The Most Concerning AI Bubble Signals — 文稿

M10:00

随着AI IPO越来越近，关于AI泡沫的讨论也越来越热闹了。

As the AI IPO inches closer, discussions of an AI bubble are also getting a lot louder.

担忧的范围从亚马逊仓库里闲置的GPU，到新型云厂商的债务质量，再到企业AI收入的高度集中。

The concerns range from GPUs sitting in Amazon warehouses unused, to the quality of neocloud debt, to the concentration of enterprise AI revenue.

在这一集里，我们将会逐一分析这些担忧，讨论哪些实际上最令人担忧，而那些尚不必担心的，未来什么情况会让它们变得更加令人担忧。

In this episode, we're going to go through all of those concerns, talking about which are in fact most concerning, and for those that aren't, what would make them more concerning in the future.

《AI每日简报》是一个每日更新的播客和视频节目，专注于AI领域最重要的新闻和讨论。

The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI.

好了朋友们，在深入之前先快速说几个通知。

All right, friends, quick announcements before we dive in.

M10:55

我们这次要做一个好久没做的事情——一期关于AI泡沫的节目。

We're doing something we haven't done for a while, which is an AI bubble episode.

最近，越来越多的人高喊AI泡沫已经走到了尽头。

Now, recently, the calls have been getting louder that the AI bubble has reached the end of the road.

周三，美国金融改革组织发布了一份报告，警告说泡沫——用他们的话讲——已经“蓄势待爆”。

On Wednesday, Americans for Financial Reform produced a report warning that the bubble is, in their words, primed to pop.

高级政策分析师Maya Jenkins警告说，如果不做出改变，劳动者将为一轮AI崩盘付出高昂代价。

Senior policy analyst Maya Jenkins warned, if nothing changes, working people will pay a high price for an AI crash.

政策制定者应该采取紧急行动来降低风险。

Policymakers should be taking urgent action to reduce the risks.

当然，关于泡沫的讨论自从去年占据叙事主导地位以来，已经发生了不小的变化。

The bubble discourse has, of course, evolved quite a bit since its dominant place in the narrative last year.

在过去一个月里，很多人都指出了不少警示信号。

And there have been many things that people have been pointing to as warning signs over the past month.

今天我们讨论的是，哪些信号最重要，有哪些理由让我们保持乐观——或者至少没那么恐惧——以及在每种情况下，如果出现什么变化会让我更加担忧。

What we're going to talk about today is which of these signs matter most, what the reasons for optimism, or at least reduced fear, are, and what things in each of those cases, if we saw them happen, would make me more concerned.

不过首先，先来点背景信息。

First though, a bit of background.

科技股已经连续三周下跌，纳斯达克指数在经历相对平淡的一周后，周四又跌了3%。

We're coming up on a 3-week downtrend for tech stocks, with the Nasdaq losing 3% on Thursday following a relatively flat week.

有人把原因归咎于Meta周三晚间的财报电话会，会上明确表示，他们AI建设下一阶段的资金部分将通过股权稀释来筹集。

Some blamed Meta's Wednesday night earnings call, which made it clear that the next leg of their AI buildout would be partially funded by equity dilution.

不过，这轮抛售已经持续了好几周了。

This sell-off, though, has been happening for weeks.

高盛在最新的资金流动报告中说，上周对冲基金抛售科技股的速度至少是十年来最快的。

In their latest trading flow report, Goldman Sachs reported that hedge funds sold tech stocks at their most rapid pace in at least a decade last week.

周四的交易中还出现了一个有趣的变化。

We also got an interesting change in behavior during the Thursday session.

过去几个月里，美国国债利率飙升，带动商业债券利率上升，使得数据中心融资变得更加昂贵。

For the past few months, Treasury bond rates have been surging, dragging up interest rates on commercial bonds and making data center financing more expensive.

周四，超长期30年期美国国债收益率跌至一个月低点5.38%。

On Thursday, the ultra-long 30-year US Treasury bond dropped to a 1-month low of 5.38%.

现在说还为时尚早，而且短期债券的收益率到目前为止还没有下降，但这表明市场上出现了经典的“避险”反应。

Now, this is early, and none of the shorter-dated bonds have seen falling rates so far, but this is indicative of a classic flight-to-safety reaction in the markets.

换句话说，更多资金正在流出AI交易这样的风险资产，涌入国债等安全港湾，这可能预示着未来更多的麻烦。

In other words, more money flowing out of risky assets like the AI trade and into the safe havens of Treasuries, which could spell more trouble ahead.

当然，过去几周也出现了不少看空的分析。

Certainly, the past few weeks have also seen quite a bit of bearish analysis.

一个典型的例子是Gartner，他们抓住新型云厂商的挫折不放，声称到2030年底，80%的新型云厂商将会破产。

One big example was Gartner, who latched onto stumbles in the neocloud sector to claim that 80% of neoclouds will go bankrupt by the end of 2030.

他们的报告认为，到那时，由于需求不足，3.5万亿美元的AI基础设施支出将面临减值。

Their report argued that $3.5 trillion in AI infrastructure spending would be subject to an impairment by then due to a lack of demand.

Gartner的首席预测师John Lovelock周一告诉CNBC说：“目前我们的算力超过了需求，很多token和处理能力都在通过免费增值模式赠送出去。”

Gartner's chief forecaster John Lovelock told CNBC on Monday, at the moment, we have more compute capacity than we have demand, and we have a lot of the tokens and processing power being given away in freemium solutions.

参与AI竞赛的每个人都在争夺最后一个站着的位置。

Everyone in the AI race is running for a last-man-standing position.

Gartner追踪的AI竞赛中的几乎每一个市场，都可能会萎缩成双寡头格局。

Pretty much every market that Gartner is tracking in our AI race is likely to collapse down to a duopoly.

用数字来具体说明的话，Gartner估计，到2030年，这些数据中心的所有者需要产生8.5万亿美元的收入，才能覆盖他们已公布的资本支出、融资成本和投资资本回报。

To put some numbers around this, Gartner estimated that through 2030, the owners of these data centers would need to generate $8.5 trillion in revenue to cover what they have announced around capital spending, financing costs, and a return on invested capital.

从等式的另一边来看，他们争论说，他们认为企业和消费者AI总收入预计不会超过3.6万亿美元。

On the other side of the equation, they argued though, they believe that total enterprise and consumer AI revenue is forecasted to not reach more than $3.6 trillion.

如果高德纳是对的，这个差距还挺大的。

Quite a big gap if Gartner are right.

与此同时，这掀起了一整周关于AI泡沫恐慌的热烈新闻周期。

That meanwhile kicked off a frenetic week-long news cycle around AI bubble fears.

Citadel的CEO肯·格里芬是众多发表意见的人之一。

Citadel CEO Ken Griffin was one of many offering his opinion.

在周二的一个华尔街会议上，他宣称我们几乎肯定处于一个泡沫之中。

At a Wall Street conference on Tuesday, he proclaimed that we are almost certainly in the middle of a bubble.

他的论点主要围绕不确定的投资回报率导致对AI支出重新思考。

His argument hinged on uncertain ROI causing a rethink on AI spending.

格里芬评论说，美国企业在从AI模型中提取价值的能力上一直非常不均衡。

Griffin commented, corporate America has been very uneven in its ability to extract value from its AI models.

我认为整个美国企业都在看着他们来自Anthropic和OpenAI的账单，然后想，好吧，我们需要考虑如何确保我们从中获得了生产力。

I think all of corporate America is looking at their bills from Anthropic and OpenAI and going, okay, we're going to need to think about how we're sure we're getting productivity out of this.

这并不是说泡沫论已经是共识了。

Which is not to say that bubble calls have been consensus.

在争论的另一边，来自私募股权公司黑石的领导们本周纷纷发声。

On the other side of the argument, leaders from private equity firm Blackstone were out in force this week.

当然，这里需要打个折扣，因为黑石在新云领域有大量的股权和债务头寸，包括在CoreWeave和Firmus的早期投资。

Now, the grain of salt here is, of course, that Blackstone has massive equity and debt positions in the neocloud sector, including extremely early involvement in CoreWeave and Firmus.

但上周，资深高管Jas Khaira表示，他并不担心数据中心的债务。

But last week, veteran executive Jas Khaira said that he isn't concerned about data center debt.

因为超大规模云服务商是租户，Khaira声称这些债务最终由世界上最值得信赖的公司支持。

Because hyperscalers are the tenants, Khaira claimed that this debt is ultimately backed by the most creditworthy companies in the world.

这是他的原话。

His phrase.

在周四接受彭博社采访时，黑石总裁John Gray直接回应了肯·格里芬关于泡沫的评论。

In a Bloomberg interview on Thursday, Blackstone President John Gray spoke directly to Ken Griffin's bubble comments.

Gray说：“当你想到泡沫时，你会想到先建设产能，然后希望需求会来。

Gray said, "When you think about a bubble, you think about building capacity and then hoping the demand comes.

在AI领域，你是在建设产能，然后希望你能跟上需求。”现在这里值得怀疑的是。

With AI, you're building capacity and you're hoping you can keep up with demand." Now the thing to be skeptical here.

就是你看到的每一个分析市场的专家都有利益关系。

Is that every talking head you see analyzing markets has a dog in the fight.

我提到过黑石在CoreWeave和Firmus等公司有头寸，但反过来，肯·格里芬在市场波动时获利最多。

I mentioned that Blackstone has positions in companies like CoreWeave and Firmus, but on the flip side, Ken Griffin profits most when there's volatility in the market.

但这些讨论中有一条主线，正如你将看到的，我认为这是最终唯一重要的事情，那就是需求问题。

But there is a through line to this discourse that, as you'll see, I think is pretty much the only thing ultimately that will matter, which is the question of demand.

在很多方面，其他一切都只是为一个大问题而进行的代理斗争，那就是未来会有多少AI需求？

In many ways, everything else is just a proxy fight for the big question of how much AI demand is there going to be?

以及这些需求的价值是否最终高于投入基础设施的金额。

And whether the value of that demand is ultimately higher than the amount being spent on the infrastructure.

现在，随着我们深入探讨过去几周塑造市场的一些重大事件，并试图区分哪些信号重要哪些不重要，我认为有必要对我们的术语做一些精确的定义。

Now, as we dig deeper into some of the big events that have shaped markets over the past couple of weeks and try to sort through the signals that matter from those that don't, I think it is worth being somewhat precise about our terms.

当我们使用像“AI泡沫”这样的大灾难术语时，我们失去了细微差别。那些谈论股市熊市、导致股市下跌20%或30%的人，与谈论像互联网泡沫破裂那样的世代泡沫爆发的人，说的是完全不同的事情。互联网泡沫破裂在两年内让纳斯达克市值蒸发了超过75%。

When we use big apocalyptic terms like AI bubble, we lose nuance, and people who are talking about a bear market in stocks of the kind that takes stock markets down 20 or 30% are talking about something quite different than a generational bubble burst like the dot-com crash, which saw over 75% wiped off the NASDAQ across 2 years.

换句话说，股市崩盘与信贷危机或金融危机不是一回事。

Stock market crashes, in other words, are not the same as a credit or financial crisis.

你可以只有其中之一而没有另一个，而在这两者中，股市崩盘的破坏性要小得多。

You can have one without the other, and of the two, a stock market crash is far less damaging.

虽然对于投资于市场的人，特别是那些依赖市场投资的人（比如靠固定收益退休账户生活的人）来说，这绝对痛苦，有时甚至极其痛苦，但如果更广泛的金融体系中没有银行系统性问题的存在，市场可以自然恢复。

While absolutely painful, sometimes extremely so, for those invested in the markets, and especially those who rely on their investments in markets, like those living off fixed-income retirement accounts, if there's not a systemic problem for banks in the broader financial system, markets can recover naturally.

另一方面，信贷危机则是一个完全不同的问题，大规模违约和传染会在整个经济中造成损害，可能需要央行干预。

A credit crisis, on the other hand, where mass defaults and contagion create impairments throughout the economy, is quite a different problem and one that can require central bank intervention.

现在，如果说AI交易中有一个领域本月一直是关注的焦点，那就是新云公司。

Now, if there's one segment of the AI trade that's been the locus of concern this month, it's the neo-clouds.

在澳大利亚，Firmus的IPO被取消了，因为投资银行无法以他们期望的价格找到足够的买家。

We had the Firmus IPO in Australia getting canceled after investment banks couldn't find enough buyers at their desired price.

随后，一部分 CoreWeave 的债务被降到 distressed 水平，意味着有相当高的违约风险。

Then a portion of CoreWeave debt traded down to distressed levels, implying a reasonable chance of default.

微软随后因电力延迟退出了英国一个计划中的数据中心，让 Nscale 陷入困境。

Microsoft then pulled out of a planned data center in the UK because of power delays, leaving Nscale high and dry.

而最近，我们开始看到 AI 巨头们赶来救援。

And more recently, we're starting to see the big players in AI ride to the rescue.

有传言称 Anthropic 正在与 Nscale 洽谈一笔新的 450 亿美元合同。

Anthropic is rumored to be in talks for a new $45 billion contract with Nscale.

高盛将 CoreWeave 股票升级为买入评级，表示对其债务的一些担忧被夸大了，而且股票已经被过度抛售。

Goldman Sachs has upgraded CoreWeave stock to a buy, saying that some concerns over their debt are overblown and the stock has become oversold.

还有传言称 Nvidia 正在洽谈向 Firmus 投资数亿美元，以帮助其融资，因为 Firmus 之前的 IPO 失败了。

And Nvidia is rumored to be in talks to invest hundreds of millions into Firmus to help finance them after that failed IPO.

当然，要说 NeoCloud 的紧张情绪被夸大了，那肯定就说得太过了。

It would certainly be going too far to say that the NeoCloud jitters are overblown.

这绝对是一个值得关注的市场领域，投资者正在密切关注。

It is absolutely an area of the market to watch, and investors are keeping a very close eye on it.

但同样重要的是，要把我们谈论的数字放在正确的视角来看。

But it's also important to keep the numbers we're talking about in perspective.

Nscale 的目标是进行 300 亿美元的 IPO。

Nscale is targeting a $30 billion IPO.

在这个关键公司总价值约 10 万亿美元的行业中，一个 300 亿美元的公司相对而言只是个小虾米。

In an industry where the key firms are worth around $10 trillion as a collective, a $30 billion company is a relative minnow.

从严格的经济角度来看，整个 NeoCloud 行业可能会归零，而不会产生太大影响。

From strictly an economic perspective, it's likely the entire NeoCloud sector could go to zero without it having much of an effect.

当然，除了叙事影响可能非常巨大。

Other than of course the narrative effect which would be gigantic.

这就是为什么巨头们正在联合起来支持这些小角色。

And that's why the big players are coming together to backstop the small guys.

根据信息，Nvidia 已经通过信用担保和数据中心租赁支持为 NeoCloud 提供了 1700 亿美元的支持。

According to the information, Nvidia has already provided $170 billion in support for the NeoClouds through credit guarantees and data center rental backstops.

前沿实验室和超大规模云提供商也表明，如果任何人出现严重不稳定，他们愿意将价值数十亿美元的合同放到头条上。

The Frontier Labs and hyperscalers have also shown they're willing to put multi-billion-dollar contracts in the headlines if anyone gets too shaky.

整个行业都有巨大的既得利益，要确保这些公司存活并且他们的数据中心建成。

The entire industry has a huge vested interest in making sure these companies survive and their data centers get built.

那么，什么才是最值得担忧的信号？

So what then would be the most worrying concerns to watch for?

如果一个 NeoCloud 陷入困境并且没有人前来救援，那将是一个更令人担忧的信号。

If a NeoCloud gets into trouble and nobody rides to the rescue, that would be a more concerning signal.

如果困境从 CoreWeave 自己的债券开始蔓延到租给 Meta、微软或谷歌的数据中心的项目债务，那可能表明市场怀疑的是租户，而不仅仅是 NeoCloud。

If distress started to spread from CoreWeave's own bonds to project debt for data centers leased to Meta, Microsoft, or Google, that might suggest that the markets doubt the tenant, not just the NeoCloud.

最后，如果一个超大规模云提供商或实验室因为不需要而放弃容量，那将是一个巨大的信号。

Finally, if a hyperscaler or lab walks away from capacity because it doesn't need it, that would be huge.

记住，微软退出英国被非常具体地归咎于电力延迟。

Remember, Microsoft's UK exit was blamed very specifically on power delays.

如果取消的原因是需求问题，那就完全是另外一回事了。

A cancellation blamed on demand would be a totally different story.

本周一些评论员非常关注的一个消息是，亚马逊有一大堆 GPU 在仓库里积灰尘。

One story that's getting a ton of attention from certain critics this week is that Amazon has a huge pile of GPUs gathering dust in a warehouse.

周二，Business Insider 报道，根据一个新的早期机架接收流程，AWS 预计在最终部署之前，会在美国设施接收大约 50 亿美元的 NVIDIA GB300 服务器机架。

On Tuesday, Business Insider wrote, under a new early rack receipt process, AWS expects to receive roughly $5 billion in NVIDIA's GB300 server racks at US facilities before final deployment.

该公司预计在可预见的未来，每个月还有大约 30 亿美元的 GB300 机架。

The company projected roughly $3 billion more in GB300 racks each month for the foreseeable future.

GB300 是目前最高端的 AI 芯片，是 Blackwell 系列的最新产品。

GB300s are the current top-of-the-range AI chips, the latest in the Blackwell series.

消息人士称，亚马逊有空间容纳更多机架，但没有电力来启动它们。

Sources said that Amazon has room for more racks, but they don't have the power to turn them on.

根据 Business Insider 看到的邮件，AWS 至少有一个团队没有明确的计划来安装这些新机架。

According to emails viewed by Business Insider, at least one team at AWS did not have a clear forecasted path to getting the new racks installed.

亚马逊发言人表示，提前在施工前摆放硬件是常规做法，准备好一旦电力可用就插入 GPU 是最佳商业实践。

An Amazon spokesperson said it's routine to stage hardware ahead of construction and that being prepared to plug in GPUs once the power is available is best business practice.

文章还提到，亚马逊正试图抢在竞争对手之前获取稀缺的 GPU。

The article also noted that Amazon is attempting to secure scarce GPUs ahead of the competition.

本周批评者的观点是，Nvidia 似乎在强迫超大规模云服务商接收 GPU，即使他们没有电力来使用这些 GPU，因为担心失去未来芯片的分配。

The critics' take here this week has been the idea that Nvidia is somehow forcing hyperscalers to take delivery of GPUs even if they don't have the power to use them for fear of losing allocation to future chips.

有直接的说法称，Nvidia 在渠道塞货，或者强迫销售以更快实现收入。

There have been direct claims that Nvidia is channel stuffing or forcing sales to realize revenue more quickly.

基本上，就是那个冷酷而强大的 Jensen Huang 把所有超大规模云服务商都捏在手心里。

Basically, that the ruthless and powerful Jensen Huang has all the hyperscalers under his thumb.

按照这些批评者的逻辑，这意味着 Nvidia 的部分收入是假的，对 GPU 以及人工智能的需求比看起来更疲软，整个泡沫即将破裂。

As the logic among those critics goes, this means that some amount of Nvidia's revenue is fake, demand for GPUs and therefore AI is softer than it appears, and the whole bubble is getting ready to fall apart.

我很难得出同样的结论。

I have a hard time coming to the same conclusion.

没有理由怀疑 Business Insider 的报道——他们在 AWS 有很好的消息来源，这显然是一篇耗时数月的调查报道，旨在查明实际安装了多少 GPU。

There's no reason to doubt Business Insider's reporting— they're very well-sourced at AWS, and this has clearly been a months-long investigative piece to find out how many GPUs are actually being installed.

但用奥卡姆剃刀来解释，这里的问题不是缺乏人工智能需求。

But the Occam's razor explanation here is not a lack of AI demand.

而是缺乏已通电的数据中心。

It's that there's a lack of powered-up data centers.

即便 Jensen 是一个冷酷的商人，亚马逊也不会订购数百亿颗 GPU，如果长远计划只是无限期地将它们存放在仓库里。

Amazon, even if Jensen was a ruthless businessman, would not be ordering tens of billions of GPUs if the long-term plan is just to warehouse them indefinitely.

更合理的解释是，亚马逊确实担心未来能否获得芯片。

It would make much more sense that Amazon is genuinely concerned about future access to chips.

目前，GPU 仍然以极高的溢价定价，旧硬件的售价甚至超过原价。

Currently, GPUs are still being priced at a gigantic premium, with old hardware selling above its original price.

同时，旧硬件仍在积极使用，这降低了将 GPU 存放几个月的负面影响。

Meanwhile, old hardware is still in active use, reducing the harm in storing GPUs for a few months.

坦白说，在我们今天要讨论的很多事情中，这是一个让人觉得是在抓救命稻草的故事——寻找任何可能表明人工智能基础设施建设正在崩溃的迹象。

Frankly, among a lot of things that we'll talk about today, this is one story that feels like grasping at straws— looking for any possible sign that the AI infrastructure buildout is falling apart.

它有点过于依赖与互联网时代暗光纤的对比，但那时的问题是对已安装的基础设施需求不足。

It's leaning a bit too hard on the comparison to dark fiber during the dot-com era, but that was an issue of too little demand for already-installed infrastructure.

而现在是基础设施太少，无法满足需求。

This is too little infrastructure to service demand.

在建设数据中心和接通电力方面，确实有很多影响和问题，但这些问题最终并不能说明对 GPU 或人工智能的整体需求有什么问题。

There are plenty of implications and issues with the challenges of getting data centers built and power connected, but those issues don't have anything to say ultimately about the demand for GPUs or AI in general.

再次强调，仅仅根据最简单的解释——奥卡姆剃刀——如果 AWS 不得不存放 GPU，这更可能是需求极高的积极信号，而不是为了提升 Nvidia 利润的阴谋。

Again, just going by the simplest available explanation— Occam's razor— if AWS has to warehouse GPUs, it seems more likely to be a positive sign that demand is sky-high than a nefarious plot to boost Nvidia earnings.

坦白说，即使真是这样，也恰恰说明 Nvidia 仍然拥有绝对的定价权。

And frankly, even if that is the case, it just demonstrates that Nvidia still has all the pricing power in the world.

不过，在每个人脑海中悄然浮现的问题是，所有这些数据中心债务到底在哪里。

Quietly bubbling away in the back of everyone's mind though is the question of where all the data center debt is sitting.

这又回到了那个观点，即股市崩盘与更系统性问题之间的区别。

This gets back to that idea of the difference between a stock market crash and a more systemic issue.

尤其是在人们经历过2008年之后，每当市场出现任何波动，自然而然的疑问就是，危机是否会蔓延以及如何蔓延。

Especially after the experience that people lived through in 2008, every time there's any sort of market wobbles, the natural question is to ask if and how contagion can flow.

在这种情况下，如果人工智能泡沫破裂，会不会像全球金融危机时那样，炸掉养老金系统或主要保险公司？

In this case, if the AI bubble bursts, is it going to blow up the pension system or major insurers like we saw during the GFC?

这是一个出了名难回答的问题，在这个领域我们绝对应该保持谦逊。

That is a notoriously difficult question to answer definitively, and this is an area where we should absolutely tread with humility.

我们确定知道的是，有大量数据中心债务已经被抵押并出售给了保险公司和养老基金。

What we know for sure is that a significant amount of data center debt has been collateralized and sold to insurers and pension funds.

The Information 报道称，一群大型保险公司在上次 CoreWeave 发行债券时购买了价值超过7.4亿美元的 CoreWeave 债务。

The Information reports that a collection of giant insurance firms bought more than $740 million worth of CoreWeave debt last time they sold bonds.

他们列出了 American General Life Insurance、Fidelity and Guaranty Life 和 Security Life of Denver，所有这些公司的投资组合都由 Blackstone 管理。

They listed American General Life Insurance, Fidelity and Guaranty Life, and Security Life of Denver, all of which have portfolios managed by Blackstone.

抽象来看，这似乎是个大数字，但实际上，7.4亿美元分散在这些庞大的投资组合中，只是一个四舍五入的误差。

In the abstract, that seems like a big number, but realistically, $740 million spread across these large portfolios is a rounding error.

他们持有数据中心债务仍然有意义，如果这些债务违约，会造成一个窟窿，但到目前为止，看起来并不像全球金融危机后我们所看到的潜在大规模减值那样。

It is still meaningful that they're carrying data center debt, and it would leave a hole if that debt defaults, but it certainly so far doesn't look like the potential of a mass impairment we saw following the GFC.

KPMG 和德克萨斯大学奥斯汀分校的一项新研究发现，当人们与人工智能合作时，相似的技能并不能保证相似的结果。

A new study from KPMG and the University of Texas at Austin found that when people work with AI, similar skills don't guarantee similar outcomes.

研究人员调查了超过500名早期职业生涯的专业人士，发现表现最出色的人通过引导、评估和优化AI的输出，持续地放大了AI的价值。

Researchers studied more than 500 early-career professionals and found that the best performers consistently amplified the value of AI by guiding, evaluating, and refining its outputs.

这些顶尖人才被称为“AI放大器”，他们的定义不仅仅在于知道什么，更在于如何与AI协作。

These top performers, called AI amplifiers, weren't defined by what they knew alone, but by how they worked with AI.

M113:52

到了这个阶段，问题已经不再是公司是否在积极使用AI。

At this point, it's no longer a question of whether companies are actively using AI.

而能否用好AI，则是另一回事了。

Using it well, on the other hand, is a whole different story.

M115:38

另一个人在没有前端工程师的情况下，交付了一整个应用程序。

Another shipped an entire application with no frontend engineer.

无论是遗留系统还是全新项目，答案都一样：软件以计算速度交付。

Legacy or greenfield, the answer is the same: software at the speed of compute.

M115:54

另一个需要注意的风险点是保险公司与私募股权公司日益增长的配对合作。

Another pocket of risk to be aware of is the growing pairing of insurance firms with private equity.

最典型的例子是Apollo Capital，它在2022年与一家名为Athene的保险公司合并。

The canonical example is Apollo Capital, which merged with an insurance firm called Athene in 2022.

这是沃伦·巴菲特开创的一种经典融资策略。

This is a classic financing strategy pioneered by Warren Buffett.

保险公司获得优惠的税收待遇，而投资公司则获得稳定的资本流入。

The insurance company gets favorable tax treatment, and the investment firm gets a steady flow of capital.

这是金融领域一个复杂的角落，显然超出了本节目的讨论范围。

This is a complex corner of finance that is certainly beyond the scope of this show.

但有一点很重要：这些不是像State Farm那样提供车险和家财险的大型保险公司。

But one important thing to understand is that these aren't major insurers like State Farm providing auto and home insurance.

相反，它们是离岸保险公司，主要销售人寿保险和年金。

Instead, they're offshore insurers that mostly sell life insurance and annuities.

这是真实的风险，在AI信贷违约时它们确实可能受损，但主要风险是针对那些投资年金的富人。

It's a real risk, and they could definitely become impaired during an AI credit default, but they're mostly a risk for the wealthy people who invest in annuities.

最后，还有养老基金，它们肯定对AI领域有敞口。

Finally, there's the pension funds, which definitely have exposure to the AI sector.

它们怎么可能没有呢？

How could they not?

它们的职责就是投资股票和债券，而在过去四年里，大部分回报都来自AI。

Their job is to invest in stocks and bonds, and for the past 4 years, the bulk of the returns have come from AI.

《华尔街日报》报道，自2022年以来，AI推动了13个公共养老基金获得1380亿美元的收益。

The Wall Street Journal reports that AI drove $138 billion in gains across 13 public pension funds since 2022.

上周，美国人金融改革发布的一份报告指出，投机性的数据中心债务正在被打包，出售给养老基金、退休基金、大学捐赠基金和其他机构投资者，其方式令人毛骨悚然地想起次贷泡沫。

Last week, a report from Americans for Financial Reform stated, speculative data center debt is being repackaged and sold to pension and retirement funds, university endowments, and other institutional investors in a manner eerily reminiscent of the subprime bubble.

私募股权公司收购了人寿保险公司，并让它们背负高风险债务，使保单持有人和公众面临损失，并增加了金融传染的威胁。

Private equity firms have purchased life insurers and loaded them up with risky debt, exposing policyholders and the public to losses and raising the threat of financial contagion.

那份报告主要意在反对AI救助计划，而许多人确信特朗普政府一有机会就会放纵这样做。

That report was largely interested in arguing against an AI bailout, which many are certain the Trump administration will indulge in at the earliest opportunity.

但这里关键是要理解它不仅与次贷泡沫相似，还要理解它有何不同。

But understanding not just how it is similar to the subprime bubble, but how it is different, is essential here.

每个人都记得次贷危机中，抵押贷款被分割成CDO卖给养老基金，在《大空头》里被描绘成叠叠乐塔。

Everyone remembers the slices of mortgages chopped up and sold to pension funds as CDOs during subprime, depicted as a Jenga stack in The Big Short.

但关于为什么那实际上是个问题，讨论得比较少。

There is less discussion about why that was actually a problem.

问题不仅仅在于把债务分割并组合成CDO。

It wasn't just about chopping up the debt and combining it into a CDO.

问题在于那些CDO被评级为投资级债务。

The problem was that those CDOs were rated investment-grade debt.

它们被视为和国债一样安全。

They were treated as being just as safe as Treasury bonds.

而这一次，数据中心债务被当作公司债券，有时是投资级，有时不是，但绝对无法与国债相提并论。

This time around, data center debt is being treated as corporate bonds, sometimes investment grade, sometimes not, and definitely nowhere near the same as Treasury bonds.

它们和其他成千上万的债券一样，躺在养老基金和保险公司的资产负债表上。

They're sitting on pension and insurer balance sheets just the same as thousands of other bonds.

在次贷危机期间，分割债务是被明确且有意地用来混淆其风险程度的。

During subprime, chopping up the debt was explicitly and intentionally used to obfuscate how risky it was.

这一次，没有人再假装数据中心债务像房子一样安全了。

This time around, no one is pretending that data center debt is as safe as houses.

但同样，我不想只关注为什么现在这些压力或许值得稍微缓一缓，还想关注未来什么可能会更令人担忧。

But again, I wanna not just focus on why things are maybe worth a little pause in the stress right now, But what could in the future be more cause for concern?

一个令人担忧的点是，如果我们看到披露的风险敞口出现数量级的跃升，或者集中在少数几家私募股权所有的保险公司身上。

One cause for concern would be that if we saw disclosed exposure jump by orders of magnitude or concentrating in a handful of PE-owned insurers.

7.4亿美元摊在大型投资组合里算很薄，但如果跃升到数百亿美元、集中在两三家保险公司手里，那就另当别论了。

$740 Million spread across big portfolios is thin, but if that jumps to tens of billions sitting in 2 or 3 insurers, that could be a different story.

另一个担忧是，数据中心债务开始被重新打包成评级高于底层贷款的证券。

Another concern would be if data center debt started to get repackaged into securities that were rated higher than the loans underneath them.

再说一次，重点不是这些事情不可能，而是它们目前还没发生。

And again, the point here is not that these things are impossible, it's that they're not the things that are happening yet.

现在回到救助这个话题。最近另一个重大讨论话题是，AI巨头们正试图让自己变得大而不能倒。

Now, going back to the idea of a bailout, another big topic of discussion of late is the idea that the large AI players are looking to make themselves too big to fail.

在Anthropic和Elon Musk先后表示将通过两种截然不同的机制向公众赠送股权之后，这个话题又强势回归了。

This discussion came back with a vengeance after Anthropic and then Elon Musk said that they would gift equity to the public through 2 very different mechanisms.

这里面有一个非常重要的政策讨论：在一个民主社会里，这样做到底合不合适。

Now, there is a whole very important policy discussion about whether this is actually appropriate in a democratic society.

这到底是重新分配收益的好方式，还是一个刺眼的信号，表明亿万富翁和超大型公司需要缴更多的税？

Whether it's a good way to redistribute gains or possibly a glaring sign that billionaires and mega-cap companies need to be paying more in taxes.

但这不是我们今天要捅的那个马蜂窝。

But that's not the particular can of worms that we're opening today.

显然有一个很站得住的论点：让公众直接持有这些公司的股份，有让它们变得大而不能倒的风险。

There is clearly a solid argument that giving the public a direct stake in the companies risks making them too big to fail.

说清楚一点，当我们说大而不能倒时，用的是过去15年里的一个特定术语，指政府觉得有义务介入保护的机构。

And to be clear, when we say too big to fail, we're using a specific term from the last 15 years that refers to institutions that the government feels obligated to come in and protect.

无论它们在自由市场里本来会发生什么。

Regardless of what would otherwise happen to them in the free markets.

在这个问题上，我可能比你们中的一些人更愤世嫉俗一点，如果是这样，请见谅。

This is an area where I am perhaps more cynical than some of you, and forgive me if so.

现实地说，如果你担心会再出现一批大而不能倒的公司，那在我看来，无论他们是否向公众赠送股份，那艘船早就开走了。

Realistically, I think if your concern is that we're going to get another group of too-big-to-fail companies, in my opinion, that ship has already sailed whether or not they give shares to the public.

在美国政府与市场关系史的这个阶段，我觉得政府极不可能站在一边，看着一家万亿美元级的公司在经济上炸出一个大洞。

At this stage in the history of the relationship between the U.S. government and markets, it seems massively unlikely to me that the government would just stand around while a trillion-dollar company blew a giant hole in their economy.

2008年政府都没让GM倒，更何况自那以后，政府与市场互动的规矩已经变得奇怪多了。

The government didn't let it happen with GM in 2008, and certainly the norms of how the government engages with markets have gotten a lot weirder since then.

另一方面，至于说这些公司是在市场崩盘前策划一场救助，这个说法我完全不买账。

On the other hand, as for the argument that these companies are engineering a bailout ahead of a market crash, that's something I just don't buy.

不管人们怎么评价Anthropic，现在很明显的是，他们确实真心相信自己的使命，而最简单的解释依然是：他们想建立一个巨大的公共福利基金来推进这个使命。

Regardless of what anyone wants to say about Anthropic, it's pretty clear at this point that they have a genuine belief in their mission, and the simplest explanation once again is that they want to establish a giant public benefit fund to further that mission.

至于Elon Musk，有几个事实是交叠的：如果他确实相信这种赠予是影响公共利益的最佳方式，那完全符合他一贯的作风。

As for Elon Musk, you have the convergence of the fact that it would be entirely consistent if he did believe that this sort of giving is the best way to impact public benefit.

但另一个更愤世嫉俗的解释是，他可能看准了风向，觉得某种再分配迟早要来。

But also there's the fact that more cynically, he might be reading the room that some sort of redistribution is going to happen.

他觉得如果自己抢先一步，也许就能掌控这件事，而不是受制于它。

And he thinks if he gets out ahead of it, he might be able to control it rather than be subject to it.

还有一个更纸上谈兵式的心理分析：这个人喜欢被人爱，而没有什么比把110亿美元送给美国公众更容易赢得爱了。

And there's also the more armchair psychologist assessment that the man loves being loved, and there's no easier way to being loved than to give $11 billion to the American public.

这个话题，目前我觉得不值得再花大量时间去展开。

This is one that at the moment I don't think is worth spending a ton of additional time on.

但为了完整起见，说说要关注什么：如果你开始看到AI公司在危机出现之前就要求明确的联邦担保、贷款计划或融资兜底，那我们可能就要展开另一场讨论了。

But for the sake of completeness, in terms of what to watch for, if you start to see AI companies begin to ask for explicit federal guarantees or loan programs or financing backstops before there's a crisis, that could cause, let's say, a different conversation here.

在所有人们提出的警示信号中，我觉得最有趣、最值得深入思考的是收入质量问题。

I think of all the warning signs that people are bringing up, the one that is most interesting and deserving of deep consideration is the question of revenue quality.

不过，即便在这个范畴内，也有好几种不同的版本。

Although even within this, there's a bunch of different versions of it.

而我认为它们的动态机制很不一样。

That I think have very different dynamics.

一方面，Nvidia报告说，仅仅两个客户就占了他们Q2收入的39%。

On the one hand, you have Nvidia, who reported that just 2 customers made up 39% of their Q2 revenue.

另一方面，《华尔街日报》最近泄露了Anthropic的IPO招股说明书，其中提到Anthropic上半年的收入有五分之一来自他们的前两大客户。

On the other is the Wall Street Journal's recent leak of Anthropic's IPO prospectus, which noted that a fifth of Anthropic's revenue in the first half came from their top 2 customers.

与此相关的是，Ramp的数据显示，前1%的企业通过Ramp平台在OpenAI和Anthropic上的消费占了80%。

Relatedly, Ramp data has shown that the top 1% of businesses account for 80% of spending volume for OpenAI and Anthropic through Ramp's platform.

那么这些有什么不同呢？

So how are these different?

嗯，Nvidia的客户高度集中，因为世界上只有少数公司在建设价值数十亿美元的数据中心。

Well, Nvidia has a highly concentrated customer base because there's only a handful of companies in the world that are building multi-billion-dollar data centers.

而且部分情况可能也适用于Anthropic的故事——他们很大一部分收入可能来自那些超大规模云服务商，因为那种关系更像是批发商和分销商，而不是供应商和客户。

And some of this might even apply to the Anthropic story— a large chunk of their revenue is likely coming from the hyperscalers because that relationship is that of a wholesaler and a distributor, rather than a vendor and customer.

当你最大的客户之一有可能会突然撤资时，收入质量就成了问题。

Revenue quality becomes an issue when there's a big risk that one of your largest customers could pull the plug.

对于转售Claude代币的超大规模云服务商来说，短期内这种情况似乎不太可能发生。

For hyperscalers reselling Claude tokens, that seems very unlikely to happen in the short term.

我觉得更大的担忧是，企业AI的使用大部分都集中在少数重度用户身上，这种分布很窄。

A much bigger concern, I think, is this narrow distribution of power users making up the bulk of enterprise AI use?

跟往常一样，我们需要将Ramp的数据放在具体语境中看，要意识到他们服务的只是市场极小的一部分——那些极具前瞻性、技术非常先进的公司，很多来自科技行业。

As always, we need to contextualize Ramp data, recognizing that they service a very, very slim part of the market— extremely forward-looking companies, extremely tech-advanced companies, many of them from the tech sector.

但值得注意的是，Ramp发现，前1%的AI客户中有80%是风投支持的初创公司。

And yet it's still worth noting that Ramp found that 80% of the top 1% of AI customers are VC-backed startups.

其中一部分交易量是把前沿模型代币包装成服务，并提供风投补贴的折扣，这当然是一些AI代理初创公司的商业模式，我们也可以推测，很多代币交易量是用于内部使用的，而这些也是由风投资金支持的。

Some amount of that volume is wrapping frontier tokens in a service and providing a VC-subsidized discount, which is of course the business model for some of the agent startups, and we can also presume that a lot of the token volume is for internal use, which is also funded by VC dollars.

问题在于，如果风投资金枯竭，这些初创公司走到了资金链的尽头。

Where this becomes a problem is if VC money dries up and these startups hit the end of their runway.

目前，AI风险投资仍然是一个火爆的牛市，但情况随时可能改变。

At the moment, AI venture is still a raging bull market, but that can always change.

更大的风险，也是真正的大问题在于：AI支出中有多少会长期遵循幂律分布而不扩散？

The bigger risk, and really the big question here, is how much of AI spending is permanently going to be subject to power laws without broadening out?

换句话说，这种惊人的集中度是否会持续成为整个AI行业的需求特征，即使买家逐渐成熟，还是说它只是反映了处于不同采用周期的公司之间的差异？

In other words, is this incredible concentration likely to hold as the demand profile for the entire AI industry, even as buyers mature, or is it simply an indicator of the difference between companies at different stages in their adoption cycle?

如果现在那些每月每名员工花费约9000美元的初创公司处于榜单顶端，那么十年后的某个时候，所有企业都会每月每名员工花费9000美元吗？

If the startups spending around $9,000 per employee per month are the top of the chart now, at some point in a decade, are all enterprises spending $9,000 per employee per month?

如果不是，它们能接近多大的数字？

And if not, how close to those sort of numbers are they going to get?

Ramp观察到，自夏季以来，所有群体的企业每名员工支出都翻了三倍。

Ramp has seen businesses across all cohorts triple their spend per employee since the summer.

不属于前1%但属于前10%的企业，每名员工支出从大约200美元增加到大约800美元，增速快于中位数。

Businesses not in the 1% but in the 10% went from around spending $200 per employee to around $800 per employee, growing faster than the median.

这表明采用曲线正在整个经济中扩展，但当然这并不能保证。

That suggests an adoption curve that is expanding out across the economy, but there's certainly no guarantee there.

另一个变数是，当我们进入下一个也是最后一个讨论点，这个特定风险在主要实验室上市后会变得更加明显。

Another curveball, which gets into our next and final line of discussion, is that this particular risk gets far more tangible after the major labs go public.

目前，这种风险基于Ramp的数据、经常被误解的Silicon Data Token Index，以及其他各种非官方渠道，这些渠道只掌握了整体情况的一小部分。

At the moment, this risk is based on data from Ramp, the often misunderstood Silicon Data Token Index, and various other unofficial sources that have a tiny sliver of the full picture.

一旦Anthropic和OpenAI上市，它们将无处可藏。

Once Anthropic and OpenAI go public, they'll have nowhere to hide.

它们经过全面审计的财务状况将按季度报告，它们的CEO将在财报电话会议上接受股票研究人员的盘问。

Their fully audited financials will be reported quarterly, and their CEOs will be grilled by equity researchers on earnings calls.

如果它们没有增长或改善收入质量，每个人都会知道。

If they're not growing and improving their revenue quality, everyone is going to know about it.

当然，很明显，即将到来的Anthropic IPO是AI泡沫重新成为话题的重要原因。

And of course, clearly, the rapidly approaching Anthropic IPO is a big part of the reason that the AI bubble is back in the discourse.

泡沫市场往往在某个打破人们暂时搁置怀疑的催化剂出现时见顶。

Frothy markets often top on a catalyst that breaks the suspension of disbelief.

对许多人来说，Anthropic的IPO似乎正好符合这个条件。

And for many, the Anthropic IPO seems likely to fit that bill.

截至目前我们了解的Anthropic财务状况，至少与许多人之前的预期相比，看起来并不那么出色。

What we've learned so far about Anthropic's financials has, compared to at least what many people were thinking, looked less than stellar.

Anthropic上半年亏损800亿美元的头条在社交媒体上疯传，尽管这只是会计亏损，他们的实际现金亏损是87亿美元。

The headline that Anthropic made an $80 billion loss in the first half went viral on social media, even though this was an accounting loss and their true cash loss was $8.7 billion.

不过，随着 Anthropic 进入最后阶段，我们看到估值在下降。

Still, we're seeing valuations soften as Anthropic enters the final stretch.

OpenAI 的融资预计很快就要结束了，The Information 报道说估值会是 1.25 万亿美元。

OpenAI's fundraising is expected to close soon, and The Information reports that the valuation will come in at $1.25 trillion.

之前的报道说是 1.4 万亿美元。

Earlier reporting had it at $1.4 trillion.

现在，我不太确定早期泄密的报道数字和最终实际数字之间的差异，到底算不算明显的估值下调，还是只是报道有误，但投资者确实就是这么看的。

Now, I don't know if you can consider the difference in an early leaked reported number and the actual factual final number as being clearly a valuation downgrade as opposed to just misreporting, but that's certainly how investors are looking at it.

虽然一些 Anthropic 的投资人最初在媒体上推动 2 万亿美元的估值，但最近有报道说，另一群人正在推动 1.5 万亿美元。

While some Anthropic investors were originally pushing for a $2 trillion valuation in the press, more recently there's been reporting that another group is pushing for $1.5 trillion.

与此同时，整个 IPO 市场完全冻结了，本月到目前为止筹集到的资金不到 6 亿美元。

Meanwhile, the rest of the IPO market is completely frozen, with less than $600 million raised so far this month.

Truist Financial 的股权资本市场主管 Wes Riggs 说，人们真的瘫痪了。

Wes Riggs, the head of equity capital markets at Truist Financial, said, people are truly paralyzed.

市场必须自己理清头绪。

The market has to sort itself out.

Deloitte & Touche 的美国资本市场交易主管说，估值上存在僵局，需要弥合这个差距，更广泛的市场才能向前推进。

The U.S. capital markets transaction leader at Deloitte & Touche said, there is a stalemate on valuation, and rationalizing that gap is what needs to happen before the broader market can move forward.

本质上，想要上市的公司要价太高，超过了投资银行愿意给的价格。

Essentially, companies looking to IPO are asking for more than investment banks will give them.

这可能意味着 NeoClouds 无法上市，也就无法获得下一轮融资，结果就是私募股权要兜底了。

This could mean NeoClouds are unable to go public and consequently unable to access their next tranche of funding, leaving private equity holding the bag.

但说到底，就像任何市场或市场心理问题一样，这个问题只能靠下一件大事来解决。

But ultimately, as with any market or market psychology issue, this one is only resolved by the next thing happening.

在本周的《彭博观点》中，Chris Hughes 写了一长串 AI 交易的问题，但结论是，目前压制市场的一些问题会随着时间解决，但如果 Anthropic 能赶紧完成 IPO，那大家就少一件操心的事了。

In Bloomberg Opinion this week, Chris Hughes wrote about the long list of problems with the AI trade but concluded, some of the questions currently weighing on the market will be resolved over time, but if Anthropic could just get on with its IPO, that would give everyone one less thing to worry about.

我认为这里确实有风险，不是那种系统性蔓延之类的风险，而是从对 AI 交易的信心角度来说的。

And I think that there is real risk here, not for some sort of systemic contagion or anything like that, but from the standpoint of confidence in the AI trade.

如果 Anthropic 在投资者几个月来一直炒作 2 万亿美元之后，以 1.5 万亿美元的估值定价 IPO，那虽然不太好，但最终可能也没那么令人担忧。

If Anthropic prices their IPO at $1.5 trillion after investors splashed around the $2 trillion number for months, that's not great, but ultimately probably not all that concerning.

反过来，如果 Anthropic 以 1.5 万亿美元定价，但市场反应依然疲软，那就会证实很多人对 AI 交易最坏的担忧。

If on the other hand, Anthropic prices at $1.5 trillion and we still see a weak reception in the market, that will confirm a lot of people's worst fears about the state of the AI trade.

今天这期节目的目的，既不是要断然否认任何令人担忧的市场迹象，也不是要吓唬你说 AI 泡沫破裂不可避免。

The point of today's episode is neither to definitively try to deny any causes for market concern, nor to surprise you and come out saying that some AI bubble burst is inevitable.

相反，我尽力逐一审视这个叙事中的各个子部分，谈谈我认为它们目前处于什么状态，以及未来什么情况会让我更担忧。

Instead, what I've tried to do is look at each of the different subcomponents of the narrative in turn and talk about where I think they are today and what would make me more concerned going forward.

一个不可否认的事实是，AI 泡沫即将破裂的说法在这个市场周期中反复出现。

One thing that's undeniable is that the narrative that the AI bubble is about to burst has been a recurring feature of this market cycle.

可以一直追溯到生成式 AI 时代刚开始的时候。

Going back all the way to the beginning of the generative AI era.

不知为什么，它似乎每年差不多这个时候就会出现。

For whatever reason, it seems to come up around this time of year.

2024 年，有报道说多家实验室看到模型改进放缓，引发了AI scaling 撞墙的广泛担忧。

In 2024, we saw massive concern about AI scaling hitting a wall after reports that multiple labs were seeing a slowdown in model improvement.

但紧接着没过多久，我们就看到了第一批推理模型。

But then just shortly after that, we got the first reasoning models.

再后来，芯片技术有了进展，内存更大，可以训练万亿参数级别的模型。

And farther after that, advances in chips with more memory that allowed multi-trillion parameter models to be trained.

然后当然，去年有人担心企业从 AI 上没看到回报，不会再继续投入了。

Then of course last year, there was a concern that enterprises weren't seeing returns from AI and wouldn't continue paying.

这当然就是让我头疼的 MIT 报告，说 95% 的生成式 AI 试点项目都失败了。

This, of course embodied in the bane of my existence, the MIT report about the 95% of generative AI pilots failing.

剧透一下：企业支出并没有枯竭。

Spoiler alert: enterprise spend didn't dry up.

相反，它蓬勃发展，每个季度还在以大约 50% 的速度增长。

Instead, it boomed and is still growing at around 50% a quarter.

当然，之前的泡沫预测错了，并不代表以后所有的泡沫预测也会错。

Now, previous bubble calls being wrong does not mean that all bubble calls in the future will be wrong as well.

这只意味着，我们现在最好多带几袋盐，来对待所有这些轰动性的大标题。

It just means we'd all be better served carrying around bags of salt at this point to take with all of these big bombastic headlines.

随着Anthropic IPO的临近，我们很快就会得到一个更明确的答案。

With the Anthropic IPO coming up, we will get a much more definitive answer soon.

无论那显示什么，其影响都依然悬而未决，令人既好奇又沮丧。

The impacts of whatever that shows remain tantalizingly and frustratingly in the future.

而现在，我们能做的就是猜测和讨论。

And for now, all we can do is speculate and debate.

希望这些能给你提供一些新的谈资。

Hopefully you've got a bit more fodder for that now.

以上就是今天AI Daily Brief的全部内容。

And that's going to do it for today's AI Daily Brief.

一如既往，感谢你的收听或观看。

Appreciate you listening or watching as always.

我们下次再见。

And until next time, peace.

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First of all, thank you to today's sponsors: KPMG, Robots and Pencils, CData, and Blitzy.

To get an ad-free version of the show, go to patreon.com/AIDailyBrief, or you can subscribe on Apple Podcasts.

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