文**
而我们明显走向了企业市场，处理问题的方式也很不相同。于是市场里出现了两家公司，仿佛一次自然实验：它们采取截然不同的路线，又同时存在于同一生态系统中。
**English / Original**
We've gone very much in the enterprise direction. we've taken, you know, just just the way we approach things is is very different. And so you have this market structure where there are these two companies that are like it's sort of a natural experiment. They're they're just taking a very different approach. Both exist in the ecosystem, but but the approach they take is very different.
## 00:11:10
**中文**
——再回顾你在 Google 的经历。Google 的 Gemini 也是顶尖模型，你怎么看他们？算是两种路线的融合吗？——Google 是我们的合作伙伴和投资者，当然它的模型同时也与我们竞争。不过我认为这种“竞合”正越来越常见。行业有芯片层、云层、模型层、市场进入与分发层，许多公司同时参与多个层级，所以……
**English / Original**
>> And then you have to reflect back at your time at Google as well. They're also very much with Gemini and, you know, very much a top model as well. How do you look at them? Do you look at them as a blend then? Yeah, I mean, you know, Google's a partner to us. They're an investor in us. Obviously, their models compete with us, compete with us at the same time. But I think this co-optition dynamic is becoming more and more common, right? As we have all these layers, we have like the chip layer, the cloud layer, the the kind of model layer, the the like the like go to market and distribution layer, and various companies are involved in more than one of these layers. and and so I
## 00:11:47
**中文**
……公司在一个领域合作、在另一个领域竞争并不罕见，非常正常。此外，我和 Google 背后的一些人很熟。我与负责 Google 研究的 Demis 做了大约十五年朋友。他可能是极少数比我更早看到这项技术潜力的人之一，也和我一样有神经科学背景。因此，即使两家公司存在竞争，我们仍能相处得很好。
**English / Original**
think it's not uncommon for companies to cooperate in one area and and compete in another area. It's fairly normal. I think it's also been helped by, you know, I I I know quite well some of the folks behind Google. I've been, you know, friends with with Demis for uh who, you know, who leads uh who leads research at Google for something like 15 years, right? I think he was maybe one of the only people who was earlier than me in in seeing the potential of the technology. He also has a neuroscience background like me. So I you know I think that helps us to get along even as there are some competitive aspects between the companies.
## 00:12:21
**中文**
——他今年获得诺贝尔奖时，你有什么反应？——我非常替 Demis 高兴。当时我正在写一篇谈 AI 在生物学中潜力的文章，叫《Machines of Loving Grace》。就在准备发表的前两天，Demis 和 AlphaFold 团队的同事获得了诺贝尔化学奖。因此我最终把文章献给了 2024 年因 AlphaFold 获得诺贝尔化学奖的获奖者，因为那正是……
**English / Original**
>> What was your reaction when he won the Nobel Prize this year? >> Uh I I was I was very happy for uh Demis. Uh uh actually you know I was writing this essay about the potential of AI in biology called machines of loving grace. And two days before I was about to publish it of course Deis and his colleagues Alphafold won the won the Nobel Prize. So um uh you know I I I ended up dedicating the essay to the 2024 you know w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w w of the Nobel Prize in chemistry for for AlphaFold because it
## 00:12:50
**中文**
……我所描述的未来的一个实例。——非常令人兴奋。回到你和 Daniela：你们在旧金山经营公司，公司一路增长。你现在观察到的模型特征中，哪些最令人意外？看着下一代又一代模型展开，什么最让你兴奋？
**English / Original**
was an example of the future that I was talking about. >> Very exciting. So just getting back to you and Daniela and you're working on and growing the company and up it goes and you're doing it right here in San Francisco, you know, what are some of the characteristics and the models that you're looking at now that are most surprising? What what's really exciting about, you know, as you as you see the next next generations of these models unfold?
## 00:13:13
**中文**
——总体而言，是能力向“智能体能力”的跃迁，也就是能够真正做事情。——刚才是什么词？我没听清。——抱歉，智能体能力，把模型变成智能体……——哦，我明白了。——别担心，Dario，我只是右耳听力有点弱。——我真以为你没听见。
**English / Original**
>> Yeah. You know, I think broadly it's the jump to being able to do agentic abilities. Being able to do things. >> What was it? I didn't hear the word. >> Oh, sorry. Agentic abilities. Um, uh, uh, uh, turning the models into agents that Oh. Oh. Oh. Oh, I see. You've been I >> don't worry about it, Dario. Don't worry. I I wasn't. I just wanted I'm a little weak in my right ear. genuinely thought you didn't hear.
## 00:13:37
**中文**
——明白了。——刚才挺好笑的，对吧？“智能体”当然是个流行词，而你可能比多数人都更推动了它的流行。但我认为它确实代表真实变化：模型能以前所不能的方式端到端完成任务。目前这种现象在编程中比其他领域更明显，不过代码其实只是领先指标；金融服务、医疗健康等任务，以及……
**English / Original**
>> I see. I understand. >> Um, >> uh, yeah, it was very funny, wasn't it? >> Definitely a buzz word and you've, you know, perhaps contributed more more to mo more than most to to making it to making it a buzz word. But I, you know, I think I think it's I think it's a real thing, which is being able to do tasks end to end in a way that was not possible before. And I think we see it more uh you know in code than uh you know we see it in in any other area. But I think code is just a leading indicator honestly in other tasks in tasks like financial services in tasks like you know health and medical in tasks like uh
## 00:14:20
**中文**
……保险、制造业等我们合作涉及的许多受监管行业里，智能体同样有价值。人们同样希望端到端完成工作。以销售、市场进入和客户管理流程为例，你希望把许多环节串起来，让模型吸收大量上下文，学习这项、执行那项、访问各种信息。因此价值完全相同，只是程序员属于早期采用者；他们接受新事物很快，让我们提前看到了未来。我认为……
**English / Original**
you know insurance or manufacturing many of the regulated industries that were working together on our on our on our partnership. Agents are agents are just as you know valuable. you just as much want to do things end to end, right? You think of the, you know, the sales and go to market and, you know, customer management workflows. You want to string a bunch of things together and you want the models to pull in a bunch of things in the context and learn this, do that, access this information. Um, so it's it's just as valuable. It's just the coders are early adopters. So, you know, they've they've kind of given us a glimpse of the future because they they adopt things so quickly. But I think
## 00:14:56
**中文**
……其他领域也会出现类似的跃升。我想就此问几个问题。我们最早几次交谈时，就讨论过这种理论，尤其是 AGI 及其未来潜力。几年前，人们对 AGI 的定义大致是：模型近乎递归地构建自己、成长和进化；它知道自己在编写自身代码，能够编码、强化自己，然后自行发展。今天早些时候 Brett Adcock 在台上说到……
**English / Original**
we're going to see a similar spike in in other areas. So I want to ask you I have a few a few questions in that area. So the f you know when we first started getting in probably I think one of our very first conversations we were starting to talk about this theory and also AGI especially and what the potential in the future and AGI at that time and this is kind of now we go back several years was kind of being defined as yeah the model is almost kind of recursive it's building itself it's growing it's evolving it knows it is coding itself it can code and then it's it's enhancing and it's off and going off and you know we had Brett Adcock on the stage earlier today and he was talking about how kind
## 00:15:36
**中文**
……一个仿佛出自《We Are Legion (We Are Bob)》的场景：机器人已经启程，开始向未来无限自我复制，产生无穷多个机器人，听起来非常有感染力。几年前我们谈到那个阶段时，设想也是模型开始构建自身、让自身成长。
**English / Original**
of like had a scene out of you know we are Bob we are Legion that the robot had taken off and was now you know self-replicating into the future and you know an infinite number of uh you know uh robots it was it was incredibly compelling would go off and that was that you know to this to that point a few years ago when we were talking it was like well now the model is kind of building itself It's growing itself.
## 00:16:03
**中文**
它在自我发展。但现实并不完全如此，对吧？我们还没到那个阶段吧？——我会把两件事分开。谈论未来 AI 时，整件事难免带上一层科幻光泽。它作为比喻有帮助，却也可能让人分心，因为它会把所有人的思维带入一种未来幻想模式。不过确实有些事情是真的：其中一件是，我们每三个月都会做出一个……
**English / Original**
It's develop. It didn't turn out exactly like that though, right? Or it's not we're not at that point yet, are we? >> Yeah. So, you know, I would separate two things. There there's I think inevitably as we, you know, talk about AI in the future, this kind of sci-fi sheen on on on, you know, the on the whole thing. And that's, you know, in a way it's helpful as a metaphor, but also it can be distracting because, you know, it just it just kind of conjures everyone's mind into this into this kind of uh, you know, into this kind of uh, you know, future dreamy mode. Um, uh, but, you know, I think there are some things that are real. One thing that's real is that, you know, every 3 months we make a model
## 00:16:39
**中文**
……比上一个更聪明的模型。模型的确在逐步达到在大多数任务上超过大多数人的水平，也许某一天会在所有任务上超过所有人。另一件真实的事是：模型并非以“某个具体模型副本制造下一代模型的具体副本”这种方式构建自身；我们没有自我复制的纳米机器人或机器人。但确实正在发生的是，在 Anthropic 和其他地方，我们正用 Claude 帮助开发基于 Claude 的产品，也帮助训练下一代 Claude……
**English / Original**
that's smarter than the month than the model we made before. And indeed, the models are slowly getting to where they're, you know, better than most humans at most things. maybe at some point better all humans than all things. The other thing I think is real is you know the model is not building itself in the sense that like I have a specific copy of the model that's like making a specific copy of the the you know the the next model you know we don't have our self-replicating you know nanobots or robots or or whatever but but what absolutely is happening is that within anthropic and elsewhere we are using claude to help build products on top of claude and to help train the next claude
## 00:17:19
**中文**
……并更快地提供 Claude 服务。六个月前我预测，六个月后 90% 的代码将由 AI 模型编写。有人认为这个预测错了，但在 Anthropic 以及我们合作的许多公司里，这绝对已经成真。——你的意思是，如今 Anthropic 90% 的代码都由模型编写？——在许多团队里是这样，但不是每个团队都完全一致。——你们有没有提供可审计的材料来说明这是怎么发生的？——团队负责编辑和监督，但你可以让 Claude……
**English / Original**
to help serve serve quad faster. Um, you know, 6 months ago I I made this prediction that, you know, in in 6 months 90% of code would be written by by by AI models. Some people think that prediction is wrong, but within Anthropic and within a number of companies that we work with, that is absolutely true. Um now 90 you know >> so you're saying that 90% of all code adenthropics being written by the by the model today >> on on many teams you know not uniformly every >> is that something that you've kind of provided something kind of >> something auditable around that or like shown how that's happened. Yeah, the teams play an editing and supervisory role, but you know, Claude can both you
## 00:17:59
**中文**
……“编写这个功能”，Claude 会把它完成，人类再审阅代码，或者请另一个模型、另一个 Claude 副本协助。有时我们也会遇到长期难解的缺陷。训练最新发布的 Claude 时，集群曾因某个缺陷而无法工作。
**English / Original**
can say write this feature and Claude will do it and the human kind of looks over the code or asks for help from another another model, another copy of Claude. Um uh the other thing is sometimes we have these long running bugs. you know, when we were training our our the most recently released Claude, it was like, you know, the cluster was broken. There was this bug.
## 00:18:20
**中文**
工程师花了几天仍没解决。于是我们对 Claude 说：“你就在集群里试试看，能不能找出哪里有问题。”Claude 找到了一个极其隐蔽、工程师遗漏的缺陷。那一刻，Claude 就像一位才华横溢的队友。那么，如果 Claude 已经编写 Anthropic 90% 的代码，你们是否需要更少的工程师？什么时候会达到 95% 或 99%？
**English / Original**
Engineers were spending a few days on it. And, you know, we just we just went to Claude and we said, I don't know, just kind of play around with the cluster and see if you can figure out what's wrong. And, you know, Claude found this just super obscure bug that the engineers had missed. So, this this was one area where it was like Claude is like having a very talented teammate. So if claude is now running writing 90% of all of the code in enthropic do you need less engineers if 90% of all the code when will it be 95% or 99%.
## 00:18:48
**中文**
——人们可能会误解成：Claude 写了 90% 的代码，就意味着我们要解雇 90% 的软件工程师。但如果你了解比较优势原则……——可是你曾对解雇高管发表过一些非常激进的看法。——那个……——我只是想把二加二算成四。
**English / Original**
>> Yeah. So you know I you know I think people can misinterpret it as you know you know like claude writing 90% of the code means we're firing 90% of the software engineers. But you know if you're familiar with the principle of >> but you have made some very aggressive comments around firing executives >> that that so um >> I just want to put two and two together to get four. Okay.
## 00:19:12
**中文**
——嗯，如果……——认识你这么久，我学会了一件事：必须回来再问一次限定性问题。因为你说得很快，我努力跟上你的思路；这非常精彩，但我想确保自己准确理解了你的意思。
**English / Original**
>> Um uh so uh um you know if >> one thing I've learned in knowing you for so long is I have to come back and kind of like get that qualifying question again. Yes. Because you're go you know you you're you're going fast. So trying to I'm trying to keep up with you and it's amazing but I want to just make sure I understand exactly what you're saying.
## 00:19:32
**中文**
——当然，我逐项解释。在比较优势下，Claude 编写 90% 的代码，通常意味着你仍需要同样多、甚至更多的软件工程师，因为他们的杠杆作用更大了。他们可以专注于编辑代码的 10%，编写最困难的 10%，或者监督一组 AI 模型。结果是生产率可能提高十倍，因为剩余的 10% 与不断提高产出能力的 AI 系统形成互补。因此……
**English / Original**
>> Yes, absolutely. Let me let me let me take them one by one. So um uh you know under comparative advantage if Claude is writing 90% of the code what that means usually is you need just as many software engineers you might need more because they can they can then be more leveraged. they can focus on the 10% that's editing the code or writing the 10% that's the hardest or supervising a group of a of AI models. And so what happens is, you know, you can just end up being 10 times more productive because the remaining 10% is is now a complement to the to the AI system that's that's getting much better at at getting much better at what it's producing. So So
## 00:20:14
**中文**
——你真正的意思是工作会重新平衡。——不是替代。——不是替代，而是重新平衡，明白了。——但当 90% 变成 95%、99%，最终实现端到端完全自动化时，可能会来到一切既有判断都不再适用的时刻。——你预计什么时候？这可是一次巨大的跃迁。
**English / Original**
>> it's a rebalancing of the work is what you're really saying. >> It's it's not a replacement. >> It's not a replacement. It's a rebalancing. Oh, okay. >> As that 90% goes to 95 99 totally automated end to end, there may be some point at which all bets are off. >> What's your time frame for that? You It's a pretty big jump there.
## 00:20:31
**中文**
——很难判断，但我们一直在密切关注，也一直寻找促进互补的方法。——你认为这是短期还是长期的事？五年目标还是一年目标？——短期内我对互补关系持乐观态度。但放眼两年到五年，我确实担心整个经济会遭遇足够大的扰动。不是说人类将无事可做，而是劳动力市场会受到冲击；本质上它与以往技术带来的变化并无不同，只是……
**English / Original**
>> It's very hard to say. Um, but you know, we're looking at it. We're looking at it closely. We're always looking for ways to encourage complimentarity. >> You see that in the short term or the long term? >> Um, I you know, >> is that a 5year goal or a one-year goal? >> I'm optimistic about 10 year goal. >> I'm optimistic about complimentarity in the short run. I you know I I I I I do worry as we get out to two years 5 years that across the economy not that there won't be anything for humans to do but that there will be enough disruption that that we'll have a you know a kind of labor disruption that is you know not fundamentally different from what we've seen with previous technologies but that
## 00:21:12
**中文**
……发生得更快、覆盖经济范围更广，因为它牵涉各种工作。我认为时间窗口是未来两到五年。——两到五年？——对。——回到之前的问题，Anthropic 的模型什么时候会编写 100% 的代码？——这仍是个棘手的问题。即使模型写了 100% 的代码，人类也可能仍在监督、提示或澄清要求。这是个意外复杂的问题。我尤其担心人们适应变化的能力，因为工作正在非常迅速地改变……
**English / Original**
operates faster that is broader across the economy because it relates to all kinds. I think that's in the next two to five years. >> Two to five years I would say. >> Okay. And at what point just coming back to my previous question, at what point is Enthropic the model writing 100% of the code? >> Yeah. Again, it's it's a tricky question because maybe even if the model's writing 100% of the code, the humans are still supervising the model or prompting it or clarif it's it's it's it's a surprisingly clever thing. I don't you know I I'm I I I am concerned particularly about people's ability to adapt as the jobs are changing fast jobs are changing so
## 00:21:55
**中文**
……但比较优势很强大，会成为我们应对变化的工具之一。——你几次提到医疗，但最近医疗领域出现了相互矛盾的准确性研究。尤其这些是语言模型，准确率似乎达不到 100%。应用到放射学等领域时，也有研究显示模型并未达到放射科医生的准确度。你认为未来也会如此吗？你如何看待这些结果？
**English / Original**
fast but comparative comparative advantage is powerful that's going to be one of our tools in this well you've mentioned healthcare several times but we've seen these kind of very conflicting studies recently in healthcare around accuracy especially because these are word models there seems to be some level of accuracy that's not 100% and we're you know you know and then when applied to some of these kind of other things like radiology is one where we saw these very interesting, you know, studies where we just didn't see the accuracy of a radiologist reflected in what the model was doing. Is that how you see it going forward or how did you reflect back on that?
## 00:22:31
**中文**
——就目前而言，我和许多实际使用模型的人，都把模型看作类似“第二意见”。——你知道我想问什么：我想弄清我们究竟处于世界演变的哪个阶段，这条曲线走到哪里。——很多实际使用者不会单独信任模型，而是把它当作第二意见。就像医生告诉我一件事，我也不一定直接视为事实。医生是专家，通常正确，但并非永远正确。所以我给你讲个……
**English / Original**
>> Yeah, I I would say where we are now is I think of the models and I think a lot of people who use the models in practice, >> you know where I'm going, right, where I'm trying to I'm trying to like understand where are we really in the evolution of the world. >> Where's the arc? So, so I think a lot of I I think and a lot of the people who use the models in practice, I think think of the models as maybe a bit like a second opinion, right? Where you don't necessarily trust them alone. Just like if a doctor says something to me, I you know, I don't I don't necessarily take that as fact. They're an expert, but and they're often right, but they're not always right. Um uh so, you know, I'll tell
## 00:23:08
**中文**
——特别是在放射学这个领域，模型似乎就是理解不了。我本想说“脑子转不过来”，不过这个比喻不合适。究竟是数据不足，还是细节太微妙，问题在哪里？——我讲一个它确实奏效的案例。刚才谈到我和妹妹共同创业。她最近生了第二个孩子，怀孕期间免疫系统受到抑制。医生们认为她的病是病毒性的，不知为何谁都没想到……
**English / Original**
>> especially in this one category, radiology. It seems strange like it just can't get its >> I was going to say can't get its head around it but it's not really the right metaphor but doesn't have >> it does there's something about either it doesn't have enough data or it's not getting it's too nuanced. What is it? >> Yeah. So let me let me actually tell you a story about about one case where it where it where it did work. Um so you know we're talking about you know founding the company with with my sister. She recently had her second child while she was pregnant. um you know pregnancy can suppress your immune system was was viral. For some reason it didn't occur to to any of them that it
## 00:23:44
**中文**
……可能是细菌感染。她把所有数据上传给 Claude，Claude 系统地列出了各种可能性，其中包括医生不知为何遗漏的情况。——太不可思议了，对吧？已经用模型以某种方式了解自身健康状况的人请举手。
**English / Original**
could be a bacterial infection. She took all her data. She uploaded it to Claude and you know Claude you know systematically listed the possibilities in the way that the doctors had somehow missed. >> That is amazing right? How many of us have already used the models in some way to look at our healthcare? Raise your hand.
## 00:24:01
**中文**
——我想大家都在经历这种事。——举手的人很多。——非常惊人。尤其是疑病症患者，有多少人在这样做？请举手。好吧，有几个，我知道我也是。——但关键在于：Claude 列出的是可能性。若她盲目照做，结果不会好。Claude 的价值在于提醒：“你考虑过这个吗？考虑过那个吗？”所以它具备辅助和增强能力。——尤其是在文字方面，对吧？
**English / Original**
>> Yeah I think we're all having exactly that. >> That's that's a lot of people. >> Yeah it's amazing right? where you can kind of say especially how many of you are the hyperchondriacs that are doing that raise your hand. Yeah, I got a few. Okay, I know I'm >> but but but here's the point which is Claude listed possibilities. If she had just blindly taken the advice of Claude, that would not have gone well. Um Claude was good for saying, "Hey, have you considered this? Have you considered that?" So, so it has this assistive augmentative ability, >> especially in regards to words, right?
## 00:24:34
**中文**
它很擅长文字。——文字，是的。读取影像等专业任务更依赖专门模型；如果没有合适的数据，模型可能表现不佳，这并不完全反映它的整体能力。——这是不是放射学问题的核心？我们一方面说 AI 会改善医疗，却有研究发现医生有时过度依赖模型，导致不良结果；另一方面，尝试解读放射影像的模型又达不到所需准确度，两者形成了奇怪的分化。
**English / Original**
is very good on words. >> Words. Yeah. Yeah. I mean, you know, this specialized stuff of reading images like I think that's more about specialized models like if you don't have the right data, maybe it's not doing well. It's less reflective of the >> is that the crux of the issue like in radiology cuz like when we're saying it's going to improve healthare but we also saw this weird study where doctors who were using the models some in some cases were relying too much of the models and then ending up with bad outcomes. On the other side then we saw models that were like trying to read radiology but then were not able to achieve accuracy. was like this kind of strange bifurcation between the two things.
## 00:25:15
**中文**
——是的。人类扮演什么角色、模型扮演什么角色，仍有很多问题需要理清，而且模型快速进步也不断改变答案。新技术常有这种情况：技术本身非常出色，但究竟如何使用、如何与它交互等实践问题，却需要出乎意料长的时间才能解决。回顾各种新技术部署早期，往往都是如此。——所以你认为未来是人类和智能体共同工作？
**English / Original**
>> Yeah. You know, I think there's a lot still left to work out in what the role of the human is and what the role of the model is. And of course, that's changing as the models improve rapidly. But, you know, I think it's something you often see in new technologies where there's this great technology and then these practical issues of exactly how do you use it, exactly how do you interact with it, they take surprisingly long to work out. And you know if you look back at you know the early days when people you know kind of you know deployed deployed new technologies I don't know it's it's just it's often >> you think this is going to be about humans and agents working together.
## 00:25:52
**中文**
——对，正是如此，只是这些现实领域中的协作模式还需要进一步打磨。编程是很好的参照，因为那里变化极快，开发者又是早期采用者，所以整个循环几个月就走完了。人们在博客里讨论 Claude Code 的最佳用法：让它先建议再由我修改，还是我写代码再让它修改？大家彼此借鉴，用三四个月就摸索出最佳实践。医疗和放射学也在经历同样过程，只是存在许多障碍……
**English / Original**
>> Yeah. No no no exactly just just the collaboration model needs to be worked out a bit more than it has in these practical areas. Code is good to point to like code happens so fast right? developers are early adopters and so that cycle we've gone through it in like months right you can see people talking in blog posts about oh you know what's the best way to use cloud code do I want it to suggest and I make edits or I write code and it makes edits and these people riff off each other and you know over the course of three or four months they work out what the best way to use quad code is I think that same thing is happening in healthcare and radiology but because there are a lot of barriers
## 00:26:32
**中文**
……而且风险很高，所以摸索速度慢得多。——这就触及核心了：它是一种协作。Claude Code 在写代码，但开发者仍需找到与它合作的最佳方式；它并不是独自完成 100% 的代码。
**English / Original**
in these industries because they're high stakes that that process is working itself out much slower. >> So that's really kind of getting down to it, right? That it's a collaborative thing and like here's the best way to use cloud code. Cloud code is writing the code, but here's really the best way as a developer now to work on cloud code. It's not writing 100% of the code.
## 00:26:54
**中文**
它写完代码，我来检查；之后还得维护代码，并提供围绕代码的所有能力和完整基础设施。可以这样理解吗？——就目前而言，这样理解是对的。随着模型变强，协作方式可能变成人类进行更远距离的监督。所以即使六个月后会怎样也很难说。不过以我们刚发布的最新模型 Sonnet 4.5 为准，你准确描述了当前状况。——它大概也是我们见过最强的编程模型之一。
**English / Original**
It's writing code now I'm like checking here's here's and now now I'm going to have to maintain the code. I'm gonna have to provide all the capabilities, the whole infrastructure around the code. Is this the right way to think about it? >> I I think that's the right way to think about it right now. Um uh you know, as as the models get stronger, then the collaboration may change to more distant supervision by the human. Um so it's it's very hard to say what will happen even 6 months from now. But but I think what you've said is a very accurate description of where we are now as of you know our our you know as of Sonnet 4.5 which was the latest model released at >> which is probably one of the best coders
## 00:27:33
**中文**
——对。我们有这样的基准：从 GitHub 拉取请求中随机抽样，模型根据描述能完成其中多大比例。过去一年半里，这个数字从约 5%——基本意味着完全不会编程——提高到了约 77%。
**English / Original**
that we've seen right >> it it you know every every we you know we have these benchmarks that are like you know what fraction of you know a random sample of GitHub PRs can this thing write from a description and that's over the last year and a half that's gone from like 5% which was basically the thing can't code at all to something like you know 77%.
## 00:27:54
**中文**
——这确实很惊人。它还催生了建立在模型之上的整个生态。比如我们昨天展示了客户可以受益的 Agentforce Vibes，还有 Lovable 等工具。看到模型之上形成完整生态，令你意外吗？——这很令人欣喜。生态里有许多不同模式：GitHub Copilot 是对 GitHub 的补充；Cursor 属于 IDE 模式；Lovable 和 Replit 更像一种……
**English / Original**
Uh so it's it's it's really >> and it's also yielding also this whole other ecosystem of things on top of it as well like even we showed agent force vibes yesterday that I think our customers will benefit from or other you know other tools lovable these things have been built on these things right has that been a surprise to you to see a whole ecosystem on top of the model >> I mean that's been that's been great to see there are there are many different models right if you look at the GitHub co-pilots of the world you know that's kind of complimentary to GitHub if you look at the cursors of the world. That's kind of an IDE model. If you look at the lovables and replets, that's more of a
## 00:28:30
**中文**
……消费产品模式，让传统上不是软件开发者的人也能写代码。Vercel 又是另一种思路，还有 Augment Code、Windsurf，形成了完整生态；此外还有 Claude Code 这类命令行工具。现在判断谁会胜出还为时过早，甚至未必只有一个赢家；也许不同产品适合不同人和不同场景。——这里简直形成了一个完整文明、一个完整操作系统般的能力，甚至比这更广，确实……
**English / Original**
consumer model. It allows people who are not traditionally software developers to write code. Um, you know, there's like a, you know, Versell is like a different a different way of looking at it. Augment code, wind surf, you know, there's a whole ecosystem. And then there's the command line tools like like claude code. Uh, so I think it's too early to say, you know, what's going to be the winner there or or even if there is one winner, it's just possible there's just different things that work for different people or or different >> there's a whole civilization. There's a whole EOS capability, right? It's a whole civilization like it's an EO it's even it's broader like it's really
## 00:29:06
**中文**
……横跨整个领域。它如此基础，以至于能催生别人创造的所有这些惊人创新，真的令人赞叹。——其中哪一种最超出你的预料？——我最没想到的，是让人们端到端写代码、让非程序员也能编程的模式。
**English / Original**
coming across the whole span. It it's really impressive, you know? It's it's it's so fundamental that it's able to yield all this incredible innovation from others. Yeah. No, this I mean >> which one of those is the most like the one you did not expect? >> Which one is the one that I most did not expect? Um I think the model of kind of allowing people to write code end to end like allowing non-coders to write code.
## 00:29:33
**中文**
看到之后它完全合乎情理，而且作为商业模式表现很好；但当初构想这一切时，我确实没想到。——你最喜欢哪个产品？——这类问题很难回答。客户就像你的孩子，实在不该选出一个最喜欢的，所以我不回答。
**English / Original**
It totally makes sense once I see it and it's doing really well as a business model. But but I I I just when I was conceptualizing all the >> which product do you love the best? Uh yeah, this is this is one of those questions that you know you know c your customers are like your children. You you you you really shouldn't give an answer. So I'm not going to give an answer.
## 00:30:00
**中文**
［音乐］［掌声］好了，大家现在对 Dario 有感觉了吗？了解 Dario 了吗？我就是想帮助大家理解你、理解你的思路和我们正走向何方。现在你是一位创业者，离开 OpenAI 后公司迅速起飞；你和 Daniela 搬进了 Slack 大楼。五年后它会走到哪里？过去五年我们已经看到了。你不必把我当投资者，也不会有人……
**English / Original**
[Music] [Applause] All right. So are you getting a sense for Daario, by the way? Are you getting a sense for Daario? Okay. So that's I'm trying to like you know help them to understand you and how you're thinking about this and where we're going. So now here you are you know you're entrepreneur you've left open AI this thing is taking off. It's you and Daniela you know um you're in the Slack building you're get where is it going to be in 5 years? What does it look like? We've seen zero to five years now. You don't have to tell me as an investor and there's nobody
## 00:30:41
**中文**
……拿你的回答追究责任。尽管畅想一下：现在不再是 2025 年，而是 2030 年，Anthropic 在哪里、是什么样子？不用管其他公司和竞争者。五年后的 Anthropic 是什么样？你最大的梦想是什么？——也许最好的思考方式之一，是看我写的《Machines of Loving Grace》。它从社会角度讨论未来，而公司当然也在努力把那个愿景付诸实践并作出贡献，由此就能推导出我们……
**English / Original**
hold going to hold you accountable for it. But just if you just fantasized out and now it's not 2025 but it's 2030 and you know where's Enthropic? What does it look like? Forget about all the other companies and all the other competitors whatever. Nobody cares. Where's Enthropic 5 years from now? What's your dream big what's your big dream? So, you know, I I think I think maybe maybe one of the best ways to think about this is, you know, I wrote this essay called Machines of Loving Grace where where it's really it was written from a societal perspective, but you know, of course, the company is trying to enact that and and and contribute to it and so you can back out from that where we
## 00:31:19
**中文**
……希望公司最终抵达的位置。
**English / Original**
where we hope the the company will be.
## 00:31:22
**中文**
我把那篇文章视为对 AI 正面潜力的描绘。AI 确实引发许多担忧，我也是最响亮地提出这些担忧的人之一；但我同样无比相信 AI 的正面潜力。相比许多自称更乐观的人，我的想象其实更加广阔。最令我兴奋的，也许是它在治愈疾病方面的作用。回到我的生物学背景：癌症、阿尔茨海默病、各种代谢疾病都是棘手难题，我认为 AI 正是治愈它们所需的工具。因此我想到所有……
**English / Original**
So, you know, I I really thought of it as like the upside of AI, right? There's lots of concerns with AI. I I you know I'm one of the loudest in voicing them but but I am you know I am I am I am incredible believer in the upside of AI you know I think I think more so than people who code or describe themselves as more optimistic I have just a really expansive view I am perhaps most excited about what it can do for curing diseases um you know going back to my background in biology like you know we look at these tough diseases like cancer like Alzheimer's um you know like like you know various kinds of metabolic disease like I I I just think AI is the right thing to cure them and so I think of all
## 00:32:03
**中文**
……可以开展的工作：与制药公司、科研机构及医疗体系合作，把愿景变成现实。我们的合作围绕受监管行业，而医疗尤其是其中之一。这是最积极的应用之一，但我认为应用会遍及各个行业。我非常看好金融服务和保险，也期待服务几乎所有企业，用越来越聪明的模型帮助每一家企业。这里的能力上限非常高。换一种说法：什么是……
**English / Original**
the work we can do working with pharmaceutical companies working with scientific research institutions and working with the health care system to kind of enact it out and you know you again our partnership is about regulated industries and one of the regulated industries I think especially is is healthcare but you know that is one of the most positive applications but I think that we will see applications across the industry I'm very excited about financial services. I'm very excited about insurance. I'm very excited about taking basically every enterprise um and learning to serve every enterprise with smarter and smarter models. And the skill ceiling is very high. One way to say it is what is
## 00:32:43
**中文**
……企业？它可以说是一种超级智能：它作为一个实体在世界中行动，拥有远超任何个人的战略、知识和力量。所以，即使模型变得比任何个人都聪明，在完成企业试图在世界中完成的事情方面，能力上限仍高得多。这些事情大多有益于世界，也大多创造经济价值。因此，我对 Anthropic 的愿景是：服务全世界的企业，改造每一家企业，把……
**English / Original**
an enterprise? It's kind of a super intelligence, right? It it is an entity that acts in the world in in in in in in a way with a level of strategy and and knowledge and power in the world that goes far beyond what any individual human can do. So, you know, even as these models get smarter than than than any than any individual human, there's a ceiling substantially higher than that in terms of doing the things that a company tries to do in the world. Um, you know, most of which are good for the world, most of which create economic value. Um and and and so then my my vision of Enthropic is a company that serves the enterprise of the world that transforms every every enterprise puts
## 00:33:22
**中文**
……AI 置于每家企业的中心。我不谈具体数字，但这个市场的真实潜力非常大。我们的收入连续三年每年增长十倍；今天早上的报道是正确的，我愿意确认，目前年化收入正接近 70 亿美元。当然，这种增速不可能再持续太久。——作为投资者，我期待明年达到 700 亿美元。以 40 亿估值投资，你不该觉得贵。
**English / Original**
AI at the center at the center of every enterprise. Um uh you know and and and and and you know I think I won't give specific numbers but like if you if you think about the actual market potential of that is very very high right our revenue has been going up 10x per year. It's currently, I think it was reported this morning, which I'm happy to confirm is correct, is approaching approaching 7 billion run rate. Um, that's gone up 10x a year for the for the last 3 years. It can't continue like that for much longer, of course, but uh you know, >> as an investor, I'm looking forward to the $70 billion year next year. You should not feel bad investing at 4 bill.
## 00:34:00
**中文**
你不该觉得贵。好了。——我认为潜力确实非常大。但比潜力更重要、甚至可能是成功的必要条件，是我们希望被视为一家值得信任、负责任的公司：一家言行一致、说到做到，并打造可信产品的公司。如果你基于我们的产品进行开发，就不会遭遇意外，也不会遇到疯狂的事情。
**English / Original**
You should not feel bad. All right. >> Um uh uh uh so you know but I I I think the potential is is is very large. But I but I think even even more important than that or perhaps even necessary to that success, we want to be known for, you know, the company that is trustworthy, the company that behaves responsibly, the company that has a that has a reputation for, you know, doing what it says, saying what it does, and building products that are trustworthy that, you know, if you if you if you build on us, you won't get any surprises. You won't get anything crazy.
## 00:34:35
**中文**
你不会看到模型宣称自己是希特勒，也不会遇到各种荒唐行为。我认为，要当好这项技术的管理者，这一点非常重要。——你是在暗示某些公司会这样吗？——完全没有。——帕洛阿尔托有一位创业者……
**English / Original**
You won't get the model, you know, saying it's Hitler. you won't you won't get, you know, all kinds of um you won't get all kinds of crazy stuff. Um and and I think that's very important to us being good stewards of this. >> Are there certain companies that you're trying to imply that that might be? >> None whatsoever. >> There's an entrepreneur down in Palo Alto.
## 00:34:53
**中文**
——没有，完全不知道你在说什么。——我明白了，是字母表里的某个字母。——我完全不知道你在说什么。——就是 Y 前面的那个字母。——抱歉，我仍不明白。——再问一件事，我行使主持人特权，多占用你几分钟。现在建设数据中心的热潮非常强烈，芯片、融资、数据中心的规模及能耗都受到狂热关注。除了提到扩展定律，你还没有直接谈到……
**English / Original**
>> None at all. I don't know what you're talking about. >> Okay, I see. That's a certain letter in the alphabet. >> I don't I don't I I have no idea what you're talking about. Um >> Okay, that's before the letter Y. I sorry I still don't know what you mean. >> Okay, one more thing. I'm going to take a couple I'm going to use moderator privilege here and take a couple extra minutes with you. So number one, we see right now a tremendous fever on building data centers and you know we've seen a tremendous fever around the chips, the financing, the size and scale of the data centers, the energy of the data centers. you haven't really addressed it in your comments per se besides the
## 00:35:35
**中文**
……这件事与 Anthropic 的关系。Amazon 显然是你们的核心合作伙伴之一，对增长非常重要。你们也和其他公司合作，但 Amazon 尤其关键。请描绘一下数据中心目前正在发生什么，未来几年会怎样。作为一个需要数据中心支撑增长的创业者，你怎么看？会找谁合作、采取什么方式？会自己建设吗？
**English / Original**
scaling laws but let's talk about it just in part and parcel to enthropic and when you think about obviously one of your core partners has been Amazon it's been very important for your growth very important company um even though you do have you know obviously relationship with others as well but that one has been especially important to you know just give us a vision of what's happening with these data centers right now what are we going to see in the next few years with these data centers and how do you think about it as an entrepreneur who's going to need data centers to grow? Who will you go to? How will you do it? Will you build your own?
## 00:36:10
**中文**
还是继续合作？你们的计划是什么？——我的看法是，出于我们已经谈到的所有原因，计算需求将极其庞大。扩展定律表明，要训练越来越聪明的模型，我们需要越来越多算力；随着收入上升，我们还要为更多用户提供更多模型服务。当收入不再是 70 亿美元而是 1,000 亿美元以上，当模型训练需要数百万颗芯片时，我们需要许多个吉瓦的电力来训练……
**English / Original**
Will you just continue to partner? What what what is your plan? >> Yeah. So, you know, my my my view is is that there is going to be an enormous need for compute for for all the reasons that uh you know that that we've laid out, right? The the scaling laws suggest that we're going to need more and more compute to train smarter and smarter models. And then as the revenue goes up, we're gonna we're, you know, we're going to need to serve more. We're going to need to serve more of our models. So when that revenue is not seven billion, but a hundred billion or more um uh and you know, when when model training requires millions of chips, you know, we're we're going to need many many gigawatts of power to to train the
## 00:36:47
**中文**
……模型。因此，我们正尽可能从各处获取所需电力，我对公司的能力有信心。不过，当媒体过度聚焦于修建数据中心以及相关交易时，我确实有些担忧。其中一些交易似乎有点可疑。
**English / Original**
models. So we're trying to secure that power basically wherever we can. Um you know, and I'm confident in the company's uh uh I'm confident in the company's ability to do so. I I I do get a bit worried when the press focuses too much on the building of the data centers and deals to build data centers. Some of these deals seem a little bit fishy.
## 00:37:09
**中文**
它们可能存在重复计算，我也担心……——你说的是哪些交易？——不知道你在说什么，我完全不知道。——谁在重复计算？它们都是上市公司。——我们很想知道是谁。——我不知道，我掌握的信息并不比你多。
**English / Original**
They seem like they're maybe double counting. And I I also worry again >> deals are you ask talking about? >> I don't know what you're talking about. I have no idea. Um uh uh uh >> who is double counting? These are all public companies. I I >> We're going to want to know who's double counting. >> I don't I don't I don't know. I don't know anything more than you.
## 00:37:27
**中文**
——那三重计算的呢？——也许确实有，哇。——我不知道。不过归根结底，所有数据中心建设都是在花钱。最重要的是赚钱。因此，我关注的是收入，以及我们实际为企业开展的工作。
**English / Original**
>> What about the ones who are doing triple counting? >> I I don't There might be some of that, too. Wow. All right. >> I don't know. Um uh uh uh but but but look look look at the end of the day, all this data center stuff is spending money, right? Um I think the thing that's most important is making money. Um and and so this is why I focus on, you know, the revenue and the actual work that we're doing with businesses.
## 00:37:52
**中文**
Anthropic 的增长速度比该领域任何其他公司都快，收入增长也更快。基本上，只要需求存在、客户需要服务并愿意付费，你就愿意向算力供应商付款，最终总能获得所需算力。
**English / Original**
Andropic is growing faster than any other company in the space. The revenue is growing faster. And you know, I think I think basically if if you know, if the if the demand is there, if customers want the money and they're willing to pay you, then you are willing to pay your comput providers and you'll get the compute you need at the end of the day.
## 00:38:11
**中文**
——Dario，我们无比感激你来到这里，留在旧金山，成为这座城市土生土长的骄傲；也感谢 Daniela，以及你们在 Anthropic 所做的一切。祝贺你。请大家为 Dario 鼓掌。［掌声］［音乐］
**English / Original**
>> Daria, we could not be more grateful for you to be here, to be in San Francisco, to be a native son, and to Daniela as well, and for everything that you're doing with Enthropic. Congratulations. Please give Dario a round of applause. [Applause] [Music]