为什么这不是互联网泡沫 | 马丁·卡萨多在《华尔街日报》的粗略标题上

如果所有称这是泡沫的人，都忘记了真正的泡沫是什么样子呢？

What if everyone who's calling this a bubble has forgotten what a real bubble actually looks like?

互联网上的第一个直播视频流是一台咖啡壶。

The first live video stream on the Internet was a coffee pot.

1991年，剑桥的一位研究人员将摄像头对准了休息室的咖啡壶，以便在下楼前知道是否有咖啡。

In 1991, a Cambridge researcher pointed a camera at the break room pot so he'd know whether there was coffee before walking downstairs.

人们称它为玩具，一个毫无实际用途的噱头。

People called it a toy, a gimmick with no serious application.

这台咖啡壶的网络摄像头，在很大程度上，成为了奈飞。

The coffee pot webcam, in no small way, became Netflix.

这种模式一再重复。

The pattern repeats.

每一次重大技术浪潮都始于看似微不足道的应用场景，而每次怀疑者都将荒谬误认为无足轻重。

Every major technology wave starts with use cases that look trivial, and every time skeptics confuse silliness with insignificance.

三十年后，数千亿美元正涌入人工智能基础设施。

Thirty years later, hundreds of billions of dollars are pouring into AI infrastructure.

顾问估计，当前的支出需要到2030年AI收入增长40倍才能合理化。

Consultants estimate the current spending would require AI revenue to grow 40 x by 2030 to justify it.

与互联网泡沫的对比不言自明。

The .com comparisons write themselves.

但互联网泡沫破裂不仅仅是股价高估。

But the .com crash wasn't just overvalued stocks.

它还涉及由世通公司融资的光纤过剩，该公司负债高达400亿美元，并且在做假账，再加上9/11事件的冲击。

It was a fiber glut financed by WorldCom, a company with $40,000,000,000 in debt that was cooking its books, compounded by 09/11.

如今资助AI基础设施建设的公司，资产负债表上都有数千亿美元的现金。

The companies funding today's AI build out have hundreds of billions of cash on their balance sheet.

比较估值并不等同于预测系统性崩溃。

Comparing valuations isn't the same as predicting systemic collapse.

这一区别至关重要。

That distinction matters.

这场对话探讨了投机性调整与经济危机之间的区别，以及为何当前时刻更像移动或云计算热潮，而非互联网泡沫。

This conversation examines what separates a speculative correction from an economic crisis and why this moment may look more like the mobile or cloud booms than .com.

马丁·卡萨多是十六Z公司的普通合伙人，几个月前，他参加了《华尔街日报》的《大胆人物》播客。

Martin Casado is a general partner at a sixteen z, and a few months ago, he joined The Wall Street Journal's bold names podcast.

我们在这里分享这段对话。

We're sharing that discussion here.

有趣的是，你在上一轮泡沫破裂时身处旧金山和硅谷。

You know, it's interesting you were in San Francisco and Silicon Valley during the last bubble bursting.

你认为有哪些迹象表明旧金山正在再次形成泡沫？

What are the signs you're gonna be looking for that San Francisco's in a bubble again?

我的意思是，深夜的场面简直太疯狂了。

I mean, the late night is just so wild.

我的意思是，人们都忘了。

I mean, think people forget.

我认为可能需要二十年才能忘记这些景象是什么样子。

I think it takes maybe twenty years to forget what these things look like.

那是林肯轿车和派对的年代。

It was the limos, the parties.

当时出租车司机都在提供股票建议。

It was the taxi drivers offering stock tips.

我的朋友在一家初创公司工作，那里的保洁员居然不想拿现金工资，只想拿股权。

I mean, like, the janitor at one of the startups my friend worked at, like, didn't wanna get paid in cash, wanted to get paid in equity.

那真是彻底的混乱。

It was just total total chaos.

你知道，我们现在还没到那一步。

You know, that's not where we are right now.

我觉得我们只是忘了真正的泡沫是什么样子。

I mean, I think we just forgot what a true bubble looks like.

今天在《大胆人物》节目中，我们邀请到了马丁·卡萨多。

Today on bold names, we have Martin Casado.

他是风险投资公司安德森·霍洛维茨的普通合伙人，在那里

He is a general partner at venture capital firm, Andreessen Horowitz, where

他负责管理他们十亿美元的基础设施业务。

he is responsible for their billion dollar infrastructure practice.

而且，米姆斯，在进入这一集之前，我们对马丁内斯有一个主要问题。

And, Mims, going into this episode, I think we had one big question for Martine.

我们是否正处于一个新的科技泡沫中？

Are we in a new tech bubble?

这一次，泡沫是由围绕人工智能的全部热情推动的。

This time fueled by all of that excitement around AI.

而且，还受到债务的推动，特别是这些公司为支付人工智能基础设施而承担的债务。

And also fueled by debt, specifically the debt these companies are taking on in order to pay for that AI infrastructure.

这是一笔巨大的数十亿美元的赌注。

It's a huge multibillion dollar bet.

目前还不清楚这笔投资是否会获得回报。

It's unclear if it's gonna pay off.

但为了得到答案，让我们听听马丁内斯的说法。

But for answers, let's hear from Martine.

来自《华尔街日报》，我是克里斯托弗·明斯。

From The Wall Street Journal, I'm Christopher Mins.

我是蒂姆·希金斯。

And I'm Tim Higgins.

这是《大胆之名》。

This is Bold Names,

在这里，您将听到《华尔街日报》报道的那些大胆企业领袖的声音。

where you'll hear from the leaders of the bold name companies featured in The Wall Street Journal.

今天，我们的问题是：对人工智能的巨额押注会成功吗？

Today, we ask, will the big bet on artificial intelligence pay off?

马丁？

Martin?

是的。

Yeah.

非常感谢您加入我们。

Thank you so much for joining us.

目前，数千亿美元正涌入人工智能领域。

Hundreds of billions of dollars are pouring into artificial intelligence right now.

帮我们理解一下这些资金将流向哪里。

Help us understand where that's going.

这些资金到底流向了哪些方面？

What's what exactly are is that those dollars flowing?

是流向了软件程序吗？

Is it into programs?

是流向了产品开发吗？

Is it product development?

是流向了‘铁锹和锄头’吗？

Is it the picks and shovels?

你看到这些钱都流向了哪里？

Where are you seeing that money go?

嗯，确实是一个混合的情况。

Well well, certainly, there's a mix.

绝大多数资金都投入到了实际的数据中心容量上。

The vast majority is going into actual data center capacity.

所以这是GPU。

So this is GPUs.

这是房地产。

This is real estate.

这是电力。

This is power.

这是用于冷却它们的暖通空调系统。

This is HVAC systems to cool them.

当然，还有团队自身及其他方面的标准软件成本。

Then, of course, there is the standard, you know, software costs of of the teams themselves and everything else.

但真正占主导地位的是基础设施。

But it's really dominated by the infrastructure.

而你的关注点是基础设施。

And you your focus is infrastructure.

所以在安德里森·霍罗维茨，这显然是一家科技投资公司，是的。

So at Andreessen Horowitz, which obviously is a tech investment firm Yeah.

因为我们面向的是广泛受众。

Since we go to a broad audience.

想

Wanna

确保

make sure

我们明确这一点。

we specify that.

我负责早期阶段的基础设施基金。

I I run the early stage infrastructure fund.

是的。

Yeah.

但你有超过十亿美元的投资资金。

But you got a more than a billion dollars to invest.

当你提到基础设施时，你指的是什么？

And when you say infrastructure, what do you mean?

是的。

Yeah.

所以，它专门指计算机科学基础设施，主要集中在软件生态系统中。

So so it's specifically computer science infrastructure and primarily in the software ecosystem.

因此，我们广义地定义为：我们投资于构建应用程序所使用的工具。

So that so we broadly define it as we invest in the stuff used to build apps.

你知道，我们投资于用于构建其他东西的工具，因此这包括传统基础设施领域的计算、网络、存储、数据库，但现在还有许多其他领域，比如开发工具、安全、AI模型等等。

You know, we invest in stuff used to build the stuff, and so this is the traditional verticals within infrastructure, our compute network storage databases, but now you have a number of others, like dev tools security, you know, AI models, etcetera.

所以，这是计算机科学基础设施，涵盖从芯片一直到技术人员所使用的实际应用程序的所有内容。

So this is computer science, infrastructure, everything from, let's say, the chips all the way up to to the actual apps that a that a technical person would use.

是的。

Yeah.

对于那些不熟悉的人来说，我觉得甚至一些认为自己

And for those who are not familiar with I feel like even people who

了解的人

think they

知道风险投资是什么的人，可能也不熟悉现代风险投资的结构。

know what venture capital is are probably not familiar with the modern structure of venture capital.

什么是A轮融资意味着什么？

What does it mean to be a series a?

我们说的是哪些轮次？

Like, what series are we talking about?

所以我们称自己为风险投资者，因为正如你所说，这些概念实际上相当模糊。

So so so we call ourselves venture investors because these things you're right are are actually pretty fluid.

我们从最初的投入开始投资，这可能被称为种子轮，一直到相当后期的B轮。

So we invest from first money in, which could would be called a seed, all the way to, you know, pretty late series b's.

通常，我们甚至会在项目尚未有明确想法时就投资，尤其是对于我们熟悉的二次创业者；有时在产品成型前，有时在市场验证前，有时在早期市场验证后，一直投资到产品已进入市场且表现良好，但尚未实现跨季度的可重复增长。

Normally, we invest often sometimes even pre idea if it's a second time founder that we know, often pre product, sometimes pre market traction, sometimes early market traction, and then all the way up to, like, say, you know, the a product is in market and they're doing pretty well, but they have not seen, you know, repeatable growth over quarters.

在某个时间点，它就转变为增长型投资，那是另一个基金和另一个团队负责的。

Like, at some point in time, it moves to growth investing, which is a separate fund and a separate team.

因此，我们倾向于评估技术、团队、团队与市场的契合度、市场趋势等。

So we we tend to evaluate technologies, teams, team market fit, market trends, things like that.

我有点觉得，你就是那种会对参与其中的人或他们可能改变世界的疯狂想法感到兴奋的人，看到其中蕴含的未来潜力。

I kinda think of it as you you're you're one of these guys who are are getting excited about the people involved or the wild idea that they might have to change the world and seeing the potential for the future of that.

对。

Right.

但其实并没有实际的财务数据来证明这一点。

Without actually, you know, having the monetary data to prove it.

是的。

Yeah.

对。

Right.

对。

Yeah.

所以，后期投资者会把整个世界抽象成一张财务报表，认为这张表就能说明公司的全部真相；而我们则会对创始人充满热情。

So like a late late stated investors, they abstract the entire world as a financial spreadsheet, and that tells all the truth about the company where, you know, we get very excited about founders.

我们会对某些尚未显现的市场感到兴奋。

We get excited about certain markets before they show up.

我想聊聊今年早些时候我在X上注意到的那些兴奋情绪。

I wanna talk about some of that excitement I noticed on X earlier this year.

你发了一条内容，我觉得非常有洞察力。

You posted something that I thought, was really insightful.

我住在旧金山，所以我也在亲身感受这些变化。

I live in San Francisco, so I'm seeing some of this too.

你在谈论如今湾区的生活状态，有点像是在描述上世纪九十年代末互联网泡沫时期的氛围。

You're talking about what it's like to be in the Bay Area right now, and you you're kind of talking about how it feels like the late nineteen nineties during the .com boom.

我引用一下，‘硅谷正处于颠覆性辉煌的巅峰’。

And I quote, just Silicon Valley in peak disruptive glory.

你所说的‘颠覆性辉煌的巅峰’是什么意思？

What do you mean by that peak disruptive glory?

这些潮流往往不仅仅是技术层面的运动。

So these these movements tend to be much more than just technical movements.

对吧？

Right?

所以它们往往也是文化运动。

So they often are culture movements.

早期的网页也是如此。

And that was the same thing with the early web.

那时有很多非常疯狂的网站，它们其实并不实用，但特别酷，人们非常喜欢。

You had kind of a lot of kind of these wild websites that weren't really practical, but they were super cool and people loved them.

比如，你知道吗？

Like, do you I don't know.

你还记得《仓鼠舞》吗？

Do you remember Hamster Dance?

哦，是的。

Oh, yeah.

对。

Yeah.

当然。

Absolutely.

一个有仓鼠跳舞的网站，而且你知道，公司常常会被重新塑造，因为全新的规则正在被制定，毕竟这是一种新技术。

A website with hamster dancing and, like, you know, often companies kind of get reconstructed because you have a whole new set of like, the rules are being written because it's a new technology.

对吧？

Right?

所以，当个人电脑出现时，那是一场全新的技术浪潮，当时并没有IBM的大型机专家去创办这些公司。

So, like, when the PC came, it was an entirely new technology wave, so you didn't have, like, mainframe people from IBM starting these companies.

你通常看到的是一群更年轻的人，或者说是年轻一代。

You had, you know, normally a younger cohort or a younger generation.

他们其实并不知道如何经营企业。

They didn't really know how to build businesses.

买家也完全是全新的群体。

The buyers were entirely new.

所以，你知道，他们没有任何现成的指南可以遵循。

And so, like, you know, there wasn't a playbook for them.

因此，你也会重新塑造公司。

So you kind of remake companies too.

你知道吗，很多五年前几乎被视为禁忌的东西，现在又重新出现了，无论是从公司层面还是消费者层面。

You know, a lot of stuff that was, you know, almost anathema, you know, five years ago is is being recreated again, both from the the company side and the consumer side.

当然，还有大量资本涌入，以及由此带来的一切外部影响。

And then, of course, you know, you've got, you know, capital flooding in and all of the externalities of that.

人们面临着完全新型的用户行为，却不知道该如何应对。

You've got entirely new user behaviors that people don't know what to deal with.

对吧？

Right?

我的意思是，AI到底擅长什么？

I mean, like, I mean, what is AI good at?

它擅长创造新事物。

It's good at, like, creating new things.

以前，计算机并不具备创造力。

Like, computers haven't been creative.

它非常擅长与人类建立情感联系。

It's great at creating emotional connections with humans.

计算机以前并不擅长这个。

Like, computers haven't been good at that.

所以这简直就是科技、文化、公司建设和洞察力的一场混战。

And so it's just kind of this melee of, you know, tech and culture and company building and insight.

而且，再一次地，硅谷正处于这场风暴的中心，就像当年互联网兴起时一样。

And and again, yet again, Silicon Valley is at the epicenter of it, you know, just like it was for the Internet.

绝对如此。

Absolutely.

但当我提到互联网泡沫时期时，很多人想到的是互联网泡沫。

And I think but I when you use the the the .com boom, I think a lot of people think of the .com bubble.

嗯。

Mhmm.

所以我认为你看到的是那个时代的积极面，那些好的类比，听起来你告诉我的是所有潜在的可能性，以及这些新想法如何被实现。

And so I think you're seeing the good parts of that, the good comparisons of that era, the the the and it sounds like what you're just telling me all the the potential, all of that kind of wave of new ideas and how it can be implemented.

是的。

Yeah.

你是否相信，这场繁荣中的泡沫部分不会重演历史？

Are you have any confidence that history isn't repeating itself with the bubble part of that boom?

所有市场都会经历波动。

So all markets go in waves.

对吧？

Right?

我的意思是，我们刚在新冠疫情中见过这种情况。

I mean, we just saw this with COVID.

对吧？

Right?

我的意思是，当时出现了一波投机浪潮，股价飙升，然后又急剧下跌。

I mean, there was a, you know, there was a I would call it a speculative wave where equity values went super high, and then, you know, it it it drops dramatically after that.

所以这种情况总会发生，我预测这也会发生。

And so that will always happen, and I I predict this will happen.

不过话说回来，我认为当前的基本面和互联网泡沫时期根本不一样。

Again, at some point in time, that said, I don't think that the fundamentals are anything like .com.

有很多方面是完全不同的。

There's a number of things that were very different.

对吧？

Right?

首先，大部分基础设施都是由世通公司提供的。

So the first one was most of the infrastructure was being provided by WorldCom.

对吧？

Right?

是的。

Yeah.

这其中包含了大量债务。

A lot of Which a lot of debt.

对吧？

Right?

而它的债务高达400亿美元。

Which had $40,000,000,000 in debt.

是的

Yep.

我们还经历了9·11事件，发生在2001年。

We also had nine eleven, which happened in 2001.

那时候，互联网上有大量的用户。

And so and and back then, there's a lot of users on the Internet.

但没多少人愿意为此付费。

There weren't a lot of people that were paying for it.

我们甚至还没真正建立起商业模式。

We hadn't even really figured out a business model.

所以如果你拿今天的情况来对比，这些方面都完全不同了。

So if you compare that today, kind of every one of those is different.

对吧？

Right?

如今，投资这些数据中心的公司，资产负债表上都有数千亿美元的资金。

So the companies that are investing in these data centers have hundreds of billions of dollars on the balance sheet.

呃，我不确定我接下来要说的答案是什么，但你觉得呢？

Like, I I don't know the answer to what I'm about to say, but what do you think?

你觉得Meta在VR上花的钱多，还是在AI上花的钱多？

Do you think Meta is spending more money on VR or AI?

可能是VR更多，但现在有了AI，还有他们开出的那些支票，我的意思是，扎克伯格说过，到2028年可能会花6000亿美元。

Probably has been VR, but now with the AI and the the checks they've been writing I mean, Zucks has talked about spending maybe $600,000,000,000 by 2028.

是的。

Yeah.

是的。

Yeah.

确实如此。

It is.

这是一笔巨款。

It's a ton of money.

对吧？

Right?

但这些公司历史上一直花很多钱在基础设施上。

But, like, these companies spend lots of money on infrastructure historically.

所以，也许他们在夸大其词，但这些公司有着出色的资产负债表和良好的现金流。

And so, like, maybe they're inflating it, but these companies have, you know, great balance sheets, great cash flow.

因此，关于谁在资助这一切，其基本面确实非常不同。

And so, like, the fundamentals of, like, who's funding this is is quite different.

我想稍后再深入讨论基本面。

I wanna get into fundamentals in second.

你知道，但请你戴上投资者的帽子，是的。

You know, the the the thing, though, put your investor hat on Yeah.

因为我觉得现在有一些令人困惑的信号。

Because I think there's some confusing signals out there.

对吧？

Right?

因为一方面，Meta的首席执行官马克·扎克伯格和OpenAI的首席执行官萨姆·阿尔特曼都谈到了兴奋之情，但他们也各自暗示，这种兴奋可能有些为时过早。

Because on one hand, Mark Zuckerberg, CEO of Meta, OpenAI CEO Sam Altman, They have talked about the excitement, but they've also had kind of their own version of suggesting some of the excitement might be premature.

这是马克·扎克伯格在《Access》播客中所说的话。

Here's what Mark Zuckerberg had to say on the Access Podcast.

我认为，至少从历史上大型基础设施建设及其引发泡沫的经验来看，这里也可能发生类似的情况。

I do think that there's definitely a possibility, at least empirically based on past large infrastructure build outs and how they led to bubbles, that, that something like that would happen here.

所以一方面，你听到了一些警告。

And so on one hand, you had some of some warnings.

另一方面，有大量的资金正在涌入。

On the other side, you have a lot of money going out there.

面对这些相互矛盾的信号和噪音，人们该如何解读呢？

And what should people make of these conflicting signals and noise sorts of situations?

你知道吗，听我说。

You know, listen.

我认为，清醒地认识到技术被采纳需要多长时间，是非常重要的。

I I think it's very important to be sober about, you know, how how long it takes for technology to be adopted.

我认为，每个人，尤其是公司领导者，都应该适当降温，因为否则，预期就会超越实际的采纳速度。

And I think everybody, especially leaders of companies, try and temper it because, otherwise, you know, expectations will outpace actual adoption.

但我会说，向人类阐明预期与实际的运营规划截然不同，因为运营规划需要提前三到五年布局，毕竟这些基础设施的建设耗时太长。

But I would say that articulating expectations for humans is very different than actual operational planning where you've got to be, you know, three to five years ahead because it takes so long to build these out.

因此，我不应将CEO为市场设定预期与运营计划混为一谈，后者才是他们过去二十年来真正从事的业务。

And so I I wouldn't conflate as CEO trying to set expectations for a market versus an operational plan, which is what they've been in the business for for the last Sure.

二十年。

Two decades.

广告之后，为什么马丁认为人工智能泡沫破裂不会对经济造成灾难性后果？

After the break, why Martin is skeptical that a bursting AI bubble would have disastrous consequences for the economy?

我很难想象，仅仅因为可能出现投机泡沫，就必然意味着我们会遭遇系统性问题。

It's very hard for me to see how just because you could have a speculative bubble, absolutely, this somehow denotes that we're gonna have a systemic issue.

想想看，我们在移动互联网领域也曾高估过许多东西。

Remember, we overvalue things in, you know, mobile.

在早期云计算热潮中，我们也曾高估过许多东西。

We overvalued things during the early cloud boom.

所有这些领域，我们都曾高估过。

All of these things we overvalued.

这并没有导致系统性崩溃。

That did not result in systemic collapse.

请继续关注我们。

Stay with us.

目前关于可能存在的泡沫，主要有两个担忧。

There there are two major concerns driving the conversation around a possible bubble.

对吧？

Right?

一是人工智能并没有像我们预期的那样具有变革性。

One that AI is not transformative as we had hoped.

另一个是，大量资金正涌入其未来建设，包括数据中心、能源和芯片，但这些投入不可能带来足够的生产性收益来证明如此高额的支出是合理的。

The other is that all this money is pouring into its its future, these data centers and energy and chips, and it's it can't possibly lead to enough productive gains to justify that level of spending.

我不想纠结于技术是否正以我们所看到的水平发展，而是直接聚焦于资金问题。

And I, you know, I wanna set aside the kind of the question of whether the technology is is is developing at the at the progress at the levels that we've seen and just go straight to that money point.

因为在我看来，近几年来，一个证明AI支出热潮不同于互联网泡沫的关键点在于，企业并没有依赖巨额债务来构建这些基础设施。

Because I think for a few years now, one of the proof points behind why the AI spending spree wasn't the .com bubble was because companies weren't relying on huge amounts of debt to build out that infrastructure.

但最近，我们看到了这种债务。

But as of late, we've seen that debt.

对吧？

Right?

我们看到一些债务开始发出红色警报。

We've seen some of that debt starting to show some some flashing red lights.

对吧？

Right?

我想起《华尔街日报》的同事们提到的一些数字，他们说OpenAI正在谈论建设价值一万亿美元的数据中心。

And I think of some of the numbers that my colleagues at the at the Journal have talked about where they see OpenAI talking about a trillion dollars for data centers.

贝恩公司的顾问估计，当前这场AI基础设施支出浪潮，到2030年需要每年产生2万亿美元的AI收入才能 justify 这笔支出。

Consultants at Bain have estimated that the current wave of AI infrastructure spending would require 2,000,000,000,000 in annual AI revenue by 2030 to justify that.

所以，这里似乎有很多红色警报或 flashing red lights。

So that seems like a lot of red flags there or flashing red lights.

为什么我们还没有陷入泡沫？

Why are we not in the bubble?

我只是觉得我们需要在这里找到一个泡沫。

Well, I just think we needed to find bubble here.

对。

Mhmm.

所以，你意思是可能会发生系统性崩溃，这和说我们正处于投机性估值泡沫是完全不同的说法。

So, like, what you're saying is there may be a a systemic collapse, which is a very different statement than saying we're in a speculative valuation bubble.

所以，通常当我们谈论泡沫时，指的是投机性行为。

So, like, often when we talk about bubbles, it's a speculative statement.

比如，我们因为某种原因高估了一组股票。

Like, oh, we're overvaluing a set of stocks for whatever reason.

对吧？

Right?

这种情况我们经常看到。

And we see these all the time.

所以，我想说，听好了。

So I would say, listen.

如果你看一下公司的估值，正如我之前提到的，它们会涨也会跌。

If you look at valuations of companies, as I mentioned before, they wax, they wane.

它们现在可能在一段时间内被高估了。

They may be overvalued over a period of time right now.

但从长期来看，情况往往如此。

It tends to be in the long terms.

这些情况最终会得到很好的合理化。

These things get pretty well justified.

比如，如果你看一下for.com的估值，即使它们当时完全疯狂，但如果你认为它是未来二十年经济的主要增长引擎，那么它们实际上还是有充分理由的。

So for example, if you look at the valuationsfor.com, even though they were totally crazy, if you look at you know, it was, like, the primary growth driver of the economy for the next twenty years, they're actually pretty well justified.

是的。

Yeah.

我的意思是，看起来你说AI是自互联网以来最大的创新，但这个观点要被正确理解还是花了一点时间。

I mean, it seems like I mean, you know, you talk about how AI is the biggest innovation since the Internet, but it took a little bit of time for that to Correct.

投资回报率需要时间才能体现。

The ROI to be there.

对吧？

Right?

是的。

Yeah.

显然，亚马逊的

Clearly, Amazon's

是的。

Yeah.

是的。

Yeah.

但我想真正谈谈这种系统性崩溃的观点。

But I wanna actually talk to this this this notion of systemic collapse.

对吧？

Right?

没错。

Right.

所以，互联网泡沫破裂实际上主要是光纤产能过剩和崩盘。

So the .com was the .com collapse was really kind of a fiber glut and a fiber bust.

正如我们之前提到的，当时有一家公司掌控着需求。

As we mentioned before, you you had one company that managed demand.

那家公司杠杆极高，而且在做假账，同时还发生了9·11事件。

It was that one company was massively levered, and it was cooking the books, and you had nine eleven.

于是，所有这些事情都发生了。

So you had all of these things happen.

但即便如此，当光纤市场下滑时，仍然在金融系统中引发了系统性问题。

And yet even in that, when fiber went down, it created a systemic issue in the financial system.

即便如此，产能过剩也只持续了大约四年。

Even then, the glut only lasted about four years.

听好了。

Listen.

问题不在于，我们是否相对于近期需求过度投资？

The question is not, are we overinvesting relative to near term demand?

大概吧。

Probably.

问题是，我们相对于长期需求是否投资过度？

The question is is, are we overinvesting relative to long term demand?

如果是这样，我们是否有足够的经济储备来阻止某种系统性崩溃？

And if so, do we have the economic reserves to stop some sort of, you know, systemic unraveling?

这一次的基本面与九十年代末相比截然不同，而且好得多。

The fundamentals are so different and so much better this time than they were during the late nineties.

对我来说，很难理解为什么仅仅因为可能存在投机泡沫——确实可能存在——就必然意味着我们会遭遇系统性问题。

It's very hard for me to see how just because you could have a speculative bubble, absolutely, this somehow denotes that we're gonna have a systemic issue.

记住，我们在移动领域曾高估过某些东西。

Remember, we overvalued things in, you know, mobile.

我们在早期云计算热潮中也曾高估过某些东西。

We overvalued things during the early cloud boom.

我们在早期SaaS热潮中也曾高估过某些东西。

We overvalued things during the early SaaS boom.

我们高估了所有这些事物。

All of these things we overvalued.

但这并没有导致系统性崩溃。

That did not result in systemic collapse.

所以我认为我们需要仔细区分这两件事。

And so I think we need to really tease these two things apart.

就像是，是的。

It's like Yeah.

估值常常在时机上出现偏差。

Like, valuations often get the timing wrong.

它们会涨也会跌。

They wax and they wet.

你知道的？

You know?

但你具体问的是，这是否意味着会发生系统性崩溃？

But you're asking specifically, does this mean there's gonna be systemic collapse?

我完全看不到任何迹象表明会这样，我认为我可以通过对带宽和数据使用的历史先例，以及资助这些事物的行业的基本原理，来推导出这个结论。

I see absolutely zero indication of that, and I think I can back into that conclusion via, you know, both historical precedents on the use of bandwidth and data plus the the the fundamentals of the industry that's funding these things.

让我就系统性崩溃插一句，我的一位最爱的专栏作家恰好在彭博社。

Let me just interject on the systemic collapse So, a you know, one of my favorite columnists happens to be at Bloomberg.

向我们的同事兼竞争对手致敬。

Shout out to our colleague slash competitors there.

康纳说，每次情况都不同。

Connor said he's says, you know, every every time is different.

人们喜欢说每次情况都不同，但确实如此。

People like to say every time is different, but that's true.

每次出现泡沫或系统性崩溃时，情况都不一样。

Every time that we have a bubble or a systemic collapse, it is different.

所以，我想说一些现在与以往不同的相关因素。

So here's some things that I think are relevant that are different now.

对吧？

Right?

是的

Yeah.

我们从未见过股票市场中前五家左右公司所占市值比例达到如今这种集中程度，而它们全部都是科技公司。

We've never had the level of concentration in the stock market in terms of the proportion of the value of the stock market represented by the top five or so companies that we have now, all of which are tech companies.

所以，风险更高了。

So, you know, the stakes are higher.

对吧？

Right?

比如，市场上有很多现金，但人们也在向整个市场大量投入资金。

Like, there's lots of cash on the side, but people are also pouring cash into the market as a whole.

当前的投资水平意味着，仅通过一个简单的粗略估算，AI及其所有形式在这些公司中产生的总收入，需要在未来四年增长约40倍，才能合理化当前的投资水平。

The current level of investment implies, just with a basic back of the envelope calculation, that the total amount of revenue generated by, let's say, AI in all of its manifestations at all these companies needs to increase something like 40 x in the next four years to justify the current level of investment.

难道不可能是，这个差距如此巨大，以至于市场和对这一基础设施的投资可能出现大幅回落，让人们事后回望时说：‘哎呀，搞砸了’？

Isn't it possible that that gap is so large that we could have a significant dip in markets and and and in investment in this infrastructure in a way that people look back on and say, oops.

那真的是一次错误。

That really was a mistake.

这完全有可能。

It's totally possible.

你这么表达的方式中有一件有趣的事，我觉得非常正确，值得提出来。

There's an there's an interesting thing in the way that you phrased it that I thought was absolutely correct, and I think it's worth calling out.

实施大量AI支出的公司都有现有的业务。

So the companies that are implementing a lot of this AI spend have existing businesses.

对吧？

Right?

AI部分需要增长40倍，这听起来很多，但相对于它们的现有业务来说，其实并不算多。

And the AI portion has to grow 40 x, which is a lot, but it is actually not a lot relative to their businesses.

如果你看看它们现有的业务，就会发现这确实是我们见过的最大规模的预算转移。

And if you look at their existing businesses, you'll actually see this is the largest shift in budget we have ever seen.

对吧？

Right?

这相当于从一边彻底转向另一边。

It's going from basically one side to the other side.

所以，我同意你需要AI部分增长。

So I would I would I would agree that you need the AI portion to grow.

但我不同意的是，这些公司本身必须增长，而人们在谈论数据时经常混淆这一点。

But what I would disagree is you need those companies to grow, and this is so often confused when people talk about numbers.

我的意思是，像Meta这样的公司，它们的全部业务就是：好吧。

I mean, you have companies that their entire job, like Meta, is like, okay.

我们推出新技术和新产品，然后将支出和用户行为转移到这些新事物上。

We launch new technologies and new things, and then we shift spend budget user behavior onto those things.

所以，再次强调，我们不要把像互联网这样全新的行为、全新的支出、全新的公司主导一切的情况，与现有公司从一个项目转向另一个项目的情况混淆——而这正是我们正在看到的。

And so, again, let's not confuse something like the Internet, which was kind of like a net new behavior, net new spend, net new companies drove basically all of it with existing companies that are shifting spend from one column to another column, which is actually what we're seeing.

接下来，这是人工智能投资者的激动人心的时刻。

Coming up, it's a heady time for AI investors.

那么，马丁认为机会在哪里？

So where does Martin see the opportunities?

我们对即将出现的新公司感到非常兴奋。

We're very excited about the fact they're gonna have new companies.

我的意思是，即使你提问的时候，心里想的也是OpenAI？

Like, I think even when you ask questions, you're like, in your head, you're thinking OpenAI?

那是你的模型，但我得告诉你，实际情况并非如此。

Like, that's your model, but I will tell you that's not what the landscape looks like.

那只是一家公司，而最先进的模型只是AI公司长尾中非常小的一部分。

That's one company, and the state of the art models is a very small subset of the long tail of of AI companies.

接下来是。

That's next.

所以你是个乐观主义者。

So you're you're an optimist.

对吧？

Right?

我听过你说，尤其是现在，不是零和思维的时候。

You I've heard you say that, you know, especially now is not a time for for zero some thinking.

你知道，这使得

You know, and that makes It's

明显在增长。

clearly growing.

是的。

Yeah.

是的。

Yeah.

是的。

Yeah.

市场明显在增长。

Market's clearly growing.

我的意思是，听好了，这并不是乐观主义。

It's always mean, listen, it's not optimist.

我的意思是，过去三十年科技的真实情况是，它一直在增长。

I mean, the realistic view of tech in the last thirty years is that it keeps growing.

没错。

True.

没错。

True.

没错。

True.

不是每个想法都能成功。

Not every idea pans out.

对吧？

Right?

不是每秒钟。

Not every second.

正如你所说，这个项目显然已经产生了大量收入。

This one is clearly already generating a lot of revenue, as you said.

是的。

Yeah.

话虽如此，关于你的投资，你预计什么时候能从过去几年的投资中看到真正的回报？

That said, on your investments, when do you expect to see real ROI on the things that you've been investing in over the past couple of years?

你知道，这个问题非常有趣，但可能和你原本想的原因不一样，因为很多最好的公司并不上市。

You know, so that this is such an interesting question, probably for a different reason than you're intending, which is a lot of the best companies don't go public.

对。

Right.

这其实是个新现象，顺便说一下。

Which is kind of a new thing, by the way.

是吗？

Right?

这确实是个全新的现象。

It is a super it's definitely a new thing.

我的意思是，是的。

I mean Yeah.

而且所以我就

And and so I

实际上，因为，而且我们刚才说得太快了，放慢一点。

actually because and and I just we'll slow down there.