人工智能是否存在泡沫？如果泡沫破裂会怎样？

当法国一座古老的玫瑰园变成露天实验室时会发生什么？

What happens when an ancient rose farm in France becomes an open sky laboratory?

而印度的美容学课程如何能为经济赋权开辟道路？

And how can a cosmetology program in India offer a road to economic empowerment?

你好。

Hi there.

我是伊莎贝拉·鲁索里尼。

I'm Isabella Russolini.

在欧莱雅集团最新一期《这不是美容播客》中，我们采访了一位有机花卉种植者和一位美容学校毕业生，探讨美容如何塑造商业。

And in the latest episode of this is not a beauty podcast from L'Oreal Group, we speak to an organic flower farmer and a beauty school graduate and how beauty shapes business.

立即在您喜爱的播客平台上收听。

Listen now on your favorite podcast platform.

我是《纽约时报》的娜塔莉·基特罗夫。

From The New York Times, I'm Natalie Kitroeth.

这里是《每日新闻》。

This is The Daily.

经过多年对AI热潮的极度乐观和巨额投资，最近几周华尔街开始认真质疑这种乐观是否过度，我们是否实际上处于一个可能即将破裂的泡沫中。

After years of soaring optimism and massive investment in the AI boom, in recent weeks, Wall Street has begun to seriously question whether that optimism was overblown and whether we're actually in a bubble that may soon pop.

然而，尽管存在这些忧虑，硅谷却加倍下注，对其投入该技术的数千亿美元表现出十足信心。

And yet, despite all that hand wringing, Silicon Valley has only doubled down, projecting total confidence about the hundreds of billions of dollars it's pouring into the technology.

今天，我的同事凯德·梅茨将解释原因。

Today, my colleague, Cade Metz, explains why.

为何科技公司如此狂热地相信AI。

Why tech companies believe so fervently in AI.

为什么他们愿意承担巨大风险来实现承诺。

Why they're willing to take huge risks to deliver on its promise.

以及这个赌注是否会适得其反。

And whether that bet could backfire.

今天是11月20日，星期四。

It's Thursday, November 20.

凯德，最近华尔街投资者、硅谷甚至华盛顿的讨论似乎已经从'我们是否处于AI泡沫中'转变为普遍认为'是的，我们很可能正处于某种泡沫中'。

Cade, it seems like the conversation on Wall Street among investors in Silicon Valley, even in Washington these days has gone from whether we're in an AI bubble to the general sense that, yes, we probably are in some sort of a bubble.

然而，你从硅谷视角所报道的这些公司，仍在为此投入巨额资金。

And yet, the companies that you cover from your perch in Silicon Valley, they're continuing to spend huge amounts of cash on this.

所以给我们解释一下。

So explain to us.

他们花这么多钱的理由是什么？

What is their justification for spending all this money?

嗯，在真正开启这场AI热潮的OpenAI聊天机器人ChatGPT问世三年后，这显然是一项强大且在某种程度上具有变革性的技术。

Well, three years after the arrival of ChatGPT, the OpenAI chatbot that really started this AI boom, this is clearly a powerful and, in some ways, transformative technology.

它不仅被用来以新方式搜索互联网，还能帮助人们比过去更快、更高效地完成特定任务。

It's used not only to search the internet in new ways, it can help people do specific tasks in a faster and more efficient way than they did in the past.

你可以看到企业正在采用能够转录会议的服务。

You see businesses adopting services that can transcribe meetings.

在医疗保健领域也有其他应用。

You see other applications in healthcare.

这项技术已经在改变我们的生活方式和工作方式。

There are ways that this technology is already changing the way we live and the way we work.

这些公司，这很典型的硅谷风格，看到了地平线上更巨大的变革。

And these companies, and this is classic Silicon Valley, see much bigger transformations on the horizon.

这些是高管们，这些行业巨头不仅着眼于当下可能实现的技术，更在思考这项技术未来的潜力。

These are people executives, these titans of industry are looking not just at what is possible today, but what they think this technology will do in the future.

这个想法意味着，构建这样的未来将极其昂贵。

And the idea is that that future, it's gonna be really expensive to build.

从根本上说，这项技术的研发成本很高。

Well, fundamentally, this technology is expensive to build.

即使对在科技行业摸爬滚打数十年的人来说，这也是个天文数字。

It's a mind boggling amount of money even for people who have spent decades in the tech industry.

仅OpenAI一家公司就宣布，将单独在美国投入5000亿美元建设数据中心来推动这些技术。

OpenAI alone has said it's going to spend $500,000,000,000 on data centers in The United States alone to drive these technologies.

我们稍停片刻，思考一下这意味着什么。

Let's stop for a second and think about what that means.

按现今的货币价值计算，5000亿美元大约可以资助15个曼哈顿计划。

$500,000,000,000 in today's money could fund about 15 Manhattan projects.

哇。

Wow.

这笔资金可以超额资助两次阿波罗计划。

It could fund the Apollo program two times over.

就是那个把人类送上太空的计划。

The program that sent humans to space.

是啊。

Yeah.

确实如此。

Exactly.

而这还只是推动一家初创公司OpenAI发展AI所需的资金。

And that's just the money to drive AI for a single startup, OpenAI.

总的来说，如果你看看全球范围内的支出，不仅仅是美国，我们谈论的是近3万亿美元。

All told, if you look at what is being spent across the globe, not just The US, we're talking about nearly $3,000,000,000,000.

对于一项具有变革性但在许多方面仍具投机性的技术来说，这是一笔巨额资金，意味着他们看到的未来前景非常广阔。

That's an awful lot of money for a technology that is transformative, but is in many ways still speculative, meaning what they see in the future is so big.

在许多情况下，他们相信自己正在构建硅谷所称的人工通用智能——一种能完成人脑所有功能的机器。

They, in many cases, believe they're building what is called in the valley, artificial general intelligence, a machine that can do anything the human brain can do.

我们能暂停一下吗？

Can we just pause?

我想请你为我定义一下这个术语——人工通用智能。

I I want you to just define this term for me, artificial general intelligence.

我们经常听到这个词。

We hear it a lot.

我们在节目中也讨论过它。

We've talked about it on the show.

这个概念似乎有点难以理解。

It seems kind of hard to get your head around.

比如，凯德，它实际上意味着什么？

Like, what does it mean actually, Cade?

这是对一种机器的简称，这种机器能完成像你我日常从事的所有具有经济价值的工作。

It's shorthand for a machine that can do all of the economically valuable work that people like you and I do on a daily basis.

他们实质上想要取代所有人类工人。

They want to essentially replace all human workers.

他们想给世界带来一种能做任何工作的技术。

They want to give the world a technology that can do any job.

理论上，这值得投入所有这些资金。

That, in theory, is worth all this spending.

但值得说明的是，我们不知道如何实现这样的目标。

But it's worth saying that we don't know how to get to such a goal.

这是一个崇高的追求。

That is a lofty thing to reach for.

但硅谷的许多高管依然毫不退缩。

But so many Silicon Valley executives remain undeterred.

Meta首席执行官马克·扎克伯格。

Mark Zuckerberg, CEO of Meta.

我猜大概在未来12到18个月内，我们会达到这样一个阶段：这些项目的大部分代码将由AI编写。

I would guess that, like, sometime in the next twelve to eighteen months, we'll reach the point where, like, most of the code that's going towards these efforts is written by AI.

英伟达首席执行官黄仁勋。

Jensen Huang, the CEO of NVIDIA.

如果有一件事我要鼓励大家去做，那就是立刻给自己找一个AI导师。

If there's one thing that I would encourage everybody to do is to go get yourself an AI tutor right away.

我们将成为超人，因为我们拥有超级AI。

We're gonna become superhumans because we have super AIs.

他们都在论证这笔支出是合理的。

They are all making the case that this spending makes sense.

这种态度的典型代表就是OpenAI的首席执行官萨姆·奥特曼。

The poster child of this attitude is Sam Altman, CEO of OpenAI.

我很少会想成为上市公司，但少数几次让我心动的情况之一，就是当那些人写着这些即将倒闭的可笑开源AI时，你知道的，随便吧。

There are not many times that I want to be a public company, but one of the rare times it's appealing is when those people are writing these ridiculous open AIs about to go out of business and, you know, whatever.

我真想告诉他们可以直接做空股票，而且我很乐意看到他们因此吃亏。

I would love to tell them they could just short the stock, and I would love to see them get burned on that.

他已经告诉全世界可以押注他的公司会失败，但风险自负，同时他还在继续炫耀公司的开支。

He has told the rest of the world to bet against his company at their own risk, and he continues to flaunt the company's spending.

他和整个行业都全情投入其中。

He and the rest of the industry are all in.

但他们承诺的东西并未按照他们承诺的时间表兑现。

But what they promised hasn't been delivered on the timeline that they promised.

那么，再解释一下为什么他们在这件事上还在加大力度，如果目前还没见效的话。

So again, just explain why they're still going even harder at this thing if it isn't panning out yet.

显然，他们不是想把钱往垃圾桶里扔。

Obviously, they aren't trying to throw money in the trash.

对吧？

Right?

你了解FOMO（害怕错过）这个概念吗？

Do you know about the concept of FOMO, fear of missing out?

这正是推动这件事的主要因素。

That's a lot of what is driving this.

我什么时候怕过？

Do I ever?

没人想错过这项可能是世界有史以来最具变革性的技术。

No one wants to miss out on what could be the most transformative technology the world has ever seen.

如果你不想错过，就必须现在就下注。

And if you don't want to miss out on that, you have to make your bet now.

这些数据中心不仅造价昂贵，还需要很长时间来建设。

These data centers, not only are they expensive, they take a long time to build.

因此几乎从定义上来说，你必须押注于数年之后才能实现的事物。

And so almost by definition, you have to make a bet on something that's years down the road.

但当前投入的资金与几年后可能实现的成果之间可能存在脱节。

But there may be a disconnect between the money that's being spent now and what is possible just a few years down the road.

你的意思是，这些公司押下重注追求（如你所说）像登月计划般的人工通用智能，其潜在收益就是可能成为成功登月的公司。

What you're saying is that the upside for these companies of taking this massive gamble on what is essentially, as you've described it, a moonshot of reaching artificial general intelligence, is that you might be the company that lands on the moon.

但风险在于，如果这些公司都判断错误呢？

The downside though is what if these companies are wrong?

如果根本不存在登月这回事呢？

What if there is no moon landing?

如果没有登月成功呢？

What if there's no moon landing?

或者如果只有一家公司成功登月呢？

Or what if only one company lands on the moon?

又或者只有两家成功，其余公司都悬在半空呢？

Or what if only two land there and the rest are left hanging?

这种情况下，即便有人获胜，也会有很多人血本无归。

This is a situation where even if somebody wins, a lot of people are going to lose.

OpenAI首席执行官萨姆·奥特曼在今年夏天旧金山的一次晚宴上如此表示。

Sam Altman, the chief executive of OpenAI, said as much during a dinner I attended here in San Francisco this summer.

他反问道：我们是否正处于投资者整体对人工智能过度兴奋的阶段？

He said rhetorically, are we in a phase where investors as a whole are overexcited about AI?

他说，在我看来，确实如此。

In my opinion, he said, yes.

他承认，从某些方面来看，这种大量投资至少部分是不理性的。

He acknowledged that a lot of this spending was, at least in some ways, irrational.

他还表示这种情况将会产生失败者。

And he said that there would be losers in this scenario.

这场引发全球头条的晚宴后，许多人开始使用'泡沫'这个词。

After this dinner, which made headlines across the country and across the world, a lot of people started using the word bubble.

当我在硅谷与金融分析师和技术历史学家讨论我们正在经历的这个时代时，他们常常会回顾九十年代末的互联网泡沫时期，特别是当早期互联网技术展现出巨大潜力，而硅谷开始大规模投资的那个二月。

And when I talk to people here in Silicon Valley and financial analysts and tech historians about this moment we're living through, what they often point back to is the dot com bubble of the late nineties and February when early Internet technologies showed enormous promise and the Valley started to invest enormous amounts of money in it.

好的。

Okay.

我们来谈谈互联网泡沫，具体来说，与我们现在所处的人工智能时代相比，有哪些异同？

Let's talk about the dot com bubble, and and specifically, what's different and what's similar to the moment that we're in now with AI?

对于经历过泡沫时期的人来说，他们印象最深的是大量初创企业涌现并上市，尽管几乎没有商业模式和收入，却获得了极高的估值。

Well, for people who live through the bubble, what they often think of is an enormous number of startups that were created and that went public and had huge valuations even though they had little or no business model, certainly no revenues.

而当市场崩盘，当人们意识到支出已超出实际可能时，许多这样的公司便倒闭了。

And then when the market crashed, when people decided that the spending was getting ahead of what was possible, a lot of those companies went out of business.

比如Cosmo这样直接送货上门的公司。

Companies like Cosmo that delivered goods straight to your door.

Pets.com，一家为你寄送宠物食品的公司。

Pets.com, which sent you pet food.

这方面有许多著名的例子，人们通常想到的就是这些。

There are famous examples of this, and that's often what people think of.

但在这背后——这个类比至今依然成立——当那些初创公司成立时，还有另一些公司在建设推动互联网所需的基础设施，它们投入巨资铺设光纤电缆，将海量信息通过互联网传输到我们的设备上。

But underneath that, and this is where the analogy really holds up to today, as those startups were being built, there were other companies that were building the infrastructure needed to drive the internet, that were spending enormous amounts of money to lay the fiber optic cable that would carry all that information across the internet to our machines.

泡沫破裂时，许多这类公司都破产了。

When the bubble burst, a lot of those companies went bankrupt.

这正是人们回顾互联网泡沫时常常想到的情景。

And that's often what people are thinking about, as they look back at the dot com bubble.

也就是说，人们担心那些正在铺设AI革命'光纤'的公司——用这个类比来说就是那些容纳所有芯片的数据中心——可能会倒闭。

Meaning, there's a fear that the companies that are laying the fiber optics of the AI revolution, which is, you know, the analogy would say these data centers that are housing all of these chips, that those companies could go under.

这就是担忧所在。

That's the fear.

就像当年一样，现在也有公司在为推进这项技术所需的基础设施投入巨额资金。

Just like then, you have companies spending enormous amounts of money on the infrastructure needed to drive on this.

不同之处在于，它们现在的投入比二十五年前要多得多。

The difference is they are spending a lot more today than they did twenty five years ago.

但凯特，让我印象深刻的是，虽然互联网泡沫确实破裂了，但也涌现出许许多多的赢家。

But I'm struck by the fact, Kate, that obviously the dot com bubble, it burst, but there were many, many winners.

对吧？

Right?

正如你所说，那个时代诞生的许多公司至今仍然存在。

I mean, we still have, as you said, a lot of these companies that were born in that era.

那么，这里的重点是什么？

So what's the takeaway there?

这个观点很棒。

This is a great point.

那些倒闭的初创公司曾承诺的许多应用，如今已成为我们日常生活的一部分。

So many of the applications that were promised by all those startups that went out of business are part of our daily lives today.

亚马逊为我们配送宠物食品。

Amazon delivers our pet food.

其他公司为我们提供实时网络视频。

Other companies deliver our real time Internet video.

当年承诺的许多事物如今已成现实，我们正在使用那些铺设多年却长期闲置的光纤电缆，现在终于收获了回报。

So many of the things that were promised in, we have today, and we're actually using that fiber optic cable that was laid and that sat there dormant for many years, and we are now reaping the benefits.

只是这一切没有人们预想的那么快实现。

It's just that it didn't happen as quickly as a lot of people thought.

所以对硅谷来说，那次泡沫的教训似乎可以简单总结为：确实，有些人会在那种情况下遭受损失。

So for Silicon Valley, it sounds like the lesson of that bubble could very easily be, sure, some people lose in a situation like that.

但总体而言，对互联网的押注是值得的。

But broadly, the bet on the Internet was worth it.

它带来了回报。

It paid off.

所以尽管下注吧。

So take the bet.

我交谈过的许多人都这么说。

So many people I talk to say that very thing.

他们指出，尽管泡沫破裂，但最终一切都如承诺的那样实现了。

They point out that in the end, despite the bubble bursting, eventually, everything turned out as promised.

他们做了这样的类比，这就是为什么他们今天要下如此巨大的赌注。

They make that analogy, and that's why they're making these enormous bets today.

他们承认可能会有输家，就像萨姆·奥特曼在那次晚餐上所说的那样，但他们认为最终会成功。

They acknowledge there might be losers, as Sam Altman did during that dinner, but they think it's going to work out in the end.

然而，硅谷和纽约金融分析师圈内的一些人担心，某些公司承担的风险远大于过去。

The concern, however, among some in the Valley and some in New York where the financial analysts are, is that the risk being taken on by some companies is far larger than in the past.

如果情况如此且泡沫再次破裂，后果可能会严重得多。

And if that's the case and the bubble bursts again, the fallout could be far more significant.

我们马上回来。

We'll be right back.

我是AO·斯科特。

This is AO Scott.

我是《纽约时报》的评论家。

I'm a critic at The New York Times.

如今有如此多的电影、书籍、电视节目和歌曲，让人难以理清头绪。

These days, there are so many movies and books and television shows and songs that it's hard to make sense of it all.

在《纽约时报》，我们评论家的工作就是尽可能多地筛选这些内容，提供建议和推荐，引导你关注那些值得你花时间和精力的作品。

At The New York Times, what the critics do is sort through as much of that as we can to come up with advice, with recommendations, to guide you toward the stuff that's worth your time and attention.

但我们不仅仅提供指南。

But we don't only offer guidance.

评论家的职责是帮助你理解事物，让你思考一部电影如何与历史或政治相联系，一首歌如何唤起情感，一件艺术品如何以只有艺术才能做到的奇妙方式照亮世界。

Critics are here to help you make sense of things, to get you thinking about the way a movie connects with history or politics, the way a song opens up emotion, how a piece of art illuminates the world in the magical way that only art can do.

事实上，我和这里其他评论家的工作，与《纽约时报》所有记者每日从事的项目同属一体，旨在为您提供清晰的视角，最重要的是，对世界更深入的理解。

Really, what I do and what the other critics here do is part of the same project that all of the journalists at The New York Times work on every day, to give you clarity and perspective, and above all, a deeper understanding of the world.

订阅《纽约时报》不仅能看到头条新闻，更能洞悉事件间的关联脉络。

When you subscribe to The New York Times, it's not just here are the headlines, but here's the way everything fits together.

如需订阅，请访问nytimes.com/subscribe。

If you'd like to subscribe, please go to nytimes.com/subscribe.

好的，凯德。

Okay, Cade.

让我们来谈谈你在休息前提到的那个令人担忧的问题——当前风险可能比预想中严重得多。

Let's get into the scary thing that you brought up before the break, that the risks here could be much more significant.

详细说说你的看法。

Talk to me about that.

我与各类人士讨论过这个问题，包括技术专家和金融分析师，他们常提到2000年代末的房地产泡沫，那场危机要严重得多。

Well, as I discussed this with all sorts of people, including technologists, but also financial analysts, the other thing that often comes up is the housing bubble of the late two thousands, which was a much more serious thing.

人们普遍认为我们目前并未经历类似情况。

People generally agree that this is not what we're going through at the moment.

不必过度类比。

Let's not go that far.

不过他们指出，当下某些现象确实与当时有相似之处。

That said, they do point out that there are elements that we're seeing now that were also present then.

具体是哪些相似点？

What are those elements?

他们在担忧什么？

What what's worrying them?

从根本上说，这关乎为建设这些数据中心所承担的巨额债务，以及为建造它们而借入的庞大资金。

Basically, this is about the enormous amount of debt that is being taken on to build these data centers, the enormous amount of money that's being borrowed to build them.

当你审视这些债务时，很难确切知道其规模有多大，也不知道债务持有人是谁。

And as you look at that debt, it's hard to know how much there is and who is holding the debt.

如果这些债务分散在众多公司之间，那么系统性风险就会更高。

If that debt is spread across a lot of companies, then you have more systemic risk.

这种风险可能会对经济其他部分造成损害。

You have greater risk that could damage the rest of the economy.

没错。

Right.

这正是导致2008年危机如此严重的原因——房地产市场中积累的巨额债务。

That was the thing that made the two thousand eight crash so bad, the amount of debt that had piled up under the housing market.

但这些科技公司可是全球最富有的企业之一。

But these tech companies, they're some of the richest corporations in the world.

那为什么他们还要通过债务融资来推动AI热潮呢？

So why are they financing the AI boom with debt?

为什么会这样？

Why is that happening?

嗯，有些公司并没有通过举债来做这件事。

Well, some companies are not taking on debt to do this.

像谷歌、微软和Meta这样的公司每年都能获得数十亿美元的收入。

Some companies like Google and Microsoft and Meta pull in billions of dollars in revenue every year.

他们完全有能力用现金支付这些巨型数据中心的费用。

They can afford to essentially pay cash for these giant data centers.

但人们对AI的兴趣如此浓厚。

But there's so much interest in AI.

对这些数据中心提供的计算能力需求如此之大，以至于我们看到各种其他公司在资金不足的情况下仍要建造这些巨型设施。

There's so much demand for the computing power that comes out of these data centers that we're seeing all sorts of other companies build these giant facilities when they don't have the money to do it.

即便是像甲骨文这样的相对大型公司——云计算巨头也不得不举债建设数据中心。

Even relatively big companies like Oracle, the cloud computing giant is having to take on debt to build data centers.

然后还有一大堆地球上大多数人从未听说过的小公司，名字诸如CoreWeave、Lambda和Nebius。

And then you have all these smaller companies that most people on earth have never heard of with names like CoreWeave, Lambda, and Nebius.

确实从没听说过它们。

Definitely never heard of them.

它们肯定也在为此举债。

They are certainly taking on debt to do this.

总部位于纽约-新泽西地区的Corweave公司向金融分析师透露，每建造50亿美元的数据中心基础设施，它们就需承担近30亿美元的债务。

Corweave, a company based in the New York, New Jersey area, has told financial analysts that for every $5,000,000,000 in data center infrastructure they build, they have to take on almost $3,000,000,000 in debt.

哇哦。

Woah.

最终，它们认为将获得偿还这些债务所需的收入。

In the end, they think that they will pull in the revenues needed to pay back those debts.

但归根结底，如果AI技术无法带来收益，就无法偿还债务，那时就会出问题。

But ultimately, if the AI technology does not pull in the money, then you can't repay those debts, and that's when you have a problem.

明白了。

Got it.

Cade，你提到的另一点让我很震惊——当你审视这些债务时，实际上很难确知其规模究竟有多大。

And I was struck by something else that you said, Cade, which is that when you look at the debt here, it's actually hard to know how much of it there is.

那是什么意思？

What's that about?

为什么我们不知道这件事？

Why why don't we know that?

嗯，部分债务确实是以你想象的方式产生的。

Well, some of the debt is taken on in the way you might think.

这些公司会去银行借钱。

These companies go to a bank and they borrow the money.

你清楚地知道谁借出钱、谁借入钱以及具体金额。

And you know exactly who lent it, who borrowed it, how much it is.

但越来越多交易中，我们很难看清债务的来源和具体数额。

But increasingly, we're seeing other deals where it's hard to see where the debt is and how much of it there is.

大量资金是由所谓的私人信贷机构放贷的。

A lot of the money is being lent by what are called private credit institutions.

从法律上讲，你无法查看这些公司的内部情况。

Legally, you can't see inside these companies.

另一个现象是这类证券的兴起。

The other thing that's happening is you're seeing the rise of these securities.

他们称之为资产支持证券，这种在房地产泡沫时期出现的东西人们可能比较熟悉。

They call them asset backed securities, something that came up during the housing bubble that people may be familiar with.

以一种不太好的方式让人想起往事。

Reminiscent in a not great way.

这些证券可以买卖交易，意味着你最终无法确定债务的实际持有人是谁。

These securities can be bought and sold and traded, and that means you don't know in the end, who is holding the debt.

你是说存在这样一种观点，对吧，即所有这些债务中可能潜藏着真正的系统性风险，而系统中的杠杆水平难以准确衡量。

You're saying there's this idea, right, that there could be real systemic risk baked into all this debt, that the leverage in the system is just hard to pin down.

因此我们目前确实无法确切知道我们所有人可能面临多大的风险敞口。

And so we really can't actually know at this point how exposed we all might be to it.

没错。

That's right.

这里的关键词是'可能'。

The keyword there is could.

可能存在一个问题。

There could be a problem.

这很难判断。

It's hard to know.

对。

Right.

这显然是个非常模糊不清的问题。

It's obviously a really murky thing.

但关于系统中债务规模的问题，我们有什么确凿的认知吗？

But is there anything that we know definitively about the magnitude of the debt in the system?

具体有多大体量？

About how big we're talking?

正如我之前所说，预计全球企业将在这些数据中心上花费近3万亿美元。

As I said earlier, it's projected that companies across the world will spend nearly $3,000,000,000,000 on these data centers.

摩根士丹利的分析师预测其中约三分之一将是债务，即1万亿美元。

Analysts at Morgan Stanley project that about a third of that will be debt, $1,000,000,000,000.

哇。

Wow.

从你的话里退一步看，似乎真的很难判断我们现在处于什么样的泡沫中，以及它可能有多糟糕或不糟糕。

Just pulling back from what you're saying, it sounds like it's actually quite hard to know what kind of bubble we may be in right now and how bad or not bad it may be.

我是说，有互联网泡沫的例子，对吧，它确实有影响，但听起来相对受控，并且造就了所有这些赢家。

I mean, there's the .com example, right, which had fallout, but it sounds like was relatively contained and produced all these winners.

然后还有风险大得多的版本，更接近我们在住房危机期间看到的情况，可能会产生更广泛的影响。

And then there's the much riskier version of things, closer to elements of things that we saw during the housing crisis that could have a much broader effect.

由于这一切中有太多未知因素，我们真的无法判断。

And because of all that's unknowable in all this, we can't really tell.

是这样吗？

Is that right?

我们做不到。

We can't.

如果真的爆发危机，我们甚至很难预知何时会发生。

If things do burst, it's hard to even know when that might happen.

像山姆·奥特曼和谷歌母公司Alphabet的CEO桑达尔·皮查伊这样的人，都承认这种不确定性。

And people like Sam Altman and Sundar Pichai, the CEO of Alphabet, the Google parent company, have acknowledged this uncertainty.

你知道吗，我一直在思考这件事里的讽刺之处——从某些角度看，对投资AI热潮的公司而言，最坏的情况反而是永远无法实现通用人工智能（AGI），即电脑无法大规模取代人类工人，AI永远达不到人脑智能水平，或者说这个目标需要极长时间才能实现。

You know, there's this irony that I've been thinking about in all this, which is that in some ways, the worst case scenario for the companies that are invested in the AI boom, right, is that they never actually reach AGI, that point where computers replace human workers en masse, where AI becomes as smart as the human brain, or that that really takes a very long time.

但我觉得，对我们许多人类劳动者来说，硅谷这个'最坏情况'反而可能是种解脱。

But I think there's a lot of us human workers who might actually view that worst case scenario for Silicon Valley as a relief.

就像，如果听说我们明天不会被大规模取代，人们普遍可能会感到高兴。

Like, people might be happy, generally, to hear that we aren't gonna be replaced en masse tomorrow.

我想知道你对这种紧张关系怎么看。

And I wonder what you make of that tension.

事实上，他们在这里努力构建的未来，可能并不是很多人真正想要的未来。

The fact that the future that they're building toward here may not actually be a future that all that many people actually want.

说得很对。

It's a great point.

当我们思考当下时，需要认清这项技术的现实情况。

As we think about this moment, we need to realize the realities of this technology.

它在很多方面都非常强大。

It is very powerful in many ways.

医疗领域或许是最典型的例子，比如药物研发。

Healthcare being perhaps the prime example, drug discovery.

我们正走在通往一些非凡成就的道路上。

We are on the path towards some amazing things.

与此同时，我们也正走向一些令人担忧的事情。

At the same time, we're on the path towards some things that are concerning.

正如我们讨论过的，如果发展速度跟不上硅谷的预期，可能会对整个经济体系造成问题。

If things don't progress at the pace that Silicon Valley says, this could cause problems across the larger economy, as we talked about.

但这或许能给我们所需的时间，继续思考悬在这项技术和我们未来之上的所有重大问题。

But it might give us the time we need to continue to think about all the big questions that hang over this technology and that hang over our future.

这可能让我们有时间去为那个未来做准备。

It might give us time to prepare for that future.

好的，凯特，非常感谢你。

Well, Kate, thank you so much.

很高兴来到这里。

Glad to be here.

周三下午，英伟达宣布最近一个季度其利润达到319亿美元，同比增长65%，并创下销售纪录。

On Wednesday afternoon, NVIDIA announced that in the most recent quarter, its profit was $31,900,000,000, up 65% from a year ago, and it reported record sales.

这一消息提振了其盘后交易股价，被视为至少暂时缓解了华尔街对人工智能的担忧信号。

The news buoyed its shares in aftermarket trading and was seen as a sign the jitters on Wall Street over AI had been calmed, at least for now.

我们马上回来。

We'll be right back.

嘿。

Hey.

我是《纽约时报》旗下产品推荐服务Wire Cutter的劳伦·德拉贡，我负责测试耳机。

It's Lauren Dragon from Wire Cutter, the product recommendation service from The New York Times, and I test headphones.

我们基本上会自制人工汗液，反复喷洒在这些耳机上，观察它们随时间的变化。

We basically make our own fake sweat and spray it over and over on these headphones to see what happens to them over time.

我们要

We're gonna

戴上降噪耳机，看看它们实际隔音效果如何。

put on some noise canceling headphones and see how well they actually block out the sounds.

我的数据库里有3136条记录。

I have 3,136 entries in my database.

孩子们，锻炼时间。

Kids, workout.

蓝牙是什么版本？

What version of Bluetooth?

在Wirecutter，我们替您完成所有调研工作。

At Wirecutter, we do the work so you don't have to.

如需获取真实世界的独立产品评测与推荐，请访问我们的网站nytimes.com/wirecutter。

For independent product reviews and recommendations for the real world, come visit us at nytimes.com/wirecutter.

以下是今日其他值得关注的要闻。

Here's what else you should know today.

周三，特朗普总统在社交媒体上宣布已签署法案，要求司法部在三十天内公布杰弗里·爱泼斯坦的相关档案。

On Wednesday, president Trump announced on social media that he'd signed legislation calling on the justice department to release its files on Jeffrey Epstein within thirty days.

但特朗普的签署并不保证所有档案都会被公开。

But Trump's signature doesn't guarantee the release of all the files.

该法案包含重要例外条款，其中规定若文件公开可能危及正在进行的联邦调查，则允许不予披露。

The bill contains significant exceptions, including a provision that allows records to be withheld if they jeopardize an active federal investigation.

上周，特朗普要求司法部对文件中提及的民主党人展开调查，司法部长帕姆·邦迪表示已启动调查。

Last week, Trump demanded that the justice department launch an investigation into Democrats mentioned in some of the files, and attorney general Pam Bondi said she'd started one.

这可能为政府提供了另一个扣留文件的理由。

That could give the administration another reason to withhold documents.

在周三一场引人注目的听证会上，联邦法官严厉质询了起诉前FBI局长詹姆斯·科米的政府检察官，揭露了他们案件中的重大漏洞。

And in a remarkable hearing on Wednesday, a federal judge grilled government prosecutors pursuing charges against former FBI director James Comey, revealing serious vulnerabilities in their case.

面对法官的质询，由特朗普亲自挑选负责此案的美国检察官林赛·哈利根承认，她从未向大陪审团全体成员展示过科米起诉书的第二版即最终版本，就在首席陪审员签署了起诉文件。

In response to the judge's questioning, Lindsey Halligan, the US attorney handpicked by Trump to bring the case, admitted she'd never shown the second and final version of the Comey indictment to the full grand jury before the foreperson signed the charging document.

科米的律师立即抓住这一程序违规，称这足以证明应彻底驳回此案。

Comey's lawyers immediately seized on that irregularity, saying it justified dismissing the case entirely.

法官并未立即对科米关于此案是特朗普报复行为的指控作出裁决，但似乎倾向于认同这一观点，并支持完全撤销指控。

The judge didn't immediately rule on Comey's claim that the case had been filed as an act of retribution by Trump, but he seemed to be leaning in that direction and in favor of throwing out the charges altogether.

此案驳回对特朗普司法部而言将是一次羞辱，该起诉从一开始就显得草率。

The dismissal would be a humiliation for Trump's justice department department in a prosecution that's appeared to be slapdash from its very inception.

本期节目由Ricky Nevetsky、Shannon Lynn和Carlos Prieto制作。

Today's episode was produced by Ricky Nevetsky, Shannon Lynn, and Carlos Prieto.

由Mark George和Lisa Chow负责剪辑。

It was edited by Mark George and Lisa Chow.

音乐由Dan Powell和Marion Lozano创作，Alyssa Moxley担任音效工程师。

Contains music by Dan Powell and Marion Lozano and was engineered by Alyssa Moxley.

以上就是本期《每日播报》的全部内容。

That's it for The Daily.

我是主持人Natalie Kitcheroeth。

I'm Natalie Kitcheroeth.

明天见。

See you tomorrow.