NVIDIA: OpenAI, Future of Compute, and the American Dream | BG2 w/ Bill Gurley and Brad Gerstner
发布时间 2025-09-26 03:36:04 来源
I think that OpenAI is likely going to be the next multi trillion dollar hyper scale company. Jensen great to be back of course with my partner Clark Tang. You know I can't believe it's been- Welcome to MV. Oh and nice glasses. There's actually a really good idea. 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? I can vouch for that.
我认为OpenAI很可能会成为下一家市值数万亿美元的超大规模公司。Jensen，很高兴能和我的合作伙伴Clark Tang一起回来。当然，我不能相信已经-欢迎来到MV。哦，眼镜不错。实际上这是个很好的想法。问题是现在大家都会希望你一直戴着它们。他们会问红色眼镜在哪？我可以保证这一点。
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 to go up by a billion times. Right. By a billion x by a billion x. 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, but this is the industrial revolution. Right. 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.
自从我们上次录制播客以来，已经超过一年了。是的，如今你们收入中有超过40%来自推理。但由于推理链即将成熟，这一部分的收入将会大幅增长。是的，马上就会增长十亿倍。没错。很多人还没有完全理解这一点。我们之前谈到的这个行业，就像是一次工业革命。说实话，自从上次播客以来，你我几乎每天都在持续这种对话，在人工智能的时间维度中，大概已经过了一百年。
I was rewatching the pod recently and the many things that we talked about that stood out. The most- The one that was probably most profound 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. Pre-training. Right. The end of pre-training, we're not going to- We're overbuilding. Yeah. This is about a year and a half ago.
我最近重温了那个播客，里面有很多谈话内容让我印象深刻。其中对我来说最深刻的一点就是你拍桌子的时候。那时候，大家在预训练方面有点低迷。人们都在说，天啊，预训练完蛋了，我们不会再用它了，我们的构建过度了。对，这大概是一年半前的事。
Yeah. And you said inference isn't going to a hundred x, a thousand x. It's going to one billion x, which brings us to where we are today. You know, you announce this huge deal. We ought to start there. I underestimated. I mean, it's going record. I underestimated. 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.
是的。你提到推理能力不会增长到一百倍、一千倍，而是达到十亿倍的增长，这正是我们今天的现状。你宣布了这个巨大的交易，我们应该从这里开始。我低估了它，我的意思是，它的记录是破纪录的。我低估了它。我们现在有三个扩展规律，对吧？我们有预训练扩展规律，还有后训练扩展规律。后训练基本上就像是AI在练习，是的，就是练习一种技能，直到掌握为止。
And so it tries a whole bunch of different ways. And in order to do that, 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.
为了实现这个目标，它会尝试多种不同的方法。为了做到这一点，你需要进行推理。所以现在在强化学习中，训练和推理是结合在一起的。这很复杂，这个过程被称为“后训练”。然后第三个步骤是推理。过去进行推理的方法是一次性的。对吧。但是我们现在欣赏的是一种新的推理方式，那就是思考。
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. And so thinking, post-training, pre-training. We now have three scaling laws, not one.
在回答之前请先思考。是的。现在你有三个扩展法则。思考得越久，你得到的答案质量就越好。在思考的过程中，你会进行研究，查找一些事实依据。你学到一些东西，然后进一步思考，再去学更多东西。然后，你才能生成一个答案。不要急于马上给出答案。因此，思考、训练后的学习和训练前的学习，现在我们有三条扩展法则，而不是仅仅一条。
You knew that last year, but is your level of confidence this year in the inference is going to 1 billion X. And where that will take the levels of intelligence. Is it higher? Are you more confident this year than you were a year ago? A more confident this year. And the reason for that is because look at the agentic systems now. And AI is no longer a language model.
你去年就知道了，但你今年对这个推断的信心程度是否会提升十亿倍？这将把智能水平提升到哪里？是否更高？你今年比去年更有信心吗？我今年确实更有信心。原因在于，现在的自主系统已经出现，而人工智能不再只是一个语言模型。
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 using doing research. And yeah, there's a whole bunch of stuff. Okay. And it's all multimodality. And look at all the video that's been generated. I mean, it's just too incredible. Crazy stuff.
人工智能是一个语言模型的系统。所有模型可能同时运行，并且可能使用一些工具。有些模型在使用工具，有些在进行研究。嗯，这其中有很多内容。而且，这一切都是多模态的。看看生成的视频，真的太不可思议了。真是疯狂的事情。
Yeah. 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 $100 billion in the company. Over a period of time, they're going to build 10 gigs.
是的。这确实把我们带到了这个星期备受关注的一个重要时刻，你们几天前宣布的一项重大协议。你们将与OpenAI和Stargate合作，成为首选合作伙伴。计划在一段时间内向该公司投资1000亿美元，他们将建设10个设施。
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 know, 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. So first of all, I'll answer that last question first. Okay. I'll come back and go into my way. Good.
如果他们在这10个项目中使用了Nvidia的技术，那可能为Nvidia带来高达4000亿美元的收入。请帮助我们理解一下，跟我们简单介绍一下这个合作关系，对你来说意味着什么？为什么这项投资对Nvidia如此有意义？首先，我将先回答最后一个问题。好的，我将回到我的观点。
I think that OpenAI is likely going to be the next multi trillion dollar hyper scale company. I think you want to know. Why do you call it a hyper scale company? Hyper scale like, like Meta's a hyper scale. Google's a hyper scale. They're going to have consumer and enterprise services. And they are very likely going to be the world's next multi trillion dollar hyper scale company.
我认为 OpenAI 很可能会成为下一个万亿美元级别的超大规模公司。我想你可能会好奇，为什么把它称为超大规模公司？超大规模就像 Meta 和 Google 这样的公司。他们将提供面向消费者和企业的服务，并且很可能成为全球下一个万亿美元级别的超大规模公司。
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 have 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.
我想你会同意这一点。我也同意。如果是这样的话，在他们到达之前投资的机会，是我们能想象到的最聪明的投资之一。而且你必须投资于你了解的东西。没错。事实证明，我们碰巧非常了解这个领域。所以在这一领域投资的机会，其资金回报会非常出色。
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 build out of Microsoft Azure. We're going to continue to do that. And that partnership is going fantastically when we have several years of build out to do, hundreds of billions that always work just to do there. Right. The second is the OCI build out. And I think there's some 567 gigawatts that are about to be built out. And so working with OCI and OpenAI and Softbank to build that out. Those projects are contracted. We're working on it. Lots of work to do.
我们非常乐意有机会进行投资。我们不需要必须去投资，对吧？投资对我们来说不是必须的，但他们给予了我们这个投资的机会，真是太棒了。现在让我从头开始说起。我们正在与OpenAI在多个项目上合作。首先，第一个项目是构建微软Azure。我们将继续推进这一项目，合作进展得非常顺利，我们还有好几年的建设，而且涉及到数千亿的投入，对吧？第二个项目是OCI的建设，我认为大约有567吉瓦的项目即将启动。因此，我们与OCI、OpenAI和软银合作去完成这些建设。这些项目都是已经签约的，我们正在努力推进，还有很多工作要做。
And then the third, the third is CoreWeave. Right. And so all of CoreWeave 4, 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 work in partnering with OpenAI to build their own self-build 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 hyper-scale company. That, I mean, this is going to go on for some time. It's going to supplement. It's going to supplement the amount of, you know, they're going through two exponentials, as you know.
那么第三个，第三个是CoreWeave。对。那么所有关于CoreWeave 4的内容，我说的还是OpenAI。是的。好吧，一切都是在OpenAI的背景下。那么问题是这项新的合作伙伴关系是什么？这项新的合作伙伴关系是为了帮助OpenAI，与OpenAI合作首次构建他们自己的自建AI基础设施。对。这意味着我们在芯片层面、软件层面、系统层面、AI工厂层面直接与OpenAI合作，帮助他们成为一家完全运营的超规模公司。我是说，这将持续一段时间。这会是一个补充。正如你所知，他们正经历指数级增长的两个阶段。
Right. The first exponential is the number of customers is growing exponentially. And the reason for that is the AI is getting better. The use case is getting better. Just about every application is connected to OpenAI now. And so they're going through the usage exponential. The second exponential is the computational exponential ever-ever use. Yes. Right. Yes. Instead of just a one-shot inference, it's now thinking before it answers. So these two exponentials compounding the compute requirements. And so we've, we've got to build out all these different projects. And so this last one is an additive on top of everything that they've already announced. All the things that we're already working on with them. It's additive on top of that.
好的。首先，第一个指数增长是指客户数量正以指数级增长。原因是人工智能技术在不断进步，实际应用也在不断改善。几乎每个应用程序现在都连接到了OpenAI，因此它们的使用也在以指数级增加。第二个指数是计算资源的指数增加。不再是一次性推理，现在系统在回答之前会进行思考。这两个指数的叠加增加了计算需求。因此，我们必须推进所有这些不同的项目。最后这个项目是在他们已经宣布的所有事情之上新增的，是我们与他们合作项目的一个增量。
And it's going to support this incredible exponential. One of the things you said that's really interesting to me is kind of, you know, they're going to be high probability, multi-trillion dollar company in your mind. You think it's a great investment. At the same time, you know, they're self-building. You're helping them self-build their data centers. So here to four, they've been outsourcing to Microsoft to build the data center. Now they want to build full stack factories themselves. They want to do, they want to basically have a relationship with us. The way that Elon and Exhaust really. Correct. I mean, Elon and Exhaust built exactly. And I think that's us.
这段话的大意是：
这将支持这个惊人的指数增长。你提到的一件很有趣的事情是，你认为这家公司很可能会成为市值数万亿美元的企业，你认为这是一个很好的投资机会。同时，他们正在自我构建，你在帮助他们自建数据中心。之前，他们一直外包给微软来建数据中心。现在，他们希望自己建立完整的工厂，与我们建立一种关系，就像埃隆·马斯克和Exhaust所做的一样。没错，我的意思是，埃隆和Exhaust就是这么做的，而我认为这也正是我们的目标。
This is a very big deal. When you think about, when you think about the advantage that Colossus had, they're building full stack. That is a hyper-scaler. Because if they don't use the capacity, they could sell it to somebody else. That's right. 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. Sounds very much like AWS or GCP or Azure. That's what you're saying. Yeah. I think they'll likely use it themselves. And just in the case of Exhaust, 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.
这是一件大事。说到Colossus的优势，他们正在构建全栈技术。这种方式是一种超大规模运营商。如果他们不需要使用这些资源，可以将其出售给其他人。没错。同样的，Stargate正在建立巨大的容量。他们预计自己会需要用上大部分容量，但这也让他们有机会将剩余的售卖给别人。这听起来非常像AWS、GCP或Azure。是的，我认为他们可能会优先自用。同样，像Exhaust这样的公司，他们也可能优先自用。但是他们还希望与我们建立直接的业务关系，包括直接的合作关系和采购关系。
Meta, just as with Zuck and Meta has with us, it's exactly a direct. Our relationship with between us and Sundar and Google, direct. Our partnership with Satya and Azure Direct, is that right? And so they've gotten to a large enough scale. They believe it's time for them to start building these direct relationships. I'm delighted to support that. And Satya knows it and Larry knows it and everybody's aware of what's going on and every is very supportive of it.
这段话的大意是：
Meta与我们之间的关系，就像扎克伯格和Meta与我们之间的关系一样，是非常直接的。我们与桑达尔（Sundar）和谷歌之间的关系也是直接的。我们与萨提亚（Satya）和Azure之间的合作也是直接的，对吗？他们已经发展到足够大的规模，认为是时候开始建立这些直接的关系了。我很高兴支持这一点。萨提亚知道这个情况，拉里（Larry）也知道，每个人都清楚正在发生的事情，并对此表示大力支持。
So one of the things I find mysterious, 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. You know, Sam's talking in terms of trillions. But of the 25 cell site 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. Okay. That is the 25 people and their only job, they get paid to forecast the growth rate for Nvidia. So clearly we're comfortable with that, but we're comfortable with that. We have no trouble beating the numbers on a regular basis.
所以我发现有件事情挺神秘的，你刚才提到甲骨文公司市值3000亿美元，他们正在建设巨头项目。我们知道主权基金在建设什么，我们知道超大规模企业在建设什么。你知道，Sam在谈论数万亿的规模。但是，在观察你们公司股票的华尔街25位通信基站分析师中，如果我查看他们的共识预测，基本上从2027年开始你的增长就趋于平稳了。2027年到2030年的增长率为8%。这些分析师的唯一工作，就是为Nvidia预测增长率，他们为此领取工资。所以显然我们对此感到放心的，但我们对此感到放心。我们没有问题，能够定期超越这些数字。
Right. No, I understand that. But there is this interesting disconnect. No. Right. I hear it every day on CNBC in Bloomberg. And I think it goes to some of these questions around, you know, shortage is 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 two months 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. Right. And we also put together forecast, you know, 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, soon are saying, such a saying, and what Wall Street still believes. And, you know, again, you're comfortable with that. I also don't think it's inconsistent. Okay. So explain that a little bit.
好的。我明白这一点。但这中间存在一个有趣的分歧。不。我每天都在CNBC和彭博电视上听到这一点。我认为这涉及到一些问题，比如短缺导致过剩。他们不相信这个观点。他们说，好吧，我们会给你26年的信用，但27年，可能我们就只有两个月的时间了，你可能不再需要那个了。但这点对我来说很有趣。我觉得有必要指出你们的共识预测认为这不会发生。对，我们也为公司制定了预测，综合考虑了所有这些数据。结果显示，即使我们已经进入AI时代两年半了，依然存在巨大的信念分歧——比如我们听到Sam Altman、你、以及其他一些人说的，与华尔街仍然相信的之间。你对此感到满意。我也不认为这不一致。好的，那请你解释一下。
So first of all, for the builders, we're supposed to be building for opportunity. Right. We're builders. Let me give you three points to think through. And in these three points, it'll help you hopefully be more comfortable with Envidia in this future. So the first point, and this is the laws of physics point. This is the most important point that general purpose computing is over and the future is accelerated computing and AI computing. Yeah. That's the first point. And so the way to think about that is there's how much how many trillions of dollars of computing infrastructures in the world that has to be refreshed. Right. 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.
首先，对于构建者来说，我们的任务是为机会而构建。对吧？我们是建设者。让我给你三个要点来思考，这三个要点希望能让你在未来更适应英伟达（NVIDIA）。第一个要点，也是最重要的一点，就是关于物理法则的：通用计算已成为过去，未来是加速计算和人工智能计算。
第一个要点是，现在世界上的计算基础设施价值数万亿美元，这些基础设施需要更新换代。而当这些设施更新时，将会转向加速计算。这是对的。首先你需要意识到，通用计算已经结束，没有人对此有异议，大家都说，没错，我们完全同意这一点。通用计算已然成为过去，摩尔定律失效了。人们常常这样说。那么这意味着什么呢？意味着通用计算将转变为加速计算。
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 is now going to GPUs doing AI. So you just take classical computing, it's going to accelerate computing AI. You take hyperscale computing, it's going from CPUs to accelerated computing and AI. And then now that's the second point. Just feeding the meta as the Googles, the bite dances, the amazons, and take their classical traditional way of doing hyper scaling and moving into AI. That's hundreds of billions of dollars.
我们与英特尔的合作是基于这样一个认识：通用计算需要与加速计算相结合，以创造新的机会给他们。对吗？因此，一方面，通用计算正在转向加速计算和人工智能。另一方面，人工智能的第一个应用实际上已经无处不在，对吧？它已经体现在搜索和推荐引擎中。没错吧？在购物方面，以前使用的基础超大规模计算基础设施是通过CPU做推荐，现在将转为通过GPU进行人工智能处理。所以，传统计算将进化为加速计算和人工智能。超大规模计算正在从CPU转向加速计算和人工智能。这是第二点。像谷歌、字节跳动、亚马逊这样的公司，正在将他们传统的超大规模计算方式转向人工智能。这涉及到数千亿美元的市场。
And because that may be four billion people on the planet today, if you take TikTok, meta into account, Google into account, who are already demanding workloads that are driven by several ways. That's exactly right. And so there's a some without even thinking about AI creating new opportunities, it's about AI shifting how you used to do something to the way new way of doing something. Okay. And then now let's talk about the future. I just so far have only spoken kind of largely about what it's just mundane stuff. Just mundane stuff. The old way is now wrong. You're going to go, you're not longer than you use fuel light lanterns. You're going to go to electricity. That's all. Right. Okay. And you can no longer, you know, prop planes. You're going to go to jets. That's all.
好，以下是这段文字的中文翻译，力求表达意思且易于阅读：
考虑到今天全球可能有四十亿人使用像TikTok、Meta和Google这样的平台，这些平台的需求工作量是通过多种方式驱动的。这是完全正确的。因此，甚至不需要考虑AI创造新的机会，仅是AI已经在改变旧有的操作方式，转变为新方式。好的，现在让我们来谈谈未来。到目前为止，我所说的基本上都是一些平常的事务。旧的方式已经不适用了，你不会再用燃油灯了，你会用上电灯。这就是全部。同样，你不会再使用螺旋桨飞机，而是会使用喷气式飞机。就是这样。
Okay. So, you know, that's so far. Yeah. That's all I've talked about. And then now that 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. Yeah. And that's the that opportunity. What is it? What does that look like? Well, the simple way of thinking about that is where motors replaced 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.
好的。所以，你知道，到目前为止，就是这样。这就是我所讨论的一切。然后，现在令人难以置信的事情是，当你进入人工智能领域，当你进入加速计算领域，会发生什么呢？会有哪些新的应用出现？这就是我们正在讨论的所有人工智能内容。对，这就是机会。那是什么样子的？简单来说，就像电动机取代了劳动和体力活动一样，现在我们有了人工智能，这些人工智能超级计算机，这些我提到的人工智能工厂，它们会生成“代币”来增强人类智力，对吧？而人类智力代表了什么？大约55%到65%的全球GDP。我们可以粗略估计为50万亿美元。
And that $50 trillion is going to get augmented by something. And so let's just 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. And that $10,000 AI as a result made the $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, right? Every single coagents. That's right. Every single worker. That's right. Every single software engineer, every single chip designer in our company already has AI is working with them. A hundred percent 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 is greater. Our profitability is greater. What's not to love about that?
那50万亿美元的价值会被某些因素增强。让我们以一个人为例。假设我雇用了一个年薪10万美元的员工，然后再为这个员工配备一个价值1万美元的人工智能助手。这个1万美元的人工智能助手让这位10万美元的员工的生产力提高了两倍或三倍。那么我会这样做吗？毫无疑问，我正在为我们公司的每一个人这样做。每一个协同工作者——对的，每一位员工，每一个软件工程师，每一个芯片设计师都已经有人工智能在协助工作。覆盖率达到100%。结果是，我们设计的芯片数量更多，增长速度加快，公司整体发展得更快。我们因此招募了更多员工，生产力提高，营收增加，盈利能力增强。这种结果有什么不值得期待的呢？
Now, apply the NVIDIA story to the world's GDP. 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 IT in the past, in a way, software was written a priori and then it runs on a CPU. 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 is 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, it needs an AI infrastructure. So if you told me that on an annual basis, the cap ex of the world was about $5 trillion, I would say the math seems to make sense. And that's kind of the future, right? The going from general purpose computing, accelerated computing, replacing all the hyper-scales with AI and then now augmenting human intelligence for the world's GDP.
现在，把NVIDIA的故事应用到全球GDP上。很可能会发生的情况是，这50万亿美元的经济体量将被额外增加，比如，增加10万亿美元。这10万亿美元需要在某种机器上运行。AI与过去的IT不同，过去的软件是先被开发出来，然后运行在CPU上，由人来操作。而在未来，AI会生成“令牌”（tokens），但这些令牌是由机器生成和思考出来的。因此，这种软件是一直在运行的，而过去的软件是开发一次就可以了。现在, AI不断地在“思考”，软件就如同一个工厂。
假设这10万亿美元的“令牌”生成有50%的毛利率，其中5万亿美元需要一个工厂来支撑，需要AI基础设施。所以，如果你告诉我全球的年资本支出大约是5万亿美元，我会觉得这个数学计算是合理的。这就是未来，从通用计算到加速计算，用AI替代所有的超级计算，然后再增强人类的智能，从而提高全球GDP。
And today, that market is about, our estimate is about 400 billion annually. So the, the TAM, you know, is a four to five X increase over where it is today. Yeah. Eddie, last night, Eddie, Alibaba said, between now and the end of the year, and excuse me, now in the end of the decade, they're going to increase their data center power by 10X, right? Right. You just said how much? 4X. There you go. There you go. They're going to increase power by 10X. And we correlate the power. And Vides revenue is almost correlated to power. Yes. Isn't that right? Yeah. That's right. Yeah, because more so. Another thing, what else did he say? He said token generation is doubling every few months. Yeah. What's that saying? The, the perf per watt has to keep on going exponentially. That's why Vides like cranking it out with perf per watt. And revenue per watt is, you know, watt is basically revenue in this future. Embedded in this assumption, I find it very fascinating.
今天，我们估计那个市场的规模每年大约是4000亿美元。所以，整体可开发市场（TAM）相比现在会增长四到五倍。是的。昨晚，Eddie，阿里巴巴表示，从现在到年底，不，抱歉，是到本十年末，他们的数据中心功率将增加10倍，对吧？对的。你刚才说多少？4倍。没错。他们将把功率增加10倍。我们发现功率和Vides的收入几乎是相关的。对吧？是的。因为更多是这样的。另一个事情，他还说什么来着？他说每隔几个月代币生成就会翻一倍。那说明了什么呢？性能每瓦必须持续呈指数增长。这就是为什么Vides在拼命提高每瓦性能。每瓦的收入，基本上在未来瓦就是收入。在这种假设中，我觉得特别有趣。
You know, historical context. Right. For 2000 years, basically GDP did not grow. Okay. And then we get the industrial revolution. GDP accelerates. We get the digital revolution. GDP accelerates. And it basically what you're saying, and Scott Besson 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 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. It has to. Right. 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 that's opening the eyes, the fastest growing revenue company in history. Right. And they're growing exponentially.
你知道，那就是历史背景。对，在过去的2000年里，基本上国内生产总值（GDP）没有增长。然后，我们迎来了工业革命，GDP开始加速增长。接着，我们又迎来了数字革命，GDP再次加速。基本上，你在说的，正如斯科特·贝松所说的，他认为明年我们将有4%的GDP增长。他的意思是，全球GDP增长将会加速，因为我们正在为世界提供数十亿个能够为我们工作的“同事”。如果说GDP是固定的劳动和资本所产生的产出的数量，那么它一定会加速增长。没错，一定会加速增长。看看AI技术正在发生的变化吧。由于AI技术的发展——我们姑且称之为大型语言模型和所有的AI代理，它正在创造一个新的AI代理行业。这是毋庸置疑的。所以，这就像是历史上收入增长最快的公司，它们正在以指数级速度增长。
Right. And 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 this growing energy is growing. Power. Shell. This is the end. This is like renaissance for the energy industry. Isn't that right? Nuclear energy, gas turbines. I mean, look at all of those companies in the infrastructure ecosystem underneath us. They're doing incredibly well. Everybody's growing.
好的。AI本身是一个快速发展的行业。因为AI背后需要工厂和基础设施的支持，所以这个行业在不断壮大。我的行业也在发展壮大，而由于我的行业的发展，底层的能源行业也在增长。这就像是能源行业的文艺复兴，对吗？核能、燃气轮机——看看在我们基础设施生态系统中的那些公司，它们发展的都非常好。每个人都在成长。
These numbers have everybody talking about a glut or a 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, Delema. Right. And walk us again through. These are very happy prisoners.
这些数字引发了人们关于供应过剩或泡沫的讨论。对吧。扎克伯格上周在一个播客中说，他认为在某个时候我们可能会遇到一个"空气口袋"这样的阶段。而Meta可能会超支100亿美元之类的，但他表示，这无关紧要。这种投入对公司未来的存在至关重要，所以这是他们不得不承担的风险。但是，当你想一想，这听起来有点像囚徒困境。对吧。我们再来看看，这些都是非常快乐的囚徒。
Walk us again through. Right. To date, our estimate is that we're going to have 100 billion of AI revenue in 2026. Excluding Meta, and excluding, you know, the GPUs running recommended engines. Yeah. Okay. So there's a certain. Correct. So there's other stuff. But let's call it 100 billion. What does that industry anyways? What is the industry already in the hyperscale? What's the hyperscale's, you know, between? The trillion. Yeah, exactly.
好的，我们重新过一遍。到目前为止，我们的估计是，到2026年，我们的人工智能收入将达到1000亿美元。这不包括Meta，也不包括运行推荐引擎的GPU。是的，没错。虽然还有其他因素，但我们就算作1000亿美元吧。那么这个行业是什么呢？在超大规模（Hyperscale）领域，这个行业已经达到多少？大约是万亿美元级别。没错，确实是这样的。
By the way, that industry is going to AI. Before anybody starts at zero, you got to start there. 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 5 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 100 billion over the course of the next five years? Are we growing that fast?
顺便提一下，那行业正在迈向人工智能。在别人从零开始之前，你必须从那里开始。但我认为持怀疑态度的人会说，我们需要将2026年1000亿的人工智能收入提高到2030年的至少1万亿。好的。你刚才提到全球GDP是5万亿。如果从零开始，你能否在接下来的五年内将人工智能推动的收入从1000亿增长到1万亿？我们的增长速度有那么快吗？
Yes. And I would also say we're already there. Okay. So explain that. Because the hyperscalers, they went from CPUs to AI. Okay. Their entire revenue base is all now AI driven. Correct. You can't do TikTok without AI. Correct. You can't do YouTube short without AI. You can't, you know, you can't do any of this stuff without AI. The amazing things that Meta's doing for, for, you know, customized content, personalized content, you can't do that without AI.
好的。我会说，我们已经进入这个阶段了。为什么这么说呢？因为大型云服务提供商已经从使用中央处理器（CPU）转向人工智能（AI）。他们的收入现在完全依赖于人工智能。没错，没有AI，你就无法运行像 TikTok 这样的应用，也无法实现 YouTube 的短视频功能。同样，Meta 为用户提供的个性化内容，也离不开AI。所有这些令人惊叹的技术成就都需要人工智能的支持。
It's all of that stuff used to be humans, you know, doing content a priori, creating four choices that are then selected by a recommender engine. Correct. And now it's infinite number of choices generated by an AI, right? But those things are all right. Like we had the transition from CPUs to GPUs largely for those recommender engines. And now they're going. That's fairly new. In the last three or four years, yeah, Zuck would tell you, I was at SIGRAF and Zuck would tell you, you know, they were late getting to shows.
这些东西以前都是由人类完成的，比如预先创建内容，然后通过推荐引擎来进行选择。对吧？而现在，是由人工智能生成无限数量的选择，对吗？但这些发展都没有问题。就像我们为了推荐引擎的需要，从CPU过渡到GPU一样。这种转变相对较新，大约是在过去三四年中发生的。对了，扎克可能会告诉你，我在SIGRAF（电脑图形和互动技术大会）上，扎克会提到他们赶不上这些变化。
For sure. Yeah, for sure. GPUs for Meta is what, a couple of years, a year and a half. It's pretty new. Search would GPUs. For sure. Brand spanking new. For sure. For sure. Brand spanking new. Search for GPUs on GPUs. 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 all on the way. Already. Already.
当然可以。是的，当然可以。Meta使用GPU大概是一两年前开始的。这是个比较新的事情。通过GPU进行搜索，这当然是全新的。完全全新无疑。所以你认为到2030年，我们的AI收入达到一万亿美元的可能性几乎是确定的，因为我们已经在这条路上了。已经在路上了。
Yeah. Okay. Let's just talk about incremental. Incremental. Incremental. Now we can talk about incremental. Incremental. Right. Exactly. Right. As you do your bottoms up or your tops down, I just heard your tops down about percentage of global GDP. Yeah. What is the percentage probability that you think will have a glat, will run into a glat in the next three or four or five years? Right. It's a distribution of, we don't know the future.
好的。我们来聊一下“逐步增加”的概念。逐步增加，逐步增加。现在我们可以讨论“逐步增加”了，对吧？正如你在做由下而上的分析或者由上而下的分析时，我刚才听到了你关于全球GDP百分比的由上而下的分析。对。那么你认为在未来三、四、五年内遇到某个问题（可能是市场饱和或停滞）的概率是多少呢？对，这其实是个概率分布，因为我们无法预测未来。
It's a distribution of properties. Until. Until. We. Fully. Convert. All. General purpose computing to accelerate computing and AI. Until we do that. Yes. I think the chances are extremely low. Okay. Okay. And that will take a few years. They'll take a few years. Yeah. Let me ask one more in that. 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 so forth.
这是一种属性的分布。直到，直到，我们完全将所有通用计算转变为加速计算和人工智能。在我们做到这一点之前，我认为可能性非常低。好的，好的。这需要几年时间，会需要几年时间的。让我再问一个问题：直到所有推荐引擎都基于人工智能，直到所有内容生成都基于人工智能，因为内容生成、面向消费者的内容生成在很大程度上都是推荐系统等等。
And all of that's going to be AI generated. Until. Until all of this stuff, what classically was hyper scale, now transitions to AI. Everything from shopping to e-commerce to all that stuff. Until everything goes over. But all this new build. Right. When we're talking about trillions, we're investing ahead of where we are. 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?
这些内容都将由人工智能生成。直到所有这些东西——那些传统上的超大规模操作——现在都转向由人工智能驱动。从购物到电子商务，一切都是如此。直到所有一切都转变过来。但新建立的一切仍在继续。对吧。当我们谈论数万亿的投资时，我们是在为未来提前投资。你知道的，这种情况是随意的，还是即使看到了经济放缓或某种过剩的迹象，你也有义务继续投资呢？
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 slowdown, we can always pull back on the level of investment. Actually, it's the other way because we're at the end of the supply chain, right? And so we respond to demand. And right now, all the VCs will tell you, you guys know, the demand, the short, there's a shortage of compute in the world. Not because there's a shortage of GPUs in the world. Okay. If they give me an order, I'll build it. Right. We've over the last couple of years, we've really plumbed the supply chain. So all of the supply chain behind me from wafer starts to co-wast, HBM memories, you know, all of that technology, we've really geared up. Yeah. If we need to double or double. Yes. Okay. So the supply chain is ready. Now we're just waiting for demand signals.
这段文字可以翻译成中文并用简单易懂的方式表达为：
还是说这只是一个让生态系统中大家行动起来的信号，告诉他们赶紧去开发？这样的话，如果有一天我们看到市场需求放缓，我们也可以减少投资。实际上，这种情况是相反的，因为我们是在供应链的末端，因此我们是根据需求来进行响应的。现在，各位风险投资家都会告诉你，你们都知道，世界上对计算的需求是很大的，存在短缺。这并不是因为世界上缺少GPU。如果有人下订单给我，我会去生产。在过去几年里，我们真的深入研究过供应链。从晶圆制造到后期的技术，如HBM内存，所有这些技术我们都已做好准备。如果需要翻倍产量，我们可以做到。因此，供应链已经准备好了，现在我们只是在等需求信号。
And when the CSPs and the hyperscalers and our customers do their annual plan and they give us, you know, their forecast, we respond to that and we build to that. Now, what's going on, of course, is that every one of their forecasts that they provide us, it turns out to have been wrong. Right. Because they under-forecast it. And so now we're always in a scramble mode. And so we've been in the scramble mode now for, you know, a couple of years. And it's whatever forecast we've been given has been always significant increase from last year. But not enough. Such a last year seem to be pulling back a little bit, you know, seem to be, you know, some people call them 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.
当云服务提供商和超大规模公司以及我们的客户进行年度计划并向我们提供他们的预测时，我们会根据这些预测作出响应并进行建设。然而，问题是他们给我们的每一个预测最终都不准确，因为他们低估了需求。所以我们一直处于紧张应对的状态，已经有几年了。每年的预测相对于前一年都有显著增长，但仍然不够。因此，去年出现了一些收缩的趋势，有些人称这是理智的选择，试图降低一些过高的预期。几周前，有人说："我今年已经建立了两个吉瓦，并且我们将在未来加速发展。"
Do you see some of the traditional hyperscalers that may have been moving a little slower than let's call it a core weave or, or, 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. Because of the second exponential. Okay. We've already had one exponential we were experiencing, which was the adoption rate of AI, the engagement of AI was growing exponentially. Yes. The second exponential that kicked in was reasoning. Yeah. That was the conversation we had one year ago. One year ago. Yeah. He said, hey, listen, the moment you take AI from one shot, memorizing an answer and general, right? Memorizing and generalizing that's basically portraying. So memorizing an answer, you know, what's eight times eight? Just memorize it. Okay.
您是否注意到一些传统的超大规模公司（hyperscalers）可能在行动上比我们称之为核心编织(Core Weave)、Elon X 或 Stargate 的企业慢一些？在我看来，他们现在似乎都更加积极了。这是因为出现了第二个指数级增长。我们已经经历了第一个指数级增长，也就是 AI 的采用率和参与度呈现指数级增长。是的。然后，第二个指数级增长是推理能力的提升。这是我们一年前讨论的话题。一年前，他说：“听着，当你让 AI 不仅是一次性记住答案，而是能够进行一般化和推理时，变革就开始了。”例如，记住一个答案，比如“8乘以8是多少？”就是简单的记忆。
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 thinking AI. One billion X. It's going to use a lot more compute. Certain hyperscale customers to your point had internal workloads that they had to migrate anyways from, 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. That's right. Everyone has now concluded that they dramatically underbuilt. One of the applications that my favorite is just good old-fashioned data processing. Structure data and unstructured data. Just good old-fashioned data processing. Yes. And very soon we're going to announce a very big initiative of accelerated data processing.
过去的“一次性人工智能”是通过记忆答案并加以泛化。然而，一年前，AI开始具备推理能力，开始进行研究，开始使用工具，现在你正在思考AI的未来发展，其计算能力将是以往的十亿倍。这将需要更多的计算资源。正如你所说的，某些超级规模的客户原本就有内部工作负载需要从通用计算迁移到加速计算，因此他们在这个过程中进行了建设。我认为可能有些超级规模客户的工作负载不同，他们不确定需要多快的速度来消化这种变化。没错，现在每个人都认识到他们的建设规模严重不足。我最喜欢的一个应用就是传统的数据处理，包括结构化和非结构化数据的处理。是的，我们很快就会宣布一个关于加速数据处理的重要计划。
Data processing represents the vast majority of the world's CPUs today. It still completely runs on CPUs. If you go to data breaks, it's mostly CPUs. If you go to snowflakes, mostly CPUs. A SQL processing at Oracle, mostly CPUs. Everybody's using CPUs to do SQL, structure 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 to, everything that Nvidia does requires acceleration layers and requires domain-specific data processing. Recipes. We got to go get built back. But that's coming. One of the pushbacks, I turned on CNBC yesterday. They're like, oh, glut, bubble. When I turned on Bloomberg, it was about round-tripping and circular revenues. For the benefit of people at home, know these arrangements are when companies enter into a misleading transaction.
数据处理在今天的世界中占据了绝大多数的中央处理器（CPU）。它仍然完全依赖于CPU。如果你查看Databricks，大部分仍然使用CPU。如果你看看Snowflake，大部分也还是CPU。在Oracle进行SQL处理，主要也是依赖CPU。每个人都在使用CPU处理SQL和结构化数据。但是在未来，这一切都将转向人工智能数据。这将成为一个巨大的新市场。不过，需要注意的是，Nvidia所做的一切都需要加速层和特定领域的数据处理方案。这个需要我们去构建。但是，这个趋势正在到来。
至于一些质疑，有时候打开电视台，比如昨天我看了CNBC，他们在谈论供应过剩和泡沫。我换到彭博社，他们在讨论回圈交易和循环收入。为了让大家理解，这些指的是公司之间进行一些具有误导性的交易。
They artificially inflate revenue without any underlying economic substance. In other words, gross propped up by financial engineering, not by customer demand. And the canonical case everybody's referencing, of course, is Cisco and Nortel from the last bubble 25 years ago. When you guys are Microsoft or Amazon are investing in companies that are also your big customers. In this case, you guys investing in OpenAI. While OpenAI is by intense ability to chips, just remind us and remind everybody else. What are the analysts on Bloomberg and otherwise getting wrong when they're hyperventilating about circular revenues or about round-tripping? 10 gigawatts is like $400 billion. Right. Something like that. That $400 billion will have to be largely funded by their off-take, their revenues, 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.
他们人为地夸大了收入，而没有任何真正的经济基础。换句话说，他们的总收入是通过财务操作支撑起来的，而不是由客户需求推动的。当然，大家提到的经典案例是25年前的Cisco和Nortel泡沫。当你们像微软或亚马逊一样在投资同时也是你们大客户的公司时，这种情况会发生。在这次情况下，你们投资了OpenAI，而OpenAI正在大规模购买芯片。提醒我们和其他人一下，当分析师们对循环收入或重复交易大惊小怪时，他们究竟错在哪里呢？10吉瓦相当于大约4000亿美元。对吧，大概是这样。这4000亿美元主要必须通过他们的收入来支持，而这些收入正在以指数级增长。还必须通过他们从股权筹集的资金以及他们能够借贷的债务来支持。这是三个途径。
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 there's 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 hyper-scale company. And who doesn't want to be an investor in that?
他们能够筹集的股本和债务与他们能够维持收入的信心有关。这是肯定的。因此，聪明的投资者和贷款人会考虑所有这些因素。这是他们基本上要做的事情。那是他们的公司，不是我的业务。当然，我们必须与他们保持密切联系，以确保我们支持他们的持续增长。好的，这涉及收入方面，与投资方面无关。投资方面不受任何限制。这是一个投资他们的机会。而且正如我们之前提到的，这家公司很可能成为下一个数万亿美元的超大规模公司。谁不想成为其中的投资者呢？
You know, my only regret is that they invited us to invest early on. I remember those conversations. We were so poor that we were so poor we didn't invest enough. And I should have given them all my money. 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 things. That's right. Yeah, that's right. There's no obligation that they have to use your chips. That's right. And like you said, you're looking at this as an opportunistic equity investment. The other thing I would say is. And we've made some great investments. I've got to put it out there. We invested in XAI. We invested in CoreWeave.
你知道，我唯一的遗憾就是他们早期邀请我们投资的时候。我记得那些对话。我们当时太穷了，以至于没有投资够多。我本应该把我所有的钱都给他们。事实是，如果你们不做好自己的工作，如果Vera Rubin芯片不够好，他们可以去找其他芯片来用。是的，没错。他们没有义务一定要用你的芯片。正如你所说，你看待这件事就像看待一个机会投资。我还想说的是，我们确实做了一些很好的投资。我必须说出来，我们投资过XAI，也投资过CoreWeave。
Incredible. Yeah. How smart was that? 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 chat GPT, 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 was. What person, company or nation says, intelligence is basically optional for us.
令人难以置信。是的，那有多聪明啊？在我回过头来看这个问题时，我觉得另一个基本点是，你知道的，你们公开宣称了你们正在做的事情。这里的基本经济实质是什么呢？并不是说你们只是简单地在两家公司之间转移收入。我们有用户每个月都在为ChatGPT付费，这个产品有15亿月活用户。你刚才说，世界上的每一个企业要么接受这个，要么就会消亡。每个国家都认为这一点对其国家安全和经济安全的重要性堪比核能。有什么人、公司或国家会说，智能对我们来说基本上是可有可无的呢？
Yeah, for us. I mean, it's fundamental to them. Well, I beat the automation of intelligence. I beat the demand question to death. So let's jump in a little bit to system design. And I'm going to turn to Clark here in a second on that. In 2024, you switched to your annual release cycle right with Hopper. You then had a massive upgrade which required, you know, significant data center overhaul with Grace Blackwell in 2025. And in the back half of 26, we're going to get Vera Rubin. 27 will get Ultron and 28 Feynman. How is the annual release cycle going? Okay. 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?
好的，对我们而言是这样的。我是说，对于他们而言，这很基础。嗯，我已经深入讨论过了智能自动化的问题，也彻底分析过需求问题。因此，让我们稍微转向系统设计方面。我马上会请克拉克来讲这个。在2024年，你们就开始采用年度发布周期，与霍珀（Hopper）一起。在2025年进行了一次大规模升级，这需要对数据中心进行重大改造，和格蕾丝·布莱克韦尔（Grace Blackwell）合作。在26年下半年，我们将迎来维拉·鲁宾（Vera Rubin）。27年将是奥创（Ultron），28年则是费曼（Feynman）。年度发布周期进行得如何？那么，你们选择年度发布周期的主要目标是什么？Nvidia内部的人工智能是否帮助你们实现年度发布周期？
Yeah, the answer is yes. On the back, the last question, without it, Nvidia's velocity or pace or scale would be limited. And so without AI these days, it's just simply not possible to build what we built. 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. And the customer use is going up exponentially. I think there are 800 million weekly active users or something like that. Yes. I mean, that's, I don't think. That's two years from Chancho Pt, right? And each of those users is generating massively more tokens because they're using inference time reasoning.
是的，答案是肯定的。就上一个问题来说，如果没有它，英伟达的发展速度、规模都会受到限制。如今，没有人工智能，我们就无法建造出我们所建造的东西。我们为什么要这样做？记得艾迪在他的财报电话会议或会议上提到过这一点，萨蒂亚也说过，山姆也讲过。代币生成率正在以指数级增长，而客户的使用率也在以指数级上升。我想现在大概有8亿的活跃用户，每周都有在使用。这是我认为对的。两年后就会超过那个数字。而且这些用户每次推理时产生的代币数量都大大增加了。
That's right. Exactly. And 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, unless we increase the performance at incredible rates, the cost of token generation will keep growing because more's loss dead, right? Because transistors basically cost the same every single year now. And power is largely the same between those two fundamental laws, unless we come up with new technologies to drive the cost down. Even if there's a slight difference in growth, you give somebody a discount of a few percent. How's that going to make up for two exponentials? And so we have to increase our performance annually at a pace that keeps up with that exponential.
没错，正是如此。因此，首先由于代币生成速度正在以极快的速度增长，呈现出双重指数增长趋势，如果我们不以惊人的速度提升性能，代币生成的成本将继续上升，因为摩尔定律已经不再适用了。如今，晶体管的成本基本上每年都保持不变，电力消耗在这两条基本定律之间也大致相同，除非我们开发新的技术来降低成本。即使增长率有轻微差异，比如给某人几个百分点的折扣，这些也无法弥补双重指数的影响。因此，我们必须每年以能够跟上这种指数增长的速度提升我们的性能。
So in the case of going from, I guess, a Kepler to, all the way to Kepler, all the way to Hopper was probably a 100,000X. That was the beginning of the AI journey for Nvidia, 100,000X in 10 years. Between Hopper and Blackwell, we increased because of MV-LINK 72, 30X in one year. And then we'll get another X-Factor again with Rubin. And then we'll get another X-Factor with Feynman. And the way we do that is because the transistors aren't really helping us very much, right? More as long as largely the density is growing up, but going up, but the performance is not.
在从Kepler这样的架构发展到Hopper架构的过程中，性能提升了大约100,000倍。这是Nvidia涉足人工智能领域的开端，在10年间实现了100,000倍的提升。在Hopper与Blackwell之间，通过MV-LINK 72，我们在一年中提升了30倍。接下来，我们会在Rubin和Feynman的帮助下再次实现性能的大幅提升。我们之所以能够实现这些进步，是因为单靠晶体管并不能带来太大的帮助。虽然晶体管密度还在增加，但性能提升已经不如过去。
And so if that's the case, one of the challenges that we have to do is we have to break the entire problem down at the system level and change every chip at the same time and all the software stack and all the systems all at the same time. The ultimate extreme co-design. Nobody's ever co-designed at this level before. We change the CPU, revolutionize the CPU, a GPU, the networking chip, the MV-LINK scale up, the Spectrum X scale out. Somebody said, I heard somebody said, oh yeah, it's just Ethernet. Yeah, right. So Spectrum X Ethernet is not just Ethernet. And people are starting to discover, oh my god, the X-Factors is pretty incredible.
如果情况是这样，我们面临的一个挑战就是必须从系统层面对整个问题进行拆解，同时改变所有芯片、软件堆栈和整个系统。这是一种极端的联合设计，以前从未有人在这样的层次上进行过联合设计。我们要更换CPU，革新CPU、GPU、网络芯片、MV-LINK扩展，以及Spectrum X的扩展。有人说过，我听到有人说，哦，是的，那只是以太网。实际上，Spectrum X以太网并不仅仅是以太网。人们开始发现，X因素真的非常了不起。
Right. Nvidia's Ethernet business, the just Ethernet business, is the fastest growing Ethernet business in the world. And so scale out. And of course, now we have to build even larger systems so we scale across multiple AI factories connected together. And then we do this at an annual pace. And so we now have an exponential of exponentials going ourselves for technology. And that allows our customers to drive the costs of tokens down, keep making those tokens smarter and smarter with pre-training and post-training and thinking. And as a result, when the AI gets smarter, they get more used. When they get more used, they're going to grow exponentially.
好的。英伟达的以太网业务，仅仅指以太网业务，是全世界增长最快的。我们正在扩大规模，当然，现在我们必须构建更大的系统，以便在多个连接在一起的AI工厂之间进行扩展。我们以每年的速度来实现这一点，因此在技术上我们正在经历指数级多重增长。这使得我们的客户能够降低令牌的成本，通过预训练和后训练不断提高这些令牌的智能水平和思考能力。因此，当AI变得更加智能时，它们的使用就会增加。使用的增加将会带来指数级的增长。
For people who may not be as familiar. Yeah. What does extreme co-design? Extreme co-design means that 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 and 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.
对于可能不太熟悉这方面的人来说，什么是极端协同设计？极端协同设计意味着你要同时优化模型算法、系统和芯片。你需要进行跨越常规的创新。过去，根据摩尔定律，你只需要让CPU的速度越来越快，一切都变得更快，你是在盒子里进行创新，只需让芯片速度更快就好。然而，如果芯片速度无法再提高，你该怎么做呢？就需要在盒子之外进行创新。
And so 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 there's all these industries we're in. We're creating all these libraries and co-design. Number one, full stack. Extreme is even beyond software and GPUs. It's now at the data center level, switches and networking and all of that software in the switches and the networking and the nicks, the scale up, the scale out, optimizing across all of that. As a result of that, Blackwell to Hopper is 30x. No Moore's Law could possibly achieve that.
英伟达真正改变了局面，因为我们做了两件事。我们发明了CUDA、GPU，并提出了大规模协同设计的理念。这就是为什么我们涉足了如此多行业。我们创建了各种库并进行协同设计。首先，我们是全栈的。我们的极致不仅限于软件和GPU，还涉及到数据中心层面，包括交换机和网络，以及交换机和网络中的所有软件、网卡，进行纵向扩展和横向扩展，并在这一切中进行优化。正因为如此，从Blackwell到Hopper的性能提升了30倍，这是摩尔定律无法实现的。
That's extreme. That's coming from the extreme co-design. That's because Nvidia has. That's why we got into networking and switching and scale up and scale out of the scale across and building CPUs and GPUs and building nicks. That's the reason why Nvidia is so rich in software and people. We check in more open-source software in the world than just about anybody except one other company. I think it's AI too or something like that. So we have such enormous richness of software and that's just in AI. Don't forget computer graphics and digital biology and times vehicles and the amount of software we produce as a company is incredible.
这很极致。这源自于极端的协同设计。这是因为Nvidia具备这种能力。因此，我们涉足了网络、交换、横向扩展、纵向扩展以及构建CPU、GPU和网络接口卡。这就是为什么Nvidia在软件和人才方面如此丰富的原因。我们在全球提交的开源软件数量仅次于另一家公司。我认为这也涉及到AI或类似的领域。因此，我们在软件方面具有极大的丰富性，这仅仅是在AI领域。不要忘记计算机图形学、数字生物学及自动驾驶汽车等领域，我们公司生产的软件数量是惊人的。
That allows us to do deep and extreme co-design. I heard from one of your competitors. Yes, he's doing this because it helps drive down the cost of token generation. But at the same time, your annual release cycle makes it almost impossible for your competitors to keep up. The supply chain gets locked up more because you're giving three year visibility to your supply chains and now the supply chain has confidence as to what they can build to. So do you think about this before you ask the question? Think about this. In order for us to do several hundred billion dollars a year of AI infrastructure build out. Yes. Think about how much capacity we had to go start a year ago. Yes. We're talking about building hundreds of billions of dollars of wafer starts and DRAM buys. Are you guys talking? This is now at a scale that hardly any company can keep up.
这使我们能够进行深入且极端的合作设计。我听说你们的一位竞争对手也在做类似的事情。是的，他这么做是因为可以帮助降低令牌生成的成本。但与此同时，你们的年度发布周期几乎让竞争对手难以跟上。由于你们为供应链提供了三年的可见性，供应链越来越被锁定，现在他们有信心知道该生产什么。因此，在你提出问题之前，有没有先考虑过这一点？想一想，要为每年几千亿美元的人工智能基础设施建设打下基础，是的，想想我们一年前需要启动多少产能。是的，我们谈论的是建设上千亿的晶圆起始量和DRAM采购。你们在讨论吗？现在的规模几乎不是任何一家公司所能应对的。
So would you say your competitive mode is greater today than it was three years ago? Yes. First of all, there's just more competition than ever before. But it's harder than ever before. 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 X factor growth. Number one, and so unless you're working on six, seven, eight chips a year, that's 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.
你会说你现在的竞争状态比三年前更强了吗？是的。首先，现在的竞争比以往任何时候都要激烈。但是，现在也比以往任何时候都更难。我之所以这么说，是因为晶圆成本在不断增加。这意味着除非你在极大规模上进行协同设计，否则你就无法实现十倍增长。这是第一点。除非你每年都在研究六、七、八个芯片，那真是很了不起的事情。这不仅仅是建造一个ASIC，而是要构建一个人工智能工厂系统。这个系统中有很多芯片，它们都是协同设计的。共同合作，它们几乎经常帮我们实现十倍的增长。
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 a you know, 400,000, 500,000 GPUs. Getting 500,000 GPUs to work together is a miracle. I mean, it's just a miracle. And so your customers are taking an 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? On an unproven architecture. That's right. A new one. A new architecture. Yeah, you just taped out a whole new chip. You're as excited as you are about it, you know, and everybody's excited for you. And you just showed the first silicon. Who's going to give you $50 billion PO? And why would you start $50 billion with a wafer for a chip that just taped out?
首先，协同设计的程度极高。其次，规模也极为庞大。当客户部署一个千兆瓦的系统时，那就意味着40万到50万个GPU。让50万个GPU协同工作简直是个奇迹，我的意思是，这真的是个奇迹。因此，客户在你身上承担了巨大的风险，他们购买所有这些设备。你得问自己，究竟是什么样的客户会在一种架构上放一个500亿美元的订单？而且这个架构还没有经过验证。对，是一个新的架构。一个全新的架构。是的，你刚刚设计了一颗全新的芯片。当你和所有人为此激动的时候，你刚刚展示了第一块硅片。谁会给你一个500亿美元的订单？而且为什么要给一块刚刚设计出的芯片的晶圆下500亿美元的订单？
But for Nvidia, we could do that because our architecture is so proven. So number, the scale of our customers, so incredible. Now the scale of our supply chains, incredible. 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 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 the scale's incredible.
但对于Nvidia来说，我们能够做到这一点是因为我们的架构已经充分验证过了。我们的客户规模非常庞大，我们的供应链规模也非常惊人。有哪个公司会预先准备好这一切，除非他们相信Nvidia能够交付？不是吗？他们相信我们能够为全球的客户提供服务。他们愿意一次性投入数千亿美元。这种规模真是令人难以置信。
To that point, you know, one of the biggest key debates and controversies in the world is this question of GPUs versus A6. Google's TPUs, Amazon's Trainiam, and it seems like everyone from ARM to OpenAI to Anthropic are rumored to be building one. Last year, you said, you know, 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 like the seeming most of them, given the seeming success of Google's TPUs, you know, how are you thinking about this evolving landscape today?
关于这一点，你知道，世界上最大的争论和争议之一就是关于GPUs（图形处理单元）和ASIC（应用专用集成电路）的问题。像谷歌的TPUs（张量处理单元）、亚马逊的Trainium，看起来从ARM到OpenAI再到Anthropic似乎每家公司都在传言要研发自己的芯片。去年，你曾说过，我们在构建的是系统，而不是芯片，你通过整个架构的每一个部分来提升性能。你也提到，许多这样的项目可能永远无法达到生产规模。但考虑到谷歌TPUs似乎取得的成功，你现在是如何看待这个不断演变的局面呢？
Yeah, first of all, the advantage that that Google had is foresight. Remember, they started TPU 1 before everything started. You know, this is no different than a startup. You're supposed to build a startup. You're supposed to create a startup before the market grows. You're not supposed to come up as a startup when the market's a trillion dollars large. You know, this fallacy and all VCs know this. 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?
首先，Google 的优势在于它的前瞻性。记得他们在一切开始之前就推出了 TPU 1。这和创业公司没什么两样。你应该在市场增长之前创建一家创业公司，而不是等到市场规模达到万亿美元才涉足。许多风险投资家都意识到这个误区：认为只要在一个大市场中占据几个百分点的份额，就能成为一家巨头公司。这实际上是有问题的。你应该在一个小行业中占据100%的份额，这正是英伟达所做的。
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. Right. And I mean, the Nvidia story, you know, which is. That's the challenge for the people who are building A6 now. It looks like a juicy market. But remember, this juicy market has evolved from a chip called the GPU. I just described an AI factory. 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 the data center.
这就是TPUs所做的事情。当时只有我俩。但你最好希望这个行业变得非常大。你正在创造一个行业。没错。我是说，Nvidia的故事就是这个。对于现在正在制造A6的人来说，这是一个挑战。看起来是一个诱人的市场。但要记住，这个诱人的市场是从一种叫做GPU的芯片发展而来的。我刚才描述了一个AI工厂。你们刚刚看到我宣布了一种叫做CPX的新芯片，用于上下文处理和扩散视频生成，这是一项非常专业的工作，但在数据中心内是一项重要的工作。
I just pre-looted 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 know, 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 the Nvidia's. Our viewpoint is now not GPU. Our viewpoint is looking at the entire AI infrastructure and what is a take for these incredible companies to get all of their workload through it, which is diverse and changing.
我刚刚提前准备了一些可能是用于AI数据处理的处理器，因为你知道吗？AI需要长期记忆和短期记忆。KV缓存处理非常密集。AI的记忆能力是个大问题。你肯定希望你的AI有良好的记忆能力，而处理系统中的所有KV缓存也是非常复杂的事情。也许它需要一个专门的处理器，也许还有其他需求。你可以看到像Nvidia这样的公司。我们的关注点现在不是仅仅在GPU上，而是看整个AI基础设施，以及这些了不起的公司如何通过它处理所有多样且变化的工作负载。
Look at the transformer. The transformer architecture is changing incredibly. If not for the fact that KUDA 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 KUDA helps you do all that because it's so programmable? And so the way to think about our business now is you look at when all of these ASIC companies or ASIC projects start 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.
观察变压器。变压器的结构正在发生巨大变化。如果不是因为KUDA操作和迭代都很简单，他们如何能够进行大量的实验，以决定使用哪种变压器版本和注意力算法？你如何解构KUDA在这些方面的帮助，这主要是因为它的可编程性极强？因此，现在我们应该这样来看待我们的业务：三、四、五年前，当所有这些ASIC公司或项目刚刚起步时，我得说这个行业非常简单和迷人。当时涉及到GPU，对吧？但现在，它已变得庞大而复杂，并且在未来两年内，它将会变得更加巨大。
The scale is going to be so large. And so I think that the battle of getting into a very large market as a nascent player, it's just hard, you know, as you guys know. Even for the customers who perhaps are successful with ASICs, isn't there an optimal balance in their compute fleet? I think investors are very much binary creatures. They just want to 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 pre-fill, for video generation, maybe a decode, you know, a platform.
规模将会非常大。所以，我认为作为初创玩家进入一个非常大的市场是相当困难的，这一点你们也知道。即便对于那些在使用ASICs方面成功的客户，他们的计算设备配置中难道不存在一个最佳平衡吗？我觉得投资者通常非常简单直接，他们只想要明确的答案——要么是，要么不是。然而，即使你能让ASIC运作，难道不会有一个最佳平衡吗？因为你可能会考虑购买英伟达的平台，比如CPX将用于预填充、视频生成，或者是解码等平台。
A video transmitter. Exactly. Yeah. So there will be like many different chips or parts to add to the Nvidia ecosystem, accelerated compute fleet, right? As new workloads are, you know, are born. That's right. And you know, 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. That's right. I said it another way. Google is a big GPU customer. Google is a big GPU customer. If you look at, and Google is a very special case, I mean, we just have to, you know, show respect where respect is for you to really deserve. I mean, TPU is on TPU 7. Yes. Right.
一个视频传输器。没错。是的。这样一来，就会有许多不同的芯片或部件可以加入到Nvidia生态系统中的加速计算阵列，对吧？随着新的工作负载的产生，就是这样。而且你知道，现在尝试设计新芯片的人其实并没有预见到一年后的发展，他们只是努力让芯片能够正常工作。没错。换句话说，谷歌是一个大型GPU客户。谷歌是一个非常特别的例子，我的意思是，我们必须给予应有的尊重。谷歌的TPU已经发展到第七代了。是的，没错。
And so, and, and it's a challenge for them as well, right? And so the work that they do is incredibly hard. So I think the first thing to let me do it, you know, remember, there are three categories of chips. There's the category chips that are architectural. X86 CPUs, ARM CPUs, and Nvidia GPUs, architectural. And it has an ecosystem above. And, and the architecture allows has rich IP and rich ecosystem, very complicated technology. It's built by the owners like us. Okay. There's A6. I worked for the original company, LSI logic, who invented the idea of A6. As you know, LSI logic is not here anymore.
翻译成中文易读版：
这是对他们的一个挑战，对吧？他们的工作也非常困难。因此，我认为首先要做的是记住有三类芯片。第一类是架构芯片，比如X86 CPU、ARM CPU和Nvidia GPU，这是架构类芯片。这类芯片有一个完整的生态系统，架构本身拥有丰富的知识产权和复杂的技术，通常由像我们这样的公司自行开发。
还有一类是ASIC芯片。我曾为最初发明ASIC理念的公司LSI Logic工作过。不过，你也知道，LSI Logic现在已经不复存在了。
And the reason for that is because A6 is really fantastic when the market size is not very large. It's easy to have somebody be a contractor to help you put the packaging of all that stuff 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 A6, there's a new way of doing things called COT, customer on tooling. And who would, who would do something like that? Apple's A6, Apple's smartphone chip, the volume is so large, they would never go pay somebody else 50, 60% gross margin to be an A6. They do customer on tooling.
这段话的意思是，A6芯片在市场规模不大的情况下非常出色。你可以很容易地找人做承包商来帮助你整合包装，并代你进行制造。而他们会向你收取50%到60%的利润率。但当市场对A6芯片的需求变大时，就有一种新的操作方式，叫做COT（客户自有工艺）。谁会用这种方式呢？就比如苹果的A6芯片，苹果的智能手机芯片的生产数量非常大，他们绝不会支付50%到60%的毛利润给别人来制造A6芯片。他们会选择用客户自有工艺来运营。
And so where will TPUs go when they, when it becomes a large business? Customer on tooling. There's no question about it. And so A6, but there's a place for A6. Video trans coders will never be too large. SmartNix will never be too large. And so when, when there's 10, 12, 15 A6 projects going on at an A6 company, I'm not surprised by that. Because they're probably five smartNix and four trans coders. Are they all AI chips? Of course not. And if somebody were to build an embedded and betting processor for a specific recommender system, and that was an A6, of course, you could do that.
那么，当TPU（张量处理单元）成为一个大业务时，未来的发展方向是什么呢？毋庸置疑，将会是为客户提供工具。而对于ASIC（专用集成电路），也有其市场。比如，视频转码器市场不会特别大，智能网卡市场也不会特别大。因此，如果在一家ASIC公司同时有10到15个项目在进行，我对此并不感到惊讶。因为其中可能有5个是智能网卡项目，4个是视频转码器项目。那些全都是AI芯片吗？当然不是。如果有人为一个特定的推荐系统开发一个嵌入式处理器，并且那是一个ASIC，那当然也是可以的。
But would you do that as the fundamental compute engine for AI that's changing all the time? You've got low latency workload. You've got high throughput workload. You have token generation for chat. You have thinking workload. You have a video generation workload. Is there a, now you're talking about the workhorse backbone of your accelerators? That's one of videos all out. Yeah. Again, dumb this down. So I play in chess and checkers. Right. The fact of the matter is, the folks who are starting A6 today, whether it's training them or whether it's some of these other intrinsic accelerators, et cetera, they're building a chip that's a component of a much larger machine. You've built a very sophisticated system platform factory, whatever you want to call it. And now you're opening up a little bit, right?
但是，你会将这样一个不断变化的AI基础计算引擎用于这种用途吗？你有低延迟的工作负载，也有高吞吐量的工作负载。你要为聊天生成文本，还有思考的工作负载，以及视频生成的工作负载。现在你谈论的是你的加速器的主力骨干吗？这是一个有多种任务的视频。
好的，把这个简单化。我在下国际象棋和跳棋。实际上，今天开始使用A6的那些人，无论是训练它们或者其他一些内置的加速器等等，他们正在制造一个大机器的一部分芯片。你已经建立了一个非常复杂的系统平台工厂，或者无论你怎么称呼它。现在你正在稍微开放一点，对吧？
So you mentioned CPS GPU, right? That is, it seems to me that in some ways you're disaggregating the workloads to the best slice of the hardware for that particular domain. And we did. We announced this thing called dynamo, disaggregated AI workload orchestration. And we open sourced it because the future AI factory is disaggregated. Right. And you launched MV Fusion that even said to your competitors, including Intel, which you just invested in. That's right. You know, 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, et cetera. Is that correct?
所以你提到过CPS GPU，对吧？在我看来，这有点像是在将工作负载分配到硬件中最适合该领域的部分。实际上，我们推出了一种叫做Dynamo的技术，进行分解的AI工作负载编排。我们将其开源，因为未来的AI工厂是分解式的。对，而且你们还发布了MV Fusion，甚至对包括英特尔在内的竞争对手表示认可——你们刚刚还投资了英特尔。没错。你们正在建设的工厂是这样运作的，因为没有其他公司愿意独自建设整个工厂。但如果你有一款足够优秀、有吸引力的产品，最终用户会说：“嘿，我们想用这个来代替ARM GPU或你的推理加速器等等，”那么你就可以接入这个工厂。这样理解对吗？
We're delighted to connect you in. Tell us a little bit more. MV link fusion, such a great idea. And we're so happy to partner with Intel on that. It takes, 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, accelerates computing it, and we fuse it together. Right. And we did that with ARM. Right. And there's several others we're going to be doing a weapon. And that that opens up opportunities for both of us. It's a win for both of us. Great, great win. I'll be a large customer of theirs. And they're going to expose us to a much, much larger market opportunity.
我们很高兴能与你联系。请多告诉我们一些信息。MV链接融合是个非常棒的主意，我们非常高兴能与英特尔合作。英特尔生态系统非常庞大，你知道，大多数世界上的企业仍然依赖于英特尔。这个生态系统结合了英伟达的AI生态系统，加速了计算，并将两者融合在一起。我们也通过ARM实现了这种融合。接下来，我们还会在其他领域继续进行这样的合作。这给我们双方都带来了机遇，这是双赢的结果。我将成为他们的大客户，而他们也将为我们打开一个更大市场的机会。
Yeah. This deeply related to this idea is the argument you've made that kind of shocks some people, where you say our competitors building A6, 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, et cetera, the intelligence out is still a better bet than buying a chip, even if it's given to you for free. Because the lamp power in shell is already $15 billion. So we've taken a crack at kind of the math on that.
好的。这与一个观点密切相关，即使有些人还是会觉得惊讶。你提到说，虽然我们的竞争对手正在开发A6芯片，而且他们的芯片在今天已经更便宜了，甚至可以定价为零。但我们的目标是，即使他们的产品免费提供，您仍然会选择购买Nvidia的系统，因为操作该系统的总成本，包括电力、数据中心、土地等，仍然使选择我们的产品更有利可图。即使芯片免费赠送，因为基础设施成本已经达到150亿美元。因此，我们对这一数学问题进行了深入分析。
But walk us through your math, because I think for people who don't spend as much time here, it doesn't compute. How could it possibly be that you were pricing your competitors chips at zero given the expense of your chips, and it still is a better bet? There's two ways to think about it. One way is, let's just think about it from a perspective of revenues. Yes. 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. Yes. So your performance or tokens per watt was twice as high as somebody else's token per watt, because I did deep and extreme co-design.
好的，让我们一步一步来理解你的计算，因为对于那些没有花太多时间在这方面的人来说，这可能不太好理解。你是如何可能在考虑到自己芯片昂贵的情况下，却把竞争对手的芯片定价为零，而且这样做依然更有利可图的呢？这里有两种思考方式。
一种方式是，从收入的角度来考虑。是的，好，大家的功率都是有限的。假设你能额外获得两吉瓦的电力。那么，你希望这两吉瓦的电力能够转化为收入。是吧？所以，如果你的每瓦性能或者说每瓦生成的代币数量是其他人的两倍，因为我进行了深入而极致的协同设计，那么这就更具优势。
And my performance was much higher per unit energy than my customer can produce twice as much revenues from their data center. Who doesn't want twice as much revenues? And if somebody gave them a 15% discount, the difference between our gross margins was called 75 points. And somebody else's gross margins called 50 to 65 points. It's not so much as to make up for the 30 times difference between black, wall and hopper. Let's pretend hopper hoppers in an amazing chip and amazing system. Let's pretend somebody else's asick is hopper. Black walls 30 times.
我的表现比客户的数据中心单位能量的表现要高出许多，客户可以从中获得两倍的收入。谁不想要两倍的收入呢？即使有人给他们提供了15%的折扣， 我们的毛利率差异仍然是75点，而别人的毛利率是50到65点。这并不足以弥补黑墙（Black Wall）和Hopper之间30倍的差距。假设Hopper是一款出色的芯片和系统，假设其他人的ASIC（专用集成电路）和Hopper一样，但黑墙的表现是其30倍。
So you've got to give up 30 x 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 two gigawatts to work with. Your opportunity cost is so insanely high, you would always choose the best per per watt. So I heard this from one of the CFAs at one of the hyperscalers that given the performance improvement, that's coming out of your chips. Again, precisely to that point, tokens per gig and power being the limiting factor, that they had to upgrade to the new cycle.
所以你要放弃这一个千兆瓦中30倍的收入。这实在是太多了，无法接受。所以即使他们免费给你，你也只能用两个千兆瓦。你的机会成本高得惊人，你一定会选择每瓦的最佳性价比。我听一家超大规模公司的一个CFA说过，由于芯片性能的提升，再加上每千兆字节的代币和功率是限制因素，他们不得不升级到新一代产品。
So when you look ahead at Ruben, at Ruben Ultra, at Feynman, does that trajectory continue? We're building what six, seven chips a year now. And you just wanted that system. That's right. And those systems, software is everywhere. And it takes the integration and the optimization across all of those six, seven chips to deliver on the 30 x black wall. Now, imagine I'm doing this every single year. Bam, bam, bam, bam, bam. And so if you build one ASIC in that soup of ASICs, in that soup of chips, and we're optimizing across that, you know, it's a hard problem to solve.
当你展望鲁本、鲁本Ultra和费曼的未来时，这种发展轨迹是否会持续？我们现在每年大约开发六到七款芯片。你只需要那个系统。没错。而这些系统，各处都离不开软件。需要在这六到七款芯片之间进行集成和优化，才能实现30倍的黑墙性能突破。现在，想象一下我每年都在这么做。一个接一个。通过在这众多ASIC中之一进行开发，并对所有芯片进行优化，这确实是一个难题。
This test brings me back to where we started about the competitive mode. We've been covering this in investors for a while. We're investors throughout the ecosystem in competitors of yours, you know, from Google to Broadcom. But when I really just first principles around this, say, are you increasing or decreasing your competitive mode? You move to an annual cadence, your co-developing with the supply chain. The scale is massively bigger than anybody anticipated, which requires scale, both a balance sheet and of development.
这次测试让我回到了我们最初讨论竞争模式的地方。我们在投资者中已经讨论了一段时间。我们是整个生态系统里的投资者，涉及到像谷歌和博通这样的竞争对手。但如果从最基本的原则来看，你们是在增强还是削弱你们的竞争模式？你们转向了年度节奏，与供应链共同开发。这种规模大到超乎大家的预期，需要拥有庞大的资产负债表和开发能力。
Right. The moves you made both through acquisition and organically with things like envy fusion or CPX, which we just talked about. All of those things together cause me to believe that your competitive mode is increasing VISA V, at least in so far as building out the factory or the system. It's at least surprising. But I think it's interesting that you're 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 four and a half trillion dollar company couldn't possibly get any bigger.
好的。通过收购和自然增长，比如你提到的envy fusion或CPX，这些举措让我相信，在某种程度上，你们在打造工厂或系统方面的竞争能力正在增强，至少比得上VISA的水平。这至少让人感到惊讶。但有趣的是，你们的市盈率远低于其他大多数公司。我想，这部分原因与一个庞大公司的增长极限有关——一个市值达四万五千亿美元的公司不太可能再变得更大。
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, you know, we know what CAPEX is doing, et cetera. Is there any conceivable world in your mind where your top line in five years isn't two or three X bigger than it is in 2025? Like what's the probability that it's actually not much higher than it is today, given those advantages? I'll answer this one. Our opportunity as I described it is much larger than the consensus.
但我在一年半前就问过你这个问题。如今，当你在这里时，如果市场上的AI工作负载将增加到原来的10倍或5倍，我们也了解资本支出(CAPEX)等方面的情况。在你看来，有没有可能在五年后，你的营业收入没有达到2025年的两到三倍？考虑到这些优势，现在的收入实际比2025年高出不多的概率有多大？对此，我来回答一下。正如我所描述的，我们的机会远比大众的共识要大得多。
I'll say it here. I think in video will likely be the first 10 trillion dollar company. And I would I've been here long enough. It wasn't that long ago, just a decade ago, as you well remember, the people said there could never be a trillion dollar company. Now we have 10. Right. And today, people's bigger. Right. And today, this is this is the back to the exponentials around GDP and the growth rate. The world is bigger. And people misunderstand what we do. They remember we're a chip company.
让我来这里说一下。我认为 in video 很可能会成为首个市值达到 10 万亿美元的公司。我在这行业待了足够久，你可能还记得，就在十年前，人们还说不可能会有万亿美元市值的公司。现在，我们已经拥有10家这样的公司。而如今，市场更大了。这一切都与GDP和增长率的指数增长密切相关。世界在变大，而人们误解了我们所做的事情。大家记得我们是一家芯片公司。
And we are we build chips. Boy, do we build chips and build the most amazing chips in the world. But in video, it's really an AI infrastructure company. You know, we are your AI infrastructure partner. And our partnership with OpenAI is a perfect demonstration of that. Yeah. That we are their AI infrastructure partner. And we work with people in a lot of different ways. You know, you you would we don't require anybody to buy everything from us.
我们是制造芯片的公司，而且我们确实制造芯片，制造世界上最棒的芯片。但在视频领域，我们实际上是一家人工智能基础设施公司。我们是你们的人工智能基础设施合作伙伴。我们与OpenAI的合作正是对此最好的证明。是的，我们是他们的人工智能基础设施合作伙伴。我们以多种方式与人合作，而且我们并不要求所有人都必须从我们这里购买所有产品。
We don't 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 we have customers just buying only our CPU. Yeah. Just buy our GPUs and buy somebody else's CPUs and somebody else's networking. You know, we're kind of okay. Hey, selling any way you like to buy. You know, my only request is just buy a little something from us.
我们并不要求他们购买整套设备。他们可以购买一个芯片、一个组件，或者我们的网络产品。有些客户只买我们的CPU。他们也可以只买我们的GPU，然后选择其他品牌的CPU和网络设备。我们对此没有意见。无论您想怎么购买都可以。我唯一的请求是，只要买我们的一点点产品就好。
You know, you said, you know, this isn't just about better models. We also have to build. We have to we have to have world class builders. And you said, you know, the most world class builder, maybe that we have in the country is Elon Musk. And we talked about Colossus one. And what he, you know, what he was doing there, standing up a couple hundred thousand, you know, at the time, H 100s, H 200s and a coherent cluster.
你说过，这不仅仅是关于更好的模型。我们还需要建设。我们必须拥有世界级的建设者。你提到，也许我们国家最顶级的建设者就是埃隆·马斯克。我们还谈到了Colossus One，以及他在那里所做的事情，比如当时组建了几百台H 100和H 200的集群。
Now he's working on Colossus too, you know, which may be 500,000 GBs, millions of H 100 equivalents in a coherent class. I would not be surprised if he gets to a gigawatt before anybody else. Right. In one. Yes, or say a little bit about that. The advantage of being, you know, the builder who, you know, isn't just building the software and the models, but understands what it takes to build those clusters.
现在他也在研究Colossus，你知道的，可能达到50万GB，相当于数百万个H100同等体积的集成系统。我不会感到惊讶，如果他比其他人更快达到千兆瓦。没错。一起来谈谈这个吧。作为一名建设者的优势在于，不仅仅是在构建软件和模型，还懂得如何打造这些集群所需的一切。
Well, you know, these AI supercomputers are complicated things. The technology is complicated, procuring it is complicated because of financing issues, securing the lamp power and shell, powering it is complicated, building it all, bringing it all up. I mean, this is unquestionably 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 are, you know, resides in one head, including the financing.
这些人工智能超级计算机确实是非常复杂的东西。技术本身就很复杂，由于融资问题，采购也很复杂，还有要确保足够的电力和外壳来支持它们，运行它们也不简单，建造和启动整个系统都很繁琐。可以说，这是人类有史以来面临的最复杂的系统难题之一。所以，埃隆有一个巨大优势，就是他能在脑海中整合这些系统，处理它们之间的相互依赖关系，包括融资问题，所有这些都在他一个人头脑中运转。
And so he's a big GPT. He's a big supercomputer himself. He's the ultimate GPU. Yeah. And so he has a great advantage there. And he has great sense of urgency. He has a real desire to build it. And so when will comes together with skill, you know, unbelievable things can happen. Yeah. Yeah. Quite unique.
所以他就像一个大型的GPT。他本身就像一台超级计算机。他是终极的GPU。是的。在这方面，他有很大的优势。他有很强的紧迫感，真的很想将其实现。当意愿与技能结合时，不可思议的事情就能发生。是的，是的，相当独特。
Something you've been so involved in is I'm going to talk about sovereign AI. I want to talk about China and the global AI race that's going on, you know. And when I look back at you 30 years ago, you couldn't have imagined you were going to be hanging out in palaces with the mirrors 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, you know, national security. So when you look at that, first just contextualize for me, like it's hard to believe that you would be in those places. If sovereigns didn't view this at least as existential, as important as maybe we did nuclear in the 1940s, right?
你一直参与的事情让我想谈谈主权人工智能。我想讨论正在进行的中国与全球人工智能竞赛。当我回想30年前的你，真难以想象本周你会在宫殿里与国王一起，并且经常出入白宫。总统曾表示，你和英伟达对美国的国家安全至关重要。所以，看到这些时，请帮我先提供一些背景信息——难以置信的是，如果各国没有把这一领域视为事关生死的关键问题，就像我们在1940年代对待核武器一样，你怎么能出现在这些地方呢？
If 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 are, think is existential to their future economic and national security. Would you agree with that? Nobody needs atomic bombs. Everybody needs AI. Well said.
如果我们今天没有一个由政府资助的“曼哈顿计划”，那么至少有类似的项目是由英伟达、OpenAI、Meta和谷歌这样的公司资助的。如今，有些公司的规模和国家相当，感谢美国，对吧？这些公司资助的项目，被各国总统和国王视为对他们未来经济和国家安全至关重要的。你同意吗？没人需要原子弹，但每个人都需要人工智能。说得好。
Okay. Here, here. Yeah. And so that's a very, very large difference. AI, as you know, it's modern software. I just, that's where I started from general purpose computing to accelerate computing from human-ridden code line of time to AI-ridden code. That foundation can't be forgotten. We've reinvented computing. There's not a new species on earth, which is reinvented computing, and everybody needs computing. It needs to be democratized.
好的，好的，是的。这是一个非常非常大的差异。正如你所知，人工智能是现代软件。我就是从通用计算开始，发展到加速计算，从人类编写的代码到人工智能生成的代码。这一基础不能被遗忘。我们已经重新定义了计算。地球上没有其他物种重新定义过计算，而每个人都需要计算。这需要被普及推广。
Which is the reason why everybody, all of these, all of the 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? You know, I used to use computers yesterday. I'm pretty good with clubs and fire tomorrow. You know? And so everybody needs to move into computing. It's just, it's just being modernized. That's all.
这就是为什么所有国家都意识到他们必须进入人工智能领域，因为每个人都需要保持在计算机技术的前沿。没有人会说，“你知道吗？我昨天还在用计算机，但是明天我就会用棍子和火了。”所以，每个人都需要向计算机技术迈进，这不过是时代在进步罢了。
Okay. Number one, it is the case that, that in order to participate in AI, you have to encode within AI your, your history, your culture, your values. And, and of course, AI is getting smarter, smarter, so that even the core AI is able to learn these things fairly quickly. You don't have to start from the ground, you know, from ground zero. And so I think that, that every country needs to have some sovereign capability.
好的。首先，为了参与人工智能，你必须在人工智能中融入你的历史、文化和价值观。当然，人工智能变得越来越聪明，以至于即使是核心的人工智能也能相当快速地学习这些内容。你不需要从头开始。所以，我认为每个国家都需要具备一些自主能力。
I recommend that they all use open AI, they all use Gemini, they all use, you know, these open models use GROC, and I think they, I recommend they all do that. I recommend they all use Anthropic. 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, national security models. There's a whole bunch of intelligence they have to go cultivate themselves. So they ought to have sovereign capability.
我建议他们都使用Open AI、Gemini，还有其他这些开放模型，比如GROC。我建议他们这么做。我还建议他们使用Anthropic。但同时，他们也应该投入资源学习如何构建人工智能。这是因为他们不仅需要学习构建语言模型，还需要为工业模型、制造模型、国家安全和其他用途构建AI。他们需要自行培养大量的智能能力，因此应该具备自主的能力。
Every country should develop it. And is that what you see? Is that what you're hearing around the way? They all realize it. They all realize it. And they, they all are going to be customers of open AI andthropic and GROC and Gemini. But they all really need to also build their own infrastructure. And this is, this is the big idea that, that what Envitya does is we're building infrastructure, just as every country needs energy infrastructure.
每个国家都应该发展它。你看到这样的趋势了吗？你周围听到这样的声音了吗？他们都意识到了这一点。他们都意识到了这一点。他们都会成为OpenAI、Anthropic、GROC和Gemini的客户。但他们也确实需要建立自己的基础设施。这就是大概念，就像每个国家都需要能源基础设施一样，Envitya正在做的事情就是在建立基础设施。
The communications and internet infrastructure. Now every single country needs AI infrastructure. So you, let's start with rest of the world. You know, our, our good friend David Sacks, the AI's are, you know, we're doing a heck of a job. We are in so lucky to have David and Shreeram in Washington, DZ doing, you know, and David, yeah, doing AI in the AI's are this, what a, what a smart move by President Trump to put them in the White House.
通信和互联网基础设施。现在每个国家都需要人工智能基础设施。那么，让我们先从世界其他地方开始。我们的好朋友大卫·萨克斯正在从事人工智能方面的工作，我们很幸运能在华盛顿特区有大卫和史瑞拉姆参与。他们在人工智能领域的工作确实非常出色。特朗普总统让他们进驻白宫真是一个聪明的决定。
Because during this pivotal time, the technology is complicated. Shreeram is the only person in Washington, DZ that I think knows Kudah. Yeah. And, and which is strange anyways, but, 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 right, that we have somebody who is clear minded, dedicating the time to understand the technology, and thoughtful to help us through that.
在这个关键时刻，技术变得复杂。Shreeram 是我认为在华盛顿特区唯一知道 Kudah 的人。这本身就挺奇怪的，但让我欣慰的是，在技术和政策都如此复杂且对国家未来影响重大的时候，有一个思想清晰的人愿意投入时间去理解这些技术，并用心帮助我们度过这一切。
And it would seem to me, you know, going back to the Manhattan Project analogy, you know, right, that you have a president who understands, you know, how existential this is. You have governors like Greg Abbott and Texas who want to remove regulations to accelerate because they understand how important it is. You have secretaries right at energy and Doug Bergram at Interior and Latinacic commerce, who also understand how important this is, how pro energy they are. Could you imagine? Could you imagine the alternative? If we had an administration right now who is not pro energy and want energy to grow in our nation, so that we could have AI, I find it. I find it. I just can't even think about it. 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. Like, that's the primitive to AI. But now you have people when we go to build it, everybody says, oh, it's a glut. Right. Like, it seems to me that this is something that the government, it is in their interest.
在我看来，回到曼哈顿计划的比喻，现任总统充分理解这一问题的生死攸关性。像得克萨斯州州长格雷格·阿博特这样的领导者，想要通过取消监管来加速发展，因为他们明白这有多重要。在能源部和内政部的秘书以及商务部的官员也都理解这一点，他们也都支持能源发展。你可以想象吗？如果我们现在的政府不支持能源发展，不希望能源在我们国家中发展壮大，以便我们能够拥有AI技术，那将会是怎样的情形？我觉得很讽刺的是，就在几年前，我们还在说中国正在建造100座核反应堆，比我们领先很多。那时，这被视为通向AI的前提。但现在当我们准备建设时，人人却都说，哦，太多了。这似乎是政府应该关注并支持的事情，因为这符合他们的利益。
And we have industry and government working together in a way that I haven't seen a long time. You've been around a long time. You're very close with President Trump at this stage. Help us understand like, what is the nature of industry government relationships? We saw that dinner last week with all the CEOs, you know, you spend a lot of time. Is it unique? Have you seen anything like this in your career over the last 30 years? It was it was hard to go to DC in the past, as you know, getting an appointment is almost impossible. Right. President Trump has an open door to leaders who wants 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 could grow economically, we will be secure. I've never met somebody who is secure, who's poor.
我们看到，如今工业界和政府之间的合作方式是我很久以来未曾见过的。你在这个领域打拼了很长时间，与特朗普总统的关系非常密切。请帮助我们理解一下，行业和政府的关系性质是怎样的？上周我们看到与所有CEO共进晚餐的场景，你花了很多时间。这样的合作是否独特？在过去30年的职业生涯中，你见过类似的情况吗？过去，要去华盛顿的确是很困难的，预约几乎不可能。特朗普总统对愿意来了解未来的领导者持开放态度。这届政府从根本上相信增长。特朗普总统希望美国能够增长。如果我们能够在经济上增长，我们在军事上就会强大。如果我们能够在经济上增长，我们就会安全。我从没见过一个穷人是安全的。
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 technology industry to run. He wants everybody in the world to be built on American technology. These are sensible, logical things. You know, the opposite is strange to me. I give 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. He understands that our technology industry is our national treasure.
作为一个国家，富裕是国家安全的重要组成部分。他明白这一点。他还希望美国在人工智能竞赛中获胜。这将是一场非常漫长的竞赛，而他也意识到这是一个关键时刻。他希望科技产业能够快速发展，希望世界上的每个人都建立在美国的技术基础上。这些都是合情合理的想法。你知道，相反的想法对我来说很奇怪。我将所有事情都反过来想：我们不希望我们的国家发展，因为我们知道发展需要能源，所以我们不要能源。实际上，我们也不希望我们的科技产业领先。他明白我们的科技产业是我们的国家瑰宝。
Correct. 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? Right. So let's talk about, you know, the internet, Google spread around the world. We had a democratic value 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's axe has been crystal clear of 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, et cetera. We know a year and a half ago. That wasn't happening. It was a concept that was called small yard tall fence or something like that. Small yard tall fence.
当然。这项技术如今已如同玉米和钢铁等过去的产品一样，成为了基础的贸易机会。它是贸易的重要组成部分。为什么不希望美国的技术受到全世界的垂青，从而用于贸易呢？我们来谈谈互联网，比如谷歌在全球的传播。我们的民主价值观通过搜索在全球传播，而谷歌并不需要去华盛顿申请许可。这些事自然而然地发生了。我们将我们的技术扩散到全世界。David 强调清楚表明需要加速出口许可证，以便美国的人工智能技术在全球占据领先地位。我们讨论的包括芯片、模型、数据中心等等。我们知道在一年半以前，这些事情并没有发生。这是一个叫做“小院高墙”之类的概念。
Yeah. And the irony of it was it was described in such a way. And it was recommended in policy in such a way. It was a small yard tall fence around America. That was the strange part. I think President Trump's got to write that we want to maximize exports. We want to maximize American influence around the world. We're supposed to maximize those things. And do you see those licenses coming? Are you seeing the acceleration in Washington? I know it's being set at the top. But are you seeing it flow down through government that's accelerating us around the world? Secretary Ludnick was all over it. Great.
是的，讽刺之处在于它被描述得那样，又在政策中被推荐得那样，就像是在美国周围竖起了一道矮矮的围栏。这是件奇怪的事。我认为特朗普总统说得对，我们应该最大化出口，努力扩大美国在全球的影响力。这本来就是我们的目标。你有没有看到相关许可正在发放？你有没有注意到华盛顿方面的加速进程？我知道最高层已经在推动这一点，但你认为这些激励措施正迅速在政府内部落实，以推动我们在全球的发展吗？Ludnick部长对此尤为关注。这太好了。
Yeah. 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. We've been there for 30 years. Been there for 30 years. What most people don't realize is up until a couple of years ago, you had dominant market share within China in terms of 95% market share. 95% market share in the most important thing arguably. And you have said that our biggest own 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 is allow Huawei to accelerate on the back of monopoly profits within China.
好的，现在来谈谈中国。你知道，大多数人可能没有意识到的是，我认为你对中国的了解可以媲美美国的任何领导者。我们已经在中国有30年的经验。直到几年前，你在中国的市场份额一直是占主导地位的，达到了95%。在某种程度上，这是最重要的市场份额。而你曾经表示，我们国家在试图阻止中国发展的幌子下所犯的最大错误就是单方面解除武装。我们逼迫英伟达退出中国市场，这反而让华为在中国凭借垄断利润加速发展。
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, you know, monopoly markets is coming true. The president said, you know, after after kind of the ban on H20s, now we have a situation where you can sell, you know, 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 kind of 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?
我今天早上刚看到，华为、阿里巴巴和其他公司宣布将开始在全球建设数据中心。华为有一个三年计划，利用在全球最大的人工智能市场中获得的垄断利润来超越英伟达。这看起来印证了你之前所说的，把垄断市场交给中国是一个巨大的错误。总统表示，在某种程度上禁止H20后，我们现在有了可以向中国出售芯片的局面，但需缴纳15%的出口税。然而，现在情况似乎是，中国可能因美国的言论感到不满，表示不允许英伟达在中国出售芯片。那目前英伟达与中国之间的状况如何？你能否重申一下你觉得我们作为一个国家应该采取哪些措施以确保我们在全球人工智能竞赛中占据有利地位？
We have a competitive relationship with China. We should acknowledge that China rightfully should want their companies to do well. Which I don't, I don't for a second begrudge him for that. They should do well. They should, 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. 996 as you know, this is a very producing the most AI engineers in the world. The audience knows nine and more into nine at night, six days a week. That is their culture.
我们与中国有一种竞争关系。我们应该承认，中国自然会希望他们的公司表现出色。我对此毫无怨言。他们的公司应该表现出色，他们可以给予公司尽可能多的支持，这是他们的权利。别忘了，中国拥有世界上最优秀的企业家，因为他们来自全球顶尖的理工科院校。他们是全球最有拼劲的，"996"工作制你应该知道，其意思是早9点到晚9点，每周工作6天。这就是他们的文化。
Okay, we're up against a formidable, innovative, hungry, fast-moving, under-regulated. Okay, people don't realize this. They are very lightly regulated. Let's regulate it. Ironically, then we are in a capitalist system. That's right. People think that they're centrally governed. But remember, the genius of China was distributed economic systems. And so all of these 33 provinces and all the mayor economy has driven enormous amount of internal competition, internal economic vibrancy, which of course has some of its side effects. But this is a vibrant entrepreneurial, high-tech, modern industry.
好的，我们面临的是一个强大、有创新意识、充满渴望、行动迅速且监管松散的对手。大家可能没意识到这一点。他们受到的监管非常少。我们需要进行监管。有趣的是，我们身处资本主义体系。没错，很多人以为他们由中央政府管控。但要记住，中国的聪明之处在于其分布式经济系统。这33个省以及各市的经济推动了大量的内部竞争和经济活力，当然这也有一些副作用。不过，这是一个充满活力的创业环境，拥有高科技和现代化的工业。
And two, one, some of the things that I heard they could never build AI chips. That just sounded insane, too. That China can't manufacture. China can't manufacture. If there's one thing they could do is manufacture. On three, their years behind us is a two years, three years. Come on, they're nanoseconds behind us. Nanoseconds behind us. Yeah, they're nanoseconds behind us. And so we've got to go compete. We've got to go compete.
可以分成以下几句来翻译：
而第二点，有人说他们永远无法制造AI芯片。这听起来简直不可思议。说中国不能制造，中国不能制造。要说他们擅长什么，那就是制造能力。第三点，他们与我们的差距是几年，两年还是三年？拜托，他们只落后我们几个纳秒，几个纳秒。是的，他们确实只落后几个纳秒。因此，我们必须积极竞争。我们必须积极竞争。
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, that I believe they believe this, is 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. And I believe that they, I hope, I believe in I hope, that would return to that in our context, answering your question, what do I see in the future? I do hope.
因此，问题就变成了，什么对中国的最大利益是？当然，这是拥有一个充满活力的产业。他们也公开表示，并且我相信他们真心这样想，他们希望中国成为一个开放的市场。他们希望吸引外国投资，希望公司来到中国并在市场中竞争。在我们所讨论的背景下，回答你的问题，我对未来的看法是，我确实希望中国能回到这样的状态。
Because they say it, their leaders say it, and I take it a 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, is a fairly sensible outcome.
因为他们这么说了，他们的领导人也这么说了，我就照字面意思理解。我相信这点，因为从我的角度来看，这对中国来说是合理的。对中国最有利的事情就是让外国公司在中国投资并在中国竞争。同时，他们也希望自己能有活力的竞争。他们也希望走出中国，在全世界范围内参与竞争。我认为这是一个相当合理的结果。
And what we need to do as a country is to enable our technology industry, which today is that 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. It is our single best industry. 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 be built on top of American technology so that we can maximize our economic success.
作为一个国家，我们需要推动我们的科技产业发展。我很荣幸能在这个被认为是国家瑰宝的行业工作。我们必须承认，这确实是我们的国宝，也是一项最重要的产业。我们为什么不让这个行业去参与全球竞争，让其技能够在全球范围内扩展呢？通过这样做，我们可以让整个世界建立在美国技术的基础之上，从而最大化我们的经济成功。
Magnum maximized our geopolitical influence, maximized this technology industry doing such a vibrant time, such a pivotal time to allow it to thrive. The skeptics 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 the skeptics. Can I just address the skeptics just because I want America ecosystem and economy to grow. It doesn't make me wrong. Right. Right.
Magnum极大地提升了我们的地缘政治影响力，并在这个关键的活力时代最大化了这个科技行业的发展，让其得以蓬勃发展。怀疑者说，Jensen只是想卖出更多芯片，如果能卖给中国，那很好，他就卖给中国。他不在乎这对美国意味着什么。这就是那些怀疑者的看法。对于这些怀疑者，我想说，仅仅因为我希望美国的生态系统和经济能发展壮大，这并不代表我错了，对吧？对吧。
Okay. So first of all, everything that has been said so far that has been made up so far about China has proven to be wrong. The facts are just 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. 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 ignores to our advantage, the probability of us winning the global AI race actually goes up if you are competing in China. That's right. Because it allows us to tap in to half of the world's AI engineers, keeping them in this ecosystem. And let's be clear what the companies we're talking about here, by dance, allie, Baba, etc. These are companies that are largely owned by American investors.
好的，首先，到目前为止，关于中国的一切言论和猜测都被证明是错误的。事实就是如此，仅仅因为我们希望美国胜出，希望这个行业发展，并不意味着我错了。而且，我认为认识你的人，特别是现在的总统和我，都知道你非常关心这个国家，非常希望美国在全球人工智能竞赛中获胜。你只是恰巧相信，而且我认为你在这方面拥有相当多甚至更多的经验，无视这一点对我们没有好处，实际上如果你在中国竞争，我们赢得全球人工智能竞赛的可能性会提高。这是对的，因为这让我们可以利用世界上一半的AI工程师，把他们留在这个生态系统中。我们要明确一点，我们所讨论的公司，比如字节跳动、阿里巴巴等，大多数都是由美国投资者控股的。
Yeah. Right. Right. Like these are global companies that are building recommender engines. And by the way, extraordinary technologies. Incredible companies. And so I think and I'm hopeful that the argument that you're making vis-a-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. But 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. 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. H-20 is really quite spectacular still, then.
好的。这些是正在构建推荐引擎的全球公司。顺便说一句，它们的技术非常出色，真的是令人赞叹的公司。所以，我觉得并且希望你关于中国的论点是正确的，虽然比起在世界其他地方传播的论点，它要难得多。我理解这一点。这就是为什么我认为当总统说“我不知道，这就像抛硬币，也许Jensen是对的，也许其他人是对的。但是如果Jensen愿意将15%投入美国财政部作为对冲，那么我就支持。”不过，在这之后我真的感到失望。我想如果中国人觉得他们被占了便宜，比如我们向他们出售的是十年前的芯片，那么我理解他们的反应。H-20仍然相当壮观。
Yeah. Of course, it's not as good as but well. And I get that. Yeah. Look, I'm patient. And I believe that they're wise or they're thinking through their situation. They have larger agendas to deal with. Relatively, you know, vis-a-vis 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 is in the best interest of China that Nvidia is able to serve that market and compete in that market. I fundamentally believe it's the best interest of China. It is of course fantastic interest in the fantastic interest of the United States. It is fundamental. But those two truths can coexist. It is possible for both to be true. And I believe it is both true.
是的，当然，这并不是最好，但我明白。我很有耐心，并且相信他们是明智的，或正在仔细考虑他们的处境，他们有更大的议程需要处理，特别是在与美国的关系上。有很多讨论正在进行中。但我想回到基础事实，我相信英伟达能够服务中国市场并在该市场竞争是符合中国的最佳利益的。我坚信这符合中国的根本利益。当然，这对美国来说也是极有利的。这是基本的。但是这两个事实是可以共存的。两者都可能是正确的，我相信这两者都是正确的。
And so I, I, I, I'm rather, you know, even though I tell all of our investors that our guidance includes no China. 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 we, you know, we've got all of that. It's 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 is has their head deep in the sand. And so this is set 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. And I think it's in the best interest of both countries that we are there.
所以，我，我，我尽管告诉所有投资者我们的预期中不包括中国。但我还是很欣赏所有投资者把我们的预期中不包括中国考虑进去。我们在其他方面有很多增长机会，这是真的。但这并不意味着中国对我们不重要，其实中国对我们非常重要。任何认为中国市场不重要的人都是在自欺欺人。因为中国市场是世界上最重要的市场之一，那里有聪明的人做着聪明的事情。我们希望能参与其中。我认为我们在中国开展业务符合两国的最佳利益。
And so I think when I take a step back, I am confident that ultimately the wisdom will prevail. Yes. Yes. I've always been confident that wisdom prevails. I've always been confident that that truth prevails. And it's taken me this far. And I believe 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. I'm not very political, but very topical is the administration's decision to charge 100,000 per H1B visa. 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.
所以我觉得，当我退一步思考时，我相信最终智慧会占上风。是的，是的。我一直相信智慧会占上风。我一直相信真相会获胜。这种信念让我走到今天。我现在依然相信这是根本的真理。因此，这些问题会得到解决，我们将有机会竞争中国市场。我不是很关注政治，但现在有个很热门的话题，就是政府决定对每个H1B签证收取10万美元的费用。你和总统有过很多交流，还称他为我们在人工智能领域的秘密武器。我也知道你希望将最优秀的人才招募到我们的国家。
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 it's a little different for large companies or small companies. How do you think about it? I'm going to start with it's a great start. What on you said it's a great start. It's a great start. I'm just going to start there. And the reason for that is this. That implies I hope it's not the end. But I think it's a great start. I just hope it's not the end. Here's what I fundamentally believe. America has won a singular brand reputation that no country in the world has and no country in the world is in the position or in the horizon to be able to say come to America and realize the American dream.
你怎么看待将H1B签证费用提高到每份10万美元的决定？这是否让招募人才变得更容易或者更困难？对于大公司和小公司来说情况会有点不同。你怎么看？我会从"这是一个好的开始"这个想法出发。你说这是一个好的开始，我认可这一点。而我认为这是因为，这意味着我希望这不是终点，而是一个起点。我认为这对美国是很好的一步。美国拥有独特的品牌声誉，这是世界上其他国家无法匹敌的，没有哪个国家能够提供像美国一样的机会，让人们追求和实现"美国梦"。
What country has the word dream behind it? 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 you know bus tables, wash dishes, clean toilets. And here I am. This is the American dream. President Trump knows that. We want legal immigrants. 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.
哪个国家的品牌中有“梦想”这个词？那就是美国。我们完全独一无二。你正在与一个代表“美国梦”的人对话。我的父母没有钱，把我们送到这边。我们从一无所有开始。你们知道，我刷过盘子，洗过碗，打扫过厕所。现在的我，就是“美国梦”的体现。特朗普总统明白这一点。我们欢迎合法移民，合法移民和非法移民是有区别的。但认为这是一个对所有人都完全开放的国家，这种想法是不合理的。
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? So the idea that he that that we put a $1,000 price tag on H-1, B probably set it sets the bar a little too high. But as a first bar, it at least eliminates illegal immigration. And that's a good start. How does it eliminate illegal immigration? Well, at least it eliminates a B-7, B-H-1, B. At least.
现在的问题是，我们如何从想要根本上保护美国梦的理念，转变为应对大规模非法移民的措施。我们如何找到一个合乎逻辑且务实的解决方案？有一种观点认为，给H-1B签证定价1000美元可能设定的标准有点高，但作为一个起步标准，至少可以减少非法移民。这是一个好的开端。那它怎么消除非法移民呢？至少可以减少B-7、B-H-1、B类的非法移民。至于是否完全能消除非法移民，至少在这方面有所成效。
And that's a good start. And at least we can have a conversation. So one of the things that we know about President Trump, he's a good listener. He actually listens to me. He listens to me. 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.
这已经是一个很好的开始了。至少我们能够展开对话。我们知道特朗普总统是一个很好的倾听者。他确实听我说话，尽管他不一定需要这样做。而且他也倾听很多其他人的意见，整合了大量的信息。显然，这是一个非常复杂的问题。因此，我认为这是一个不错的开始，一个好的开端。
But I'm not confused that that anyone in the administration, anyone in the White House is confused. That that legal immigration, immigration is the foundation of the American dream. And it's the ultimate brand that we want to protect. And that's the future we want to protect. And I would also say it seems to me that certainly SACs and other people in the administration know that we have to recruit the world's best and brightest.
我并不认为政府内或白宫的任何人对此感到困惑。合法移民是美国梦的基石，也是我们要保护的终极品牌。这就是我们要保护的未来。我还想说，我认为，SAC和政府内的其他人确实知道，我们需要招募世界上最优秀的人才。
We should not sacrifice the greatness of the brand. Charging $100,000 or let's say you know it got lower to 50 or whatever the case is. It does seem like it it it tilts the plain field in favor of big companies who can effectively sponsor all these people. 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. It also has an unintended consequence. It might accelerate investment outside the United States.
我们不应该牺牲品牌的伟大。收取10万美元或即使降到5万美元，不管怎样，似乎都让大公司占了优势，因为他们可以有效地资助所有这些人。而对于初创公司的生态系统来说，这更具挑战性，因为人员成本已经很高，现在还要再支付这笔费用。这还会带来一个意想不到的后果，就是可能促使资金流向美国以外的地方进行投资。
And so there are unintended consequences. But like I said, start somewhere, move towards the right answer. Right. You know, oftentimes 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. It's important to me.
因此，会有一些意想不到的后果。但就像我说的，要从某个地方开始，朝着正确的答案前进。很多时候，人们希望直接从错误的答案或不理想的情况跳到完美的答案，但完美的答案很难找到。只需从某个点开始。这是创业者的方式，对我来说很重要。
And the president talked about before when he was running for office, he wanted to staple a green card to the, you know, to the diplomas of these STEM students. You know, smart people coming to the United States from from China AI researchers studying at Stanford. Yeah. Like we want to keep them here. We want to get, you know, and by the way, if their families can't get here, they're going to leave after a few years.
总统在竞选期间曾谈到过，他想给这些STEM专业的毕业生的学位证书“附上”绿卡。意思是说，那些从中国来美国的聪明人才，比如那些在斯坦福大学学习的人工智能研究人员，我们希望他们能留在这里。但是，如果他们的家人无法来到美国，他们可能几年后就会离开。
So you might even want to make it easier for their families to come here. And in others, are you confident that we have a strategic plan in this administration? You know, this is a start, but your conversation, say, give you confidence that we have a broader strategic plan to make sure we're recruiting the best in the brightest. I don't know that I have an answer for that. Okay.
所以你可能会希望让他们的家人更容易来到这里。另外，你是否有信心我们在这个政府中有一个战略计划？你知道，这只是个开始，但你的对话是否让你有信心我们有一个更广泛的战略计划，以确保我们能够招募到最优秀和最聪明的人才。我不确定我有这个问题的答案。好的。
But I understand that where we're at is not where we want to be. Yeah. And I don't think anybody's lost, lost their focus on, you know, the American dream, the importance of immigration, the importance of attracting all of the world's best talent to United States, create the conditions for them to stay here. There are things that are done from time to time that works against what I just described.
我明白，我们现在所处的状态并不是我们想要的。是的。我认为没有人失去对美国梦、移民的重要性以及吸引世界上优秀人才来美国并为他们创造留下条件的关注。虽然有时候做的一些事情与我刚才描述的目标相悖。
Making foreign students uncomfortable in being here in the US. 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 that slippery slope isn't crossed. And so there are all of these things that goes along with finesse and nuance. But the fact of the matter is we know where we want to be.
让外国学生在美国感到不安。这个品牌可能会威胁到自己的声誉。我们不能忘记，与中国竞争是可以的，但一定要小心，不要对中国人过于苛刻。因此，我们需要确保不要越过这条危险的界限。在处理问题时，需要的是技巧和细微的把握。但事实是，我们知道自己想要达到的目标。
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. And so to the extent that we move in that direction, I believe it's a good start. You're great. 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.
我们知道我们处在一个困难的局面。我们不想待在这样的局面中。特朗普总统没有多少时间来将我们引导至那种情况。因此，只要我们朝那个方向前进，我认为这就是一个好的开始。你很棒。是的。我听说美国一个顶尖实验室的中国研究员提到，三年前，90%的中国大学顶尖人工智能研究毕业生都想来美国，并且确实来到美国，加入了我们的顶级实验室工作。
And he guessed that today that's closer to 10 or 15%. Right. So seeing a precipitous drop, that's precisely a concern that we have. Right. So have you seen this? Have you, you know, your paying attention to both markets? Do you see this? And what are the things we need to do in order to reverse that? Definitely see a greater concern of Chinese students who come here and remain here. Yeah. And or many of them who come here for school and are thinking about going elsewhere. Right. Many of them thinking about Europe. Right. And so I think I think we need to be super, super concerned about this. This is this is this is a source of existential crisis. This is definitely the early indicators of a future problem. Right. Right. You know, smart people's desire to come to America and smart people smart students desire to stay. Those are what I would call KPIs. Yes. Early indicators of future success. Yes.
他猜测今天这个比例接近10%或15%。对。因此看到如此急剧的下降，这正是我们担心的问题。对。那么你是否注意到这种情况？你有没有关注两个市场？你看到这个趋势了吗？为了扭转这种局面，我们需要做些什么？确实，我们看到有更多的中国学生在这里学习后宁愿留在这里。是的。或者他们中许多人在这里上学，但考虑去其他地方。对，很多人在考虑去欧洲。所以我认为我们必须非常、非常关注这一点。这是一个生存危机的来源，绝对是未来问题的早期指征。对，聪明的人来美国的愿望以及聪明的学生留下的愿望，这是我所称的关键绩效指标。这些是未来成功的早期标志。
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. Yeah. But the second that recruiting pipeline, right, because of the brand of the warriors gets to manage 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 I 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, you know, 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. That's right. Right. This needs to be the place that welcomes the best in the brightest, that attracts as a strategic plan for recruiting the best in the brightest and making sure that this is the place that they want to work.
我觉得这有点像勇士队，就是说如果他们能够招募到NBA所有最优秀的球员， 那他们就可以持续赢得冠军。但一旦这种招募渠道因为勇士队的品牌管理不善或者其他原因出现问题，他们就无法招募未来最优秀的球员，也就无法再赢得冠军。当你谈论美国梦时，你是如此富有表现力地在谈论美国这个品牌，来到这里并实现自己的梦想。我希望对政府的反馈是，不仅仅是针对政府， 而是整个国家如何谈论移民的问题。对的，这里需要成为欢迎最优秀和最聪明人才的地方，有一个吸引这些人才的战略计划，并确保这里是他们愿意工作的地方。
As you know, there's in and there's a phrase, and I didn't even 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. It's a badge of shame. There's no questions, a badge of shame. Now, 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 think they're doing the right thing for our country, but it's not patriotic. Not not even a little bit.
正如你所知，有一个短语，我几年前才听说过，这个短语是“中国鹰派”。是的，显然如果你是一个中国鹰派，你会自豪地佩戴这个标签，几乎像是一种荣誉徽章。但实际上，这是耻辱徽章，毫无疑问是耻辱徽章。虽然他们希望的是国家的最大利益，我们也都希望国家利益最大化，但摧毁美国梦的途径并不爱国。他们以为自己是在为国家做好事，但这根本不是爱国的行为，哪怕一丁点都不是。
And so we need to continue to be the great country we are to have the confidence of a great country. Yes. And to have the confidence of a great country and and have somebody who wants to compete with us and to have the attitude, bring it on. Right. Right. Bring it on. Right. Because I believe in 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. And is it your take that that's where the president is? Like he's a pragmatist. He's a 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.
所以，我们需要继续保持我们国家的伟大，以拥有伟大国家的自信。是的。为了拥有伟大国家的自信，我们需要有人愿意与我们竞争，并且要有那种“放马过来”的态度。对，放马过来。因为我相信我们的人民。我相信我们这里的人们。我相信我们的文化。我相信我们的国家。我相信我们的制度。放马过来。您是否认为总统也是这样想的？他是个实用主义者，他相信美国的增长和竞争能力。在我看来，他就是这样的。
There's no question. President Trump is the bring it on president. 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. I really really do hope so. Yeah. And I think he he speaks he speaks positively with great respect and great eloquence about 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 against the single most the two most important relationships for the next century. That doesn't make any sense at all decoupling is exactly the wrong concept. Right.
毫无疑问，特朗普总统是一位具有挑战精神的总统。对吗？对的。我之所以有信心并在这个播客上说过我认为他会与中国达成一项重大协议，是因为我真的非常希望如此。我觉得他在谈论他与中国的关系及其重要性时，总是充满积极态度、极大的尊重和卓越的表达能力。我从未听过他提到“脱钩”这个词，而这个词在上届政府中经常被提及。与下个世纪最重要的两个关系脱钩是完全没有意义的，“脱钩”概念是完全错误的。对吧？
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. That 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 that ultimately said the best way to understand me is I'm a great deal maker. I make deals. Right. Whereas I think in other camps there are people who are iconoclastic or dogmatic. You know it's the mere shimer view of China that there's a great power struggle. One must must win and one must lose versus this idea that every country has to look exactly like ours. Right. Right.
在我看来，他和斯科特·贝松是在说，我们需要让美国再次伟大。我们需要重新工业化美国。我们需要确保贸易公平，保护需要帮助发展的产业。我们要让中国帮助我们做到这些，认识到在过去的25年里，我们也帮助了中国。但最终，他说，最了解我的方式是，我是一个出色的交易者，我会做交易。而在其他阵营中，有人则持有不同的观点，比如认为与中国存在一个大国竞争，必须一方胜利一方失败，而不是接受每个国家都能有自己的发展模式。
We want to worsen. 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. Yeah we're that going 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. Right. Partnering with Intel, a company that spent most of its life trying to put us out of business. Right. And I had no trouble partnering with them. Right. You know and so and the reason for that is because number one bring it on. Yes. 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. Yeah. Yeah. But nonetheless bring it on.
我们想要变得更强大。你希望美国取得胜利，但这并不意味着要以牺牲他人为代价，不需要去刺伤别人的眼睛或让他们失败。因为我们对自己的信心很足，是的，我们有这样的自信，因为我们非常强大，因为我们非常了不起。正如你所知，我在与生态系统中的所有同事合作方面从来没有问题，对吧？请注意，我们刚刚完成了一笔重要的合作，对吧？我们与英特尔这家曾经花费大部分时间试图让我们出局的公司合作，对吧？而我与他们合作毫无困难，对吧？这是因为，首先，我们欢迎挑战，是的。其次，未来会更加美好，成功不必非此即彼，它可以是我们和他们一起成功，是的，是的。但尽管如此，我们仍然准备迎接挑战。
Yeah. You know you you mentioned something that's profoundly important to both of us. You and I've talked a lot about this the American dream. You know and it was I think Abraham Lincoln who said fundamental to the American dream is the right to rise. Yeah. That's right. The belief that your kids can do better than you did. That's right. Right. And you you've experienced the right to rise. We've all experienced the right to rise in America. So now you go to Wikipedia you go look up American dreams come my picture. Right.
好的。你提到了一件对我们双方都非常重要的事情。你和我曾多次讨论过这个，就是美国梦。我记得亚伯拉罕·林肯曾说过，美国梦的基础是每个人都有向上的权利。是的，没错。这意味着人们相信自己的孩子可以比自己过得更好。这是对的。而且你也经历过这“向上的权利”。我们在美国都经历过这种向上的权利。所以现在如果你去维基百科查找“美国梦”，可能会看到我的照片。
Yeah. 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 will probably have individuals that are worth a trillion. Those are the incentives that give people the 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. Yeah. Right. And they feel left out and left behind. So it makes sense for them to attack this system of capitalism.
是的。然而，我们生活在这样一个时代，由于这些技术系统的性质，一些公司可能会达到10万亿美元的市值，甚至可能会有个人拥有一万亿美元的财富。这些激励措施推动人们努力向上。但是，与此同时，当我们进入这个充裕时代时，我深感担忧的是，太多人会被落下。他们感到被忽视和被落下，因此他们攻击这个资本主义体系是有道理的。
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 the old social security and open AI etc. And they benefit. Right. As the company country wins they win and they own it individually. They can see it on their phone. 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 well I want to thank you for starting it for driving it.
我们曾一起努力过的一件事情，我非常感激的，就是“投资美国”的理念。我们要从每个孩子出生开始，让他们踏上资本主义的成功之旅。给他们一千美元，投资于像旧版社保和OpenAI这样的优秀公司。当公司和国家赢得胜利时，他们也会获益，而且他们是个人拥有这些投资的。他们可以在手机上看到每个孩子都是美国未来的股东。因此，基于您的支持，我想借这个播客的机会感谢您启动和推动这个项目。
Yeah. Yeah. Thank you. What a great idea. And you know so this you're genius. The please this past in the big beautiful bill. Yeah. Most people don't even realize that starting in 2026 every child born forever more in the history of this country. We'll start off with an investment account at birth. Yeah. See in 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 philanthropy and companies. We think every company across America.
是的，是的，谢谢你。真是个好主意。你知道吗，你真是个天才。请看看这个宏伟壮丽的计划。大多数人甚至都没有意识到，从2026年开始，这个国家历史上每一个新出生的孩子都会在出生时就拥有一个投资账户。账户里会有一千美元投资在美国最好的公司。而且你的公司已经同意不仅为你员工的孩子增加账户资金，也可能为其他孩子这样做。我打算支持学校以及很多慈善机构和企业。我们希望全美的每家公司都参与进来。
Wonderful way for companies to give back. Right. Yeah. 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 and the social contract needs to keep up with it. Obviously President Trump and bipartisan group in the House and Senate passes into law. So maybe just talk to us a little bit when you think about the pace and magnitude of changes that are coming.
这是一种公司回馈社会的美好方式。对吧。是的。这是401k计划的一部分。在我看来，这似乎是社会契约变革的一部分，因为我们看到快速的进步，政府和社会契约的演变需要跟上这种速度。显然，特朗普总统和国会两党的一个小组通过了法律。所以也许可以跟我们稍微谈谈您对即将到来的变化的速度和规模有何看法。
Right. I know you believe it would be a net good but there 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. There's several things that that President Trump has done and let me just start start there has done that is incredibly good for bringing everybody along. The first thing is re industrializing America.
好的。我知道你认为这将总体上是件好事，但在这个过程中也会有很多人受到影响。我们可能需要这样的政策和其他措施来帮助所有人跟上这个变化。特朗普总统做了一些非常有利于让大家共同进步的事情。首先，就是重新工业化美国。
Yeah. President Trump, Secretary Lutnik you know 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 re-skilling 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 you know one of the great schools and only in that way can you build a great life. Right. And deserve to have a great living. We've got to change all that.
是的。特朗普总统和卢特尼克部长都在全力支持他们所做的一切工作。他们鼓励公司在美国投资建厂，并努力提升和再培训熟练劳动力。对我们的国家来说，这是极其宝贵的。我们不能再坚持只有获得博士学位或者就读于顶尖学校才能建立美好生活的观念。我们需要改变这种想法。
That doesn't make any sense. We love craft. Right. I love people who make things with their hands and and we're now we're not going to go back and build things. Yes. Build magnificent incredible things. I love that. Yes. That's going to transform America. There's no question about that. There's a whole there's a whole whole band of an economy, a whole band of society that that has been largely left behind because we outsourced everything. Right. Now I'm not suggesting we ensourse everything. Right. You know all the people arguing about you know manufacturing tennis shoes and toothpicks. I mean you know that's that's denigrating a perfectly good discussion into some insane level. You know we've got to recognize that re industrial in the United Read Industrial Lizing America is just fundamentally going to be transformed with transformative.
这太荒谬了。我们热爱手工艺，对吧？我喜欢那些用双手制作东西的人。然而，我们现在不再去建造东西了。是的，我热爱那些建造壮丽奇妙事物的人。这会改变美国，这是毫无疑问的。有整个经济和社会阶层在大量外包的情况下被遗忘了。对吧？但我并不是建议我们要把一切都内包化。你知道，人们争论制造运动鞋和牙签的问题，把本来很不错的讨论降级到一些疯狂的层次。我们必须认识到，再工业化的美国将会以一种根本性的方式被转变。
Number one number two. And aspirational. Oh it's fantastic. Elon taking us to Mars watching spaceships caught with you know topics. Topics out of the sky. This is not only great for the industrializing base of America. It's aspiration for fantastic. That's right. And then of course AI. 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 this somebody had to learn once they use a computer for their economic or career benefit. They have to learn C++ or C or at least Python. Now they just have to learn human. I know. And so and 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.
第一，第二，还有雄心壮志。哦，太棒了。埃隆带我们去火星，观看飞船从天而降（抓住）这些话题。这不仅对美国的工业基础有利，也是一个伟大的愿景。没错。当然，还有人工智能。它是最大的平等工具。想一想，现在每个人都可以拥有一台人工智能。这是终极的平等器，我们弥合了技术鸿沟。记得以前有人为了经济或职业利益使用计算机时，他们必须学习C++、C或者至少是Python。现在他们只需学会如何与人交流。我知道。如果你不知道怎么编程一个人工智能，你只需告诉人工智能：“嗨，我不知道怎么编程一个人工智能。请问我该怎么做？”然后人工智能会为你解释或者直接为你完成。
And so it's incredible. Isn't that right? It's and we've now closed the technology divide with technology. This is something that everybody's got to engage. You know open AI has 800 million active users. Gosh it really really needs to be six billion. Yeah right. It really needs to be eight billion soon. And so I think that that's number one. And the number three. You know I think the the AI will change tasks. Yeah. 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. Right. And so for example I'm using AI all the time. You're using AI all the time. My analysts are using AI all the time. Engineers every one of them use AI continuously.
这实在是令人难以置信。不是吗？我们现在通过技术克服了技术鸿沟。这是每个人都应该参与的事情。你知道，OpenAI有8亿活跃用户。天哪，它真的需要达到60亿。没错，很快就应该达到80亿。所以我认为这是第一点。第三点，我认为AI将会改变任务。人们常常混淆的是，有许多任务将被淘汰，但实际上也会创造出许多新的任务。不过，很可能对许多人来说，他们的工作会被稳定保护。例如，我一直在使用AI，你也在一直用AI。我的分析师们无时无刻不在使用AI，工程师们也都是一直在使用AI。
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. Yes. 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. Because we became more rich. We can hire more people to go after those ideas. Right. The the the concept that that AI comes along and therefore there's going to be a mass destruction of jobs starts with the I starts with the premise that we have no more ideas. Right. It starts with the premise we have nothing left to do. Everything we're doing in our lives today.
我们正在招聘更多的工程师，招聘更多的人才，招聘各个领域的人。这样做的原因是我们有更多的想法。是的，我们现在可以追求更多的创意。原因是我们的公司变得更高效了。因为提高了效率，我们变得更加富有。因为我们变得更富有，就可以雇佣更多的人去实现这些想法。没错。认为人工智能出现会导致大量工作消失的观点，是以为我们没有更多想法为前提的。这种观点是基于我们已经无事可做。然而，事实并非如此。
Yeah. This is the end. Yeah. And if somebody else were to do that one task for me, I have one task less. Now I have to sit there and wait for something. Yes. You know, wait for retirement. Sit on my rocking chair. That idea doesn't make sense to me. And so I think I think that 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. And so I think for for I don't know what the world looks like in a million years, that's going to be left for my my children.
是的，这就是终点。如果有人能为我完成那项任务，我的任务就少了一项。现在我只需要坐在那里，等待某件事情，比如退休，坐在我的摇椅上。这种想法对我来说没有意义。我认为智力不是零和游戏。我身边越多聪明人和天才，我就拥有越多的想法，我们可以解决的问题就越多，创造的工作和就业机会就越多。因此，我不知道一百万年后的世界是什么样子的，那就留给我的孩子们去面对吧。
But 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 job will some jobs will be lost. And we're not going to be writing horses on streets. And those things will be fine. You know, 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. In other great futures, Ray Kurzweil said, in the 21st century, we're not going to have 100 years of progress. We're likely to have 20,000 years of progress. Right.
在未来的几十年里，我认为经济将会增长。会创造出大量新的工作机会。每一份工作都会发生变化，有些工作会消失。我们不会在街上骑马，这些变化都会顺利进行。众所周知，人类对复利系统持怀疑态度，并且不擅长理解这些系统。而对随着规模增长而加速的指数型系统，人类理解得更差。今天我们谈了很多关于指数增长的话题。在其他伟大的未来中，Ray Kurzweil 说过，在21世纪，我们不会经历100年的进步，而是可能经历2万年的进步。对吧。
Right. 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 2030, things like robots. 30 years is easier than 2030. Oh, really? Yeah. Okay. So I'll get a great license to go out 30. As you think out over the course of, I like these shorter time frames because they have to marry bits and atoms. More important. 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. 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.
好的。你刚才提到，我们很幸运生活在这个时代，并为这个时代做出贡献。我不会让你预测未来10年、20年或30年的情况，因为我认为这很有挑战性。但当我们想到2030年，比如说机器人。相比之下，预测30年后的事情反而更容易。哦，真的？好吧，那我就大胆地展望未来30年的发展。我喜欢讨论较短的时间段，因为这些阶段需要结合物理与数字元素。构建这些东西的难点就在于此。因为大家都在说某些事情会发生，这很有趣，但并不实用。确实如此。但如果我们有2万年的发展历程，回顾Ray的那句话，思考指数级增长。以及我们所有的听众，无论你在政府工作、创业或经营大公司，都需要考虑变化加速的速度、增长加速的速度，以及在这个新世界中如何变得更加智能。
Well, there are a lot of things that many people have already said. And they're all very sensible. I think in the next five years, one of the things that is really cool that's going to get solved is the fusion of artificial intelligence and megatronics robotics. And so we're going to have, we're going to have, you know, AIs that are going to be wandering around us. And we all, and that everybody knows. We all know that we're going to all grow up with our own R2D2. And that R2D2, remember everything about us and coach us along the way and be our companion. We already know that. And so the idea and the idea that every human will have their own GPUs associated with them in the cloud, and that they're 8 billion people, 8 billion GPUs, that's a, you know, viable outcome. And so, and he's having their own model. He's fine-tuned for them. Fine-tuned for them. And that AIs in the cloud is also embodied in a whole bunch of, it's embodied in your car, it's embodied in your own robot, it's everywhere with you.
很多人已经提到了很多事情，而且它们都很有道理。我认为在未来五年内，一件非常酷的事情将得到解决，那就是人工智能和机电一体化机器人技术的结合。到时候，我们会看到人工智能在我们身边游走。这是众所周知的事情：我们都知道每个人都会在生活中拥有一个属于自己的“R2D2”（像《星球大战》中的机器人），它会记住有关我们的一切，指导我们，并成为我们的伙伴。我们已经知道这一点。
此外，每个人都会有一个云端的GPU（图形处理单元）与之关联，并且全球80亿人都有80亿个GPU，这是一种可行的结果。这样，每个人都有自己的AI模型，并根据个人需求进行了调优。这些云端的人工智能会被整合到我们生活的各个方面，比如我们的汽车、个人机器人，它们无处不在地陪伴我们。
And so that I think that that future is a very sensible thing. The idea that we're going to understand the infinite complexity of biology and understanding the system of biology and how, how, 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 at healthcare, of course we would. And so, you know, a digital system that predicts how, how we're going to age with disease, we're likely going to have. And anything that's about to happen maybe even next week or, you know, tomorrow afternoon and predict it early, of course, we wouldn't have all that. And so I think all of that is a given.
我认为这样的未来是非常合理的。我们会逐渐理解生物学的无限复杂性，了解生物系统，并学会如何预测它，同时为每个人创建一个健康的数字孪生体，就像我们在亚马逊购物时有自己的数字孪生体一样。为什么我们在医疗健康领域没有数字孪生体呢？当然我们应该有。这样一个数字系统可以预测我们随着疾病老化的过程，甚至可能预测到下周、明天、甚至是明天下午即将发生的事情。提前预测自然是可能的。我认为这一切都是理所当然的。
I think the, the, the part that that I'm asked a lot by CEOs that I work with about now given all of that, what happens? What do you do? And this is, this is the, this is a common sense of, of things that move fast. If you, if you have a, if you have a train that's about to get faster and faster and go exponential, the only thing that you really need to do is get on it. Yeah. And once you get on it, you'll figure everything else out along the way. 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.
我常常被我合作的CEO问到，现在在这样的情况下，该怎么做？这是一个很普遍的问题，尤其在事物发展迅速的背景下。如果你有一列即将加速并呈指数级增长的火车，实际上你唯一需要做的就是上车。对，一旦上了车，其他事情自然会在途中解决。因此，预测这列火车未来会到达的地点，并尝试提前在那个位置有所行动，或者试图找到火车加速中的某个交叉口等待它，都是不可能的任务。你只需要在火车还算慢速时上车，随着它一起加速前进。
A lot of people think this just happened overnight. You know, you've been, 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 answer it, before you even ask it and give you the answer without having to look. Right. I heard Bill Gates say in 2016, because contextually, you must be asking about, well, you must be wondering about that. Right. I heard Bill Gates say in 2016 when somebody said it hasn't all the things been done. We've had the internet. We've had cloud. We've had mobile, social, et cetera. He said, we haven't even started. He said, what do you think? Why would you say that? He said, we won't even begin until machines go from being dumb calculators to beginning to think for themselves, to think with us. Right.
很多人认为这件事是一夜之间发生的。然而，你知道，你已经在这个领域坚持了35年。我记得在大概2005或2006年时，拉里·佩奇曾说过，谷歌的终极目标是能够让机器在你问出问题之前，预测你的问题，并让你无需查找就得到答案。对此比尔·盖茨在2016年也做出过评论，因为你可能在好奇这一点。当时有人问他，是否所有事情都已经完成了，因为我们已经有了互联网、云计算、移动技术、社交网络等等。他说，我们甚至还没有开始。他反问：你怎么看？为什么会这样认为？他说，机器从愚笨的计算器变得能够自主思考，能够与我们一起思考，这才是真正的开始。
Kind of that is the moment. Right. That we're in. I think to have leaders like you, leaders like Sam and Elon, Satch, et cetera. It's such an extraordinary advantage for this country. Right. And to have the cooperation that we see between a system of risk capital that I take, you know, that I'm part of, which can provide the risk capital for people to do. 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. Right. Right. It's an extraordinary time.
这正是当下的时刻。对吧。我们身处其中。我认为，拥有像您这样的领导者，像Sam、Elon、Satch等这样的领导者，对我们的国家是一个极大的优势。对吧。我们还看到了风险资本体系之间的合作，我也参与其中，这些资本可以为人们提供进行创新的资金支持。我们不依赖政府进行曼哈顿计划那样的大项目，我们实际上可以凭借自己的力量和共同的努力造福国家。这是一个非凡的时代，而且规模之大超乎想象。对吧。确实，这是一个非凡的时代。
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 plutocrats at the top hanging out in Silicon Valley.
我也认为，我很感激的一件事是，我们有一些领导者，他们明白自己对正在加速发生的变革负有责任。我们知道，尽管这对于绝大多数人来说可能是件好事，但过程中难免会遇到一些挑战。我们会在挑战出现时应对它们，提高每个人的基本生活水平，确保这不仅仅是硅谷顶端少数富豪的胜利，而是惠及所有人的。
And don't scare them. But it's a win. It's a win. Don't scare them. That's right. Bring them along. And we will. Yeah. So thank you for that. Exactly. As a reminder to everybody, just our opinions, not investment advice.
不要吓到他们。但这是个胜利，是个胜利。不要吓到他们。没错，让他们一起来。我们会的。是的，所以谢谢你。正如提醒大家的，这只是我们的意见，不是投资建议。