英伟达 CEO：OpenAI 将成为下一个万亿美元超大规模公司

我认为 OpenAI 很可能会成为下一个价值数万亿美元的超大规模公司。好的，Jensen。很高兴再次回来，当然还有我的搭档 Clark Tang。你知道吗，真不敢相信……欢迎来到 Invidia。哦，眼镜不错。

I think that OpenAI is likely going to be the next multi-trillion dollar hyperscale company. Okay, Jensen. Great to be back, of course, with my partner Clark Tang. You know, I can't believe it's... Welcome to Invidia. Oh, and nice glasses.

那副眼镜真的很适合你。问题是现在大家都会想让你一直戴着。他们会问：“红眼镜呢？”

Those actually look really good on you. The problem is now everybody's going to want you to wear them all the time. They're going to say, "Where are the red glasses?"

我可以作证。距离我们上次播客已经过去一年多了。是的。如今你们超过 40% 的收入来自推理，但由于思维链，推理即将迎来变革。对。它即将增长十亿倍，对吧？百万倍到十亿倍。没错。这是大多数人还没有完全理解的部分。这就是我们谈论的那个行业。这就是工业革命。

I can vouch for that. So, it's been over a year since we did the last pod. Yeah. Over 40% of your revenue today is inference, but inference is about ready because of chain of reasoning. Yeah. Right. It's about... It's about to go up by a billion times, right? By a million x by a billion. That's right. That's the part that most people have, you know, haven't completely internalized. This is that industry we were talking about. This is the industrial revolution.

说实话，感觉从那以后我们每天都在延续这个播客。你知道，按 AI 时间算，大概已经过了一百年。我最近重看了那期播客，我们谈到的很多事情都很突出。对我来说最深刻的是你拍着桌子说，记得当时预训练有点低迷，人们都在说：“哦，天哪，预训练的终结，对吧？预训练的终结。我们不会继续了。我们建得太多了。”那是大约一年半以前。而你说推理不会增长 100 倍、1000 倍，而是 10 亿倍。嗯。这就把我们带到了今天。你知道，你宣布了这笔大交易。我们应该从那里开始。

Honestly, it's felt like you and I have had a continuation of the pod every day since then. You know, in AI time, it's been about a hundred years. I was re-watching the pod recently and the many things that we talked about that stood out. The most profound one for me was you pounding the table that, you know, remember at the time there was kind of a slump in terms of pre-training and people were like, "Oh my god, the end of pre-training, right? The end of pre-training. We're not going. We're overbuilding." This is about a year and a half ago. And you said inference isn't going to 100x, a thousandx, it's going to 1 billionx. Mhm. Which brings us to where we are today. You know, you announced this huge deal. We ought to start there.

我低估了。让我正式说一下。我估计我们现在有三个 Scaling 定律，对吧？我们有预训练 Scaling 定律。我们有后训练 Scaling 定律。后训练基本上就像 AI 在练习，是的，练习一项技能直到做对。所以它尝试很多不同的方法，为了做到这一点，是的，你必须进行推理。所以现在训练和推理在强化学习中整合在一起了。非常复杂。这就是所谓的后训练。然后第三个是推理。旧的推理方式是一次性的，对吧？但新的推理方式，我们欣赏的是思考。所以在回答之前先思考。是的。所以现在你有三个 Scaling 定律。你思考的时间越长，得到的答案质量就越好。在你思考的时候，你做研究，你去查证一些基本事实。你学到一些东西，你再思考，再学习，然后生成答案。不要一开始就直接生成。

I underestimated. Let me just go on record. I estimated we now have three scaling laws, right? We have pre-training scaling law. We have post-training scaling law. Post-training is basically like AI practicing, yes, practicing a skill until it gets it right. And so it tries a whole bunch of different ways and in order to do that, yeah, you've got to do inference. So now training and inference are now integrated in reinforcement learning. Really complicated. And so that's called post training. And then the third is inference. The old way of doing inference was one shot, right? But the new way of doing inference, which we appreciate, is thinking. So think before you answer. Yeah. And so now you have three scaling laws. The longer you think, the better the quality answer you get. While you're thinking, you do research, you go check on some ground truth. And you learn some things, you think some more, you go learn some more, and then you generate an answer. Don't just generate right off the bat.

所以思考、后训练、预训练，我们现在有三个 Scaling 定律，而不是一个。你去年就知道了，但今年你对推理将增长 10 亿倍以及这将把智能水平带到何处的信心是否更高了？你比一年前更有信心吗？

And so thinking, post-training, pre-training, we now have three scaling laws, not one. You knew that last year, but is your level of confidence this year in the inference going to 1 billionx and where that will take the levels of intelligence is it higher? Are you more confident this year than you were a year ago?

我今年更有信心了，原因在于看看现在的智能体系统，AI 不再是一个语言模型，AI 是一个语言模型系统，它们都在并发运行，可能还使用工具。我们中的一些使用工具，一些做研究，是的，有很多东西，而且都是多模态的，看看那些生成的视频。我的意思是，这太疯狂了。是的。

I'm more confident this year and the reason for that is because look at the agent systems now and AI is no longer a language model and AI is a system of language models and they're all running concurrently maybe using tools. Some of us using tools, some of us doing research and yeah, there's a whole bunch of stuff and it's all multimodality and look at all the video that's being generated. I mean, it's just crazy stuff. Yeah.

这真的把我们带到了本周那个具有里程碑意义的时刻，每个人都在谈论那笔巨额交易。几天前你宣布了与 OpenAI 的 Stargate 项目，你将作为首选合作伙伴，在一段时间内向该公司投资 1000 亿美元。他们将建设 10 吉瓦的设施，如果这些设施使用英伟达的产品，可能会为英伟达带来高达 4000 亿美元的收入。所以请帮助我们理解，告诉我们一点关于这个合作伙伴关系，它对你意味着什么，以及为什么这笔投资对英伟达如此有意义。

It really brings us to, you know, kind of the seminal moment this week that everybody's talking about the massive deal. You announced a couple days ago with OpenAI Stargate where you're going to be a preferred partner, invest hundred billion dollars in the company over a period of time. They're going to build 10 gigs and if they used Nvidia for those 10 gigs that could be upwards of 400 billion in revenue to Nvidia. So help us understand you just tell us a little bit about that partnership what it means to you right and why that investment makes so much sense for Nvidia.

首先，我先回答最后一个问题，然后再从头讲起。我认为 OpenAI 很可能会成为下一个价值数万亿美元的超大规模公司。好的。我认为你和我……你为什么称它为超大规模公司？超大规模就像 Meta 是超大规模。谷歌是超大规模。他们将拥有消费者和企业服务，他们很可能会成为世界上下一个价值数万亿美元的超大规模公司。是的。我想你会同意这一点。我同意。如果是这样，在他们达到那个水平之前投资的机会，这是我们可以想象的最明智的投资之一。你必须投资一些东西，对吧？而且碰巧我们了解这个领域。所以投资的机会，这笔钱的回报将会非常棒。所以我们喜欢这个投资机会。我们不是必须投资，对吧？我们不需要投资，但他们给了我们投资的机会。太棒了。现在让我从头开始。我们正在与 OpenAI 在几个项目上合作。第一个项目是建设 Microsoft Azure。我们将继续这样做，这个合作进展得非常顺利。我们还有几年的建设工作，仅在那里就有数千亿美元的工作要做。对。第二个是 OCI 的建设，我认为大约有 5、6、7 吉瓦即将建成。所以我们正在与 OCI、OpenAI 和 SoftBank 合作建设这些项目，对吧？这些项目已经签约。我们正在努力。有很多工作要做。然后是第三个，CoreWeave，对吧？所以所有的 CoreWeave，我仍然在说 OpenAI。是的。好的。一切都在 OpenAI 的背景下。那么问题来了，这个新的合作伙伴关系是什么？这个新的合作伙伴关系是关于帮助 OpenAI，与 OpenAI 合作，第一次建立他们自己的 AI 基础设施，对吧？所以这是我们直接在芯片层面、软件层面、系统层面、AI 工厂层面与 OpenAI 合作，帮助他们成为一个完全运营的超大规模公司。我的意思是这将会持续一段时间。

So first of all, I'll answer that last question first and then I'll come back and present my way through. I think that OpenAI is likely going to be the next multi-trillion dollar hyperscale company. Okay. I think you and I... Why do you call it a hyperscale company? Hyperscale like Meta is a hyperscale. Google's a hyperscale. They're going to have consumer and enterprise services and they are very likely going to be the world's next multi-trillion dollar hyperscale company. Yes. And I think you would agree with that. I agree. If that's the case, the opportunity to invest before they get there, this is some of the smartest investments we can possibly imagine. And you got to invest in things, you know, right? And it turns out we happen to know this space. And so the opportunity to invest in that, the return on that money is going to be fantastic. So we love the opportunity to invest. We don't have to invest, right? And it's not required for us to invest, but they're giving us the opportunity to invest. Fantastic thing. Now let me start from the beginning. So we're partnering with OpenAI in several projects. First the first project is the buildout of Microsoft Azure. We're going to continue to do that and that partnership is going fantastically. We have several years of buildout to do hundreds of billions of dollars of work just to do there. Right. The second is the OCI buildout and I think there's some five, six, seven gigawatts that are about to be built out. And so we're working with OCI and OpenAI and SoftBank to build that out, right? Those projects are contracted. We're working on it. Lots of work to do. And then the third is CoreWeave, right? And so all of CoreWeave, I'm talking about OpenAI still. Yes. Okay. Everything in the context of OpenAI. And so the question is what is this new partnership? This new partnership is about helping OpenAI, working partnering with OpenAI to build their own self-built AI infrastructure for the first time, right? And so this is us working directly with OpenAI at the chip level, at the software level, at the systems level, at the AI factory level to help them become a fully operated hyperscale company. I mean this is going to go on for some time.

而且它会补充……他们正在经历两个指数级增长。第一个指数是客户数量在指数级增长，因为 AI 越来越强，用例越来越多，几乎每个应用都接入了 OpenAI。所以他们正在经历使用量的指数增长。第二个指数是每个用例的计算量指数增长。不再是单次推理，而是先思考再回答。

And it's going to supplement the amount of... they're going through two exponentials. The first exponential is the number of customers is growing exponentially because AI is getting better, use cases are improving, and just about every application is connected to OpenAI now. So they're going through the usage exponential. The second exponential is the computational exponential of every use. Instead of just a one-shot inference, it's now thinking before it answers.

对。没错。是的。

Yes. Right. Yes.

所以这两个指数叠加在一起，放大了他们的算力需求。我们必须把所有不同的项目都建起来。这最后一个项目是在他们已经宣布的所有计划之上新增的，也是我们已经在跟他们合作的所有项目之上新增的。它会支撑这个惊人的指数级增长。

And so these two exponentials are compounding their compute requirements. So we have to build out all these different projects. And this last one is additive on top of everything they've already announced, all the things we're already working on with them. It's additive on top of that, and it's going to support this incredible exponential growth.

你刚才说的有一点我觉得很有意思，就是你认为他们很可能成为一家市值数万亿美元的公司。我觉得这是一笔很好的投资。但同时，他们自己在建设，你在帮他们自建数据中心。此前他们一直外包给微软建数据中心，现在他们想自己建全栈工厂。

One of the things you said there that's really interesting to me is that they're going to be a high probability multi-trillion dollar company in your mind. I think it's a great investment. At the same time, they're self-building. You're helping them self-build their data centers. So heretofore, they've been outsourcing to Microsoft to build the data center. Now, they want to build full stack factories themselves.

他们基本上想跟我们建立像 Elon 和 X 那样的关系。

They want to basically have a relationship with us the way that Elon and X have a relationship.

对。我是说，Elon 和 X 自己建了。

Correct. I mean, Elon and X built.

没错。但我觉得这非常重大，想想 Colossus 的优势就知道了。他们在建全栈，这就是一个超大规模云服务商，因为如果自己用不完，可以卖给其他人。同样，Stargate 也在建巨大的容量。他们觉得自己会用掉大部分，但也让他们有能力卖给其他人。这听起来很像 AWS、GCP 或 Azure。

Exactly. But I think that's a very big deal when you think about the advantage that Colossus had. They're building full stack. That is a hyperscaler because if they don't use the capacity, they could sell it to somebody else. In the same way Stargate, they're building monstrous capacity. They think they'll need to use most of it, but it puts them in a position to sell it to somebody else as well. It sounds very much like AWS or GCP or Azure.

你就是这个意思。

That's what you're saying.

是的，我觉得他们很可能自己用。想想 X 的例子，他们很可能自己用。但他们希望跟我们建立同样的直接关系——直接的工作关系和直接的采购关系。Meta，就像扎克伯格和 Meta 跟我们那样，完全是直接的。我们跟 Sundar 和 Google 的关系是直接的，我们跟 Satya 和 Azure 的合作伙伴关系也是直接的。对吧？所以他们的规模已经大到他们认为该开始建立这些直接关系了。我很乐意支持这一点。Satya 知道，Larry 知道，所有人都知道发生了什么，而且都非常支持。

Yeah, I think they'll likely use it themselves. Just think of the case of X, they'll likely use it themselves. But they would like to have the same direct relationship with us, direct working relationship and direct purchasing relationship. Meta, just as with Zuck and Meta has with us, it's exactly direct. Our relationship with Sundar and Google direct, our partnership with Satya and Azure direct. Isn't that right? And so they've gotten to a large enough scale that they believe it's time for them to start building these direct relationships. So I'm delighted to support that. And Satya knows it, Larry knows it, everybody's aware of what's going on and everybody's very supportive of it.

所以我觉得有一件事很神秘。你刚才提到 Oracle 3000 亿、Colossus 在建的项目。我们知道主权基金在建什么，知道超大规模云服务商在建什么。Sam 在谈论数万亿美元。但华尔街覆盖你们股票的 25 位卖方分析师，如果我看共识预期，基本上从 2027 年开始你们的增长就持平了。2027 到 2030 年增长 8%。那是 25 个人唯一的工作，他们拿钱就是预测 Nvidia 的增长率。所以显然……

So one of the things I find mysterious, right? You just mentioned Oracle 300 billion, Colossus what they're building. We know what the sovereigns are building. We know what the hyperscalers are building. Sam's talking in terms of trillions. But of the 25 sellside analysts on Wall Street who cover your stock, if I look at the consensus estimate, it basically has your growth flatlining starting in 2027. 8% growth 2027 through 2030. That is the 25 people in their only job. They get paid to forecast the growth rate for Nvidia. So clearly...

顺便说一句，我们对此很满意。

We're comfortable with that by the way.

对。你看，我们对此很满意。好吧，我们经常轻松超越这些数字，对吧？不，我明白。但这里有一个有趣的分歧。

Right. Look, we're comfortable with that. Okay, we have no trouble beating the numbers on a regular basis, right? No, I understand that. But there is this interesting disconnect.

不。

No.

对。我每天都在 CNBC 和 Bloomberg 上听到这个。我认为这涉及到一些关于短缺导致过剩的问题，他们不相信。他们说：‘好吧，我们认可 26 年，但 27 年，你知道，也许我们会产能过剩，你们就不需要那么多了。’但我觉得这很有趣，而且我认为有必要指出，你们的共识预期是这不会发生。我们也综合考虑所有这些数字为公司做了预测，结果告诉我，即使我们已经进入 AI 时代两年半，我们听到 Sam Altman 说的、你说的、Sundar 说的、Satya 说的，与华尔街仍然相信的之间，存在巨大的信念分歧。而你知道，你对此很满意。

Right. I hear it every day on CNBC and Bloomberg. And I think it goes to some of these questions around shortages leading to a glut that they don't believe. They say, 'Okay, we'll give you credit for 26, but 27, you know, maybe we'll have too much and you're not going to need that.' But it is interesting to me and I think it's important to point out that your consensus forecast is that this won't happen. And we also put together a forecast for the company taking into account all of these numbers, and what it shows me is still, even though we're two and a half years into the age of AI, a massive divergence of belief between what we hear Sam Altman saying, you saying, Sundar saying, Satya saying, and what Wall Street still believes. And you know, again, you're comfortable with that.

我也不认为这矛盾。

I also don't think it's inconsistent.

好。那稍微解释一下。

Okay. So explain that a little bit.

首先，对于建设者来说，我们应该为机遇而建设。我们是建设者。我给你三个要点来思考，这三个要点会让你对 Nvidia 在这个未来中更放心。第一个要点，也是物理定律的要点，是最重要的：通用计算已经结束，未来是加速计算和 AI 计算。这是第一点。所以思考方式是：世界上有多少万亿美元的计算基础设施需要更新换代？对吧。当它更新换代时，将会是加速计算。没错。所以你必须意识到第一件事是通用计算——没有人质疑这一点。每个人都说：‘是的，我们完全同意。通用计算结束了。摩尔定律已死。’人们这么说。那么这意味着什么？通用计算将转向加速计算。我们与 Intel 的合作正是认识到通用计算需要与加速计算融合，为他们创造机会。对吧？所以第一，通用计算正在转向加速计算和 AI。第二，AI 的第一个用例实际上已经无处不在，对吧？在搜索、推荐引擎中，不是吗？在购物中。基本的超大规模计算基础设施过去是用 CPU 做推荐，对吧？现在转向用 GPU 做 AI，对吧？所以你只需把经典计算替换成加速计算 AI。

So first of all, for the builders, we're supposed to be building for opportunity. We're builders. Let me give you three points to think through, and these three points will help you hopefully be more comfortable with Nvidia in this future. So the first point, and this is the laws of physics point, is the most important point: general purpose computing is over and the future is accelerated computing and AI computing. That's the first point. And so the way to think about that is there's how many trillions of dollars of computing infrastructure in the world that has to be refreshed. Right. And when it gets refreshed, it's going to be accelerated computing. That's right. And so the first thing you have to realize is that general purpose computing, and nobody disputes that. Everybody goes, 'Yeah, we completely agree with that. General purpose computing is over. Moore's law is dead.' People say these things. And so what does that mean? So general purpose computing is going to go to accelerated computing. Our partnership with Intel is recognizing that general purpose computing needs to be fused with accelerated computing to create opportunities for them. Is that right? And so one, general purpose computing is shifting to accelerated computing and AI. Two, the first use case of AI is actually already everywhere, right? It's in search, recommender engines, isn't that right? In shopping. The basic hyperscale computing infrastructure used to be CPUs doing recommenders, right? Is now going to GPUs doing AI, right? So you just take classical computing, it's going to accelerated computing AI.

你拿超大规模计算来说，从 CPU 转向加速计算和 AI。然后现在是第二点：就是给 Meta、Google、字节跳动、亚马逊这些公司提供支持，把他们传统的超大规模计算方式转向 AI。那是数千亿美元的规模。而且因为今天全球可能有 40 亿人，如果把 TikTok、Meta 算进去，还有 Google，他们已经在要求由加速计算驱动的工作负载了。

You take hyperscale computing, going from CPUs to accelerated computing and AI. And then now that's the second point: just feeding the Metas, the Googles, the ByteDances, the Amazons, and take their classical traditional way of doing hyperscaling and moving into AI. That's hundreds of billions of dollars. And because that may be four billion people on the planet today, if you take TikTok, Meta into account, that's Google into account, who are already demanding workloads that are driven by accelerated computing.

完全正确。所以有一个简单的理解方式，甚至不用考虑 AI 创造新机会。就是 AI 把你过去做事情的方式转变成了新的方式。

That's exactly right. And so there's a simple way without even thinking about AI creating new opportunities. It's about AI shifting how you used to do something to the new way of doing something.

好的。那现在我们来谈谈未来。到目前为止，我基本上只讲了些平常的东西。

Okay. And then now let's talk about the future. I so far I've only spoken kind of largely about just mundane stuff.

就是平常的东西。旧的方式现在不对了。你不再用油灯了，你要用电。就这么简单。

Just mundane stuff. The old way is now wrong. You're going to go, you're no longer going to use fuel light lanterns. You're going to go to electricity. That's all.

对。

Right.

好的。你不再用螺旋桨飞机了，你要用喷气式飞机。就这些。所以到目前为止，我就讲了这些。

Okay. And you no longer, you know, prop planes. You're going to go to jets. That's all. And so, you know, so far, you know, that's all I've talked about.

然后现在不可思议的是，当你转向 AI，转向加速计算，会发生什么？由此产生了哪些新应用？这就是我们谈论的所有 AI 相关的东西。那就是机会。它是什么？它看起来怎么样？

And then now the incredible thing is when you go to AI, when you go to accelerated computing, then what happens? What are the new applications that emerge as a result? And that's all the AI stuff that we're talking about. And that's the opportunity. What is it? How does that look?

嗯，简单的思考方式是，就像电机取代了劳动和体力活动。我们现在有了 AI。这些 AI 超级计算机，我所说的 AI 工厂，它们将生成 token 来增强人类智能，对吧？而人类智能占世界 GDP 的 55% 到 65%，姑且称之为 50 万亿美元。这 50 万亿美元将被某种东西增强。所以我们回到一个人身上。假设我雇佣了一个年薪 10 万美元的员工。我用一个价值 1 万美元的 AI 来增强这个 10 万美元的员工。是的。结果这个 1 万美元的 AI 让那个 10 万美元的员工生产力翻倍，甚至三倍。我会这么做吗？毫无疑问。我现在就在我们公司的每个人身上这么做。

Well, the simple way of thinking about that is where motors replace labor and physical activity. We now have AI. These AI supercomputers, these AI factories that I talk about, they're going to generate tokens to augment human intelligence, right? And human intelligence represents what, 55, 65% of the world's GDP. Let's call it $50 trillion. And that $50 trillion is going to get augmented by something. So let's come back to a single person. Suppose I were to hire a $100,000 employee. And I augmented that $100,000 employee with a $10,000 AI. Yes. And that $10,000 AI as a result made that $100,000 employee twice more productive, three times more productive. Would I do it? Heartbeat. I'm doing it across every single person in our company right now.

每个智能体同事。

Every single co-agents.

没错。我们公司的每一位软件工程师、每一位芯片设计师都已经有 AI 在和他们一起工作。100% 覆盖。结果，我们制造的芯片质量更好了。数量在增长。我们的速度也合适。所以我们公司增长得更快。结果，我们雇佣了更多人。我们的生产力更高了。我们的营收更高了。我们的利润更高了。这有什么不好的呢？

That's right. Every single software engineer, every single chip designer in our company already has AIs working with them. 100% coverage. As a result, the number of chips we're building is better. The number is growing. The pace at which we're doing it is right. And so we're growing faster as a company. As a result, we're hiring more people. Our productivity is greater. Our top line's greater. Our profitability is greater. What's not to love about that?

现在把英伟达的故事应用到全球 GDP 上。

Now apply the Nvidia story to the world's GDP.

是的。所以很可能发生的是，这 50 万亿美元被一个数字增强，比如 10 万亿美元。这 10 万亿美元需要在机器上运行。现在 AI 与过去不同的原因是，过去软件是先编写好的，然后在 CPU 上运行，它不运行，由人来操作。未来，当然 AI 在生成 token，但机器必须生成 token，而且它在思考。所以那个软件一直在运行，而过去软件只编写一次。现在软件实际上一直在编写，它在思考。为了让 AI 思考，它需要一个工厂。所以假设这 10 万亿美元的 token 生成，50% 的毛利率，其中 5 万亿美元需要一个工厂，需要 AI 基础设施。所以如果你告诉我全球每年的资本支出大约是 5 万亿美元，我会说这个数字看起来合理。

Yeah. And so what's likely to happen is that that $50 trillion is augmented by, let's pick a number, $10 trillion. That $10 trillion needs to run on a machine. Now the reason that AI is different than in the past, in a way software was written a priori and then it runs on a CPU and it doesn't, it runs, a person would operate it. In the future, of course, AI is generating tokens, but a machine has to generate the tokens and it's thinking. So that software is running all the time, whereas in the past the software was written once. Now the software is in fact writing all the time, it's thinking. In order for the AI to think, it needs a factory. And so let's say that that $10 trillion of token generated, 50% gross margins, and $5 trillion of it needs a factory, needs an AI infrastructure. So if you told me that on an annual basis the capex of the world was about $5 trillion, I would say the math seems to make sense.

是的。

Yeah.

这大概就是未来，对吧？从通用计算转向加速计算，用 AI 取代所有超大规模计算，然后现在增强人类智能以提升全球 GDP。而今天这个市场，我们估计每年大约 4000 亿美元。

And that's kind of the future, right? Going from general purpose computing to accelerated computing, replacing all the hyperscalers with AI, and then now augmenting human intelligence for the world's GDP. And today that market is about, our estimate is about $400 billion annually.

是的。

Yeah.

所以总可寻址市场大约是今天的 4 到 5 倍。

So the TAM is about a 4 to 5x increase over where it is today.

是的。昨晚，阿里巴巴的吴泳铭说从现在到本十年末，他们将把数据中心电力增加 10 倍。

Yeah. Eddie last night, Eddie Wu at Alibaba said between now and the end of the decade, they're going to increase their data center power by 10x.

对。

Right.

你刚才说多少？4 倍。

You just said how much? 4x.

就是这样。

There you go.

是的。他们将把电力增加 10 倍。而我们与电力相关。英伟达的收入几乎与电力相关。不是吗？

Yeah. They're going to increase power by 10x. And we correlate to power. Nvidia's revenue is almost correlated to power. Isn't that right?

是的，没错。因为还有一件事，他还说了什么？

Yeah, that's right. Yeah. Because one other thing, what else did he say?

他说 token 生成每几个月就翻一番。

He said token generation is doubling every few months.

是的。这说明什么？每瓦性能必须持续指数级增长。这就是为什么英伟达在每瓦性能上不断突破。

Yeah. What's that saying? The perf per watt has to keep on going exponentially. That's why Nvidia's like cranking it out with perf per watt.

而每瓦收入，你知道，在这个未来，瓦特基本上就是收入。

And revenue per watt is, you know, watt is basically revenues in this future.

在这个假设中，我发现一个非常迷人的历史背景，对吧？两千年来，GDP 基本上没有增长。然后我们有了工业革命，GDP 加速了。我们有了数字革命，GDP 加速了。基本上你在说的，斯科特·贝森特也说过，他说我认为明年我们将有 4% 的 GDP 增长。基本上你在说的是，世界 GDP 增长将加速，因为现在我们给世界数十亿的同事，他们将为我们工作。如果 GDP 是固定劳动力和资本下的产出量，对吧，它必须加速。

Embedded in this assumption, I find it very fascinating historical context, right? For 2,000 years, basically GDP did not grow. Okay? And then we get the industrial revolution, GDP accelerates. We get the digital revolution, GDP accelerates. And basically what you're saying, and Scott Bessent has said it, he said, I think we're going to have 4% GDP growth next year. Basically, what you're saying is the world's GDP growth is going to accelerate because now we are giving the world billions of co-workers that will do work for us. And if GDP is an amount of output for a fixed amount of labor and capital, right, it has to accelerate.

它必须，对吧？

It has to, right?

它必须看看 AI 技术带来的结果。而 AI 技术，我们就称之为大语言模型和所有 AI 智能体。它现在正在创造一个新的 AI 智能体行业。这毫无疑问。所以 OpenAI 是历史上收入增长最快的公司，对吧？而且他们在指数级增长，对吧？所以 AI 本身就是一个快速增长的行业，因为 AI 背后需要一个工厂，对吧？一个基础设施。这个行业在增长。我的行业在增长。因为我的行业在增长，它下面的行业也在增长。能源在增长。电力。这就像是能源行业的复兴，不是吗？核能，燃气轮机。我的意思是，看看我们下面基础设施生态系统中的所有那些公司。他们做得非常好。每个人都在增长。

It has to look at what's going on with AI as a result of the technology of AI. And that technology of AI, let's just call it the large language models and all the AI agents. It's now creating a new industry of AI agents. There's no question about that. Okay. So, so that's OpenAI is the fastest growing revenue company in history, right? and they're growing exponentially, right? And so, so AI itself is a fast growing industry because of AI needs a factory behind it, right? An infrastructure behind it. There's this industry is growing. My industry is growing. And because my industry is growing, the industry underneath it is growing. Energy is growing. Power shell. This is like renaissance for the energy industry, isn't that right? Nuclear energy, you know, gas turbines. I mean, look at all of those companies in the infrastructure ecosystem underneath us. They're doing incredibly well. Everybody's growing.

这些数字让所有人都在谈论泡沫或过剩，对吧？扎克伯格上周在一个播客里说：“听着，我认为很有可能在某个时候我们会遇到一个气穴，Meta 可能实际上会多花 100 亿美元或什么的，但他说这没关系。这对他的业务未来如此生死攸关，以至于这是他们必须承担的风险。”但当你想到这一点，这听起来有点像囚徒困境。对吧。再跟我们解释一下

These numbers have everybody talking about a glut or bubble, right? Zuckerberg said last week on a podcast, you know, he said, "Listen, I think it's quite possible at some point that we will have an air pocket and Meta may in fact overspend by $10 billion or whatever, but he said it doesn't matter. It's so existential to the future of his business that it's a risk that they have to take." But when you think about that, it sounds a little bit like prisoners dilemma. Right. And walk us again through

这些是非常快乐的囚徒。

These are very happy prisoners.

再跟我们解释一下

Walk us again through

对。今天我们估计，到 2026 年我们将有 1000 亿美元的 AI 收入，不包括 Meta，也不包括运行推荐引擎的 GPU。好吧。所以还有

Right. Today our estimate is that we're going to have $100 billion of AI revenue in 2026, excluding Meta and excluding the GPUs running recommender engines. Okay. So there's

或搜索或

or search or

正确。所以还有其他东西，但我们就称之为 1000 亿美元。

Correct. So there's other stuff but let's call it $100 billion.

那个行业到底有多大？

What is that industry anyways?

这个行业已经超大规模了？超大规模是多少，你知道的，在数万亿之间？

What is the industry already in hyperscale? What is the hyperscale, you know, between trillions?

是的，没错。顺便说一句，那个行业正在转向 AI

Yeah exactly. By the way, that industry is going to AI

在任何人从零开始之前。你必须从那里开始。

before anybody starts at zero. You got to start there.

但我认为怀疑论者会说，我们需要从 2026 年的 1000 亿 AI 收入增长到 2030 年至少 1 万亿的 AI 收入。好吧。你刚才谈到全球 GDP 时提到了 5 万亿。如果你做自下而上的分析，你能看到从 1000 亿到 1 万亿 AI 驱动的收入在未来 5 年内实现吗？我们增长得那么快吗？

But I think the skeptics would say we need to go from $100 billion of AI revenue in '26 to at least a trillion of AI revenue in 2030. Okay. You just were talking a minute ago about five trillion when you look at kind of global GDP. If you did a bottoms up, can you see your way to a trillion dollars of AI-driven revenues from a hundred billion over the course of the next 5 years? Are we growing that fast?

是的。而且我还会说我们已经达到了。

Yes. And I would also say we're already there.

好吧。那么解释一下。

Okay. So explain that.

因为超大规模云服务商，他们从 CPU 转向了 AI。好吧。他们整个收入基础现在都是由 AI 驱动的。

Because the hyperscalers, they went from CPUs to AI. Okay. Their entire revenue base is all now AI-driven.

正确。

Correct.

没有 AI 你无法做 TikTok。

You can't do TikTok without AI.

正确。

Correct.

没有 AI 你无法做 YouTube Shorts。没有 AI 你无法做任何这些事情。Meta 在定制内容、个性化内容方面所做的惊人事情。没有 AI 你无法做到。所有这些过去都是由人类完成的，你知道，先验地创建四个选择，然后

You can't do YouTube Shorts without AI. You can't do any of this stuff without AI. The amazing things that Meta is doing for customized content, personalized content. You can't do that without AI. All of that stuff used to be humans, you know, doing content a priori creating four choices that are then

由推荐引擎选择。正确。而现在是由 AI 生成的无限选择，对吧？

selected by a recommender engine. Correct. And now it's infinite number of choices generated by an AI, right?

但那些事情已经发生了，就像我们经历了从 CPU 到 GPU 的过渡，主要是为了那些推荐引擎，现在它们正在

But those things are already like we had the transition from CPUs to GPUs largely for those recommender engines and now they're going

而且这相当新，我会说

and that's fairly new I would

在过去三四年里。扎克会告诉你，我在 SIGGRAPH 上，扎克会告诉你他们很晚才用上 GPU，肯定的。

in the last three or four years. Zuck would tell you, I was at SIGGRAPH and Zuck would tell you they were late getting to GPU, for sure.

Meta 用 GPU 是多久，两年半？

GPUs for Meta is what, a couple years and a half?

这相当新。用 GPU 搜索

It's pretty new. Search with GPUs

肯定的

for sure

全新的

brand spanking new

肯定的

for sure

全新的

brand spanking new

在 GPU 上搜索 GPU

search for GPUs on GPUs

所以你的论点是，到 2030 年我们拥有 1 万亿 AI 收入的可能性几乎确定，因为我们几乎已经达到了。好吧，

So your argument would be the probability that we're going to have a trillion dollars of AI revenues by 2030 is near certain because we're almost already there. Okay,

让我们只谈从我们现在位置的增长。

let's just talk about incremental from where we are.

现在我们可以谈从今天开始的增长，对吧？当你做自下而上或自上而下时，我刚刚听到你自上而下关于全球 GDP 的百分比。

Now we can talk about incremental from where we are today, right? As you do your bottoms up or your tops down, I just heard your tops down about percentage of global GDP.

是的。

Yeah.

你认为我们在未来三、四或五年内遇到过剩的概率百分比是多少？

What is the percentage probability that you think we'll have a glut, will run into a glut in the next three or four or five years?

对。这是一个分布，我们不知道未来。这是一个力量的分布

Right. It's a distribution of we don't know the future. It's a distribution of power

直到我们完全将所有通用计算转换为加速计算和 AI。在那之前，

until we fully convert all general purpose computing to accelerated computing and AI. Until we do that,

是的，

yes,

我认为可能性极低。

I think the chances are extremely low.

好吧。好吧。那需要几年时间。

Okay. Okay. And that will take a few years.

那需要几年时间。

That'll take a few years.

是的。

Yeah.

是的。让我再问一个，然后

Yeah. Let me ask one more and then

直到所有推荐引擎都基于 AI，直到所有内容生成都基于 AI，因为内容生成，面向消费者的内容生成很大程度上是推荐系统等等，所有这些都是由 AI 生成的，直到所有经典超大规模的东西现在都过渡到 AI，你知道从购物到电子商务到所有那些东西，直到一切都过渡

until all recommender engines are AI based, until all content generation is AI based because content generation, consumer oriented content generation is very largely recommender systems and so on and so forth, and all of that's going to be AI generated, until all of the stuff what classically was hyperscale now transitions to AI, you know everything from shopping to e-commerce to you know all that stuff, until everything goes over

因为但所有这些新建设，当我们谈论数万亿时。我们正在超前投资。嗯，你知道，这是随意的吗？即使你看到放缓或某种过剩来临，你是否有义务投资这笔钱，还是这只是你向生态系统挥舞旗帜说出去建设，而在某个时间点如果我们看到一些放缓，我们总是可以撤回投资水平的事情之一。

because but all this new build right when we're talking about trillions. We're investing ahead of where we are. Um, you know, is that like at will? Are you obliged to invest the money even if you see a slowdown or a kind of a glut coming or is this one of these things that you're just waving the flag to the ecosystem to say get out and build and at some point in time if we see some of this slow down, we can always pull back on the level of investment.

实际上，恰恰相反，因为我们处于供应链的末端，对吧？所以，我们对需求做出响应。

Actually, it's the other way because we're at the end of the supply chain, right? And so, we respond to demand.

好吗？现在所有风投都会告诉你，你们也知道

Okay? And right now all the VCs will tell you and you guys know

需求，世界上存在算力短缺，不是因为世界上 GPU 短缺。

the demand, there's a shortage of compute in the world not because there's a shortage of GPUs in the world.

好吧，如果他们给我订单，我就建造。

Okay, if they give me an order I'll build it.

嗯。

Mhm.

对。在过去几年里，我们确实深入了供应链。所以我身后的所有供应链，从晶圆启动到 co-ass HBM 内存，你知道所有那些技术。我们真的准备好了。

Right. We've over the last couple years we've really plumbed the supply chain. So all of the supply chain behind me from wafer starts to co-ass HBM memories, you know all of that technology. We've really geared up.

是的。

Yeah.

如果我们需要翻倍，我们就翻倍。

If we need to double we'll double.

是的。

Yes.

好吧。所以供应链准备好了。现在我们只是在等待需求信号，当云服务提供商、超大规模云服务商和我们的客户制定他们的年度计划并给我们他们的预测时，我们对此做出响应并据此建设。

Okay. So the supply chain is ready. Now we're just waiting for demand signals and when the CSPs and the hyperscalers and our customers do their annual plan and they give us their forecast, we respond to that and we build to that.

现在当然发生的是，他们提供给我们的每一个预测结果都是错误的

Now what's going on of course is that every one of their forecasts that they provide us turns out to have been wrong

对

right

因为他们低估了预测

because they under forecasted

所以现在我们总是处于争抢模式。

and so now we're always in a scramble mode.

嗯。

Mhm.

所以我们处于争抢模式已经，你知道，几年了

And so we've been in the scramble mode now for you know a couple of years

而且无论我们得到什么预测，总是

and it's whatever forecast we've been given has been always

比去年显著增加，但还不够。

significant increase from last year but not enough.

萨提亚去年似乎有点退缩。你知道，似乎，你知道有些人称他为房间里的大人，在压低一些这些预期。几周前他说，嘿，我今年也建了两个千兆瓦，我们未来会加速。你看到一些传统的超大规模云服务商可能比，比如说 CoreWeave 或 Elon X 或可能比 Stargate 慢一点吗？你看到他们全部了吗？在我看来，他们现在都更加投入了，而且他们也都在

Satya last year seemed to be pulling back a little bit. You know seemed to be, you know some people called him the adult in the room tamping down kind of some of these expectations. A few weeks ago he said hey I've also built two gigs this year and we're going to accelerate in the future. Do you see some of the traditional hyperscalers that may have been moving a little slower than let's call it a CoreWeave or or Elon X or maybe a little slower than Stargate? Do you see them all? It sounds like to me they're all leaning in more now and they're all also

因为第二个指数级增长。

because of the second exponential.

好吧。

Okay.

我们已经经历了一个指数级增长，那就是 AI 的采用率，AI 的参与度正在指数级增长。

We've already had one exponential we were experiencing which was the adoption rate of AI, the engagement of AI was growing exponentially.

是的。第二个指数级增长是推理能力。

Yes. The second exponential that kicked in was reasoning.

对。

Yeah.

这是我们一年前的对话。

That was the conversation we had one year ago.

一年前。

One year ago.

对。我们说：‘听着，当你把 AI 从单次推理、记忆答案和泛化中解放出来，那基本上就是预训练。’

Yeah. We said, 'Hey, listen. The moment you take AI from one shot, memorizing an answer and generalizing, that's basically pre-training.'

对。

Yeah.

所以记忆答案，比如你知道 8*8 是多少？直接记住就行。好吧。所以记忆答案和泛化，那是单次推理 AI。一年前，推理出现了，研究出现了，工具使用出现了，现在你有了会思考的 AI。它会消耗更多算力。

So memorizing an answer, you know what's 8*8? Just memorize it. Okay. And so memorizing an answer and generalizing, that was one shot AI. Now a year ago, reasoning came about, research came about, tool use came about, and now you're a thinking AI. It's going to use a lot more compute.

10 亿倍。

1 billion X.

某些超大规模客户，正如你所说，有内部工作负载无论如何都需要从通用计算迁移到加速计算。所以他们挺过了这个周期。我想也许一些超大规模厂商有不同的工作负载，所以不太确定能多快消化，但现在所有人都得出结论：他们严重建设不足。

Certain hyperscale customers, to your point, had internal workloads that they had to migrate anyways from general purpose computing to accelerated computing. So they built through the cycle. I think maybe some hyperscalers had different workloads so they weren't quite sure how quickly they could digest it, but everyone has now concluded that they dramatically underbuilt.

我最喜欢的应用之一就是传统的数据处理，结构化和非结构化数据。就是传统的数据处理。很快我们将宣布一个非常大的加速数据处理计划。数据处理目前占全球 CPU 工作负载的绝大部分。它仍然完全运行在 CPU 上。你知道，如果你去 Databricks，主要是 CPU；去 Snowflake，主要是 CPU；Oracle 的 SQL 处理，主要是 CPU。每个人都在用 CPU 做 SQL 结构化数据。未来，这一切都将转向 AI 数据。那是一个巨大的市场，我们将进入。但你需要 Nvidia 所做的一切都需要加速层和特定领域的数据处理方案。我们必须去构建它，但这即将到来。

One of the applications that my favorite is just good old-fashioned data processing, structured data and unstructured data. Just good old-fashioned data processing. And very soon we are going to announce a very big initiative of accelerated data processing. Data processing represents the vast majority of the world's CPUs today. It still completely runs on CPUs. You know, if you go to Databricks, it's mostly CPUs. You go to Snowflake, mostly CPUs. SQL processing at Oracle, mostly CPUs. Everybody's using CPUs to do SQL structured data. In the future, that's all going to move to AI data. That is one gigantic massive market that we're going to move to. But you need everything that Nvidia does requires acceleration layers and requires domain-specific data processing recipes. We got to go build that, but that's coming.

一个反对意见是，我昨天打开 CNBC，他们说‘过剩泡沫’。打开彭博社，说的是循环收入和回流交易。为了家里观众的利益，这些安排是指公司进行误导性交易，人为夸大收入，没有任何经济实质。所以增长是由金融工程支撑的，而不是客户需求。大家引用的经典案例是 25 年前上次泡沫中的思科和北电。所以当你们或微软、亚马逊投资于也是你们大客户的公司时，比如你们投资 OpenAI，而 OpenAI 购买数百亿芯片，请提醒我们，彭博社和其他分析师在过度炒作循环收入或回流交易时，到底错在哪里？

One of the pushbacks, I turned on CNBC yesterday, they were like 'glut bubble'. When I turned on Bloomberg, it was about round-tripping and circular revenues. For the benefit of people at home, these arrangements are when companies enter into a misleading transaction that artificially inflates revenue without any underlying economic substance. So growth propped up by financial engineering, not by customer demand. The canonical case everybody's referencing is Cisco and Nortel from the last bubble 25 years ago. So when you guys or Microsoft or Amazon are investing in companies that are also your big customers, in this case you guys investing in OpenAI while OpenAI is buying tens of billions of chips, just remind us what are the analysts on Bloomberg and otherwise getting wrong when they're hyperventilating about circular revenues or about round-tripping?

10 吉瓦大约相当于 4000 亿美元，对吧？差不多。那 4000 亿美元必须主要由他们的承购来资助，对吧？他们的收入，正在指数级增长。它必须由他们的资本、通过股权筹集的资金以及他们能筹集的任何债务来资助。这是三种方式。他们能筹集的股权和债务与他们能维持的收入信心有关，当然。所以聪明的投资者和聪明的贷款人会考虑所有这些因素。从根本上说，这就是他们要做的。那是他们的公司，不是我的事。当然，我们必须与他们保持密切联系，确保我们的建设支持他们的持续增长。好吗？所以，收入方面与投资方面无关。投资方面不与任何东西挂钩。这是一个投资他们的机会。正如我们之前提到的，这很可能是下一个万亿美元级别的超大规模公司。谁不想成为投资者呢？你知道，我唯一的遗憾是他们早期邀请我们投资。我记得那些对话，我们当时太穷了，你知道，我们太穷了，投资不够，你知道，我应该把所有的钱都给他们。

10 gigawatts is like $400 billion, right? Something like that. And that $400 billion will have to be largely funded by their offtake, right? Their revenue, which is growing exponentially. It has to be funded by their capital, the money they've raised through equity and whatever debt they can raise. Those are the three vehicles. And the equity that they could raise and the debt that they could raise has something to do with the confidence of the revenues that they could sustain, for sure. And so smart investors and smart lenders will consider all of these factors. Fundamentally, that's what they're going to do. That's their company. It's not my business. And of course, we have to stay very close to them to make sure that we build in support of their continued growth. Okay? And so, there's the revenue side of it and has nothing to do with the investment side of it. The investment side of it is not tied to anything. It's an opportunity to invest in them. And as we were mentioning earlier, this is likely going to be the next multi-trillion dollar hyperscale company. And who doesn't want to be an investor in that? You know, my only regret is that they invited us to invest early on. I remember those conversations and we were so poor, you know, we were so poor, we didn't invest enough, you know, and I should have given them all my money.

现实是，如果你们不做好本职工作，跟不上节奏，如果 Vera Rubin 没有变成好芯片，他们可以去拿其他芯片放进这些数据中心，对吧？他们没有义务必须用你们的芯片。就像你说的，你把这看作一个机会主义的股权投资。另一件事我想说，我们做了一些很棒的投资。我得说出来，你知道，我们投资了 xAI，投资了 CoreWeave。太棒了。是啊。那有多聪明？

And the reality is, if you guys don't do your jobs and keep up with, if Vera Rubin doesn't turn into a good chip, they can go get other chips and put them in these data centers, right? There's no obligation that they have to use your chips. And like you said, you're looking at this as an opportunistic equity investment. The other thing I would say, and we've made some great investments. I got to put it out there, you know, we invested in xAI, we invested in CoreWeave. Incredible. Yeah. How smart was that?

对。当我回顾这一点时，另一个基本问题似乎是，你知道，你把它摆出来了。你说这就是我们在做的。而背后的经济实质，对吧？并不是你们两家公司之间来回输送收入。我们有用户每月为 ChatGPT 付费，15 亿月活用户在使用产品。你刚才说世界上每个企业要么做这个，要么死。每个主权国家都认为这对他们的国家安全和经济安全如同核能一样生死攸关。哪个人、公司或国家会说智能对我们来说基本是可有可无的？我的意思是，这对他们来说是根本性的。

Yeah. As I go back to this, the other fundamental thing it seems to me is, you know, you're putting it out there. You're saying this is what we're doing. And the underlying economic substance here, right? It's not that you're just somehow sending revenues back and forth between the two companies. We got people sending money every month for ChatGPT, a billion and a half monthly users using the product. You just said every enterprise in the world is either going to do this or they will die. Every sovereign views this as existential to their national security and economic security as nuclear power. What person, company or nation says intelligence is basically optional for us? I mean it's fundamental to them.

嗯，智能的自动化。我把需求问题讲烂了。所以我们稍微跳进系统设计。我马上要问 Clark。但在 2024 年，你切换到了年度发布周期，对吧，用 Hopper。然后你进行了一次大规模升级，需要 Grace Blackwell 对数据中心进行重大改造。2025 年，以及 26 年下半年，我们将迎来 Vera Rubin。27 年我们将有 Ultra，28 年 Fineman。年度发布周期进展如何？采用年度发布周期的主要目标是什么？Nvidia 内部的 AI 是否让你能够执行年度发布周期？

Well, the automation of intelligence. I beat the demand question to death. So let's jump in a little bit to system design. I'm going to turn to Clark here in a second on that. But in 2024, you switched to your annual release cycle, right, with Hopper. You then had a massive upgrade which required significant data center overhaul with Grace Blackwell. In 2025, and in the back half of 26, we're going to get Vera Rubin. 27 we'll get Ultra and 28 Fineman. How is the annual release cycle going? What were the main goals of going to an annual release cycle? And did AI inside Nvidia allow you to execute the annual release cycle?

是的，答案是肯定的。关于最后一个问题，没有它，Nvidia 的速度、节奏和规模都会受限。所以如今没有 AI，根本不可能建成我们建成的。现在，我们为什么这么做？记得 Eddie 在他的财报电话会议或他的会议上说过。Satya 说过，Sam 也说过。Token 生成率正在指数级增长。

Yeah, the answer is yes. On the back on the last question, without it, Nvidia's velocity, our pace, our scale would be limited. And so without AI these days, it's just simply not possible to build what we built. Now, why do we do it? There's something that remember Eddie said it at his earnings call or his conference. Satya has said it, Sam has said it. The token generation rate is going up exponentially.

客户使用量正在指数级增长。我记得他们周活跃用户大概有 8 亿？距离 ChatGPT 推出还不到两年，对吧？而且每个用户生成的 token 数量也大幅增加，因为他们使用了推理时推理。

And the customer use is going up exponentially. I think they're at 800 million weekly active users or something like that. That's less than two years from ChatGPT, right? And each of those users is generating massively more tokens because they're using inference time reasoning.

没错，正是如此。首先，token 生成速率增长得如此惊人，两个指数叠加在一起，我们必须以难以置信的速度提升性能，否则 token 生成成本会持续上升，因为摩尔定律已经失效了。现在晶体管每年的成本基本不变，电力成本也大致相同。除非我们发明新技术来降低成本，否则即使增长率略有差异，也只能带来几个百分点的折扣。这怎么能抵消两个指数增长呢？所以我们必须每年以跟上那个指数的速度提升性能。

That's right. Exactly. So the first thing is because the token generation rate is going up so incredibly, two exponentials on top of each other, we have to increase the performance at incredible rates, or the cost of token generation will keep growing because Moore's law is dead. Transistors basically cost the same every year now, and power is largely the same. Unless we come up with new technologies to drive the cost down, even a slight difference in growth gives a discount of a few percent. How's that going to make up for two exponentials? So we have to increase our performance annually at a pace that keeps up with that exponential.

那么从 Kepler 到 Hopper，性能提升大概是 10 万倍。那是英伟达 AI 之旅的开端。10 年 10 万倍。

So in the case of going from Kepler all the way to Hopper was probably 100,000x. That was the beginning of the AI journey for Nvidia. 100,000x in 10 years.

从 Hopper 到 Blackwell，因为 NVLink 72，我们在一年内实现了 30 倍提升。然后 Rubin 会再带来一个倍数，Fineman 再一个。我们能做到这一点，是因为晶体管帮不上太多忙了。摩尔定律主要体现在密度增长，但性能并没有提升。所以一个挑战是，我们必须从系统层面分解整个问题，同时改变每一块芯片、整个软件栈和所有系统。这是终极的极致协同设计。以前从来没有人在这个层面上进行过协同设计。我们改变了 CPU，革新了 GPU、网络芯片、NVLink 纵向扩展、Spectrum-X 横向扩展。有人说“哦，不就是以太网吗”。Spectrum-X 以太网可不是普通的以太网。人们开始发现这个倍数非常惊人。英伟达的以太网业务是全球增长最快的以太网业务。

Between Hopper and Blackwell, we increased because of NVLink 72, 30x in one year. Then we'll get another X factor with Rubin, and then another with Fineman. The way we do that is because transistors aren't really helping us much. Moore's law is largely density growing, but performance is not. So one challenge is we have to break the entire problem down at the system level and change every chip at the same time, all the software stack, and all the systems. The ultimate extreme co-design. Nobody's ever co-designed at this level before. We change the CPU, revolutionize the GPU, the networking chip, the NVLink scale-up, the Spectrum-X scale-out. Someone said, "Oh yeah, it's just Ethernet." Spectrum-X Ethernet is not just Ethernet. People are starting to discover the X factor is pretty incredible. Nvidia's Ethernet business is the fastest growing Ethernet business in the world.

对于可能不太熟悉的人来说，什么是极致协同设计？

For people who may not be as familiar, what is extreme co-design?

极致协同设计意味着你必须同时优化模型、算法、系统和芯片。你必须跳出框框创新，因为摩尔定律说只要让 CPU 越来越快就行，一切都会变快。你是在框框内创新，只要让芯片更快。但如果芯片不再变快，你该怎么办？跳出框框创新。英伟达真正改变了局面，因为我们做了两件事：发明了 CUDA，发明了 GPU，并且发明了大规模协同设计的理念。这就是为什么我们涉足所有这些行业，创建了所有这些库和协同设计。全栈极致甚至超越了软件和 GPU，现在到了数据中心层面：交换机、网络、交换机里的所有软件、网卡、纵向扩展、横向扩展，优化所有这些。结果就是 Blackwell 到 Hopper 提升了 30 倍。没有任何摩尔定律能实现这一点。这来自极致协同设计。这就是为什么英伟达进入了网络、交换、纵向扩展、横向扩展、跨域扩展，构建 CPU、GPU 和网卡。这也是英伟达软件如此丰富的原因。我们贡献的开源软件比几乎所有公司都多，除了另一家，可能是 AI2 之类的。我们的软件极其丰富，而这还只是 AI 领域。别忘了计算机图形学、数字生物学、自动驾驶。我们公司生产的软件量令人难以置信，这让我们能够进行深入而极致的协同设计。

Extreme co-design means you have to optimize the model, algorithm, system, and chip at the same time. You have to innovate outside the box, because Moore's law said you just have to keep making the CPU faster. Everything got faster. You were innovating within a box. Just make that chip faster. Well, if that chip doesn't go any faster, then what are you going to do? Innovate outside the box. Nvidia really changed things because we did two things: we invented CUDA, invented GPUs, and we invented the idea of co-design at a very large scale. That's why we're in all these industries, creating all these libraries and co-design. Full-stack extreme is even beyond software and GPUs. It's now at the data center level: switches, networking, all that software in the switches and networking and NICs, scale-up, scale-out, optimizing across all of that. As a result, Blackwell to Hopper is 30x. No Moore's law could possibly achieve that. That comes from extreme co-design. That's why Nvidia got into networking, switching, scale-up, scale-out, scale-across, building CPUs, GPUs, and NICs. That's the reason Nvidia is so rich in software. We check in more open-source software than just about anybody except one other company, I think AI2 or something. We have such enormous richness of software, and that's just in AI. Don't forget computer graphics, digital biology, autonomous vehicles. The amount of software we produce as a company is incredible, allowing us to do deep and extreme co-design.

我从你一个竞争对手那里听说，你这样做是为了降低 token 生成成本，但同时你的年度发布周期让竞争对手几乎无法跟上。供应链被锁得更紧，因为你给了供应链三年的可见性。现在供应链对他们能建造什么有了信心。你考虑过这个吗？

I heard from one of your competitors that you're doing this to drive down the cost of token generation, but at the same time your annual release cycle makes it almost impossible for competitors to keep up. The supply chain gets locked up more because you're giving three-year visibility to your supply chain. So now the supply chain has confidence as to what they can build to. Do you think about this?

等等，在你提问之前，想想这个。为了每年完成数千亿美元的 AI 基础设施建设，想想一年前我们必须启动多少产能。我们说的是数千亿美元的晶圆启动和 DRAM 采购。这个规模现在几乎没有公司能跟得上。

Wait, wait, before you ask the question. Think about this. In order for us to do several hundred billion dollars a year of AI infrastructure buildout, think about how much capacity we had to go start a year ago. We're talking about building hundreds of billions of dollars of wafer starts and DRAM buys. This is now at a scale that hardly any company can keep up with.

那么你会说你的护城河今天比三年前更深了吗？

So would you say your competitive moat is greater today than it was three years ago?

是的。你知道，首先，竞争比以往任何时候都多，但也比以往任何时候都更难。

Yeah. You know, first of all, there's just more competition than ever before, but it's harder than ever before.

我之所以这么说，是因为晶圆成本越来越高，这意味着除非你进行极大规模的协同设计，否则根本无法实现 10 倍的增长。第一点。所以，除非你每年做六、七、八颗芯片，对吧？这才是关键。这不是造一颗 ASIC，而是建一个 AI 工厂系统。这个系统里有很多芯片，它们都是协同设计的，共同实现我们几乎定期获得的 10 倍提升。好了。所以第一点，协同设计是极端的。第二点，规模也是极端的。当你的客户部署一个吉瓦时，那就是 40 万或 50 万颗 GPU，对吧？让 50 万颗 GPU 协同工作是一个奇迹。我的意思是，这简直就是一个奇迹。所以你的客户承担着巨大的风险来购买这一切。你得问问自己：哪个客户会为一个架构下 500 亿美元的订单，对吧？一个未经证实的全新架构，对吧？一个全新的架构。是的。你刚刚流片了一颗全新的芯片。你自己很兴奋，每个人都为你兴奋，你刚展示第一颗硅片，对吧？谁会给你 500 亿美元的订单，对吧？你又为什么要为一颗刚刚流片的芯片启动价值 500 亿美元的晶圆？但对英伟达来说，我们可以做到，因为我们的架构已经非常成熟。所以我们的客户规模是如此惊人。现在，我们供应链的规模也是惊人的，对吧？谁会为一家公司启动所有这些，预先建造所有这些，除非他们知道英伟达能够交付？不是吗？他们相信我们能够交付给全球所有的客户。他们愿意一次启动数千亿美元。这就是规模，令人难以置信。

And the reason why I say that is because wafer costs are getting higher, which means that unless you do co-design at an extreme scale, you're just not going to be able to deliver the 10x factor growth. Number one. And so unless you're working on six, seven, eight chips a year, right? That's the amazing thing. It's not about building an ASIC, it's about building an AI factory system. And this system has a lot of chips in it, and they're all co-designed, and together they deliver that 10x factor that we get almost regularly. Okay. So number one, the co-design is extreme. The second thing is that the scale is extreme. When your customers deploy a gigawatt, that's 400,000 or 500,000 GPUs, right? Getting 500,000 GPUs to work together is a miracle. I mean, it's just a miracle. And so your customers are taking enormous risk on you to go buy all of this. You got to ask yourself: what customer would place a $50 billion PO on an architecture, right? On an unproven architecture, a new one, right? A new architecture. Yeah. You just tape out a whole new chip. You're as excited as you are about it, and everybody's excited for you, and you just show the first silicon, right? Who's going to give you a $50 billion PO, right? And why would you start $50 billion worth of wafers for a chip that just taped out? But for Nvidia, we could do that because our architecture is so proven. So the scale of our customer is so incredible. Now the scale of our supply chain is incredible, right? Who's going to start all of that stuff, pre-build all of that stuff for a company unless they know that Nvidia can deliver through? Isn't that right? And they believe that we can deliver through to all of the customers around the world. They're willing to start several hundred billion dollars at a time. This is just the scale is incredible.

说到这一点，全球最大的关键辩论和争议之一就是 GPU 与 ASIC 的问题，比如 Google 的 TPU、Amazon 的 Trainium，而且似乎从 ARM 到 OpenAI 到 Anthropic，每个人都被传在造自己的芯片。去年你说我们造的是系统，不是芯片，你通过堆栈的每一部分来驱动性能。你还说很多这类项目可能永远无法达到生产规模。但考虑到 Google TPU 看似成功，你今天如何看待这个不断演变的格局？

To that point, one of the biggest key debates and controversies in the world is this question of GPUs versus ASICs, Google's TPUs, Amazon's Trainium, and it seems like everyone from ARM to OpenAI to Anthropic are rumored to be building one. Last year you said we're building systems, not chips, and you're driving performance through every single part of that stack. You also said that many of these projects may never get to production scale. But given the seeming success of Google's TPUs, how are you thinking about this evolving landscape today?

首先，Google 的优势在于远见。记住，他们在一切开始之前就启动了 TPU1。这和创业公司没什么不同。你应该在市场成长之前就创建一家创业公司。你不应该等到市场价值万亿美元时才作为创业公司出现。有一个谬论，所有 VC 都知道这个谬论，那就是一个大市场，如果你能只占几个百分点的市场份额，你就能成为一家巨头公司。这实际上是根本错误的。你应该占据一个小公司、一个小行业的 100%，这就是英伟达所做的，对吧？TPU 也是。当时只有我们两家。但你最好希望那个行业变得非常大。你是在创造一个行业。没错。所以这就是现在那些造 ASIC 的人面临的挑战。这看起来是一个诱人的市场，但记住，这个诱人的市场已经从一颗叫 GPU 的芯片演变成了一个 AI 工厂。你们刚刚看到我发布了一颗叫 CPX 的芯片，用于上下文处理和扩散视频生成，这是一个非常专门的工作负载，但在数据中心内很重要。我刚刚把它预告为可能是 AI 数据处理处理器，因为猜怎么着？你需要长期记忆。你需要短期记忆。KV 缓存处理非常密集。AI 记忆是个大事。你希望你的 AI 有好的记忆，而处理系统中所有的 KV 缓存，非常复杂。也许它需要一个专门的处理器。也许还有其他东西，对吧？所以你看，英伟达的观点现在不是 GPU。我们的观点是着眼于整个 AI 基础设施，以及这些了不起的公司需要什么来让它们所有多样且不断变化的工作负载通过它。看看 Transformer。Transformer 架构正在发生难以置信的变化。如果不是因为 CUDA 易于操作和迭代，他们如何尝试大量的实验来决定使用哪个 Transformer 版本、哪种注意力算法？如何解耦？CUDA 帮你做所有这些，因为它可编程性极强。所以现在思考我们业务的方式是：当所有这些 ASIC 公司或 ASIC 项目在三、四、五年前开始时，我得告诉你，那个行业非常可爱和简单。当时涉及一颗 GPU，对吧？但现在它巨大而复杂，再过两年它将变得完全庞大。规模将如此之大。所以我认为，作为一个新玩家进入一个非常大的市场是非常困难的，正如你们所知。即使对于那些可能成功使用 ASIC 的客户来说也是如此。

First of all, the advantage that Google had is foresight. Remember, they started TPU1 before everything started. This is no different than a startup. You're supposed to build a startup before the market grows. You're not supposed to come up as a startup when the market's a trillion dollars large. This fallacy, and all VCs know this fallacy, that a large market, if you could just take a few percent market share, you could be a giant company. That's actually fundamentally wrong. You're supposed to take 100% of a tiny company, a tiny industry, which is what Nvidia did, right? Which is what TPUs did. There were only the two of us. But you better hope that that industry gets really big. You're creating an industry. That's right. And so that's the challenge for the people who are building ASICs now. It looks like a juicy market, but remember, this juicy market has evolved from a chip called a GPU to an AI factory. And you guys just saw I just announced a chip called CPX for context processing and diffusion video generation, a very specialized workload but an important workload inside a data center. I just prelude it to maybe AI data processing processors because guess what? You need long-term memory. You need short-term memory. The KV cache processing is really intense. AI memory is a big deal. You kind of like your AI to have good memory, and just dealing with all the KV caching around the system, really complicated stuff. Maybe it wants to have a specialized processor. Maybe there's other things, right? So you see that Nvidia's viewpoint is now not GPU. Our viewpoint is looking at the entire AI infrastructure and what it takes for these incredible companies to get all of their workload through it, which is diverse and changing. Look at the transformer. The transformer architecture is changing incredibly. If not for the fact that CUDA is easy to operate on and iterate on, how do they try all of their vast number of experiments to decide which one of the transformer versions, what kind of attention algorithm to use? How do you disaggregate? CUDA helps you do all that because it's so programmable. And so the way to think about our business now is: when all of these ASIC companies or ASIC projects started three, four, five years ago, I got to tell you, that industry was super adorable and simple. There was a GPU involved, right? But now it's giant and complex, and in another two years it's going to be completely massive. The scale is going to be so large. And so I think that the battle of getting into a very large market as a new player is just hard, as you guys know. Even for the customers who perhaps are successful with ASICs.

他们的计算集群中是否存在一个最优平衡？我认为投资者是非常二元化的生物。他们只想要一个是或否、黑或白的答案。但即使你让 ASIC 工作，难道没有一个最优平衡吗？因为你想，我买英伟达平台，CPX 会出来用于预填充、视频生成，也许还有解码，一个视频平台。

Isn't there an optimal balance in their compute fleet? Like, I think investors are very much binary creatures. They just want a yes or no, black and white answer. But even if you get the ASIC to work, isn't there an optimal balance because you think I'm buying the Nvidia platform, CPX is going to come out for prefill for video generation, maybe a decode, a platform video.

完全正确。所以会有很多不同的芯片或部件加入英伟达生态系统，加速计算集群，对吧？随着新工作负载的出现。

Exactly. So there will be many different chips or parts to add to the Nvidia ecosystem, accelerated compute fleet, right? As new workloads are born.

而且今天试图流片新芯片的人并没有真正预料到一年后会发生什么。他们只是想让芯片工作。

And people trying to tape out new chips today are not really anticipating what's happening a year from now. They're just trying to get a chip to work.

没错。

That's right.

换个说法，Google 是一个大型 GPU 客户。

Set another way, Google's a big GPU customer.

Google 是一个大型 GPU 客户。

Google's a big GPU customer.

如果你看看谷歌，那是一个非常特殊的案例。我的意思是，我们必须对值得尊重的地方表示敬意。TPU 已经到了 TPU7。没错。这对他们来说也是一个挑战。他们所做的工作极其困难。所以让我回想一下：芯片有三类。有架构芯片：X86 CPU、ARM CPU、英伟达 GPU。一种架构之上有生态系统，架构允许丰富的 IP 和丰富的生态系统，技术非常复杂。它由像我们这样的所有者构建。还有 ASIC。我曾在发明 ASIC 概念的原公司 LSI Logic 工作过。如你所知，LSI Logic 已经不在了。原因是当市场规模不是很大时，ASIC 确实很棒。很容易找承包商帮你把封装做好，并替你进行制造，他们收取 50-60 个点的利润。但当 ASIC 的市场变大时，有一种新的做法叫 COT，即客户自有工具。谁会这么做呢？苹果智能手机芯片的规模如此之大，他们绝不会付给别人 50-60% 的毛利率来做 ASIC。他们做客户自有工具。那么当 TPU 成为大业务时，它会走向何方？客户自有工具。毫无疑问。但 ASIC 也有其用武之地。视频转码器永远不会太大。智能网卡永远不会太大。所以当一家 ASIC 公司同时有 10、12、15 个 ASIC 项目在进行时，我并不惊讶，因为可能其中有五个智能网卡和四个转码器。它们都是 AI 芯片吗？当然不是。如果有人要为特定的推荐系统构建一个嵌入式嵌入处理器，并且那是一个 ASIC，当然可以。但你会把它作为不断变化的 AI 的基础计算引擎吗？你有低延迟工作负载、高吞吐量工作负载、用于聊天的 token 生成、思考工作负载、AI 视频生成工作负载。现在你谈论的是加速计算的主力骨干。这正是英伟达的全部。简单来说，就像下国际象棋和跳棋。事实是，今天开始做 ASIC 的人，无论是 Tranium 还是其他一些加速器，他们都在构建一个芯片，这个芯片是更大机器的一个组件。

If you look at Google, it's a very special case. I mean, we just have to show respect where respect is really deserved. TPU is on TPU7. Right. And it's a challenge for them as well. The work they do is incredibly hard. So let me remember: there are three categories of chips. There are architectural chips: X86 CPUs, ARM CPUs, Nvidia GPUs. An architecture has an ecosystem above it, and the architecture allows rich IP and rich ecosystem, very complicated technology. It's built by the owners like us. There are ASICs. I worked for the original company LSI Logic, who invented the idea of ASIC. As you know, LSI Logic is not here anymore. The reason is that ASIC is really fantastic when the market size is not very large. It's easy to have a contractor help you put the packaging together and do the manufacturing on your behalf, and they charge you 50-60 points of margin. But when the market gets large for an ASIC, there's a new way of doing things called COT, customer-owned tooling. Who would do something like that? Apple's smartphone chip volume is so large they would never pay somebody else 50-60% gross margin to be an ASIC. They do customer-owned tooling. So where will TPUs go when they become a large business? Customer-owned tooling. There's no question about it. But there's a place for ASIC. Video transcoders will never be too large. Smart NICs will never be too large. So when there are 10, 12, 15 ASIC projects going on at an ASIC company, I'm not surprised, because there are probably five smart NICs and four transcoders. Are they all AI chips? Of course not. If somebody were to build an embedded embedding processor for a specific recommender system and that was an ASIC, you could do that. But would you do that as the fundamental compute engine for AI that's changing all the time? You've got low latency workload, high throughput workload, token generation for chat, thinking workload, AI video generation workload. Now you're talking about the workhorse backbone of your accelerated computing. That's what Nvidia is all about. To dumb it down, it's like playing chess and checkers. The fact is, the folks who are starting ASIC today, whether it's Tranium or some of these other accelerators, they're building a chip that's a component of a much larger machine.

你构建了一个非常复杂的系统、平台、工厂，随便你怎么称呼，现在你稍微开放了一点。所以，你提到了 CPXGPU，对吧？在我看来，你在某种程度上将工作负载解耦到最适合该特定领域的硬件切片上。

You've built a very sophisticated system, platform, factory, whatever you want to call it, and now you're opening up a little bit. So, you mentioned CPXGPU, right? It seems to me that in some ways you're disaggregating the workloads to the best slice of the hardware for that particular domain.

嗯，我们宣布了一个叫 Dynamo 的东西，解耦式 AI 工作负载编排，并且我们将其开源，因为未来的 AI 工厂是解耦的。

Well, we announced this thing called Dynamo, disaggregated AI workload orchestration, and we open sourced it because the future AI factory is disaggregated.

对，你推出了 NV Fusion，这甚至对你的竞争对手说，包括你刚刚投资的英特尔，没错，你们参与我们正在构建的这个工厂的方式，因为没有其他人疯狂到试图建造整个工厂，但如果你有一个足够好、足够有说服力的产品，最终用户会说，‘嘿，我们想用这个而不是 ARM GPU，或者我们想用这个而不是你的推理加速器等等。’是这样吗？

Right, and you launched NV Fusion, which even said to your competitors, including Intel which you just invested in, that's right, the way in which you participate in this factory that we're building, because nobody else is crazy enough to try to build the entire factory, but you can plug into that if you have a product that's good enough, compelling enough that the end user says, 'Hey, we want to use this instead of an ARM GPU or we want to use this instead of your inference accelerator, etc.' Is that correct?

我们很高兴让你接入。是的。告诉我们一点。Fusion 是个很棒的主意，我们很高兴与英特尔合作。它利用了英特尔生态系统，你知道，世界上大多数企业仍然运行在英特尔上。它结合了英特尔生态系统、英伟达 AI 生态系统、加速计算，我们将它们融合在一起。对吧？我们也和 ARM 这样做了。对吧？还有几个其他公司我们也会这样做。这为我们双方都打开了机会。这是双赢。巨大的胜利。我会成为他们的大客户，而他们将让我们接触到更大的市场机会。

We're delighted to connect you in. Yeah. Tell us a little bit. Fusion is such a great idea, and we're so happy to partner with Intel on that. It takes the Intel ecosystem, you know, most of the world's enterprise still runs on Intel. It takes the Intel ecosystem, takes the Nvidia AI ecosystem, accelerated computing, and we fused it together. Right? And we did that with ARM. Right? And there are several others we're going to be doing it with. That opens up opportunities for both of us. It's a win for both of us. Great win. I'll be a large customer of theirs, and they're going to expose us to a much larger market opportunity.

是的。这与你的一个论点密切相关，这个论点让一些人震惊：你说我们的竞争对手做 ASIC，他们的芯片今天已经更便宜了，但他们甚至可以定价为零，我们的目标是他们可以定价为零，而你仍然会购买英伟达系统，因为运行该系统的总成本——电力、数据中心、土地等——产出的智能仍然比购买芯片（即使免费）更划算，因为土地、电力和外壳已经花了 150 亿美元。对吧？是的。所以我们尝试计算了一下。但请带我们过一遍你的计算，因为我认为对于不常接触这方面的人来说，这根本说不通。考虑到你芯片的昂贵，怎么可能你的竞争对手芯片定价为零，而你的仍然是更好的选择？

Yeah. That's deeply related to this idea is the argument you've made that kind of shocked some people where you say our competitors building ASIC, they could literally all their chips are cheaper already today, but they could literally price them at zero, our objective is they could price them at zero and you would still buy an Nvidia system because the total cost of operating that system, power, data center, land, etc., the intelligence out is still a better bet than buying a chip even if it's given to you for free, because the land, power, and shell is already $15 billion. Right? Yeah. So, we've taken a crack at kind of the math on that. But walk us through your math because I think for people who don't spend as much time here, it just doesn't compute. How could it possibly be that you were pricing your competitor's chips at zero given the expense of your chips and it still is a better bet?

有两种思考方式。一种是从收入的角度。好吧。每个人都受限于电力，假设你能够获得额外的 2 吉瓦电力。那么，你希望这 2 吉瓦电力转化为收入。所以你的性能或每瓦 token 数是别人的两倍，因为你做了深度和极致的代码设计，对吧？我的每单位能量性能高得多，那么我的客户可以从他们的数据中心产生两倍的收入。谁不想要两倍的收入呢？如果有人给他们 15% 的折扣，你知道，我们的毛利率（称为 75 个点）和别人的毛利率（比如 50 到 65 个点）之间的差异，并不足以弥补 Blackwell 和 Hopper 之间 30 倍的差距。假设 Hopper 是一款了不起的芯片，一个了不起的系统。假设别人的 ASIC 就是 Hopper。是的。Blackwell 是 30 倍。所以在那 1 吉瓦电力上，你不得不放弃 30 倍的收入。这太多了，无法放弃。所以即使他们免费给你，你只有 2 吉瓦可用。

There are two ways to think about it. One way is from a perspective of revenues. Okay. So everybody's power limited, and let's say you were able to secure two more gigawatts of power. Well, that two gigawatts of power you would like to have translate to revenues. So your performance or tokens per watt was twice as high as somebody else's tokens per watt because you did deep and extreme code design, right? And my performance was much higher per unit energy, then my customer can produce twice as much revenues from their data center. And who doesn't want twice as much revenues? And if somebody gave them a 15% discount, you know, the difference between our gross margins, which is called the 75 points, and somebody else's gross margins, call it the 50 to 65 points, is not so much as to make up for the 30 times difference between Blackwell and Hopper. Let's pretend Hopper is an amazing chip, an amazing system. Let's pretend somebody else's ASIC is Hopper. Yeah. Blackwell's 30 times. So you've got to give up 30x revenues in that one gigawatt. It's too much to give up. So even if they gave it to you for free, you only have 2 gigawatts to work with.

你的机会成本高得离谱。

Your opportunity cost is so insanely high.

你总是会选择每瓦性能最好的。

You would always choose the best perf per watt.

我听到一家超大规模云服务商的 CFO 说，鉴于你们芯片带来的性能提升——正好说到每千兆 token 和功耗这个限制因素——他们不得不升级到新周期。那么展望 Rubin、Rubin Ultra、Feynman，这个轨迹会持续吗？

So I heard this from one of the CFOs at one of the hyperscalers that given the performance improvement right that's coming out of your chips again precisely to that point tokens per gig and power being the limiting factor right that they had to upgrade to the new cycle. So when you look ahead at Rubin, at Rubin Ultra, at Feynman, does that trajectory continue?

我们现在每年大概做六、七款芯片。每一款都是那个系统的一部分。没错。而且系统软件无处不在，需要整合和优化这六、七款芯片才能实现 Blackwell 的 30 倍性能。现在想象我每年都这样做。砰砰砰砰砰砰。所以如果你在那堆芯片里只做一个 ASIC，而我们是在整体优化，那是个很难解决的问题。

We're building what, six, seven chips a year now. And each one is part of that system. That's right. And that system software is everywhere and it takes the integration and the optimization across all of those six or seven chips to deliver on the 30x Blackwell. Now imagine I'm doing this every single year. Bam, bam, bam, bam, bam, bam. And so if you build one ASIC in that soup of chips and we're optimizing across that, it's a hard problem to solve.

这让我回到我们一开始谈的护城河。我们一直在报道这个，投资者也是。我们投资了整个生态系统，也包括你的竞争对手，从 Google 到 Broadcom。但当我从第一性原理出发问：你的护城河是在扩大还是缩小？你转向了年度迭代。你和供应链共同开发。规模比任何人预期的都要大得多，这需要资产负债表和开发规模都跟上。你通过收购和自研所做的那些事——比如我们刚谈到的 NVLink、CPX——所有这些让我相信你的护城河在扩大，至少在建设工厂或系统方面是这样。

This does bring me back to where we started about the competitive moat. We've been covering this and investors for a while. We're investors throughout the ecosystem and in competitors of yours, from Google to Broadcom. But when I really first principles around this and say: are you increasing or decreasing your competitive moat? You move to an annual cadence. You're co-developing with a supply chain. The scale is massively bigger than anybody anticipated, which requires scale both of balance sheet and of development. The moves you made both through acquisition and organically with things like NVLink, CPX, which we just talked about. All of those things together cause me to believe that your competitive moat is increasing, at least in so far as building out the factory or the system.

至少是令人惊讶的。

It's at least surprising.

但我觉得有意思的是，你的市盈率比大多数其他公司低得多。我认为部分原因是大数定律。一家 4.5 万亿美元的公司不可能再大了。但一年半前我问过你：今天坐在这里，如果市场 AI 工作负载增长 5 倍或 10 倍，我们知道资本支出在做什么等等。你能否想象一个世界，五年后你的营收不是 2025 年的两到三倍？考虑到这些优势，它实际上不比今天高多少的概率有多大？

But I think it's interesting that your multiple is much lower than most of those other people. And I think part of that has to do with this law of large numbers. A $4.5 trillion company couldn't possibly get any bigger. But I asked you this a year and a half ago: as you sit here today, if the market's going to AI workloads are going to 10x or 5x, we know what capex is doing, etc. Is there any conceivable world in your mind where your top line in 5 years isn't two or three times bigger than it is in 2025? What's the probability that it's actually not much higher than it is today given those advantages?

我这样回答吧。我们面临的机会比我描述的要大得多，远超共识。我在这里说：我认为 Nvidia 很可能成为第一家 10 万亿美元的公司。我在这里够久了，就在十年前，正如你记得的，人们说永远不可能有万亿美元公司。现在我们有 10 家，对吧？今天世界更大了。这又回到了 GDP 和增长的指数级。世界更大了，人们误解了我们在做什么。他们记得我们是一家芯片公司。我们造芯片。天哪，我们确实造芯片，造出世界上最神奇的芯片。但 NVIDIA 实际上是一家 AI 基础设施公司。我们是你的 AI 基础设施合作伙伴，我们与 OpenAI 的合作就是完美证明。我们是他们的 AI 基础设施合作伙伴，我们以多种方式与人们合作。我们不要求任何人从我们这里买所有东西。我们不要求他们买整机柜。他们可以买芯片，可以买组件，可以买我们的网络，可以买我们的 CPU。你知道，只买我们的 GPU，然后买别人的 CPU 和别人的网络。我们基本上可以按你喜欢的任何方式卖。我唯一的要求就是买点我们的东西。

I'll answer it this way. Our opportunity as I described it is much larger than the consensus. I'll say it here. I think Nvidia will likely be the first 10 trillion dollar company. And I've been here long enough, it wasn't that long ago, just a decade ago, as you well remember, that people said there could never be a trillion dollar company. Now we have 10, right? And today the world's bigger. This is back to the exponentials around GDP and the growth. The world is bigger and people misunderstand what we do. They remember we're a chip company. We build chips. Boy, do we build chips and build the most amazing chips in the world. But NVIDIA is really an AI infrastructure company. We are your AI infrastructure partner and our partnership with OpenAI is a perfect demonstration of that. We are their AI infrastructure partner and we work with people in a lot of different ways. We don't require anybody to buy everything from us. We don't require that they buy the full rack. They could buy a chip. They could buy a component. They could buy our networking. They could buy our CPU. You know, just buy our GPUs and buy somebody else's CPUs and somebody else's networking. We're kind of okay selling any way you like to buy. My only request is just buy a little something from us.

你说这不只是关于更好的模型。我们还需要世界级的建造者。你说我们国家最世界级的建造者可能就是 Elon Musk。我们谈过 Colossus 1，他在那里做了什么，在一个一致性集群里部署了几十万块 H100、H200。现在他在做 Colossus 2，可能包含 50 万块 GB，数百万块 H100 等效算力在一个一致性集群里。如果他是第一个达到单集群 1 吉瓦的人，我不会惊讶。所以谈谈这个。作为建造者的优势，不只是构建软件和模型，而是理解建造这些集群需要什么。

You said this isn't just about better models. We also have to have world-class builders. And you said the most world-class builder maybe that we have in the country is Elon Musk. And we talked about Colossus 1 and what he was doing there, standing up a couple hundred thousand H100s, H200s in a coherent cluster. Now he's working on Colossus 2, which may be 500,000 GBs, millions of H100 equivalents in a coherent cluster. I would not be surprised if he gets to a gigawatt before anybody else does in one. So say a little bit about that. The advantage of being the builder who isn't just building the software and the models, but understands what it takes to build those clusters.

嗯，这些 AI 超级计算机是很复杂的东西。技术复杂。采购也复杂，因为融资问题。确保土地、电力和外壳、供电都很复杂。建造它、让它全部上线。我的意思是，这不幸是人类有史以来最复杂的系统问题。所以 Elon 有一个巨大优势：在他脑子里，所有这些系统都在相互运作，相互依赖关系都在一个人脑子里，包括融资。

Well, these AI supercomputers are complicated things. The technology is complicated. Procuring it is complicated because of financing issues. Securing the land, power, and shell, powering it is complicated. Building it all, bringing it all up. I mean, these are unfortunately the most complex systems problem humanity has ever endeavored. And so Elon has a great advantage that in his head all of these systems are interoperating and the interdependencies reside in one head, including the financing.

他就是一个大型 GPT。他自己就是一台大型超级计算机。

He's a big GPT. He's a big supercomputer himself.

他是终极 GPU。是的。所以他在这方面有很大优势。而且他有很强的紧迫感。他有真正的建造欲望。所以当意志与技能结合时，不可思议的事情就会发生。非常独特。

He's the ultimate GPU. Yeah. And so he has a great advantage there. And he has a great sense of urgency. He has a real desire to build it. And so when will comes together with skill, unbelievable things can happen. Quite unique.

你深度参与的一件事，我想谈谈主权 AI。我想谈谈中国和正在进行的全球 AI 竞赛。回想 30 年前，你无法想象这周你会和国王在宫殿里，还经常去白宫。总统说过你和 Nvidia 对美国国家安全至关重要。

Something you've been so involved in is I want to talk about sovereign AI. I want to talk about China and the global AI race that's going on. When I look back at you 30 years ago, you couldn't have imagined you were going to be hanging out in palaces with airs and the king this week and you're at the White House all the time. The president has said that you and Nvidia are critical to US national security.

那么，当你第一次看到这个时，先帮我梳理一下。很难相信，如果主权国家不认为这件事至少像我们在 1940 年代看待核武器那样关乎存亡，你会出现在那些地方。我们今天没有曼哈顿计划，至少不是政府资助的，而是由 Nvidia、OpenAI、Meta、Google 资助的。我们有今天规模相当于民族国家的公司，感谢上帝保佑美国，对吧？它们正在资助一些在我看来总统和国王们认为对其未来的经济和国家安全至关重要的事情。你同意吗？

So when you look at that first, just contextualize for me. It's hard to believe that you would be in those places if sovereigns didn't view this as at least as existential as maybe we did nuclear in the 1940s. We don't have a Manhattan Project today, at least funded by the government, but it's funded by Nvidia, it's funded by OpenAI, it's funded by Meta, it's funded by Google. We have companies today the size of nation states, and thank God for America, right? Who are funding something that it appears to me presidents and kings think is existential to their future economic and national security. Would you agree with that?

没有人需要原子弹。每个人都需要 AI。

Nobody needs atomic bombs. Everybody needs AI.

说得好。

Well said.

所以这是一个非常非常大的区别。AI，如你所知，是现代软件。我刚刚从通用计算到加速计算，从人类逐行编写代码到 AI 编写代码。这个基础不能被遗忘。我们重新发明了计算。地球上没有新物种；我们只是重新发明了计算，每个人都需要计算。它需要被民主化。

And so that's a very, very large difference. AI, as you know, is modern software. I just started from general-purpose computing to accelerated computing, from human-written code one line at a time to AI-written code. That foundation can't be forgotten. We've reinvented computing. There's not a new species on Earth; we just reinvented computing, and everybody needs computing. It needs to be democratized.

这就是为什么所有这些国家都意识到他们必须进入 AI 世界，因为每个人都需要留在计算领域。世界上没有人会说：“你知道吗？我昨天还在用电脑。明天我就能用好棍棒和火了。”所以每个人都需要进入计算领域。这只是在现代化而已。就是这样。第一，为了参与 AI，你必须在 AI 中编码你的历史、你的文化、你的价值观。

Which is the reason why all of these countries realize they have to get into the AI world, because everybody needs to stay in computing. There's nobody in the world that says, "Guess what? I used to use computers yesterday. I'm pretty good with clubs and fire tomorrow." So everybody needs to move into computing. It's just being modernized. That's all. Number one, it is the case that in order to participate in AI, you have to encode within AI your history, your culture, your values.

当然，AI 正变得越来越聪明，以至于即使是核心 AI 也能相当快地学习这些东西。你不必从零开始。所以我认为每个国家都需要拥有一些主权能力。我建议他们都使用 OpenAI、Gemini、这些开放模型、Grok，我建议他们都这样做。我建议他们都使用 Anthropic。

And of course, AI is getting smarter and smarter so that even the core AI is able to learn these things fairly quickly. You don't have to start from ground zero. And so I think that every country needs to have some sovereign capability. I recommend that they all use OpenAI, they all use Gemini, they all use these open models, use Grok, and I recommend they all do that. I recommend they all use Anthropic.

但他们也应该投入资源学习如何构建 AI。原因在于他们需要学习如何构建它，不仅是为了语言模型，还需要为工业模型、制造模型、国家安全模型构建它。他们必须自己去培养一大堆智能。所以他们应该拥有主权能力。每个国家都应该发展它。

But they should also dedicate resources to learn how to build AI. And the reason for that is because they need to learn how to build it not just for language models, but they need to build it for industrial models, manufacturing models, national security models. There's a whole bunch of intelligence they have to go cultivate themselves. So they ought to have sovereign capability. Every country should develop it.

这就是你看到的吗？这就是你在世界各地听到的吗？

And is that what you see? Is that what you're hearing around the world?

他们都意识到了。

They all realize it.

他们都意识到了。而且他们都将成为 OpenAI、Anthropic、Grok 和 Gemini 的客户，但他们也都确实需要建立自己的基础设施。这就是一个大想法：Nvidia 所做的就是建设基础设施。就像每个国家都需要能源基础设施、通信和互联网基础设施一样，现在每个国家都需要 AI 基础设施。所以让我们从世界其他地方开始。我们的好朋友 David Sacks，AIS 做得非常出色。

They all realize it. And they all are going to be customers of OpenAI, Anthropic, Grok, and Gemini, but they all really need to also build their own infrastructure. And this is the big idea that what Nvidia does is we're building infrastructure. Just as every country needs energy infrastructure, communications and internet infrastructure, now every single country needs AI infrastructure. So let's start with the rest of the world. Our good friend David Sacks, the AIS are doing a heck of a job.

我们太幸运了。

We are so lucky.

是的。有 David 和 Shriram 在华盛顿特区，在 AISR 做 AI。特朗普总统把他们安排进白宫是多么明智的举动。因为在这个关键时刻，技术很复杂。

Yeah. To have David and Shriram in Washington DC, doing AI in the AISR. What a smart move by President Trump to put them in the White House. Because during this pivotal time, the technology is complicated.

Shriram 是华盛顿特区我认为唯一懂 CUDA 的人。

Shriram is the only person in Washington DC that I think knows CUDA.

是的。这无论如何都很奇怪。但我就是喜欢这样一个事实：在这个关键时刻，技术复杂，政策复杂，对我们国家未来的影响如此巨大，我们有一个人头脑清醒，花时间理解技术，并且深思熟虑地帮助我们度过难关。

Yeah. And which is strange anyways. But I just love the fact that during this pivotal time when technology is complicated, policy is complicated, the impact to the future of our nation is so great, that we have somebody who is clear-minded, dedicating the time to understand the technology and thoughtful to help us through that.

在我看来，回到曼哈顿计划的类比，你有一位总统理解这件事的存亡攸关。你有像德克萨斯州州长 Greg Abbott 这样的州长，想要取消法规以加速发展，因为他们理解这有多重要。你有能源部长、内政部长 Doug Burgum、商务部长 Lutnick，他们也理解这有多重要，他们多么支持能源。你能想象另一种情况吗？如果我们现在有一个不支持能源、不希望能源在我们国家增长以便我们拥有 AI 的政府？我觉得讽刺的是，就在几年前，我们还在说中国正在建造 100 座核反应堆，他们远远领先于我们。那是 AI 的原始阶段。但现在当我们去建造时，每个人都说：“哦，过剩了。”在我看来，这是政府符合其利益的事情。而且我们看到了行业和政府以一种我很久没见过的合作方式。你在这个行业很久了。你现在和特朗普总统关系密切。帮我们理解一下行业与政府关系的本质。我们看到了上周与所有 CEO 的晚宴。你花了很多时间。这是独特的吗？你在过去 30 年的职业生涯中见过这样的事情吗？

And it would seem to me, going back to the Manhattan Project analogy, that you have a president who understands how existential this is. You have governors like Greg Abbott in Texas who want to remove regulations to accelerate because they understand how important it is. You have secretaries at Energy, and Doug Burgum at Interior, and Lutnick at Commerce who also understand how important this is, how pro-energy they are. Could you imagine the alternative if we had an administration right now who is not pro-energy and wants energy to grow in our nation so that we could have AI? I find it ironic that just a couple years ago we were saying China's building 100 nuclear reactors, they're so far ahead of us. That's the primitive to AI. But now you have people when we go to build it, everybody says, "Oh, it's a glut." It seems to me that this is something that the government, it is in their interest. And we have industry and government working together in a way that I haven't seen in a long time. You've been around a long time. You're very close with President Trump at this stage. Help us understand the nature of industry-government relationships. We saw that dinner last week with all the CEOs. You spent a lot of time. Is it unique? Have you seen anything like this in your career over the last 30 years?

过去去华盛顿特区很难，如你所知。预约几乎不可能。特朗普总统对想要进来帮助他理解未来的领导者敞开大门。这是一个相信增长的政府。从根本上说，特朗普总统希望美国增长。如果我们能经济上增长，我们就会在军事上强大。如果我们能经济上增长，我们就会安全。我从未见过一个安全的人是穷人。作为一个国家富裕是国家安全的必要组成部分。他知道这一点。他还希望美国赢得 AI 竞赛。这将是一场非常长期的竞赛。他理解这是一个关键时刻。他希望科技行业蓬勃发展。他希望世界上每个人都建立在美国技术之上。这些都是明智、合乎逻辑的事情。相反的情况对我来说很奇怪。

It was hard to go to DC in the past, as you know. Getting an appointment is almost impossible. President Trump has an open door to leaders who want to come in and help them understand the future. This is an administration that believes in growth. Fundamentally, President Trump wants America to grow. If we can grow economically, we will be strong militarily. If we can grow economically, we will be secure. I've never met somebody who is secure who's poor. Being rich as a nation is an essential part of national security. And he knows that. He also wants America to win the AI race. This is going to be a very long-term race. And he understands that this is a pivotal time. He wants the technology industry to run. He wants everybody in the world to be built on American technology. These are sensible, logical things. The opposite is strange to me.

如果我把一切都反过来想，我们希望国家不增长，因为不希望国家增长，我们就不需要任何能源，因为我们知道增长需要能源，所以干脆不要能源，甚至不希望我们的科技产业领先。

If I take everything and I just reversed it, we want our country not to grow, and because we don't want our country to grow, we don't need any energy because we know we need energy to grow, and so let's not have any energy, and in fact we don't want our technology industry to lead.

他明白我们的科技产业是我们的国家宝藏。

He understands that our technology industry is our national treasure.

没错。

Correct.

而且科技，就像过去的玉米和钢铁一样，现在是如此基本的贸易机会。它是贸易的重要组成部分。为什么你不希望美国科技被所有人渴望，从而用于贸易呢？

And that technology, like corn and steel and things in the past, are now such fundamental trade opportunities. It's an essential part of trade. And why would you not want American technology to be coveted by everyone so that it could be used for trade?

对。那么我们来谈谈互联网。谷歌遍布全球。我们通过搜索将民主价值观传播到世界各地，谷歌不需要去华盛顿获得许可。它就这样发生了。我们将技术扩散到全球。David Sachs 非常明确地指出需要加快出口许可，以便美国 AI 堆栈在全球获胜。对吧？我们说的是芯片、模型、数据中心等等。我们知道一年半前这并没有发生。当时有一个概念叫“小院高墙”之类的。讽刺的是，它的描述和政策建议方式，是在美国周围建一个小院高墙。这就是奇怪的地方。我认为特朗普总统说得对，我们要最大化出口。我们要最大化美国在全球的影响力。我们应该最大化这些东西。

Right. So let's talk about the internet. Google spread around the world. We had democratic values spread around the world by way of search, and Google didn't have to go to Washington to get permission to do it. It just happened. We diffused our technology around the world. David Sachs has been crystal clear on the need to accelerate export licenses so that the American AI stack wins around the world. Right? We're talking chips, we're talking models, we're talking data centers, etc. We know a year and a half ago that wasn't happening. There was a concept called 'small yard, tall fence' or something like that. The irony of it was it was described in such a way and it was recommended in policy in such a way that it was a small yard, tall fence around America. That was the strange part. I think President Trump's got it right that we want to maximize exports. We want to maximize American influence around the world. We're supposed to maximize those things.

你看到这些许可在发放了吗？你看到华盛顿在加速吗？我知道高层在这么说，但你看到它通过政府层层落实，从而加速我们在全球的发展了吗？

And do you see those licenses coming? Are you seeing the acceleration in Washington? I know it's being said at the top, but are you seeing it flow down through government that's accelerating us around the world?

Lutnick 部长对此非常上心。

Secretary Lutnick was all over it.

太好了。是的。

Great. Yeah.

那么，现在我们来谈谈中国。你可能不知道，我认为你比美国任何一位领导人都更了解中国。

So, now let's talk about China. You know what most people may not realize is I think you understand China as well as any leader in the United States.

我们在中国已经 30 年了。

We've been there for 30 years.

已经 30 年了。大多数人没有意识到的是，直到几年前，你在中国的市场份额占主导地位……

Been there for 30 years. What most people don't realize is that up until a couple years ago, you had dominant market share within China in terms of...

95% 的市场份额。

95% market share.

可以说是最重要的事情上拥有 95% 的市场份额。而且你曾说过，我们国家在试图减缓他们发展的幌子下，最大的目标就是单方面解除武装。我们迫使英伟达退出中国，这反而让华为凭借在中国的垄断利润加速发展。我今天早上刚看到，华为、阿里巴巴等公司宣布将在全球建设数据中心。现在华为有一个三年计划，要利用全球最大 AI 市场的垄断利润来超越英伟达。看来你的警告——把垄断市场拱手让给中国是一个巨大错误——正在成为现实。总统说过，在 H20 禁令之后，现在的情况是你可以向中国出售芯片，但要征收 15% 的出口税。但现在看来，中国可能被美国的言论激怒了，表示英伟达不得在这里销售。那么今天英伟达和中国之间的关系如何？你能重申一下你认为我们国家应该怎么做才能在全球 AI 竞赛中占据最佳位置吗？

95% market share in the most important thing arguably. And you have said that our biggest goal that we as a country could have under the guise of somehow trying to slow them down is we've unilaterally disarmed. We forced Nvidia out of China, which has allowed Huawei to accelerate on the back of monopoly profits within China. And I just saw this morning, you're seeing announcements out of Huawei and Baba and others that they're going to build data centers around the world. Now Huawei has a three-year plan to pass Nvidia funded by the monopoly profits in the biggest AI market in the world. So it's looking like your admonition that this is a huge mistake to hand China monopoly markets is coming true. The president said, after the ban on H20s, now we have a situation where you can sell chips to China, but there's a 15% export tax. But now it appears that the Chinese, perhaps offended by statements out of the United States, are saying no, Nvidia is not allowed to sell here. Now where do we stand today between Nvidia and China? And can you reiterate what you think we as a country should be doing to put ourselves in a best position to win the AI race around the world?

我们与中国是竞争关系。我们应该承认，中国理所当然地希望自己的公司做得好。我一点也不嫉妒他们。他们应该做得好。他们应该给予他们想要的支持。这是他们的特权。别忘了，中国拥有一些世界上最好的企业家，因为他们来自世界上最好的 STEM 学校。他们是世界上最有干劲的。

We have a competitive relationship with China. We should acknowledge that China rightfully should want their companies to do well. I don't for a second begrudge them. They should do well. They should give them as much support as they like. It's all their prerogative. And don't forget that China has some of the best entrepreneurs in the world because they came from some of the best STEM schools in the world. They're the most hungry in the world.

是的。

Yes.

996，你知道的。

996, as you know.

这是一个非常……

This is a very...

培养出世界上最多的 AI 工程师。

Producing the most AI engineers in the world.

996。所以观众知道：早上 9 点到晚上 9 点，每周 6 天。这就是他们的文化。

996. So the audience knows: 9 in the morning to 9 at night, 6 days a week. That is their culture.

是的。

Yeah.

好吧。我们面对的是一个强大、创新、有干劲、行动迅速、监管宽松的对手。

Okay. We're up against a formidable, innovative, hungry, fast-moving, underregulated.

是的。

Yeah.

人们没有意识到这一点。他们监管非常宽松，对吧？讽刺的是，在资本主义体系中，他们比我们监管更少。

People don't realize this. They are very lightly regulated, right? Less regulated, ironically, than we are in a capitalist system.

没错。人们认为他们是中央集权管理。但记住，中国的天才之处在于分布式经济体系。

That's right. People think that they're centrally governed. But remember, the genius of China was distributed economic systems.

是的。

Yeah.

所以所有这些 33 个省份和市长经济推动了大量的内部竞争、内部经济活力，这当然有一些副作用。但这是一个充满活力、创业精神、高科技、现代的产业。我听到的一些说法：他们永远造不出 AI 芯片。这听起来就很荒谬。第二，中国制造不行。如果说有一件事他们擅长，那就是制造。第三，他们落后我们好几年。是两年还是三年？拜托。他们只落后我们几纳秒。

And so all of these 33 provinces and all the mayor economy has driven an enormous amount of internal competition, internal economic vibrancy, which of course has some side effects. But this is a vibrant, entrepreneurial, high-tech, modern industry. And some of the things I heard: they could never build AI chips. That just sounded insane. Two, that China can't manufacture. If there's one thing they can do, it's manufacture. And three, they're years behind us. Is it two years, three years? Come on. They're nanoseconds behind us.

几纳秒。

Nanoseconds.

是的，他们只落后我们几纳秒。所以我们必须去竞争。

Yeah, they're nanoseconds behind us. And so we've got to go compete.

是的，我们必须去竞争。

Yeah, we've got to go compete.

那么问题就变成了：什么最符合中国的利益？当然，他们有一个充满活力的产业。他们也公开表示，而且我相信他们确实这么认为，他们希望中国是一个开放的市场。他们希望吸引外国投资。他们希望公司来中国并在市场上竞争，对吧？而且我相信，我希望，我相信并希望他们会回到那个状态，在我们所处的背景下。回答你的问题，我如何看待未来？我确实希望，因为他们说了，他们的领导人说了，我姑且相信，因为我认为这对中国有意义：最符合中国利益的是外国公司在中国投资、在中国竞争，同时他们自己也进行激烈的竞争，并且他们也希望走出中国，参与全球市场。我认为这是一个相当合理的结果。而我们作为一个国家需要做的是，支持我们的科技产业——我很荣幸能在一个堪称国家宝藏的行业工作。我们必须承认它是国家宝藏。它是我们最好的产业。

And so the question then becomes what's in the best interest of China, of course, is that they have a vibrant industry. They also publicly say, and rightfully I believe they believe this, that they want China to be an open market. They want to attract foreign investment. They want companies to come to China and compete in the marketplace, right? And I believe that they, I hope, I believe and I hope that would return to that in our context. Answering your question, what do I see in the future? I do hope, because they say it, their leaders say it, and I take it at face value and I believe it because I think it makes sense for China, that what's in the best interest of China is for foreign companies to invest in China, compete in China, and for them to also have vibrant competition themselves, and they would also like to come out of China and participate around the world. That is, I think, a fairly sensible outcome. And what we need to do as a country is to enable our technology industry, which today is—I'm privileged to be working in an industry that is our national treasure. We have to acknowledge it is our national treasure. It is our best industry.

它是我们唯一最好的产业。

It is our single best industry.

是的。

Yeah.

我们为什么不允许这个行业为生存而竞争，让这个行业在全球推广技术，让世界建立在 American 技术之上，从而最大化我们的经济成功、地缘政治影响力，让这个行业在如此充满活力、如此关键的时刻蓬勃发展呢？

Why would we not allow this industry to go compete for its survival, for this industry to go and proliferate the technology around the world, so that we could have the world built on top of American technology, so that we can maximize our economic success, maximize our geopolitical influence, maximize this technology industry during such a vibrant time, such a pivotal time, to allow it to thrive?

怀疑论者说 Jensen 只是想卖更多芯片，如果能卖给中国，那就太好了。他会卖给中国。他不在乎这对 America 意味着什么。这就是怀疑论者的看法。

The skeptic says Jensen just wants to sell more chips, and if he can sell them to China, great. He'll sell them to China. He doesn't care about what that means for America. That's a skeptic.

我能回应一下怀疑论者吗？仅仅因为我希望 America 的生态系统和经济成长，并不代表我是错的。

Can I just address the skeptics? Just because I want America's ecosystem and economy to grow doesn't make me wrong.

没错。没错。

Right. Right.

首先，到目前为止所有关于中国的编造说法都被证明是错的。事实就是错的。基本事实是错的。所以仅仅因为我们希望 America 赢，仅仅因为我们希望这个行业成长，并不代表我是错的。

So, first of all, everything that has been said so far that's been made up about China has proven to be wrong. The facts are just wrong. The ground truth is wrong. And so just because we want America to win, just because we want this industry to grow, doesn't make me wrong.

没错。我认为任何了解你和总统的人，当然也包括我，都知道你深深关心这个国家。你深切希望美利坚合众国赢得全球 AI 竞赛。你恰好相信——而且我认为你比任何人都更有经验——这对我们有利：如果你在中国竞争，我们赢得全球 AI 竞赛的概率实际上会上升，因为这让我们能够利用全球一半的 AI 工程师，让他们留在这个生态系统中。让我们明确一下我们在这里谈论的公司：字节跳动、阿里巴巴等。这些公司大部分由 American 投资者拥有。

Correct. And I think anybody who knows you and now the president, certainly myself, you deeply care about the country. You deeply want the United States of America to win the global AI race. You just happen to believe, and I think you have as much experience or more experience than anyone, that it enures to our advantage—the probability of us winning the global AI race actually goes up if you are competing in China, because it allows us to tap into half of the world's AI engineers, keeping them in this ecosystem. Let's be clear with the companies we're talking about here: ByteDance, Alibaba, etc. These are companies that are largely owned by American investors.

没错。这些是全球性公司，正在构建推荐引擎，顺便说一句，它们拥有非凡的技术，是令人难以置信的公司。

Right. Like these are global companies that are building recommendation engines, by the way extraordinary technologies, incredible companies.

所以我认为，并且我希望，你关于中国的论点——这比向世界其他地区扩散更难论证——我理解这一点。这就是为什么当总统说，我不知道，这就像抛硬币一样。也许 Jensen 是对的。也许其他人是对的。如果 Jensen 愿意把 15% 的一点钱投入美国财政部作为对冲，那我就支持。但随后我感到非常失望。

And so I think, and I'm hopeful, that the argument that you're making vis-à-vis China, which is a harder argument than diffusion to the rest of the world, I understand that. And that's why I thought when the president said, you know, I don't know, it's a flip of a coin. Maybe Jensen's right. Maybe the other guys are right. If Jensen's willing to put a little bit of 15% into the US Treasury as a hedge on that, then I'll go for it. But I was really disappointed on the heels of that.

嗯。

Mhm.

我认为如果中国人觉得他们被利用了，我们将向他们发送 10 年前的芯片之类的，那么我理解他们为什么会有那样的反应。

I think if the Chinese feel like they're being taken advantage of, that we're going to send them chips that are 10 years old or something, then I get why they had that response.

H20 仍然非常出色。当然它不如 Blackwell，我理解这一点。

H20 is really quite spectacular still. And of course it's not as good as Blackwell, and I get that.

你看，我们有耐心，我相信他们是明智的。他们在思考自己的处境。他们有更大的议程要处理，显然包括美国。有很多讨论在进行。但我要回到基本事实、根本真理。我相信，Nvidia 能够服务那个市场并在其中竞争，符合中国的最佳利益。我从根本上相信这符合中国的最佳利益。当然，这也非常符合美国的最佳利益。

I look, you know, we're patient, and I believe that they're wise. They're thinking through their situation. They have larger agendas to deal with, visibly the United States. There are a lot of discussions going on. But I'll come back to the ground truth, fundamental truth. I believe that it is in the best interest of China that Nvidia is able to serve that market and compete in that market. I fundamentally believe it is in the best interest of China. It is of course in the fantastic interest of the United States.

是的。

Yeah.

这很有趣。但这两个真理可以共存。两者都可能为真，我相信两者都是真的。

It is fun. But those two truths can coexist. It is possible for both to be true, and I believe it is both true.

所以，尽管我告诉所有投资者，我们的指引不包括中国。

And so, even though I tell all of our investors that our guidance includes no China.

是的。

Yeah.

我感谢所有投资者，在我们的任何指引中都不包括中国。我们在外部有很多增长机会，这一切都是真的。但这并不意味着中国对我们不重要。它对我们非常重要。任何认为中国市场不重要的人都是把头埋在沙子里。

And I appreciate all of our investors, to include no China in any of our guidance. We've got plenty of growth opportunities outside, and all of that is true. It doesn't make China not important to us. It's very important to us. Anybody who thinks that the Chinese market is not important has their head deep in the sand.

是的。

Yeah.

所以这是世界上最重要的市场之一。聪明的市场，如你所知，聪明的人在做聪明的事，我们想在那里。

And so this is one of the most important markets in the world. Smart markets, as you know, smart people doing smart things, and we want to be there.

是的。我认为我们在那里符合两国的最大利益。所以当我退一步思考时，我相信最终智慧会胜出。

Yeah. And I think it's in the best interest of both countries that we are there. And so I think when I take a step back, I am confident that ultimately the wisdom will prevail.

是的。

Yes.

我一直相信智慧会胜出。我一直相信真理会胜出，这让我走到了今天，我现在从根本上相信这一点。所以这些事情会得到解决，我们将有机会在中国市场竞争。

I've always been confident that wisdom prevails. I've always been confident that truth prevails, and it's taken me this far, and I believe that to be fundamentally true now. And so these things will get sorted out, and we will have the opportunity to go compete in that China market.

我不太政治化，但非常热门的是政府决定对每份 H1B 签证收取 10 万美元。

I'm not very political, but very topical is the administration's decision to charge $100,000 per H1B visa.

嗯。

Mhm.

你和总统相处了很多时间。你称他为我们在 AI 领域的秘密武器。我也知道你想招募最优秀和最聪明的人到我们国家。那么，你怎么看待对每份 H1B 签证收取 10 万美元的决定？这会让招聘人才变得更容易还是更困难？而且，也许对大公司或小公司来说有点不同？你怎么看？

You've spent a lot of time with the president. You've called him our secret weapon in AI. I also know you want to recruit the best and brightest to our country. So, how do you think about the decision to charge $100,000 per H1B visa? Does this make it easier or harder to recruit talent? And, you know, does perhaps it's a little different for large companies or small companies? Like, how do you think about it?

我先说这是一个很好的开始。

I'm going to start with it's a great start.

等等。你说这是一个很好的开始。

Hold on. You said it's a great start.

这是一个很好的开始。

It's a great start.

我就从那里开始。

I'm just going to start there.

原因如下。

And the reason for that is this.

这意味着我不——我希望这不是终点。

That implies I don't—I hope it's not the end.

但我认为这是一个很好的开始。我只是希望这不是终点。以下是我从根本上相信的。America 拥有世界上任何国家都没有的独特品牌声誉。世界上没有任何国家现在或即将能够说：来 America 实现 American 梦。

But I think it's a great start. I just hope it's not the end. Here's what I fundamentally believe. America has a singular brand reputation that no country in the world has. And no country in the world is in a position or on the horizon to be able to say: come to America and realize the American dream.

哪个国家后面有“梦”这个词？

What country has the word dream behind it?

是的，这是它品牌的一部分。我们是独一无二的，你正在和一个代表 American 梦的人说话。我的父母没有钱。把我们送到这里。我们从零开始。你们知道我曾端盘子、洗碗、打扫厕所，而现在我在这里。

Yes, it's part of its brand. We are utterly singular, and you're talking to somebody who represents the American dream. My parents didn't have any money. Sent us over here. We started from nothing. You guys know I bust tables, wash dishes, clean toilets, and here I am.

是的。

Yeah.

这就是 American 梦。特朗普总统知道我们想要合法移民。

This is the American dream. President Trump knows that we want legal immigrants.

是的。

Yeah.

合法移民和非法移民之间有区别。但认为这是一个对所有人免费的国家是没有道理的。

There's a difference between legal immigrants and illegal immigrants. But the idea that it's a country that's free for all doesn't make sense.

所以现在的问题是，我们如何从想要从根本上保护 American 梦的想法，转向处理如此大规模的非法移民？我们如何找到一个合乎逻辑、务实的解决方案？

And so now the question is how do we go from the idea that we want to protect fundamentally the American dream to dealing with illegal immigrants at such a large scale? How do we find a logical, pragmatic solution?

对。所以，我们对 H-1B 贴上 10 万美元的价签可能把门槛设得有点太高了，但作为第一个门槛，它至少消除了非法移民，这是一个好的开始。

Right. So, the idea that we put a $100,000 price tag on H-1B probably sets the bar a little too high, but as a first bar, it at least eliminates illegal immigration, and that's a good start.

它如何消除非法移民？

How does it eliminate illegal immigration?

嗯，它至少消除了 H-1B 的滥用。是的，至少如此。这是一个好的开始。至少我们可以展开对话。

Well, it at least eliminates abuse of H-1B. Yeah. At least. And that's a good start. And at least we can have a conversation.

所以，我们对特朗普总统的了解之一是，他善于倾听。他真的会听。我是说，他听你的，听我的，而且他本不必如此。他听取很多人的意见，整合大量信息，这显然是一个非常复杂的问题。所以，我认为这是一个不错的开始。确实是个不错的开始。但我并不困惑，政府中的任何人、白宫中的任何人都不应该困惑：合法移民是美国梦的基石，是我们想要保护的终极品牌，也是我们想要保护的未来。

So, one of the things that we know about President Trump, he's a good listener. He actually listens. I mean, he listens to you, he listens to me, and he doesn't have to. And he listens to a lot of people, and he's integrating a lot of information, and this is obviously a very complicated issue. And so, I think that this is a fine start. It's a fine start. But I'm not confused that anyone in the administration, anyone in the White House is confused that legal immigration is the foundation of the American dream and is the ultimate brand that we want to protect and that's the future we want to protect.

我还要说，在我看来，Saxs 和政府中的其他人当然知道我们必须招募世界上最优秀、最聪明的人才。我们不应该牺牲这个品牌的伟大。收取 10 万美元，或者说降到 5 万或其他什么数字，这似乎确实让竞争环境向大公司倾斜，因为它们有能力有效赞助所有这些人才，对吧？而对初创生态系统来说，挑战更大，因为人才已经非常昂贵，现在还要额外支付这笔费用。

And I would also say it seems to me that certainly Saxs and other people in the administration know that we have to recruit the world's best and brightest. We should not sacrifice the greatness of the brand. Charging $100,000 or let's say, it got lowered to 50 or whatever the case is, it does seem like it tilts the playing field in favor of big companies who can effectively sponsor all these people, right? And it's more challenging for the startup ecosystem where people are already super expensive and now I got to pay this fee on top of it.

它还有一个意想不到的后果。可能会加速美国以外的投资，对吧？所以确实有 unintended consequences，但就像我说的，从某个地方开始，朝着正确的答案前进，对吧？你知道，很多时候人们想直接从错误答案、错误状态——我们不想处于现在这种状态，对吧？——直接跳到完美答案，但完美答案很难找到，对吧？就从某个地方开始。这是创业者的方式。

It also has an unintended consequence. It might accelerate investment outside the United States, right? And so there are unintended consequences, but like I said, start somewhere, move towards the right answer, right? You know, often times people want to go directly from a wrong answer, wrong condition. We don't want this condition where we're at, right? And directly jump to the perfect answer is hard to find, right? Just start somewhere. It's the entrepreneurial way.

这对我来说很重要，你知道，总统在竞选时曾说过，他想给这些 STEM 学生的毕业证上钉一张绿卡。所以，来自中国的聪明人，在斯坦福学习的 AI 研究员，我们想把他们留在这里。而且，如果他们的家人过不来，他们几年后就会离开，所以你可能甚至想让他们的家人更容易过来。

It's important to me, you know, the president talked about before when he was running for office, he wanted to staple a green card to the diplomas of these STEM students. So smart people coming to the United States from China, AI researchers studying at Stanford, like we want to keep them here. And by the way, if their families can't get here, they're going to leave after a few years, so you might even want to make it easier for their families to come here.

还有其他人，你确信本届政府有一个战略计划吗？你知道，这是一个开始，但你的对话是否让你相信我们有一个更广泛的战略计划来确保我们招募最优秀、最聪明的人才？

And others, are you confident that we have a strategic plan in this administration? You know, this is a start, but your conversations, they give you confidence that we have a broader strategic plan to make sure we're recruiting the best and the brightest?

我不知道我对此有答案。

I don't know that I have an answer for that.

好的。

Okay.

但我明白，我们现在的处境不是我们想要的。

But I understand that where we're at is not where we want to be.

是的。

Yeah.

而且我认为没有人失去对美国梦、移民的重要性、吸引全世界最优秀人才到美国并为他们创造留下条件的关注。时不时会有一些事情与我所描述的背道而驰，对吧？让外国学生感到不舒服，对吧，身在这个品牌中会威胁到品牌。我们不要忘记，与中国竞争是可以的，但要小心不要对中国人严厉。所以我们需要确保不越过那条滑坡。

And I don't think anybody has lost focus on the American dream, the importance of immigration, the importance of attracting all of the world's best talent to the United States, create the conditions for them to stay here. There are things that are done from time to time that work against what I just described, right? Making foreign students uncomfortable, right, and being here in the brand threatens the brand. Let's not forget that it's okay to be competitive with China, but be careful not to be tough on Chinese. And so we need to make sure that slippery slope isn't crossed.

是的。

Yeah.

所以，所有这些都需要技巧和细微差别。但事实是，我们知道我们想去哪里。我们知道我们处境困难。我们不想待在这里，而特朗普总统没有太多时间带我们朝那个方向前进。

And so there are all of these things that go along with finesse and nuance. But the fact of the matter is we know where we want to be. We know we're in a difficult situation. We don't want to be here and President Trump doesn't have much time to move us in that direction.

对。

Right.

所以，只要我们朝那个方向前进，我相信这是一个好的开始。

And so to the extent that we move in that direction, I believe it's a good start.

同意。

Agreed.

是的。我听说一位领导美国顶尖实验室的中国研究员说，三年前，中国大学毕业的顶尖 AI 研究人员中有 90% 想来美国，也确实来了美国，在我们的顶尖实验室工作，而他猜测今天这个比例接近 10% 或 15%。对吧？所以出现了急剧下降。这正是我们的担忧，对吧？那么你看到了吗？你关注两个市场。你看到了吗？我们需要做些什么来扭转这一局面？

Yeah. I heard from a Chinese researcher leading one of our leading labs in the US that three years ago 90% of the top AI researchers graduating from universities in China wanted to come to the United States and did come to the United States to work in our leading labs, and he guessed that today that's closer to 10 or 15%. Right? So seen a precipitous drop. That's precisely a concern that we have, right? So have you seen this? You're paying attention to both markets. Do you see this? And what are the things we need to do in order to reverse that?

确实看到中国学生来美国并留下来的问题更令人担忧。是的。很多来上学的人都在考虑去别处，对吧？很多人考虑欧洲，对吧？所以我认为我们需要极度关注这一点。这是 existential crisis 的根源。这绝对是未来问题的早期指标。

Definitely see a greater concern of Chinese students who come here and remain here. Yeah. And many of them who come here for school are thinking about going elsewhere, right? Many of them thinking about Europe, right? And so I think we need to be super concerned about this. This is a source of existential crisis. This is definitely the early indicators of a future problem.

对，对。你知道，聪明人想来美国的愿望，聪明学生想留下来的愿望，这些我称之为 KPI。是的。未来成功的早期指标。是的。我把它有点像勇士队。你知道，如果他们拥有招募 NBA 所有最佳球员的优势，对吧，那么他们就能继续赢得总冠军。但一旦那个招募管道，对吧，因为勇士队的品牌受损或发生其他事情，那么他们就无法招募到未来的最佳球员，也就无法赢得总冠军。当你如此雄辩地谈论美国梦，即品牌美国，对吧？来这里做你所做的事情的权利。所以我希望给本届政府的反馈，不仅仅是政府，还有我们作为一个国家如何谈论移民。

Right. Right. You know, smart people's desire to come to America and smart students' desire to stay, those are what I would call KPIs. Yes. Early indicators of future success. Yes. I think of it a bit like the Warriors. You know, if they have an advantage of recruiting all the best players in the NBA, right, then they can continue to win championships. But the second that recruiting pipeline, right, because of the brand of the Warriors gets diminished or something else happens, then they're not going to be able to recruit the best future players and you're not going to win championships. And when you talk about the American dream so eloquently, that being brand USA, right? The right to come here and to do what you've done. And so I hope that the feedback to this administration, it's not just the administration, it's also just how we as a country talk about immigration.

没错。

That's right.

对。这需要成为欢迎最优秀、最聪明人才的地方，吸引他们，有一个战略计划来招募最优秀、最聪明的人才，并确保这是他们想要工作的地方。

Right. This needs to be the place that welcomes the best and the brightest, that attracts, has a strategic plan for recruiting the best and the brightest and making sure that this is the place that they want to work.

如你所知，有一个短语，我直到几年前才听说，China hawks。是的。显然，如果你是一个 China hawk，你会自豪地戴上这个标签。它几乎像一枚荣誉徽章，对吧？这是一枚耻辱徽章。毫无疑问，这是一枚耻辱徽章。

As you know, there's a phrase, and I didn't hear about this phrase until just a few years ago, China hawks. Yes. And apparently if you're a China hawk, you get to wear that label with pride. It's almost like a badge of honor, right? It's a badge of shame. There's no question it's a badge of shame.

毫无疑问，尽管他们想要为我们的国家谋取最大利益，我们也都想为国家好，但摧毁美国梦的管道是不爱国的。他们以为自己在为国家做正确的事，但这并不爱国，一点都不。

There's no question that although they want what's in the best interest of our country, and we all want what's in the best interest of our country, destroying that pipeline of the American dream is not patriotic. They think they're doing the right thing for our country, but it's not patriotic. Not even a little bit.

所以我们需要继续做我们这样的伟大国家，拥有一个大国的自信。

And so we need to continue to be the great country we are, to have the confidence of a great country.

是的，说得好。

Yes. Well said.

并且要拥有一个大国的自信，面对想要与我们竞争的人，态度是：放马过来。

And to have the confidence of a great country and have somebody who wants to compete with us and to have the attitude, bring it on.

对，对。放马过来。因为我信任我们的人民，信任这里的人，信任我们的文化，信任我们的国家，信任我们的制度。放马过来。

Right. Right. Bring it on. Because I believe in our people. I believe in our people. I believe in the people that are here. I believe in our culture. I believe in our country. I believe in our system. Bring it on.

你认为总统也是这个立场吗？他是一位实用主义者，相信美国的增长和竞争能力。在我看来他就是这样的。

And is it your take that that's where the president is? Like he's a pragmatist. He's a believer in the growth and the ability of the United States to compete. It seems to me that's where he is.

毫无疑问，特朗普总统就是那位“放马过来”的总统。

There's no question President Trump is the bring it on president.

对，对。而且在我看来，他并不是那种……我之所以有信心，是因为我在这个播客里说过，我认为他会与中国达成一项重大协议。

Right. Right. And he doesn't seem to me like the reason I'm confident and I've said on this pod that I think he'll get a big deal done with China.

我真的希望如此。

I really do hope so.

是的。而且我认为他积极、尊重且雄辩地谈论他与中国的关系以及中国的重要性。我从未听他说过“脱钩”这个词，而上一届政府我们经常听到。你不能脱钩，这是下个世纪最重要的关系之一，这毫无意义。脱钩完全是个错误的概念。

Yeah. And I think he speaks positively, with great respect and great eloquence about his relationship and the importance of China. Not one time have I ever heard him say the word decouple, which we heard a lot in the last administration. You can't decouple the single most important relationship for the next century. That doesn't make any sense at all. Decoupling is exactly the wrong concept.

对吧？

Right?

我的意思是，在我看来，他和斯科特·贝森特在说：‘听着，我们需要让美国伟大。我们需要再工业化美国。我们需要平衡并确保公平贸易。我们保护那些需要帮助建设的产业，而中国帮助我们做到这一点，同时认识到过去 25 年里我们也帮助了他们。’但最终他说，理解我的最好方式是我是一个伟大的交易者。我做交易，对吧？而在其他阵营中，我认为有些人是不守常规或教条的。那是纯粹的现实主义中国观，认为存在大国斗争，一方必须赢，一方必须输，而不是这种每个国家都必须和我们一模一样的想法。

I mean, it seems to me he and Scott Besson are saying, 'Listen, we need to make America great. We need to re-industrialize America. We need to balance and make sure that we have fair trade. We protect industries that we need to help build that China helps us do that recognizing that we have helped them do it over the course of the last 25 years.' But ultimately he said the best way to understand me is I'm a great dealmaker. I make deals, right? Whereas I think in other camps there are people who are iconoclastic or dogmatic. It's the mere shimer view of China that there's a great power struggle, one must win and one must lose versus this idea that every country has to look exactly like ours.

你知道，我们想要多样性。你希望美国赢，但这不必以戳别人眼睛、告诉别人他们必须输为代价，因为我们足够自信。

You know, and we want diversity. You want America to win, but that doesn't have to come at the expense of poking an eye and telling somebody else they have to lose because we're that confident.

是的，我们就是那么自信。因为我们那么强大，那么不可思议。你知道，我和生态系统中的所有同事合作毫无问题，对吧？注意我们刚刚做了一笔终极交易，与英特尔合作，这家公司大半辈子都在试图让我们倒闭。我和他们合作毫无问题。原因第一是放马过来，第二是未来更加广阔。不必非此即彼，可以是我们和他们共赢。

Yeah, we're that confident. Because we're that mighty. Because we're that incredible. I've got no trouble, as you know, I've got no trouble working with all my colleagues in the ecosystem, right? And notice we just did the ultimate deal, partnering with Intel, a company that spent most of its life trying to put us out of business. And I had no trouble partnering with them. And the reason for that is because number one, bring it on. And number two, the future is so much greater. It doesn't have to be all us or them. It could be us and them.

是的，是的。但尽管如此，放马过来。

Yeah. Yeah. But nonetheless, bring it on.

是的，同意。你知道，你提到了一件对我们俩都至关重要的事情。你和我多次谈到这个，美国梦。我想是亚伯拉罕·林肯说过：‘美国梦的根本是上升的权利。’

Yeah. Agreed. You know, you mentioned something that's profoundly important to both of us. You and I have talked a lot about this, the American dream. And it was, I think, Abraham Lincoln who said, 'Fundamental to the American dream is the right to rise.'

是的，没错。相信你的孩子能比你做得更好。

Yeah. That's right. The belief that your kids can do better than you did.

没错。你体验过上升的权利。我们在美国都体验过上升的权利。所以，是的，你去维基百科查美国梦，会看到我的照片，对吧？是的，终极美国梦。然而我们生活在这样一个时代，由于这些技术系统的性质，有些公司价值将达到 10 万亿，可能还会有个人价值万亿。这些激励给了人们上升的动力。但与此同时，当我们进入这个富足时代时，我深感担忧的是太多人被抛在后面。他们感到被排斥和落后。所以他们攻击资本主义体系是有道理的。

That's right. And you've experienced the right to rise. We've all experienced the right to rise in America. So, yeah, you go to Wikipedia, you look up American dream, my picture, right? Yeah. And the ultimate American dream. And yet we live at this time where because of the nature of these technological systems, we have companies that are going to be worth 10 trillion. We'll probably have individuals that are worth a trillion. Those are the incentives that give people the encouragement to rise. But at the same time, when we head into this age of abundance, something that I was deeply worried about was that too many people get left behind. And they feel left out and left behind. So it makes sense for them to attack this system of capitalism.

你和我共同推动的一件事，我深表感激，就是“投资美国”的理念：我们必须让每个孩子从出生起就踏上资本主义的上升之旅，给他们一千美元投资于像英伟达这样的伟大公司、社会保障等，并开设一个账户。随着国家获胜，他们也获胜，他们个人拥有它，他们可以看到……每个孩子都是美国未来的股东。所以，在 200 上，因为你的支持，我想借这个播客的机会……

Something that you and I worked on together and I'm deeply grateful for was the idea of invest America that we have to start every kid at birth on the capitalist right to rise journey, give them a thousand bucks in great companies like Nvidia, social security, and open a high etc. And they benefit as the country wins, they win and they own it individually, they can see it on their... every kid is a shareholder in the future of America. So on the 200 because of your support and I wanted to take the chance on this podcast and the support of...

嗯，我想感谢你发起并推动它。真是个好主意。

Well, I want to thank you for starting it, for driving it. What a great idea.

是的。你知道，所以这……你是个天才。这已经包含在那份宏大而美丽的法案中通过了。大多数人甚至还没意识到。从 2026 年开始，这个国家历史上每一个出生的孩子，从出生起就会拥有一个投资账户。是的，一千美元投资于最好的美国公司，而你的公司已经同意不仅为员工的孩子，甚至可能为其他孩子增加账户资金。我将领养学校，你知道，还有很多慈善家和公司。我们认为全美每家公司……这是公司回馈社会的绝佳方式，对吧？作为 401k 的一部分。在我看来，这是社会契约需要发生的变革的一部分，因为如果我们看到这种指数级进步，我们知道政府在社会契约中的演变需要跟上它。显然，特朗普总统和国会两党议员已经将其通过成为法律。

Yeah. And you know, so this... you're a genius. This passed in the big beautiful bill. Most people don't even realize that yet. Starting in 2026, every child born forever more in the history of this country will start off with an investment account at birth. Yeah. Seen a thousand bucks in the best American companies and your company has agreed to add to the accounts of not only the kids who work for your employees but maybe even kids of others. I'm going to adopt schools, you know, and lots of philanthropists and companies. We think every company across America... wonderful way for companies to give back, right? as part of the 401k. This seems to me to be part of the change in the social contract that needs to occur because if we're seeing this exponential progress, we know that the evolution of government in the social contract needs to keep up with it. Obviously President Trump and a bipartisan group in the House and Senate passed this into law.

那么，也许跟我们聊聊你如何看待即将到来的变化的速度和规模，对吧？我知道你认为这总体上会是好事，但过程中也会有很多人失业。我们可能需要这样的东西和其他东西，对吧？为了，你知道，让每个人都跟上这趟旅程。

So maybe just talk to us a little bit when you think about the pace and magnitude of changes that are coming, right? I know you believe it will be a net good, but there are also going to be a bunch of people displaced along the way. We probably need things like this and other things, right? In order to, you know, bring everybody along for the journey.

特朗普总统做了几件事，我就从那里开始，这些事对让每个人都跟上步伐非常有益。第一件事是再工业化美国。特朗普总统、卢特尼克部长，他们都全力支持，鼓励企业来美国建厂，投资工厂，并对熟练劳动力进行再培训和技能提升，对吧？这对我们国家极其有价值。那种认为只有拿到博士学位或进入名校才能过上好生活、才配拥有好收入的想法，我们必须改变。这毫无道理。我们热爱手艺。我喜欢那些用双手制造东西的人。我们现在要回去建造东西，建造宏伟而不可思议的东西。我喜欢这样。这将改变美国，毫无疑问。有一整个经济领域、一整个社会阶层，因为我们将一切外包而被大大抛在了后面。我不是说我们要把所有东西都内包。那些争论制造网球鞋和牙签的人，我是说，他们把一场很好的讨论贬低到了荒谬的程度。我们必须认识到，再工业化美国从根本上讲将是变革性的。这是第一点。

There's several things that President Trump has done and let me just start there has done that is incredibly good for bringing everybody along. The first thing is reindustrializing America. President Trump, Secretary Lutnik, they're all in behind that, all the work that they're doing encouraging companies to come build here in the United States, investing in factories and reskilling and upskilling that skilled labor workforce, right? Incredibly valuable to our country. The idea that we no longer make it only that you get a PhD or you go to one of the great schools and only in that way can you build a great life, and deserve to have a great living, we've got to change all that. It doesn't make any sense. We love craft. I love people who make things with their hands. And we're now going to go back and build things, build magnificent incredible things. I love that. That's going to transform America. There's no question about that. There's a whole band of an economy, a whole band of society that has been largely left behind because we outsourced everything. Now, I'm not suggesting we insource everything. All the people arguing about manufacturing tennis shoes and toothpicks, I mean, that's denigrating a perfectly good discussion into some insane level. We've got to recognize that reindustrializing America is just fundamentally going to be transformative. Number one.

而且令人向往。

And aspirational.

哦，太棒了。埃隆带我们去火星，看着飞船像筷子一样从空中被接住。这不仅对美国工业化基础有好处，对每个人来说都令人向往。太棒了。没错。

Oh, it's fantastic. Elon taking us to Mars, watching spaceships caught with chopsticks out of the sky. This is not only great for the industrializing base of America, it's aspirational for everyone. Fantastic. That's right.

然后，当然，还有 AI。

And then, of course, AI.

是的，它是最大的均衡器。想想看，现在每个人都能拥有一个 AI。终极均衡器。我们弥合了技术鸿沟。还记得以前人们为了经济或职业利益必须学习如何使用电脑吗？他们得学 C++、C 或者至少 Python。现在他们只需要学人类语言。所以，如果你不知道如何编程 AI，你就告诉 AI：“嗨，我不知道怎么编程 AI。我该怎么编程 AI？”然后 AI 会解释给你听，或者直接帮你做。它帮你做了。所以，这太不可思议了，不是吗？我们现在用技术弥合了技术鸿沟。这是每个人都必须参与的事情。OpenAI 有 8 亿活跃用户。它真的需要达到 60 亿。很快需要达到 80 亿。所以我认为这是第一点。

Yes, it is the greatest equalizer. Just think, everybody can have an AI now. The ultimate equalizer. We've closed the technology divide. Remember the last time that somebody had to learn how to use a computer for their economic or career benefit. They had to learn C++ or C or at least Python. Now they just have to learn human. And so, if you don't know how to program an AI, you tell the AI, 'Hi, I don't know how to program an AI. How do I program an AI?' And the AI explains it to you or does it for you. It does it for you. And so, it's incredible, isn't that right? We've now closed the technology divide with technology. This is something that everybody's got to engage. OpenAI has 800 million active users. It really needs to be 6 billion. It really needs to be 8 billion soon. So I think that's number one.

是的。

Yeah.

然后第二点，第三点，我认为 AI 会改变任务。人们混淆的是，很多任务会被淘汰，但也有很多任务会被创造出来。但对很多人来说，他们的工作很可能是有保障的。例如，我一直在用 AI，你一直在用 AI，我的分析师一直在用 AI，我的工程师每个人都在持续使用 AI。而且我们正在招聘更多的工程师，更多的人，全面招聘。原因是我们有了更多的想法。我们现在可以追求更多的想法。原因是我们公司变得更高效了。因为我们变得更高效，我们变得更富有。我们变得更富有，就能雇佣更多的人去追求这些想法。那种认为 AI 来了就会大规模摧毁工作的观点，其前提是我们没有更多想法了。前提是我们无事可做了。我们今天生活中所做的一切就是终点。如果别人替我做了那一项任务，我就只剩一项任务了。然后我就得坐在那里等什么，等退休，坐在摇椅上。这种想法对我来说没有意义。所以我认为智能不是零和游戏。我身边越是有聪明的人，越是有天才，令人惊讶的是，我就会有更多的想法，想象出更多我们可以解决的问题，从而创造更多的工作，更多的岗位。所以未来几十年，我的感觉是经济会增长。会创造大量新工作。每份工作都会改变。有些工作会消失。但我们不会在街上骑马之类的。一切都会好的。

Then number two, and then number three, I think AI will change tasks. The thing that people confuse is there are many tasks that will be eliminated. There are many tasks that will actually be created. But it is very likely that for many people their jobs are gainfully protected. For example, I'm using AI all the time. You're using AI all the time. My analysts are using AI all the time. My engineers, every one of them use AI continuously. And we're hiring more engineers. We're hiring more people. We're hiring across the board. The reason for that is because we have more ideas. We can now go pursue more ideas. The reason for that is because our company became more productive. And because we became more productive, we became more rich. We became more rich, we can hire more people to go after those ideas. The concept that AI comes along and therefore there's going to be a mass destruction of jobs starts with the premise that we have no more ideas. It starts with the premise we have nothing left to do. Everything we're doing in our lives today. This is the end. And if somebody else were to do that one task for me, I have one task left. Now I have to sit there and wait for something. Wait for retirement, sit on my rocking chair. That idea doesn't make sense to me. And so I think intelligence is not a zero sum game. The more intelligent people I'm surrounded by, the more geniuses I'm surrounded by, surprisingly, the more ideas I have, the more problems I imagine that we can go solve, the more work we create, the more jobs we create. So for the next several decades, my sense is that economy is going to grow. Lots of new jobs are going to be created. Every job will be changed. Some jobs will be lost. And we're not going to be riding horses on streets and those things. It'll be fine.

人类以怀疑著称，非常不擅长理解复合系统，更不擅长理解随规模加速的指数系统。我们今天谈了很多指数增长。伟大的未来学家雷·库兹韦尔说过，在 21 世纪，我们不会只有一百年的进步，而很可能有两万年的进步。你之前说过，我们很幸运能活在这个时刻并为之贡献。我不打算让你展望 10 年、20 年或 30 年，因为我觉得那太有挑战性了。但当我们想到像机器人这样的东西……

Humans are famously skeptical and terrible at understanding compounding systems and they're even worse at understanding exponential systems that accelerate with size. We've talked about exponentials a lot today. The great futurist Ray Kurzweil said in the 21st century, we're not going to have a hundred years of progress. We're likely to have 20,000 years of progress. You said earlier, we're so fortunate to be living at this moment and contributing to this moment. I'm not going to ask you to look out 10 or 20 or 30 years because I think it's so challenging. But when we think about things like robots...

30 年比 2030 年更容易预测。

30 years is easier than 2030.

哦，真的吗？

Oh, really?

是的。是的。

Yeah. Yeah.

好吧。那我就允许你展望 30 年。

Okay. So, I'll grant you license to go out 30.

当你思考这些较短的时间框架时，我喜欢它们，因为它们必须将比特和原子结合起来。构建这些东西的难点就在这里，因为每个人都说它会实现，但这有趣却无益。

As you think out over the course of I like these shorter time frames because they have to marry bits and atoms. The hard part of building this stuff right because everybody's saying it's going to happen. It's interesting but not helpful.

没错。但如果我们有 20,000 年的进步，反思一下 Ray 的那句话，反思指数增长，以及我们所有的听众——无论你在政府工作、在创业公司还是经营大公司——都需要思考加速变化的速度、加速增长的速度，以及你将如何在这个新世界中实现协同智能。

Exactly. But if we have 20,000 years of progress, reflect on that statement by Ray, reflect on exponentials and how all of our listeners, whether you work in government, whether you're in a startup, whether you're running a big company, need to be thinking about the accelerating rate of change, the accelerating rate of growth, and how you will be co-intelligent in this new world.

嗯，很多人已经说过很多事情，而且都非常有道理。我认为在未来 5 年内，一个真正酷且将被解决的问题是人工智能与机电一体化、机器人技术的融合。我们将拥有在我们周围游走的 AI。

Well, there are a lot of things that many people have already said and they're all very sensible. I think in the next 5 years, one of the things that is really cool that's going to get solved is the fusion of artificial intelligence and mechatronics, robotics. And so we're going to have AIs that are going to be wandering around us.

而且我们都知道，我们将伴随着自己的 R2-D2 成长。

And we all know that we're going to grow up with our own R2-D2.

是的。

Yeah.

那个 R2-D2 会记住关于我们的一切，一路指导我们，成为我们的伙伴。我们已经知道这一点。

And that R2-D2 will remember everything about us, coach us along the way, and be our companion. We already know that.

好的。所以，每个人在云端都有自己的 GPU，80 亿人就有 80 亿个 GPU，这是一个可行的结果。

Okay. And so the idea that every human will have their own GPUs associated with them in the cloud, and that there are 8 billion people, 8 billion GPUs, that's a viable outcome.

是的。

Yeah.

而且每个人都有自己的模型，经过微调以适应他们。

And each having their own model that's fine-tuned for them.

为他们微调。而且云中的 AI 也体现在很多事物中：体现在你的车里，体现在你自己的机器人里。它无处不在，与你同在。

Fine-tuned for them. And that AI in the cloud is also embodied in a whole bunch of things: it's embodied in your car, it's embodied in your own robot. It's everywhere with you.

所以我认为那个未来是非常合理的。我们将理解生物学的无限复杂性，理解生物学系统，如何预测它，并拥有每个人的数字孪生——我们自己的医疗数字孪生，就像我们在亚马逊购物时有数字孪生一样。为什么我们在医疗领域没有数字孪生？当然会有。所以一个系统能预测我们将如何衰老，可能会得什么病，以及任何即将发生的事情，甚至可能是下周或明天下午，并提前预测。当然，我们都会拥有这些。所以我认为这一切都是必然的。

And so I think that future is a very sensible thing. The idea that we're going to understand the infinite complexity of biology, understand the system of biology, how to predict it, and have digital twins of everybody — our own digital twin for healthcare, like we have a digital twin for shopping at Amazon. Why wouldn't we have our digital twin in healthcare? Of course we would. And so a system that predicts how we're going to age, what disease we'll likely have, and anything that's about to happen, maybe even next week or tomorrow afternoon, and predict it early. Of course, we're going to have all that. And so I think all of that is a given.

我认为与我合作的 CEO 们经常问我的部分是：鉴于这一切，会发生什么？你该怎么做？这是关于快速变化事物的常识。

I think the part that I'm asked a lot by CEOs I work with is: given all of that, what happens? What do you do? And this is common sense of things that move fast.

对。

Right.

如果你有一列即将越来越快、呈指数增长的火车，你真正需要做的就是上车。

If you have a train that's about to get faster and faster and go exponential, the only thing you really need to do is get on it.

是的。

Yeah.

一旦你上了车，沿途你会解决所有其他问题。

And once you get on it, you'll figure everything else out along the way.

对。

Right.

所以预测火车会到哪里，然后试图朝它开枪，或者预测火车会到哪里，但它每秒都在指数加速，然后去弄清楚在哪个路口等它——那是不可能的。只要在它还在缓慢行驶时上车，然后一路指数增长。

And so to predict where that train's going to be and try to shoot a bullet at it, or predict where that train's going to be and it's going exponentially faster every second and go figure out what intersection to wait for it — that's impossible. Just get on it while it's going kind of slowly, and go exponential along the way.

很多人认为这只是在一夜之间发生的。你知道，你已经从事这个领域 35 年了。我记得拉里·佩奇大概在 2005 或 2006 年说过，谷歌的最终状态是机器能在你提问之前预测问题并给出答案，无需搜索。我听到比尔·盖茨在 2016 年说，当有人说‘所有事情都做完了吗？我们有了互联网、云、移动、社交等。’他说，‘我们甚至还没开始。’他说，‘直到机器从愚蠢的计算器变成开始自己思考、与我们共同思考，我们才算开始。’这就是我们所在的时刻。

A lot of people think this just happened overnight. You know, you've been at this for 35 years. I remember hearing Larry Page say probably around 2005 or 2006 that the end state of Google will be when the machine can predict the question before you even ask it and give you the answer without having to look. I heard Bill Gates say in 2016 when somebody said 'Hasn't all the things been done? We've had the internet, cloud, mobile, social, etc.' He said, 'We haven't even started.' He said, 'We won't even begin until machines go from being dumb calculators to beginning to think for themselves, to think with us.' That is the moment we're in.

我认为拥有像你、Sam、Elon、Satya 这样的领导者，对这个国家来说是巨大的优势。而且我们看到了风险资本体系之间的合作，我参与其中，可以为人们提供风险资本来做这件事。我们不依赖政府搞曼哈顿计划。我们实际上可以自己一起做，为了国家的利益。这是一个非凡的时代，规模难以想象。

I think to have leaders like you, leaders like Sam and Elon, Satya, etc., it's such an extraordinary advantage for this country. And to have the cooperation we see between a system of risk capital that I'm part of, which can provide the risk capital for people to do this. We're not relying on government having a Manhattan Project. We can actually do this ourselves and together for the benefit of the country. It's an extraordinary time, and at a scale that's unimaginable.

对，对。这是一个非凡的时代。但我也认为，我感激的一点是，我们有领导者也理解他们的责任，即我们正在以加速的速度创造变革。我们知道，虽然这对绝大多数人来说很可能是好事，但过程中会有挑战。我们会随着挑战的出现而应对，提高每个人的底线，确保这是所有人的胜利，而不仅仅是硅谷顶层的一些精英官僚。

Right. Right. It's an extraordinary time. But I also think, you know, one of the things that I'm just grateful is that we have leaders who also understand their responsibility to the fact that we are creating change at an accelerating rate. And we know while it will most likely be great for the vast majority, there'll be challenges along the way. And we'll deal with those as they come, and raise the floor for everybody, and make sure that this is a win, not just for some elite bureaucrats at the top hanging out in Silicon Valley.

不要吓唬他们。带着他们一起前进。不要吓唬他们。带着他们一起前进。

And don't scare them. Bring them along. Don't scare them. Bring them along.

我们会做到的。

And we will.

是的。

Yeah.

所以，谢谢你。

So, thank you for that.

正是如此。提醒大家，这只是我们的观点，不是投资建议。

Exactly. As a reminder to everybody, just our opinions, not investment advice.