人工智能泡沫或将如此破裂

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今天的话题：AI泡沫。今年美国科技公司将在人工智能上投入约3000至4000亿美元。按名义金额计算，这超过了任何企业集团为单一领域投入的历史纪录。值得注意的是，这些公司远未收回即将投入的4000亿美元成本。这就是为什么开始有人质疑：这场AI建设热潮是否会演变成史上最大的经济泡沫。

Today, the AI bubble. This year, American tech companies will spend about 300 to $400,000,000,000 on artificial intelligence. That's more in nominal dollars than any group of companies has ever spent to do just about anything. And notably, these companies are not anywhere close to earning back that 400,000,000,000 that they're about to spend. This is why you're starting to hear some people wonder if the AI build out is turning into the mother of all economic bubbles.

技术批评者常这样反驳：他们指出按照当前轨迹，这十年我们将耗费数万亿美元构建的可能是场彻头彻尾的骗局。但我更关注AI拥护者的观点——他们声称我们正经历堪比互联网、铁路或电报诞生的技术革命。我认为他们或许是对的。

Sometimes you'll hear this case from critics of the technology. Critics will sometimes point out that we're on track to spend trillions of dollars this decade building something that might be all smoke and mirrors. I'm more interested, though, in the boosters of artificial intelligence. They'll sometimes argue that we are living through a transformative tech akin to the creation of the internet, or the railroads, or the telegraph. I think they might be right.

我也认为他们没有意识到‘正确’意味着什么。互联网基础设施的建设在九十年代末和两千年代初制造了一个巨大的泡沫。电报基础设施的建设则在十九世纪制造了另一个泡沫。正如我们在前几期节目中所解释的，横贯大陆铁路系统的建设引发了一系列泡沫，最终导致了1857年恐慌、1873年恐慌和1893年恐慌——半个世纪的恐慌。二十世纪，无线电是一个泡沫，汽车和航空公司的兴起也充满了泡沫气息。

I also think they don't realize what being right would imply. The infrastructure build out of the internet created an enormous bubble in the late nineteen nineties and early two thousands. The infrastructure build out of the telegraph created another bubble in the nineteenth century. The construction of the transcontinental railroad system, as we explained in a previous episode, created several bubbles ending in the Panic of eighteen fifty seven, the Panic of eighteen seventy three, and the Panic of eighteen ninety three a half century of panics. In the twentieth century, radio was a bubble the dawn of automobiles and aviation companies also quite bubbleicious.

简而言之，如果AI鼓吹者将其与过去150年最伟大技术相提并论的判断是正确的，那么他们自己的类比就预示着，他们的产品在改变世界的过程中也将经历一场灾难性的崩溃。如果你关心美国经济，这绝对会让你感到恐慌。GDP增长的一半来自AI基础设施支出，包括数据中心、芯片和能源。过去几年股市涨幅的一半以上来自与AI相关的公司。如果你拆解这些巨头公司——Meta、微软、Alphabet、亚马逊——的财报，AI基础设施支出或资本支出占它们收入的近一半，正如你所料。

In short, if AI's boosters are right with their comparison of AI to the greatest technology of the last one hundred fifty years, their own analogy anticipates that their product too will pass through a calamitous crash on the way to changing the world. This should absolutely scare you if you care about The US economy. Half of GDP growth comes from infrastructure spending on AI, on data centers, chips, and energy. More than half of stock market appreciation in the last few years comes from companies associated with AI. If you open up the hood of these biggest companies, Meta, Microsoft, Alphabet, Amazon, AI infrastructure spending or CapEx accounts for, you guessed it, nearly half of their revenue.

如果AI支出项目在未来几年内崩盘，正如我们下一位嘉宾所说的那样，其对技术、经济和政治的影响将是巨大的。保罗·库德洛夫斯基是一位投资者兼作家。今天我们将讨论AI热潮的运作方式、资金来源及其融资机制。我们将AI建设置于历史背景中审视，然后花大量时间探讨可能出错的地方及时间节点。我是德里克·汤普森。

If the AI spending project blows up in the next few years, as our next guest says it might, the implications for technology, the economy, and politics would be immense. Paul Kudrowski is an investor and writer. Today we talk about the AI boom, how it works, who's paying for it, and how they're financing it. We put the AI build out in historical context, and then we spend a great deal of time walking through what could go wrong and when it might go wrong. I'm Derek Thompson.

这里是Plain English节目。保罗·库德洛夫斯基，欢迎来到我们的节目。

This is Plain English. Paul Kudrowski, welcome to the show.

嘿，德里克。很高兴来到这里。

Hey, Derek. Good to be here.

在我们开始之前，能介绍一下你自己吗？你是做什么的？

Before we start, who are you? What do you do?

是的。这是个好问题。我有几份日常工作。一份是在SK Ventures风投公司担任合伙人，主要从事早期阶段投资，这意味着高失败率、低资金投入，大多数项目都会失败。同时我还是MIT数字经济中心的研究员。

Yeah. That's a good question. So my I have a couple of day jobs. One day job is I'm a partner with a venture capital firm called SK Ventures where we're mostly doing early stage investing, which is to say high failure rate, low capital, most things break. And then I also sit in as a a fellow at the MIT Center for the Digital Economy.

这部分工作更贴近我们正在研究的一些核心理念。此外我还运营一份通讯刊物，主要读者是对冲基金和买方机构——因为我早年曾在卖方工作，为经纪公司效力，这个身份烙印始终挥之不去。我总忍不住想给他们提供建议，不管他们爱不爱听。所以我至今仍与多家对冲基金和买方机构保持合作，这又让我们绕回到数据中心和人工智能那些话题上。

So this is sort of we're closer to the the spirit of some of the things we're working on. And then I also have a newsletter that goes out to a bunch of hedge funds and generally to hedge funds and buy side firms and things like that just because my background way back when was I was on the sell side. I worked for a brokerage firm, I've just never been able to shake that, so I can't help myself. Sometimes I just provide. I wanna give them advice and whether they like it or not, and so I still do a lot of work with a bunch of hedge funds and buy side firms, which is takes us back to data centers and AI and blah blah blah.

其实你应该知道，你的通讯刊物读者不只有对冲基金，还包括播客主持人——这也是你这次受邀的其中一个原因

Well, you should know your newsletter doesn't just go out to hedge funds. It also goes out to podcast hosts, which is one reason why you're on

来上节目。没错。

this show. Yes.

你的分析最让我感兴趣的一点是，人们常把人工智能视为未来科技，而我正竭力强调AI已是当下最重要的经济现象。它已经到来，正在发生。而你比任何人都更早、更有效地警示了美国对AI的投资规模在历史上有多么巨大。不如就从你的核心论点开始？

One thing I find so interesting about your analysis is that artificial intelligence is sometimes talked about as being the technology of the future, and that I'm trying to ring the bell very loudly that AI is the most important economic phenomenon of the present. It is here. It's happening right now. And you've been sounding the alarm maybe more than just about anybody or more effectively than just about anybody just how massive US investment in artificial intelligence is by historical standards. So why don't you just start with your thesis statement?

这规模有多大？

How big is this?

好的。让我先快速回顾一下背景故事？因为吸引我注意的正是你描述的现象——巨额资金正流向极少数接收方，比如某些芯片公司，且集中在北弗吉尼亚等极小地理区域。这是高度集中的资本池，但规模之大，经过汇总计算后似乎足以影响GDP。

So yeah. Let's maybe go can I go back and tell a quick back story here first? Just because what got me interested was what you're describing, which is there's a huge amount of money being deployed. It's going to a very narrow set of recipients, some of these chip firms and others, and it's going to some really small geographies like Northern Virginia. So it's an incredibly concentrated pool of capital and yet it's so large that when you do the aggregating and do the math, it seems to be large enough to affect GDP.

我当时就想：这太疯狂了，必须验算。结果发现今年上半年，数据中心相关支出——那些装满GPU、机架和服务器的巨型建筑，被大型AI公司用来生成响应和训练模型——可能占到了上半年GDP增长的一半，这简直荒谬。我用四五种不同方法反复验证想推翻这个结论，最后不得不接受事实。

So I was saying, okay, fine, this is crazy. I should do the math. So I did the math and I found out that in the first half of this year, the data center related spending, so spending on these giant buildings full of GPUs and racks and servers and what have you that are then used in turn by the large AI firms to generate responses and train models, that that probably accounted for something like half of GDP growth in the first half of the year, which was absolutely bananas. And I was like, I did the math four or five different ways trying to prove myself wrong. And then I said, okay, fine.

我觉得有必要指出：这个数字令人震惊的原因很多，包括你提到的历史对比。无论是电信泡沫还是铁路建设，我们稍后可以深入讨论，但当前规模都是空前的。更特别的是支出性质——铁路与GPU的差异不仅表象，而是深层次的本质区别，这点却常被忽视。

I should this is feels like something I should mention. And so I said it and it's I think it's it's a startling figure for a whole bunch of reasons, one of which you alluded to, which is that even compared to historical spending, whether you pick the telecom bubble or railroads or whatever else, we can dive into those. It's unprecedented. It's also unprecedented because of the nature of the spending, which I think is incredibly important because railroads are very different from GPUs, not just in the trivial sense, but in some very deep and important ways. And all of this gets missed.

但结论很明确：支出规模巨大，正在驱动经济。人们对此非常困惑，导致政策制定出现偏差——你以为政策A在推动经济，实际起作用的是左边这些看似疯狂的东西。

But the upshot is spending is huge. It's driving the economy. People are very confused about this. And as a result, you end up making bad policy decisions because you think policy decision A is driving the economy when it's this wacky stuff over here on the left.

所以我们讨论的是堪比90年代末至21世纪初宽带建设的基础设施热潮，虽仍不及19世纪铁路繁荣，但对单一新兴技术的投资规模至少是60-100年来前所未有的。AI资本支出具体如何构成？我们谈的正是资本开支问题。

So we're talking about the infrastructure boom that is on par with the broadband build out of the nineteen nineties, early two thousands. Still behind, it seems like, the railroad boom of the nineteenth century, but we're talking essentially about an amount of spending on one emerging technology that is without precedent in at least sixty to a hundred years. How does AI CapEx break down? Right? We're talking about capital expenditures.

那么这些资金主要投入在机器而非人力上。芯片、能源和实际数据中心建设各占多少比例？有没有好的方法来理解这些资金的流向？

So money that's being spent on essentially machines rather than people. How much of this is chips versus energy versus building the actual data centers themselves? Is there a good way to think about where all this money is going?

数据中心成本中略超一半是芯片投入，大约60%，具体比例因数据中心模式而异——存在多种不同类型的数据中心。有些近乎是按需建造的，比如CoreWeave这类公司，他们购买设备就像希望租户入驻大楼一样，可以类比为商业地产，期待吸引客户入驻。

So a little more than half the cost of a data center is the is are the chips that are going in. So say 60%, it varies depending on the model of the data center because there's a whole bunch of different styles of data centers, if you will. There are some that are built almost on spec. Think of companies like CoreWeave where they're buying it and it's almost like they're hoping to tenant a building. Think about it as commercial real estate and I'm hoping to get people to move in.

我建造一个外壳，人们搬进来，我希望招揽租客，然后租客支付租金。而像Meta、谷歌和亚马逊这样的公司，他们自建自用，其中约50%到60%是GPU成本，其余是冷却和能源的组合，实际建筑只占相对较小部分。

I'm building a shell and people are moving in and I'm hoping to get tenants and then the tenants pay rent. Right? So think of it in those terms. And then there's the Metas and the Googles and the Amazons where they're using a huge amount of what they're building, which again, roughly 50% to 60% of it is the GPU cost. The rest is a combination of cooling and energy, and then a relatively small component is the actual construction.

所以可以这样分解：建筑框架、混凝土基座和地产购置。具体取决于用途规划——如果用于训练，就需要购买更昂贵的GPU，对吧？

So think about the frame of the building, the concrete pad, and purchasing the real estate. So you can break it out that way. So it depends a little bit on what you're planning to use it for. If I'm trying to build something that's for training, well, I'm gonna buy more expensive GPUs. Right?

我需要英伟达的最新产品；如果是用于推理，主要服务于生成响应场景，那就不需要最新GPU，可以降低成本、适当妥协。你可以将其视为一个连续体。

I need the latest products from NVIDIA. If I'm building something that's more for inference, meaning that I'm just gonna have using it in largely for people that are trying to generate responses, I'm hoping, well, then I don't need the latest GPUs, and I can cut costs and cut some corners in there. So you can think about it as that continuum.

你多次将这次基础设施热潮与铁路建设、光纤铺设相类比，但也指出这个类比存在不适用之处。我想探讨这点——类比遗漏了什么。比如19世纪60年代铺设的铁轨到90年代仍在使用，甚至部分可能沿用至20世纪50年代。

You compare the infrastructure boom several times to the railroads, the fiber build out. You also indicated that there's ways in which that analogy does not hold up. So I wanna get into that, right, what the analogy misses. Like, the rail that we laid in, say, the eighteen sixties was still around in the eighteen nineties. Maybe some of it's still around the nineteen fifties.

对吧？铺设的光纤电缆多年后仍能工作。但我不断看到GPU性能持续提升的新闻。所以我在想，企业购买这些设备是否三五年后就得更换？

Right? The fiber optic cable that was laid still works for years. But I keep seeing news headlines about GPUs getting better all the time. Right? So I wonder, like, are companies buying something they're gonna have to replace in, like, three years?

能否谈谈人工智能与钢轨或光纤电缆的根本区别？这种区别对于我们理解正在构建的内容至关重要。

Talk a little bit about how AI is just fundamentally different than steel rail or fiber optic cable in a way that's really important in understanding what it is that we're building here?

我将从宏观层面开始。这是我对经济统计数据的普遍不满。你看，这是大白话对吧？'资本支出'这个术语实在是个误称，甚至可以说是误导性的——当然不是故意误导。问题在于它过度笼统的统计方式。

So I'll start at a high level. This is my complaint about economic statistics in general. You know, this is plain English, right? So capital expenditures is such a misnomer and such a, I'll say misleading, it's not consciously misleading. It's just that it's so aggregated up.

它假设所有资本支出项目——无论是AI数据中心、铁路建设，还是互联网泡沫时期的基建——都被混为一谈。但正如你暗示的，这些项目的本质差异在于所创造事物的生命周期截然不同。以19世纪铁路泡沫时期（比如1855年）建造的铁路为例：五年后开始运营时，我面临的最大问题可能是什么？

It assumes that everything I'm spending money on that's capital expenditure and AI data centers are lumped into that loosely as were railroads, as are, let's suppose, the .com construction. But they're all very different for exactly the reason you allude to, which is the lifespan of the thing you're creating is wildly different. So when you think about comparing railroads, which let's say I built something during the railroad bubble in the nineteenth century, say 1855. I only got around five years later running traffic down the line. What were the biggest issues I potentially had?

杂草？我不确定。或许是杂草？也可能有牛群占据了轨道？说实话，我根本不清楚当时要对抗的具体阻力是什么。

Weeds? I don't know. Weeds? Maybe some cows had settled in? It's not clear to me what it was that I was what the forces I was pushing against were.

实际上，我可以非常迅速地'点亮'这条铁路线（投入使用）。就像90年代末光纤热潮时期，如果我安装了当时Sienna和JDS Uniphase等知名企业的设备铺设光纤，结果却发现：等等，根本没人需要我启用这些光纤。

So in all likelihood, I could, quote, light that line very, very quickly. I could put it into use relatively easily. Similarly with the fiber boom back in the late 1990s, if I was putting in some gear from Sienna and JDS Uniphase and all the great names of that era and building out fiber. And it was like, wait a minute. Nobody wants me to light the fiber.

没人需要传输数据。那时Netflix还没出现。于是我等了五年才启用光纤，这时会遇到什么阻力吗？完全没有。

Nobody wants to send data data. Netflix isn't doing that yet. Okay, so I wait five years and I light the fiber. What are the things that then are pushing against me? Nothing.

或许偶尔会有挖掘机意外挖断光纤，但修复起来非常快。光纤本身并不会因为没用来传输Netflix流媒体就贬值——这根本不相关。现在我们转向当前这波所谓的'资本支出'，情况就完全不同了：GPU的生命周期只有两年半到三年半。

And maybe someone accidentally put a backhoe through a fiber line, but I can very quickly put that back together. So it's not as if the fiber optic cables themselves are depreciating asset, that they're becoming less useful over time because I didn't write it to send some streaming stuff for Netflix down. It has no bearing. Now we turn to the current wave of, quote, capital expenditures and that's why this is very different. The lifespan of a GPU is on the order of two and a half to three and a half years.

这与铁路投资截然不同——铁路五年后仍能保持同等价值，光纤几年后也能为奈飞所用。但若我今天建数据中心并配备英伟达Blackwell GPU，却指望三年后仍能维持当前租金水平，那简直是痴人说梦。这些资产价值呈指数级衰减，与我们历史上那些持续投入的同等级泡沫完全不同。

This is nothing like the spending that's being done on railroads where five years later, completely the same value or in the case of fiber, a couple years later, light it for Netflix. No problem. If I build a data center today and populate it with Blackwell GPUs from NVIDIA and hope in three years I can get the same rental prices that I could have gotten today, I'm dreaming. There's likelihood I'll get a fraction of that, if anything at all. So these assets decline exponentially, which is completely different from all these historical bubbles that we were spending on the same level.

因此你面临一个棘手问题：必须极速收回投资，因为你持有的资产在不断贬值，这就形成了恶性循环。

So you have this problem that you need to recoup your investment if you are doing this very, very quickly because you're sitting on a depreciating asset, which creates this perverse problem.

当人们看到超大规模企业每年在资本支出（或称AI基础设施）上豪掷2000亿、3000亿甚至近4000亿美元时，反泡沫论者会说这就像修建铁路——可以永久使用。如今投入的3000亿美元在未来十到二十年仍具价值，这是铁路类比。而铁路的对立面，则是香蕉对吧？

So when people look at the fact that these hyperscalers are spending 200, 300, almost $400,000,000,000 a year on, we can call it CapEx, we can call it, you know, just AI infrastructure, there's a way in which if you're rooting against a bubble, you could say, well, it's like building a railroad. You can use it forever. So the $300,000,000,000 that's being spent right now can be made useful ten years from now, twenty years from now. That's the railroad analogy. On the opposite side of railroads, there's like bananas, right?

如果你今天花3000亿美元买香蕉，两周后这些资本支出就一文不值——因为香蕉全烂了。GPU虽不完全像香蕉，但也不完全像...

If you spend $300,000,000,000 on bananas today, your CapEx isn't worth shit in like two weeks because all the bananas are brown. And I don't think GPUs are entirely like bananas, but they're also not entirely like

它们比其他任何东西都更接近香蕉。

They're closer to bananas than anything they're else.

比起钢材更接近香蕉。那么这从宏观层面告诉我们什么？关于这类支出的价值，以及企业可能无法从前期投资中回收资本的风险？

To bananas than steel. And so what does this tell us at a high level about the value of this kind of spending and the threat that these companies are just not going to be able to return capital from all this upfront investment?

虽然不愿承认，但这某种程度上让我想起企业的比特币国库策略。就像微策略公司那样——把比特币纳入国库反而推高市值，每投入1美元比特币市值就增长约2美元。现在我们目睹同样的畸形现象：市场奖励这种毫无经济理性的行为，毕竟未来三年根本不可能收回资本支出。于是你被迫玩起荒谬的壳游戏，辩称没关系——不是双关语——因为数据中心建筑本身五年后会有价值。

And I hate to say this, but it's reminiscent in some ways of Bitcoin treasury for companies. So this idea that it made no sense that companies were like strategy, like MicroStrategy, Michael Sailor's firm, were being rewarded for putting Bitcoin into treasury. Their market value was increasing by $2 roughly for every dollar of Bitcoin they put into, quote, treasury. So we have the same perverse phenomenon happening here, which is that the market's rewarding you for doing this even though it makes no economic sense to spend at this level because there's no way I can recoup the value of the capital spending I'm making over the next three years. So then you're forced to do these kind of wacky shell games where you say, well, it's okay because the shell itself, not to use shell for two different purposes here, but the shell, the building itself, will actually be valuable in five years.

它仍会有能源，仍会有水源，仍能进行冷却，墙壁也依然矗立。我只需更换显卡。

It'll still have energy. It'll still have water. It'll still be able to cool things. The walls will still be standing. I'll just swap out the GPUs.

但正如我们最初讨论的，问题在于显卡占据了大部分成本。因此粗略来说，建筑结构是我愿意计提折旧的部分。我可不想每三年就因显卡报废而计提损失——毕竟它们占我们所谓数据中心成本的绝大部分。你不能玩这种资本游戏，说什么这些投入几年后仍有价值。再次强调，与电信业不同，与光纤热潮不同，与铁路建设不同，这里实际存在两种资产：一种是长寿命的建筑（仅占数据中心成本的极小部分）

But as we talked about at the outset, the problem is the GPUs are the majority of the cost. So the shell, to a first approximation, is the thing I'd like to write off. I would I don't wanna have to write off GPUs every three years because they're the most of the cost of the thing that we call a data center. So you can't play the game of saying, well, there actually is capital here that I'm money that I'm spending that will be valuable in a couple of years. Again, unlike telecom, unlike the fiber boom, unlike in railroads, there is actually two assets here, one that's long lived, a building, which is essentially a small fraction of the cost of the center.

另一种是极短寿命的显卡——我们本希望其使用寿命更长却事与愿违，但它们却占到数据中心成本的60%。这就是矛盾所在，也是问题根源。

And then there's one that's very short lived, which is the GPUs, which is the thing we'd like to have last and doesn't, but yet represents as much as 60% of the cost of the data center. So there's the perversity, and that's the problem.

在深入探讨这如何导致泡沫或崩盘之前，我想先谈谈当前对经济的影响。它正在吞噬技术岗位。马里兰大学研究发现，若从所有IT岗位中剔除AI相关职位，基本上整个IT行业都在萎缩。科技行业正大规模转变为对人工智能未来的就业豪赌。我还注意到，尽管关税政策名义上旨在推动再工业化，但美国的建筑、采矿和制造业岗位都在减少。

And before we talk really deeply about how this could lead to a bubble or a crash, I do wanna talk about how this is affecting the economy right now. It's eating tech jobs. There was a University of Maryland study that found that if you subtract out AI jobs from all IT jobs, basically, all IT is declining when you subtract out AI. Like, tech is just in large part becoming an enormous employment bet in the future of artificial intelligence. I'm also looking at the fact that, like, you know, construction jobs are declining, mining jobs are declining, manufacturing jobs are declining in America despite the fact that the tariffs are nominally about reindustrialization.

保罗，这给我的感觉就像AI是颗引力巨大的恒星，正从整个经济体中虹吸所有资源。用你自己的话来说——希望我的引导方向正确——你认为AI支出将如何扭曲2025年的经济格局？

It almost feels to me, Paul, like AI is like this like this like this star that is pulling in all of these resources gravitationally from throughout the economy. In your own words, and hopefully I got you started along the right track, how do you see AI spending warping the 2025 economy?

是的，我做的类比是回顾历史：1990年代对经济某个狭小领域的大规模资本投入，导致美国制造业——特别是小型制造业——的资金流失。有些优质研究准确揭示了这种效应。这并不令人意外，因为当时投资电信业的人获得了回报，他们因投入高回报领域而受益。

Yeah. So the analogy I draw is looking back, you can see how a similar effect happened. That is massive capital spending in one narrow slice of the economy during the 1990s caused a diversion of capital away from manufacturing and away from small manufacturing in The United States. There's been some good studies on this showing exactly the effect. And it's not surprising because people were rewarded for accepting that money to build out telecom and they were rewarded for spending that money because, look, I'm spending in an area with high returns.

但这导致小型制造商资金枯竭，使他们难以低成本融资，资本成本上升意味着利润率必须更高。与此同时，中国加入了世贸组织，关税下降。我们让本土制造商在很大程度上（虽非全部）因资本成本上升而难以与中国竞争——因为这些资金全被虹吸走了。

But what that did was it starved small manufacturers of capital, which made it very difficult for them to raise money cheaply, which raised their cost of capital, meaning their margins had to be higher. Now let's follow that along. During that same time, China had entered the World Trade Organization. Tariffs were dropping. We've made it very difficult for domestic manufacturers to compete against China in large part, not entirely, but because of the rising cost of capital, because it all got sucked.

你原本想用你的‘死亡之星’这个说法，结果整个行业都被吸入了电信这个‘死亡之星’。所以从某种诡异的角度来看，我们可以将九十年代制造业岗位的部分流失归因于电信行业——它就像个巨大的吸尘器，把经济中其他领域的资本全都吸走了。如今同样的现象正在重演。作为大型私募股权公司或任何形式的资本配置者，如果把钱投在数据中心以外的领域根本得不到回报。这就是为什么当你看到黑石、BlueOwl等大型私募机构或私募信贷机构的公告时，他们最热衷宣传的就是那些投向数据中心的数十亿美元巨额支票。历史再次重演。

Your was to use your your death star term, it got all got pulled into this death star of telecom. So in a weird way, we can trace some of the loss of manufacturing jobs in the nineties to what happened in telecom because it sucked it was the great sucking sound that sucked all the capital out everywhere else in the economy. The exact same thing is happening now. There is no reward for spending money if I'm a a large private equity firm, if I'm a any kind of large capital allocator anywhere else but in data centers, which is why if you watch the announcements from places like BlackRock or from BlueOwl or from any of the large private equity firms or private debt providers, the thing that they're making the most noise about and are most excited about are these giant multi billion dollar checks they're writing towards data centers. And so again, the same phenomenon.

假如我是一家小型制造商，希望通过关税带来的制造业回流获利（暂且不论关税政策的经济利弊）。当我以此为投资主题去融资时，准入门槛已大幅提高——这意味着我必须创造更高回报，因为资本方会拿我和那些能吸纳巨额资金的数据中心作比较。而数据中心看似能带来惊人回报，看看AI热潮和OpenAI的爆发式增长就知道了。结果我再次无意中扼杀了经济中的一大板块，就像九十年代那样。

If I'm a small manufacturer and I'm hoping to benefit from the onshoring of manufacturing as a result of tariffs. It's leaving aside whether they're good or bad economic policy, but I want to benefit from it. So I go out trying to raise money with that as my thesis. The hurdle rate just got a lot higher, meaning that I have to generate much higher returns because they're comparing me to this other part of the economy that will accept giant amounts of money, huge checks I can write for this to data centers, and it looks like the returns are gonna be tremendous because look at what's happening in AI and the massive uptake of OpenAI. So I end up star inadvertently starving a huge slice of the economy yet again much like what we did in the nineteen nineties.

这个解读太有意思了。主流叙事总说中国贸易抢走了我们的工作岗位，经济学家David Autor所称的‘中国冲击’把制造业转移到了中国，导致铁锈地带空心化。而你的观点是：对华贸易可能只是边缘因素，电信基建热潮同样抽走了本该投向制造业的资本，将其转移到科技领域。更有趣的是，当特朗普试图用高关税逆转‘中国冲击’时，我们却通过AI重现了当年的‘资本冲击’，AI成了新世纪的电信业。

It's such an interesting interpretation because the story that we tell is that trade with China took our jobs. The China shock, as economists like David Autur call it, moved manufacturing to China, and that is what's hollowed out the Rust Belt. You're saying, yes, trade with China might have been a factor at the margins, but also the telecom build out took capital once allocated to manufacturing and moved it to tech. And what's so interesting about that is if you fast forward to the twenty twenties, Trump is trying to reverse the China shock with the high tariffs. But we're recreating the capital shock with AI serving as the new telecom.

因此，特朗普政府非但没有扭转制造业衰落的局面，反而讽刺性地通过将资金从传统制造业导向AI的方式，加剧了制造业的困境。这个观点真令人深思。

So rather than reverse the conditions that led to the decline of manufacturing, the Trump administration is ironically recreating those conditions in a way that's hurting manufacturing even more with all of this money moving toward AI and away from traditional manufacturing. It's such an interesting idea.

没错，而且情况比这更隐蔽——需要些行业内幕才能理解。假设你是某家掌控5000亿美元资金的巨型私募机构，你最不愿意做什么？就是每次500万美元地投资制造业，因为光是跟踪这些五花八门的小公司就够让人头疼了。

Yeah. And it's even more insidious than that, and this requires some inside baseball. And it's insidious because let's say you're Derek's giant private equity firm and you control, I don't know, let's say you've got $500,000,000,000 burning a hole in your pocket. What do you not want to do? I do not want to allocate that money one $5,000,000 check at a time manufacturers because all I see is a nightmare of having to keep track of all of these little companies doing who knows what and everything else.

那我想要怎么做？我想开出300亿或500亿美元的巨额支票。这是外界对私募行业不了解的运作逻辑——资本配置方式千差万别。即便投资回报率相当，这些机构的合伙人也不愿给众多小制造商开小额支票，哪怕它们确实能与数据中心的预期回报竞争。因为说到底我是人类，不想同时担任40家公司的董事。

What would I like to do? I'd like to write $30 $50,000,000,000 checks or $30 I'd like to write a small number of huge checks. And this is a dynamic in private equity that people don't understand, that capital can be allocated in lots of different ways. But the partners of these firms do not want to write a bunch of small checks to a bunch of small manufacturers, even if the hurdle rate is competitive, even if they're operating at a level where they can compete against what the perceived return is on data centers because I'm a human. I don't want to sit on 40 boards.

于是形成了这种扭曲的机制：即便其他条件相同，实际也不平等。部分由于资本运作的内部逻辑，那些本可能从制造业回流中受益的企业反而陷入了更糟的境地。

And so you have this other perverse dynamic that even if everything else is equal, it's not equal. So we've put manufacturers who might otherwise benefit from the onshoring phenomenon at an even worse position in part because of the internal dynamics of capital.

那么能源方面呢？电价已经在上涨了。这场革命某种程度上才刚刚开始，而这些数据中心对能源的需求极其旺盛。你认为这会导致能源通胀演变成经济消费甚至政治问题吗？数据中心本质上被视为推高电价的杠杆，以至于普通民众会抱怨：为什么我的经济本质上成了AI的殿堂，而它唯一的作用就是让我更难在孩子睡觉时保持她房间69华氏度的温度？这种情况会如何发展？

What about the energy piece of this? So electricity prices are already rising. This revolution in a way is just getting started, and these data centers are incredibly energy thirsty. How much do you think this is gonna result in energy inflation that becomes an economic consumer and even political problem that these data centers are essentially seen as a lever on electricity inflation such that you've got, you know, your average Joe saying, why is my economy essentially a temple to AI, and all it does is make it harder for me to keep my child's room 69 degrees while she's sleeping? Like, how is that gonna play out?

这种情况已经开始以最奇怪的方式显现。最明显的是我们已经看到能源通胀，部分原因是消费者被数据中心'出价更高'——这有点像私募股权现象。作为电力公司，我当然希望接入一批大客户，因为他们便于管理、付款可靠且不会消失。但弗吉尼亚州农村郊区的普通居民？他们可能按时缴费，也可能拖欠。这本质上是大规模资本配置中出现的相同现象。

So that's already beginning to play out in the strangest possible ways. The most obvious way is that we're already seeing energy inflation in part driven by, again, consumers being outbid, if you will, by data centers because it's almost like the private equity phenomenon. If I'm a utility, I would love to have a bunch of large people I can put on, large buyers I can put on the grid because I can manage them, they're good for payment, they're not going to go away. But a bunch of people in some exurb in rural Virginia, yeah, I don't know, maybe they'll pay their bills, maybe they won't. So again, it's the same phenomenon that's happening at the larger scale in terms of the capital allocation.

我很乐意将这些大客户接入电网，因为付款有保障。但与此同时出现了扭曲现象——PJM最近的监管文件（虽被搁置）显示，这家东北部大型互联运营商提议在电网压力时切断数据中心供电，比如热浪或供暖期间。他们想通过这种'有需要就断电'的条款鱼与熊掌兼得：既接入大客户，又向居民保证'别担心，我们有应急条款'。

I'm perfectly happy to put these large buyers onto my network, meaning the power grid, because I feel like there's some security of payment. But there is this perverse thing happening at the same time, and we saw this in the PJM recent regulatory filing that got kind of ditched, but they were proposing to add people to their network. They're an interconnect provider in the Northeast, one of the largest, And they were proposing to add data centers to the grid with the proviso that any time the utility is under utility, the grid is under stress and I have to cut back because of a heat wave or because of heating or whatever else, I can disconnect the data centers because it's fine for a few hours if they disconnect the data center. And so they're trying to have their energy cake and eat it too by connecting these large bars but saying, it's Okay. Don't worry, consumers, because we have a provision in our agreement with these data centers to disconnect them if things become really difficult.

数据中心当然会拒绝：'这方案行不通'。仔细分析就能发现，这种无法简单调和的矛盾正在发酵：一边是能源通胀，一边是提议中不靠谱的互联协议——竟要求数据中心接受随时断电。这种条款根本不可能实施。

Well, of course, if you're a data center, you're like, yeah, no, that doesn't work for me. That's not going to work. And so you can see, if you look underneath the hood, how the tensions are beginning to play out in ways that cannot be resolved straightforwardly. We have energy inflation on the one side and we have these somewhat dodgy interconnection agreements being proposed where we propose that someone will actually be cut off from the grid, meaning a data center will be cut off from the grid. And that's just not it's not gonna fly.

即便我现在签约，两年后你若真断电，我100%会起诉你。诉讼规模将非常庞大——哪怕今天同意，两年后照样告你。

Even if I sign on to that now, rest assured, I will sue you in two years if you do it to me. 100%, these lawsuits will be just massive. Even if I agreed to it today, I will sue you in two years.

那么合理预测是什么？如果居民开始明确反对本地数据中心建设（视其为窃取能源或抬高电价的杠杆），而数据中心本身拥有巨大政治经济实力（作为资金雄厚的大企业），你认为两年内会如何发展？

So what's a reasonable prediction here if if, you know, consumers are going to, I think, start to be much more explicitly NIMBY about the construction of local data centers if they see these data centers as essentially not just you could either say it stealing energy or basically a a very clear lever on raising energy prices. The data centers have enormous political power of their own, enormous economic power of their own. These are large, rich companies that can spend a lot, pay a lot maybe for that energy. I mean, how is this gonna play out, you think, in two years?

我认为会快速出现数据中心离岸化趋势。印度、中东正在大规模新建数据中心，中国各地也是如此——最近中国政府甚至警告'不是每个城市都需要数据中心'，因为地方层面已出现过度建设。虽然就近建设数据中心有利于服务提供，但出于这种邻避心理，建设重点必将向海外转移。

So I think you're gonna rapidly see an offshoring of data centers. So that will be the response. It'll increasingly be that it's happening in India, it's happening in The Middle East, for example, where massive allocations are being made to new data centers, and it's happening all over the world in China where to the point that there was recently a warning from the Chinese government that every city does not need its own data center, that because what they're trying to do, obviously, is create a massive oversupply at local regional level. There's an incentive to create these things, and so you're seeing lags aside because it's nice to have a data center located locally to you in terms of actually providing services. Nevertheless, the focus will increasingly move offshore for exactly this sort of NIMBY esque reason.

彭博社前几天有一篇精彩报道，讲的是弗吉尼亚北部一个被数据中心包围的社区。这里原本是乡村地区，周围所有农场都被收购了。当地居民的反应是：等等，我该起诉谁？我从未同意这样。他们晚上出门会听到噪音，纷纷表示这不是当初承诺的生活。这正是不愿与邻为敌（NIMBY）现象的开端，因为人们开始产生强烈的情感抵触。

And there's been some great Bloomberg had a great story the other day about an excerpt in Northern Virginia that's essentially surrounded now by data centers. This was previously a rural area and everything around them, all the farms sold out. And people in this area were like, wait a minute, who do I sue? I never signed up for this. I never signed up because at night they would go outside their houses and they hear And it's like, didn't sign up for I didn't this is the beginnings of the NIMBY phenomenon because it's become, you know, visceral and emotional for people.

问题不仅在于价格。还包括身边这座六英亩的建筑日夜不停地制造噪音。这不是我当初选择的生活方式。我认为抵制已经开始，两年内会愈演愈烈。未来大型建设将逐渐转移到其他地区。

It's not just about prices. It's also about this isn't having this this six acre building beside me that's making this noise all the time. This is not what I signed up for. So I think the pushback has already begun, and it'll become much larger within two years. And increasingly, the largest construction will move elsewhere.

我想谈谈未来几年可能出现的负面情况。在讨论之前我要说明：当我说AI存在泡沫时，有人认为我在唱衰技术。但铁路曾出现泡沫（1857年、1873年、1891年恐慌），经历过多次萧条，却改变了世界。宽带也曾是泡沫。

I wanna talk about how some of this might go badly in the next few years, and I wanna preface that discussion by saying that when I talk about AI as a bubble, I think some people see me as being pessimistic about the technology. The railroads were a bubble. There was a panic of 1857, of 1873, 1891, I think. There were constant railroad depressions, and also the railroads changed the world. Broadband was a bubble.

但它同样改变了世界。重大基础设施建设在改变世界的过程中往往经历泡沫阶段。所以说AI目前存在泡沫并非悲观——从历史规律看，每次工业革命都会经历泡沫期。

It also changed the world. Right? Big infrastructure build outs that changed the world often pass through a bubble phase. So it's not particularly pessimistic to say that AI is currently in a bubble. You could say it's actually incredibly historically in tune to say that we could we are very likely in the middle of a bubble because every industrial revolution like this passes through bubble phases.

让我们从这里切入：超大规模企业（Meta、谷歌、微软这些巨头）在AI领域的投入与收入何时能平衡？

So let's start here. How close are the hyperscalers? Meta, Google, Microsoft, the the big boys. How close are they to aligning spending and revenue in the AI space? Right?

或者换个角度问：距离'AI收入能合理匹配AI支出'的目标还有多远？

Or how far, I guess, you could say on the other hand, how far are they from seeing what could be plausibly called AI revenue catching up with AI spending?

还差得远。首先我同意泡沫论。我的观点是：资本投入永远无法精准——总会先过度投入再回调。就像迈克尔·金斯利说的：在新设备上的资本支出永远不可能全程保持经济理性，最终总会超支然后收缩。

Nowhere near. I'll say first, I agree with you about the bubbles. I mean, my general argument is you never know if you've spent enough on capital so you spent way too much. So it's it's like Michael Kinsley used to say this sort of had a similar wording but the notion being that you're never going to have a rational expenditure of capital on new equipment and do it in a way that makes economic sense all the way up. Will eventually spend too much and then pull back.

那么我们就将此视为既定事实。正如你所说，这只是建设过程中的一部分。但更深层次的问题是，你是否会到达这样一个节点——很明显企业在某些方面已经捉襟见肘，比如我们熟悉的大多数上市公司，那些超大规模企业，正将高达50%的收入用于资本支出，这是前所未有的。正常情况下，如果我是微软或亚马逊这样做，绝对会被投资者严厉批评，因为这种投资规模不仅体现在资本支出上，更集中在某个狭窄的资本支出领域，你会因此受到惩罚。

So let's take that as a given. It's, as you said, it's just part of the process of building out. But the deeper issue is, are you going to get to a point where it's obvious that the companies are stretched in terms of let's take for example, most of the publics that we are familiar with, the hyperscalers, are spending as much as 50% of income on capex, which is unprecedented. This doesn't happen. Normally, I did that as a Microsoft or an Amazon, I would absolutely be taken to the woodshed and beaten by investors because that's such an incredible investment, not just in terms of capital expenditures, but on one narrow slice of CapEx that you're going to be punished for that.

但他们并未因此受罚。那么他们实际在做什么？这就涉及到你关于我们应该关注什么的观点。有种思考方式可以追溯到柴明斯基等经济学家的理论：当企业用于筹集资金的机制变得越来越不透明时，就是你需要警惕的信号。所以我关注的是他们如何将融资移出资产负债表，因为这反映出他们不愿让信用评级机构看到其开支情况。

So they're not being punished for that. So what are they doing instead? And this goes to your point about what we should be watching for in a sense. There's a way of thinking about it goes back to economists like Chaimaninsky and others that what you start looking for are whenever the mechanisms that they use to raise money to do this become increasingly opaque. So what I'm watching is how they're moving the financing off balance sheet because that's a way for me is a reflection of I don't want the credit rating agencies to look at what I'm spending.

我也不想让投资者将其合并到我的损益表中。因此我们越来越多地看到这些特殊目的载体（SPV）的创建，比如Meta在其中持有股份，某家大型私人债务/信贷提供商也持有股份。最终数据中心虽然归我控制，

I don't want investors to roll it up into my income statement. So what we're seeing increasingly are these SPVs, these special purpose vehicles, being created where I have a stake in it as Meta. Some giant private debt provider, credit provider has a stake in it. And yeah, okay, fine. The data center at the end is under my control.

但严格来说我并不拥有它。这样在评估我的信用状况时，你就不能将其合并回我的资产负债表。这不会影响我的信用评级，也不会改变我的收入。过去六七个月里，我们首次目睹了这类特殊目的载体和更复杂融资结构的涌现浪潮。

But hey, hey, hey, I don't own it. And so you don't get to roll it back into my balance sheet in terms of assessing my creditworthiness. It doesn't change my credit rating. It doesn't change my income. So we're seeing for the first time over the last six, seven months the beginnings of a wave of these special purpose vehicles and other more exotic financing structures.

我们看到类似于旧式债务抵押债券（CDO）的形式重现——把数据中心债务权益证券化。对我而言，这些都是泡沫开始疲软的初期迹象，因为市场开始惩罚（至少他们感知到会被惩罚）继续将这类支出留在损益表的行为。所以我选择将其转移到别处，这使得整个流程更加不透明，几乎是在刻意阻挠人们理解真相——比如我该如何从财务报表附注中梳理出这些信息？这才是需要关注的重点。

We're seeing the equivalence of some of the old collateralized debt obligations emerge where you're this tradable debt interest in data centers, these are all, for me, the beginning of the sign that the bubble is becoming tired because the market is beginning to punish at least their perception that the market will punish me if I continue to keep this on my income statement. So I won't. I'll move it somewhere else, and that makes the entire process much more opaque. It's almost defuscatory in terms of preventing people from understanding it, like how do I go through all these the footnotes of all of these statements? And so that for me is that's the thing to watch.

人们往往纠结于错误的评估角度，比如现在GPU租赁费率是否与数据中心运营成本相匹配？这类成本与租赁费率的对比确实值得关注。但要从企业角度思考：他们隐藏支出的力度有多大？

People get hung up on, I think, a lot of the wrong things in terms of trying to assess what's going on. Like, for example, is the rental rate of GPUs now competitive in terms of the actual cost of running the center? These are good things to look at, comparing your cost to your rental rates. But look at it from a company standpoint. How hard are they trying to hide the expenditure?

对我而言，这才是关键指标，而且这种趋势正在加速形成。

And for me, that's the factor to watch, and it's just begun accelerating.

我觉得那些记得2006年2月、2007年的人，听你谈论这项通用法律时眼皮都会开始跳——我特别喜欢你的表述方式。这就像是，你知道如果试图隐瞒行为就说明它不道德。你知道如果把经济活动包装成财务不透明，那就说明它充满泡沫。让我们具体聊聊这其中的运作机制。我...我在其他地方的采访中也见过你讨论这个。

I feel like people who remember 02/2006, 2007 are feeling their eyes start to twitch as you talk about this general law that I I love the way you put it. It's kind of like, you know your behavior is unethical if you try to keep it a secret. You know your economic activity is bubblicious if you try to dress it up in financial opacity. Let's talk about just exactly how this works. I've I've seen you talk about this in other locate in in other interviews.

我认为理解这些数据中心如何建设非常重要，特别是要明白事情并不像'哦，Meta的总体支出项目里就写着：我们在弗吉尼亚州阿什本附近买了块地建了个数据中心'这么简单。实际情况是像Meta这样的超大规模企业正在与阿波罗等私募股权公司合作，双方都往这个'盒子'里投钱——就是这些特殊目的实体，然后由这个实体来投资建设数据中心。请详细解释这具体是如何运作的。

I think it's really important to understand how these data centers are being built and specifically how it's not as simple as, oh, Meta just has a line item in their overall spending that says, and then we bought a bunch of land near Ashburn, Virginia and built a data center there. What's happening is the hyperscalers like Meta are getting together with the private equity firms like Apollo, and they're they're both putting money into this box, right, these special purpose vehicles, and that box is the thing that's investing in these data centers. Just take me through exactly how this works.

所以这个构想可以从几个角度理解：一方面，阿波罗等私募信贷公司想要持有数据中心股份，但他们希望投资的是已有稳定客户的数据中心。从他们的立场看，只要与Meta或谷歌这类企业合作，就能确保数据中心的使用率——会有租用收入源源不断回流，这正是他们想要的。

So if I don't so the the idea, is you can look at it from a couple of different ways. One is that the private credit firms, the Apollos and others, want a stake in data centers, but they also want their stake in data centers to be in a data center that has built in customers. So from their standpoint, I can write a large check and if I partner with a Meta or Google or whoever, there's a high likelihood that people will be using it. It'll be populated. There'll be rental income flowing back from it because that's what they want.

可以把它想象成债券利息——因为人们按小时付费使用这些GPU，产生的收益会作为数据中心的共同所有者回流给我。我追求的就是对这种租赁收入的分成权益，本质上和持有债权没有区别。现在有多方参与，部分原因是利益一致，但从这些上市公司的角度看，还因为只要持股不超过50%就不需要合并报表。这个前提至关重要——我既要实际控制权来使用和获益，又不要法律控制权，否则会影响我的信用评级、杠杆率，以及资产负债表上的债务权益比——这些对CFO来说枯燥但极其重要的事项。

Think of it like interest on a debt note, that there'll be interest flowing back because people are paying for hourly usage of these GPUs and that flows back to me as a partial owner of this data center. And that's what I'm looking for, a stake in that rental income, no different than having a stake in a note that I've extended to someone else in the form of debt. So now I have multiple people participating in part because their interests are aligned, but also from the standpoint of these individual public companies because I don't have to roll it up into my income statement if I control less than 50% of it. So that's a really important proviso that I want de facto control because I'm actually using it and benefiting from it. But from a legal standpoint, I don't want legal control because then that flows back and I have to deal with it from the standpoint of my credit rating in terms of the leverage, the amount of debt I have on my balance sheet against my equity, and all of these things that are really mundane and boring but matter immensely to CFOs.

所以从他们的立场看，与大型私募信贷公司合作创建这些定制化的特殊目的实体——这些我们共同签署加入的一次性载体来建设数据中心——非常理想。这样既能获得想要的新数据中心，又避免了信用评级受损。在当前支出已达历史峰值的情况下，这种模式创造了巨大的激励来持续复制。

So from their standpoint, the idea of partnering with a large private credit firm to create these bespoke special purpose vehicles that are these one off vehicles that we all sign up for and we join in and the data center gets created, they're great because now I get what I wanted, which is a new data center, and I don't get what I didn't want, which is a hit to my credit rating. So there's a huge incentive to create these and create more, especially given that we're already at these historical limits in terms of the amount of spending we're already making. So there's a huge incentive to put it somewhere else.

让我试着复述以确认理解：Meta想建造这些巨型AI数据中心，项目总成本高达数百亿美元。尽管Meta很富有，但他们不想通过常规方式借款，也不愿让这些支出直接体现在资产负债表上。

Let me try to restate this so I understand it. So Meta wants to build these gigantic AI data centers. These projects cost tens of billions of dollars altogether. Even though Meta's rich, they don't wanna just borrow all the money the normal way. They don't want the spending necessarily on their balance sheets.

于是他们通过创建我说的这种'特殊盒子'来解决问题：Meta投入部分资产，其他私募投资者投入资金，现在这个特殊目的实体就能对外借款、支付建设费用并拥有数据中心所有权。是这样吗？

So they solve the problem by creating, like, this special box, as I put it. Meta put some assets into the box. Another private investor put some money in the box. And now that box, that special purpose vehicle, is going out borrowing money, paying for construction, and owning the data center. Right?

表面上来看，可以说大家都挺高兴的。对吧？Meta既赚到了钱，又没搞乱资产负债表。投资者呢，也能获得高回报，而且由于他们基本是和Meta合作，风险看起来也不明显。但如果我们建了太多数据中心会怎样？

On the surface, I guess, could say everyone's happy. Right? Meta gets money without messing up its balance sheet. The investors get, you know, high returns, I guess, without obvious risk because they're basically working with Meta. But what happens if we build too many data centers?

对吧？Meta首当其冲。私募股权公司可能更关键，它们也会受冲击。也许某些房地产信托基金也逃不掉。这意味着有限合伙人（LPs），就是那些往私募基金投钱的人，同样会被波及。

Right? Meta's exposed. The private equity firms maybe more importantly are exposed. Maybe some of these REITs are exposed. And that means the limited partners, the LPs, whoever's putting the money into those private equity firms, they're exposed as well.

就像回溯到2006年2月、2007年2月时我们在想：如果这整座纸牌屋倒塌，谁会受伤？你可能会说贝尔斯登啊，AIG啊。现在请告诉我，如果AI资本支出领域出现严重放缓或大幅收缩，哪些类型的公司会最受影响？

So the same way that, like, if you were going back to 02/2006, 02/2007, we were thinking, if this whole house of cards comes down, who's hurt? You could say, oh, it's Bear Stearns. Oh, it's AIG. Like, give me a sense of the kind of companies that would be most exposed if we saw a significant slowdown in the AI CapEx world or some kind of significant pullback here.

没错。虽然不想说得太像对冲基金，但真正受益的公司其实在建筑行业和空调领域。以开利公司为例——如果我正在以前所未有的规模为巨型数据中心建造工业级空调系统，我最想做什么生意？当然是卖空调给他们，因为给这些建筑降温是个大难题。作为工业空调供应商，这简直是天赐良机。

Yeah. So not to go full hedge fund, but if you think about it in terms of the companies that have really benefited, they're in construction. They're in air conditioning. So for Carrier, for example, think about them as being a if I'm building out industrial class air conditioning for giant data centers at an unprecedented scale, what business would I really like to be in? I want to be selling them air conditioning because cooling those buildings is a huge problem, and it's great if I'm an industrial provider of industrial air conditioning, for example.

这类公司虽不起眼，却是这波建设潮的大赢家。先抛开你我这些AI的受益者，想想建筑供应商、设计公司、物流承运商和空调供应商——所有那些产品最终帮助把一块地皮变成能塞进GPU的运转外壳的人。他们都乐在其中。但讽刺的是，作为个人投资者你可能会说：干脆让他们全完蛋吧。

So these are the kinds of companies that aren't as obvious but are huge beneficiaries of this build out. So leaving aside you and I as beneficiaries from AI, think about the construction providers, architectural providers, think about the carriers of those worlds and the air conditioning providers, and all of these people whose products end up helping turn a piece of real estate into a functioning shell into which I can insert GPUs. And all of them are delighted to be participating in this. But then there's the perverse fact that you as an individual investor might say, well, you know what? Let them all burn.

如果情况恶化，那是开利、那些私募公司、信贷机构甚至Meta他们的问题。但现实不会这样发展。部分原因是这推动了经济增长——我们讨论过这点。但更因为这些通过特殊目的实体进行的投资，以及其他数据中心相关支出，正越来越多地出现在房地产信托基金（REITs）里。

If this goes bad, it's their problem Carrier or these private equity firms or the private credit firms or even Meta and whoever else. But yet, it's not going to work out that way. And the reason why it's not going to work out that way is in part because it's driving economic growth. And we've talked about that a little bit. But it's also because increasingly these investments in special purpose vehicles and other related data center spending is showing up inside of things like REITs, so real estate income trusts.

现在美国任何大型REITs内部，已有10%-22%的比例直接与数据中心相关。如果你是个保守投资者，持有REITs是因为觉得'我才不碰那些疯狂的科技玩意，商业地产最稳妥'——建议你仔细看看自己持有的REITs成分。

So if I'm creating a if you look inside of any large REIT in The United States today, somewhere between 1022% of it is already directly data center related. So if you're a conservative investor with a REIT in your portfolio because you're saying, you know what? I don't care about any of that crazy tech stuff. I'm going be over here safe as houses, commercial real estate or whatever else, getting real estate income. Go have a look inside your REIT.

看看今天里面实际有什么。两年前，那里还没有任何与数据中心相关的内容。如今一些最大的项目中，我们已达到20%，22%直接与数据中心相关。所以，你懂的，你已经沉浸其中了。老兄，你已经身在其中了。

See what's actually in there today. Two years ago, there was nothing in there that was related to data centers. Some of the largest ones today, we're up to 20%, 22% is directly data center related. So, you know, you're soaking in it. You're already in there, my friend.

好吧，那么把这些都整合起来。对吧？假设你是个典型的老派投资者，保守型投资者。你在房地产投资信托基金(REITs)里投了些钱。

Well, and then putting this all together. Right? Let's say you're you're a typical you're an older investor. You're conservative investor. You've got some money in REITs.

你以为这只是你常规的、基本的投资工具。而现在你说这些REITs中有10%到20%直接或间接与数据中心挂钩。

You think this is just sort of sort of your meat and potatoes investment vehicle. And now you said between 1020% of these REITs are directly or indirectly tied to data centers.

他们管理资产的10%或20%。所以几乎所有REITs，但他们管理资产的10%或20%。

10 or 20% of their assets under management. So all REIT pretty much all of the REITs, but 10 or 20% of their assets under management.

关于管理资产。好的，你说得对。这些REITs管理资产的10%到20%投资于数据中心。你25分钟前告诉我数据中心成本70%是GPU，实际上意味着这些REITs基本上大量投资于英伟达。

To Asset under management. Okay. So you're right. So so 10 to 20% of these REITs assets under management is in data centers. You told me twenty five minutes ago or whatever that data center costs are, like, 70% GPUs, which means in effect that these REITs are basically just, like, significantly in NVIDIA.

对吧？我是说，这些祖父母辈的投资者甚至不知道自己投资了英伟达，实际上就是英伟达的投资者。这意味着英伟达的走势直接影响他们的投资组合。这似乎也是很重要的一部分——要知道美国经济规模高达35万亿美元，其季度增长无论是股票还是GDP，很大程度上都取决于英伟达的表现。现在经济增长的很大一部分基本上就是看芯片销售情况如何。

Right? Like, I mean, these grandparents who, like, don't even know that they're, like, NVIDIA investors are, like, investors in NVIDIA, which means as Nvidia goes, so do their investment portfolios. I mean, that also seems like a significant part of this, which is that, like, you know, you've got this enormous US economy, $35,000,000,000,000, and it's like a significant amount of its growth on a quarter to quarter basis, whether it's equities or GDP, like, balances on the narrow read of, like, how's NVIDIA doing? It really it it just seems like that, like, an enormous share of economic growth right now is, like, basically, how are we doing with with chip sales?

没错。虽然不好笑，但确实有点滑稽。想象一下你感到害怕——我是个风险厌恶型投资者，然后我说：知道吗？

Yeah. Absolutely. And it's well, it's it's not funny, but it is kind of funny. But imagine you got scared. I'm a I'm a risk averse investor, and I said, you know what?

我只投资指数基金。一两年前有人告诉你，知道吗？你可能以为自己很规避风险，但标普500指数30%的权重现在都绑在所谓的'科技七巨头'股票上。实际上你重仓了英伟达，而且是大幅重仓。

I'm only in index funds. And so a year or two ago, someone told you, you know what? You may think you're being risk averse, but 30% of the S and P 500 is now tied to what's euphemistically called the Mag-seven stocks. You're actually long Nvidia. You're long Nvidia in a huge way.

你会说'我要退出标普500，只投资房地产信托基金这类安全资产'。但现在问题在于无处可逃——越来越明显的是你根本无处躲藏。而且通过后门方式，退休基金现在也被允许投资私募信贷了。

You're like, oh, I'm getting out of the S and P 500. I'm going only into really safe stuff like REITs. So now it's sort of this problem of there's nowhere to run. It's increasingly the case that you've got nowhere to run. And in a backdoor kind of way, private credit now is now allowed inside of retirement funds.

你会发现这些资产正以其他形式渗透，不仅是房地产信托基金。比如作为散户投资者，我投资私募信贷时以为自己在投资爱荷华州某制造商的私有化业务。其实不是——你投资的是数据中心。而通过投资数据中心，你间接又持有了英伟达。这个系统很复杂，但存在单一故障点。

You're seeing increasingly these showing up in other ways, not just as REITs, but let's say I'm an investor in private credit thinking that as a retail investor, I'm now investing in, I don't know, take private operations for a manufacturer in Iowa. No, you're not. You're in data centers. And by proxy, by being in data centers, you're also in Nvidia. So this notion of it's a complex system, but there is a single point of failure.

这个单一故障点就是几只半导体股票。它们高度杠杆化地关联着所有领域，却像癌细胞般从标普500扩散到房地产信托基金，再到私募信贷，又通过后门进入新型私募信贷ETF。这种渗透极其隐蔽且严重，但大多数人甚至没意识到它已深入骨髓。

And in this single point of failure is a couple of semiconductor stocks who are highly leveraged to everything that's going on and yet have kind of metastasized across each of these pieces from the S and P 500 to REITs to private credit to backdooring their way into new private credit ETFs. It's it's incredibly insidious and important, and yet most people haven't even realized how deeply it's it's insinuated itself.

沿着这个思路继续深入，你认为泡沫会是什么样子？会出现哪些新闻头条？

So going further along this particular train of thought, what does a bubble look like to you? What are the news headlines?

我认为新闻头条首先会是'未来数据中心建设的最大份额都通过特殊目的载体进行'。对我来说，泡沫的标志就是人们说'看啊，现在都采用合作模式了，对Meta和亚马逊来说风险小多了，他们在搞合作'。

So I think the news headlines are, for starters, it would be the largest share of future building in terms of data centers is all through SPVs. So for me, it's people saying, oh, look, it's now all being done in partnerships. It's not as risky for Meta. It's not as risky for Amazon. Look, they're partnering.

在我看来这就是泡沫达到临界点的特征——我们需要高度警惕，因为企业正在激进地抽身，他们预见到了潜在影响。另一个预警信号是配套设备的交付延迟，比如对数据中心至关重要的空调系统和互联设备（用于连接机架和GPU）。这类延迟曾达到四五个月。如果这种延迟再次出现，我会密切关注——因为这意味着'既然能拿到货了，说明需求在放缓'的反向信号。

For me, that would be the hallmark of a bubble that's hitting the point of, okay, we need to really be paying close attention because the companies themselves are stepping away so aggressively because they see the effect this might have on them. And the other thing to watch for is delays in terms of the the provision of air conditioning and other of these ancillary equipment that's incredibly important. Interconnect gear for interconnecting racks and GPUs inside of these centers. Delays at one point were going out to four and five months. If that continues to come back, I'd be watching that because now it's the reverse phenomenon where it's like, oh, wait, if I can actually get stuff, that must mean things are slowing down.

因此，如果你突然听说某款工业级空调销量下滑，这些都是需要警惕的信号。他们今天业绩不佳的唯一原因，就是失去了数据中心这个客户群体。若非如此，他们的业绩本可以一飞冲天。真正需要关注的是这些边缘迹象，而不是听信什么'我姐夫试用OpenAI后就不喜欢了'之类的闲谈。或者回到你最初的观点——没错，AI确实在抢夺工作岗位，人们越来越感到威胁，尤其是白领阶层，比如软件行业，可能还包括法律等领域。

So these are things to watch for if you suddenly hear about any industrial class air conditioner suddenly missing their numbers. Well, the only reason they're going to miss their numbers today is because they don't have data centers to sell to. That's the only reason because otherwise, they're going to blow the doors off from now into eternity. So these are some it's these things at the edges that you need to watch as opposed to saying, you know, my brother-in-law tried OpenAI and doesn't like it anymore. Or, you know, or even to go back to your original point, yes, AI is stealing jobs probably, and people are increasingly being feel threatened, especially in white collar jobs, especially in areas like software, maybe in law and someone else.

但更大的风险在于：资本正从小型制造商那里抽离，这些企业本可能回流本土并创造就业，现在却被迫承认'我无法与之抗衡'。这又回到我常说的观点——糟糕的政策决策往往就是这样形成的。如果有人对你说'经济疲软'，但二季度增长了3%根本不弱，那是因为他们没算清数据中心相关投资的占比，也没意识到这种支出的短暂性。虽然这个比喻很蠢，但我还是要再说一次：搞错因果关系就像我家的狗——

But the bigger risk remains this great sucking sound of capital being pulled out of small manufacturers who might otherwise be on shoring and employing people and are now forced to say, wait a minute, I can't compete against this. So this goes back to a point I make all the time about this stuff, which is that this is how you end up making bad policy decisions. So if you say to yourself, oh wait, people say the economy is weak, it grew 3% in the second quarter, it's not weak at all. Well yeah, but you're not factoring in how much of that was tied to data centers and how transient that spending is. And I make this stupid joke all the time but I'll make it one more time which is that when you having messed up causality in terms of understanding the causal nature of what's going on is a little bit like my dog.

每次邮差上门它都狂吠不止，等邮差走了它就得意洋洋，觉得是自己吼跑的。不不不，邮差本来就要走的，你吼再久也没用。

He barks every time the mailman comes to the house, and then he keeps barking and the mailman goes away. And he's like, dude, I totally have this. If I bark long enough, the mailman goes away. No, no, no, the mailman goes away every time. It doesn't matter how long you bark.

所以狗的因果认知完全错误。我们当前对经济增长动因的理解，就像那只乱吠的狗。以为是关税政策，以为是其他各种因素，其实都不是。这种扭曲的激励让人持续犯错，只因表面看来'方法有效'。

So dog's notion of causality is completely wrong. We're like that barking dog in terms of understanding the drivers of economic growth right now. We think it's because of tariffs. We think it's because of all of these other factors, and it's not. So there's this perverse incentive to keep doing the wrong things because, look, they're working.

而所谓'有效'，不过是因为没人深究真正的驱动因素。

And they only are working because no one's going down deep enough to understand, wait a minute, it's being driven by completely different things.

经济评论员诺亚·史密斯曾撰文探讨数据中心衰退演变成真正金融危机的可能性。我很想听听你对这个逻辑链的评价：第一，主流叙事强调'这次不同'，认为AI将颠覆所有技术；第二，大量持续增长的债务集中投入单一领域，导致贷款违约概率高度关联——一笔违约往往预示连锁违约；

The economic commentator, Noah Smith, wrote a piece about what it would look like if a data center slowdown became a true financial crisis. And he put it this way, and I would just love to to hear you evaluate this particular logic. He said, you know, number one, we've got this big story about how this time is different, that that AI is going to be the technology to overtake all technologies. Number two, we've got a large and increasing amount of debt being used to fund one single sector, and that means that the loan's probability of default is highly correlated. If one loan defaults, it means there's probably others that are gonna default as well.

第三，正如你所说，金融体系中不透明的私人信贷规模激增；最后，系统重要性机构（银行甚至保险公司）深度介入——我记得寿险公司正是你提到那些信贷机构的重要有限合伙人。当这个新兴领域可能面临收缩时，你认为这些要素在多大程度上构成了真正的金融危机配方？

We've got an opaque corner, as you've said, of the financial system with private credit that's grown a lot. And finally, we have systemically important lenders, banks, and even insurance companies. I believe life insurance companies in particular are significant LPs to some of these some of these private credit firms you've talked about, and they're enmeshed in this new sector that that might see a drawback in the near future. To what extent do you think that this represents the ingredients for an actual financial crisis?

哦，这绝对有关系。所有环节都齐备了。我就挑你提到的一个点稍作调整来说，比如与保险业的联系就非常清晰可见。过去几年发生的情况是，与其说保险公司是这些私募信贷机构的大额有限合伙人（即主要投资者），不如说情况恰恰相反。

Oh, it absolutely does. It has all the pieces. So I'll pick on just one that you mentioned, and I'll just flip it slightly, which is that the connection, for example, to insurance is very clearly understood. So what's happened over the last few years, it's not so much that insurance companies are large LPs in these private credit providers, meaning that they're large investors in them. It's the other way around.

实际发生的是私募股权和私募信贷收购了保险公司，他们称之为'自有资本来源'，意思是保费收入被重新投资到私募基金的业务中，而这些资产又可被用于投资数据中心或其他任何选择。但这里存在一个自贝尔斯登和金融危机时代就有的问题：典型的期限错配。债务到期时间、付款时间与提供服务时间之间存在时序差异。数据中心相对是短期资产，而另一边的保险保单持有人义务却是长期性的。

So what's happened is private equity and private credit have purchased insurance companies because and they call it the term of ours, they called it a captive source of capital, which is to say the premiums get reinvested in what the private equity firm is doing, and I can use those assets in turn to invest in data centers or whatever else I choose to do. But what we have and this goes back to the time of Bear Stearns and the financial crisis. We have a classic temporal mismatch, a timing mismatch in terms of when the debt comes due and when I have to make my payments and when I provide things. You can see how the data centers are relatively transient. But on the other side, I've got these obligations to my insurance policyholders, which are longer term.

因此我的资产与负债在期限上严重错配，这与金融危机时期贝尔斯登的情况如出一辙——他们长期放贷却短期负债，最终因此崩盘。你可以看到同样的危机会通过看似与数据中心无关的后门爆发，因为这些债务提供方（私募信贷机构）的资金来源日益绑定于一个义务与数据中心回报不匹配的行业——即越来越多被私募基金持有的保险公司。当前经济中驱动这一切的资本结构本质已变，却远未被充分认知，这种期限错配正在制造新的风险源头。

So I have mismatched assets and liabilities, wildly mismatched on a temporal, on a time horizon, no different than what happened way back during the financial crisis, which did in Bear Stearns, which was they had lent long and owed short, right? And so they ended up blowing up on that basis. So you can see how the same thing would happen through a backdoor that doesn't look like it has anything to do with data centers. It's because the nature of the funding of the providers of this debt, private credit firms, is increasingly tied to a sector whose obligations don't match the returns from the data centers and that specifically is insurance firms which are increasingly owned by private equity firms. And that's not nearly well understood enough that the nature of the capital structure in the economy that's driving this has changed, and that's created a new source of risk because of this temporal mismatch.

你认为我们关于泡沫的论断最可能出错的地方在哪里？比如假设迈克尔·塞姆比斯参加这个会议，他可能会说：这些公司拥有的自由现金流是现代资本主义史上任何企业集团都无法比拟的。

What's the most likely way that you're wrong or that we're wrong? That, like, the case for the bubble has some error in it. Right? Like, I could imagine, like, if maybe if, like, Michael Semblis was on this call, he'd say, look. These companies have more free cash flow than any group of companies in the history of modern capitalism.

它们能够承受多年持续巨额的基础设施投入，仍能保持高盈利，因为无论是广告销售还是微软涉足的任何业务组合，其根本商业模式都具备极强的抗压能力。它们现在就在承受这种冲击，这是第一点。第二点，或许这项技术比你我现在认为的更接近能产生重大收益的突破点？

They can withstand enormous, enormous amounts of infrastructure spending for years and years, and they'll still be highly profitable because their fundamental business models, whether it's ad sales or, you know, whatever collection of of businesses you could say, you know, Microsoft is in, they can withstand an enormous hit to their balance sheet. They are withstanding it right now. That's number one. And number two, maybe this technology is closer to a breakthrough that will yield significant income than you and I think at the moment. Right?

就拿现在OpenAI的盈利模式来说，它们通过订阅服务和企业合作赚钱，但或许它们正处在爆发前夜，即将形成年收入千亿美元的业务——那样自然就能覆盖所有训练和推理的投资。你觉得我们最可能错在哪个环节？

Like, right now, when I think about, like, how OpenAI makes money, you know, they've made money from subscriptions. They make money from their business relationships. But maybe they're on the cusp of something that's, like, about to become, like, a $100,000,000,000 annual business, in which case, of course, that's going to pay for all of their investment in in training and inference. What's the most likely way that you're wrong?

我和迈克尔·塞姆比斯讨论过这个问题，所以我来告诉你...

So I've had this discussion with Michael Sembliss, so I'll tell you so Tell me tell

我如何曲解了他的论点。所以事情是这样的

me how I mischaracterized his argument. So here's what

我们听到的是，讨论的核心在于当前我们通过出租GPU获得的收入与数据中心成本之间的差异。假设我每小时租金35美元，成本是12美元，扣除空调电费和债务净额后，每小时有23美元的差额。假设未来两年这个差额减半。

we hear. The nut of the discussion we had was about this difference between what we're earning right now, what a data center earns on renting out GPUs versus what its costs are. So let's say I can rent for $35 an hour and it's costing me $12 an hour. The combination of air conditioning power and the net of my debt on this, that's a $23 per hour gap. So let's say that gets halved over the next two years.

即便如此，相比数据中心的租赁成本，这仍是巨额溢价。虽然资本涌入会带来冲击，但作为商业地产投资，考虑到成本之上的溢价收益，仍然极具竞争力。这个论点完全合理——可以说我们过去每小时能获得25到30美元的纯利润，即便减半，兄弟，那仍是笔大钱。

That's still a huge premium over the costs, the rental cost of these data centers. So as much as you might say the capital flowing into this is going to cause a big hit, it's still very competitive as a commercial real estate play, if you will, in terms of the amount of premium I'm earning on top of my costs. And that's perfectly sound argument. You could make that argument and say that, yeah, we've earned we used to earn, I don't know, 25 or $30 an hour of straight margin on top of the cost of these data centers from a rental standpoint, and that's going to get cut in half. But bro, that's still a lot of money.

这是对方阵营的普遍观点：即便GPU资产租赁利润率急剧下降，仍不影响最终收益。但问题在于，这没解决根本问题——这些租金收入从何而来？我接触的大多数人（普通消费者）并不为ChatGPT付费，对吧？

That's the argument you will get from many on the other side of this, that even a sharp decline in the margins on the rentals of these GPU assets still doesn't affect the amount that I'm going to get back. Now, the problem with that is it doesn't get to the question of, Okay, fine, where is that money coming from? Where is the money coming from that's the rental? The rental price is coming from somewhere. Most people I talk to are not most people you probably you know as well, typical consumers are not paying for ChatGPT, right?

部分企业确实在付费，ChatGPT也建立了不错的业务，但他们未来两年预计仍将亏损约1000亿美元。深层问题在于当前存在巨大补贴——数据中心租金来自那些经济模式尚未跑通且短期内无改善迹象的企业。作为数据中心提供商，他们确实持续获利，但这本质上反映了租用方即使享受半价仍获得巨额补贴。

Some enterprises are and others, and ChatGPT has built a nice little business on it, but they're still going to burn what was it I lost, like 100,000,000,000 over the next two years I think was the number. And so the deeper problem is there's a great subsidy going on right here. So the data center rental income is coming from people whose economic models currently don't work and they show no sign of it working in the near future. So yeah, they're continuing to earn margin as a data center provider because of the monies that they're being spent, but that still reflects a massive subsidy to the people who are paying the data centers even at half off prices. And so for me, that's the way I'd be wrong.

我可能犯错的地方在于：利润率未必持续下跌到与运营数据中心成本上升、租赁价格下降形成死交叉的程度。我认为两者终将趋同导致行业变成沉没成本，但对方观点是：成本将持续优化，服务商会找到高利润业务支撑租金价格。

The way I'd be wrong is that margin doesn't continue to decline, that even though it declines, it doesn't decline back to the point where it's no longer economically viable given rising costs of operating a data center and declining costs or declining prices of being able to rent them, that those two don't come into line. I think they're going to come into line and it's going to become a deadweight loss business. The argument from the other side is no, it won't. Costs will continue to improve. The providers of these services will find high margin businesses that will support those rental prices.

来自私募信贷和风投的事实补贴维持着现有价格，这种支付能力不会消失——这就是对方的论点。

The facto subsidy from private credit and venture capital and others that allow these prices to stay so people continue to pay, that's not gonna go away. That's the argument from the other side.

根据你所描述的数学模型，什么时候可以合理预期系统会出现某种崩溃？比如，你现在无法直接看出问题，现状似乎基本维持。但当你看到这些大公司拥有的自由现金流规模、它们在基础设施上的支出水平，以及为了保持技术前沿每两到三年就必须更新一代GPU的事实时，对你而言这个数学模型何时会失去合理性？

Based on the math that you're describing, when is it reasonable to think that some kind of break could appear in the system? Like, you you can't look at it right now and say, oh, like, things are starting to break. It it seems like it's basically status quo. But when you look at the amount of free cash flow that these biggest companies have and their spending levels on infrastructure and the fact that they're going to have to buy essentially each generation of GPUs every two to three years in order to stay up to the frontier, When when does the math stop making sense for you?

我先做个简单预测。按照当前衰退率推算，大约两年半后这些公司将无法获得与数据中心运营成本相匹配的风险调整后收益。这意味着它不再是一项生产性投资，因为租金收入已不足以覆盖你刚才描述的所有成本——不仅是建造数据中心，还包括建成后持续翻新、重建数据中心内的GPU集群。简单预测显示约两年半后会出现这种情况。除非企业在AI服务销售收益方面发生实质性变化，否则很难想象这个时间不会来得更快。

So I'll start with a naive projection. So a naive projection given current decline rates would put you into about two and a half years out where they're no longer earning a risk adjusted return commensurate with the cost of doing business as a data center, meaning that it no longer becomes a productive investment because I'm not earning enough in rental prices to compensate for the cost of doing all of the things you just described. Not just building the data center, but having built the data center, continuing to refurbish, continue to rebuild the GPU constellation inside of this data center footprint. So a naive project will put you out like two and a half years. It's hard to imagine, absent something changing materially with respect to the the amount that companies are earning from selling the AI services, that it doesn't happen even faster than that.

所以我猜测两到两年半内，我们会突然看到这两组数字高度趋同，那时你就必须认真思考：我看不出这种状况如何能持续下去。补贴消失，数据中心建设停止，这些动态要素中必然有部分会在那时终止——因为如果无法获得有竞争力的回报率，这就和运营一栋维护成本高于律所租金收入的写字楼没有区别。

So my guess is two to two and a half years we'll see a we'll suddenly see these two numbers come very close into alignment and that's when you really have to be saying to yourself, I don't see how this can continue at that point. The subsidy goes away, data center construction stop, something in this these these moving pieces has to stop at that point because if you can't earn on that rate a competitive rate of return, it's no different than having an office building whose costs are higher than the amount I'm able to rent it out to to my favorite law firm.

虽然不想混淆话题，但两年后我们将迎来民主党总统初选辩论，两年半后则处于2028年大选周期中期。因此AI泡沫开始破裂与2028年大选的相互作用，很可能会让2028年的新闻周期异常混乱。我想以积极态度结束讨论，因为和你一样，我认为这项技术堪比铁路和宽带——虽然现在明显处于泡沫状态，但预测泡沫不等于预测它不会对世界产生影响。

And, not to blend subject matter here, but, two years from now, you're gonna have, the debates in the democratic primary for president. And two and a half years from now, you are in the middle of the twenty twenty eight election cycle. So I think the interaction effect between an AI bubble beginning to pop and the twenty twenty eight election could certainly put us in line for for quite a chaotic news cycle in 2028. I wanna end on a positive note because I think you, like I, do see this technology as akin to the railroads and broadband in that it's almost certainly in a bubble dynamic now. But predicting that something is a bubble is not the same as predicting that it will have no effect in the world.

我认为这很可能最终会成为2030年代最具决定性的重要技术。目前你最看好或最感兴趣的AI应用领域是什么？

I think that this is probably gonna end up being conclusively and definitively the most important technology of, let's say, the twenty thirties. Where are you most bullish on or interested in the application of AI at the moment?

我最近写了篇相关文章提到：ChatGPT就像是原罪——人类总会被类人事物吸引。从最早的在线虚拟心理医生Eliza（它会反问'你为什么这么想？'）开始就是如此。ChatGPT将这种拟真度提升到新高度，它太像人类了，以至于我们想和它做朋友。因此这些工具最有趣的应用——包括大语言模型、预测性token等所有技术术语——都存在于更深层面。

So I wrote a piece recently related to this where I said, I think we went ChatGPT is kind of the original sin, meaning that we as humans get sucked into things that sound like us. You know, dating back to Eliza, the original fake psychologist online where you could ask him questions and it would say, why do you feel that way? ChatTPT is that to a different level of verisimilitude. It sounds so much like us that we want it to be our friend. So the most interesting applications of these tools and of this whole idea of large language models and predictive next tokens and all the technical gobbledygook is at a deeper level.

想象我是个小制造商，要引入一批新供应商。他们各有不同系统，我得雇人在后台处理：'他们说邮编时不一定带连字符，这该怎么处理？'这些人工工作不仅构成岗位，更阻碍了更具竞争性的市场格局形成。

Think about I'm a small manufacturer and I'm trying to bring on a bunch of new suppliers. All of them have different systems. I got a person who sits in the back office and tries to say, whenever they say zip code, they don't always have a dash. What do I do with that? These are all things that people do that not only is it a job, but it prevents a more competitive landscape emerging.

我不想对接20家供应商，因为引入新供应商实在太困难了。想想企业间那些底层枯燥的沟通方式，就像英语、法语、西班牙语一样。这正是大语言模型擅长的领域——它们通晓语法规则，能预测下一个词元。

I don't want to have 20 providers because it's too hard to bring on new providers. If you think about the ways that companies communicate with each other at a very low and boring level, it's kind of like English, French, Spanish. It's the things that large language models are good at. They know the grammar. They can predict the next token.

它们会说：对对对，那就是邮编。虽然看起来不像，但那确实是邮编。诸如此类非常琐碎的事情。我认为这个领域前景巨大。实际上我们正在考察该领域一家潜在投资对象，但广义上说，这些模型能高效处理所有这类'语言'是最合理的。

They say, yeah, yeah, yeah, that's a zip code. I know it doesn't look like a zip code, but that's a zip code. All these kinds of very mundane. So think about that as one of the areas that I think there's huge promise. I actually think that this is an area where we've got a company that we've been looking at in this area as an investment, but it just broadly makes the most sense that these are all languages that these models can handle really effectively.

关键就在这个层面。我们曾沉迷于'它们说话太像人类了，这肯定很重要'的错觉。这其实是条死胡同，正如你看到上市公司纷纷退缩并承认：'上季度我们给所有产品都加了聊天功能'，分析师问效果如何时，得到的回答却是'没啥变化，毫无起色'。

And it's at that level. We got sucked into the idea of they sound so much like us, this must be super important. That's kind of a dead end because you can only be as you watch public companies increasingly pulling back and saying, oh, we added a bunch of chat stuff to all of our products last quarter, then analysts asked how that's doing. Yeah, not so much. Nothing's happened.

人们并不需要所有东西都附带聊天功能。这只是人类作为双足猿猴的疯狂执念——我们总想和周围一切对话，随后又发现根本不需要。真正有价值的东西都藏在底层：混乱、枯燥的商业互动机器，比如'这是不是邮编'之类的琐事。而这正是AI的强项，它能带来革命性改变——我现在能对接20个不同的小部件供应商，而不只是两家，这对我们供应商来说太棒了。

People don't want chat added to everything. That's just some crazy bipedal ape thing where we want to talk to everything around us and then realize we don't actually want to talk to everything around us. The interesting stuff is all deep under the hood, messy, boring, the language of business talking to each other in this kind of mundane business of, is that a zip code or not? And that's the stuff that this stuff is tremendous at, and it is really transformational. I can now have 20 different suppliers of my of that widget, not just two, and that's great for me as a provider of widgets.

这对经济有利，对个人有利。这才是至关重要的部分，尽管没人讨论它。

It's great for the economy. It's great for individuals. That's it's super important, and no one talks.

保罗·库德洛夫斯基，非常感谢你。

Paul Kudrowski, thank you very much.

好的。谢谢，埃里克。

Yeah. Thanks, Eric.

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