The Shrugflation Triangle: How AI, Oil, and Treasuries are Impacting the Economy

This piece was written in several cities - Durango, Colorado, Chicago, St. Louis, Las Vegas, New York City, Cleveland, and Tulsa, Oklahoma.

这篇文章是在几个城市写成的——科罗拉多州杜兰戈、芝加哥、圣路易斯、拉斯维加斯、纽约市、克利夫兰和俄克拉荷马州塔尔萨。

I love traveling because I get to talk to so many different people about how they experience the economy, and I’ve told some of those stories here.

我喜欢旅行，因为我可以和很多不同的人谈论他们如何体验经济，我在这里讲述了其中的一些故事。

The goal of the piece is to connect a lot of dots that tend to float by one another, and to hopefully provide a comprehensive explanation of the three core factors in the economy right now – AI, Treasuries, and oil – and talk about how they feed into one another.

这篇文章的目标是将许多容易相互浮动的点联系起来，并希望对当前经济的三个核心因素——人工智能、国债和石油——提供全面的解释，并讨论它们如何相互促进。

The paperback version of In This Economy?

平装本《在这个经济中？》

came out!!

出来了！！

Yay!

耶！

It has a new afterword about tariffs and AI.

它有一个关于关税和人工智能的新后记。

I partner with Skylight Books if you want to support local as well!

如果您也想支持本地，我会与 Skylight Books 合作！

I am also working on a new website called Ask Kyla where you can submit any questions that you have about the economy and markets.

我还在开发一个名为 Ask Kyla 的新网站，您可以在其中提交有关经济和市场的任何问题。

This is a reader-supported publication.

这是一本由读者支持的出版物。

To receive new posts and support my work, consider becoming a free or paid subscriber.

要接收新帖子并支持我的工作，请考虑成为免费或付费订阅者。

In Vegas, very early in the morning (although there really isn’t such a thing in Vegas) I was getting a coffee.

在维加斯，一大早（虽然维加斯确实没有这样的事情）我正在喝咖啡。

The barista asked if she could make my coffee without the machine (a touch screen machine was humming behind her, where you can pick exactly what drink you want to make from a menu of pictures.) She said that she liked to add a “human touch” to the coffee.

咖啡师问她是否可以在没有机器的情况下为我制作咖啡（触摸屏机器在她身后嗡嗡作响，您可以从图片菜单中准确选择您想要制作的饮料。）她说她喜欢在咖啡中添加“人性化”。

I said yes, of course.

我说是的，当然。

I couldn’t sleep.

我无法入睡。

Neither could the people peppered around the casino playing slots, all of us floating in a world where time didn’t matter.

赌场里挤满了人玩老虎机的人也不能，我们所有人都漂浮在一个时间无关紧要的世界里。

Bleary eyed, drinking my human-made coffee, I watched them install four new slot machines, absolutely enormous, reaching into the ceilings, like Easter Island heads.

我睡眼惺忪地喝着自己煮的咖啡，看着他们安装了四台新老虎机，它们绝对巨大，直达天花板，就像复活节岛的头像一样。

The slot machines have screens, so for a while, as the workers were setting them up, lines of raw code danced across the uncalibrated screens, a brief otherworldly glimpse into what would soon be hypnosis.

老虎机有屏幕，所以有一段时间，当工人们设置它们时，原始代码行在未经校准的屏幕上舞动，短暂超凡脱俗地一瞥即将进入催眠状态的东西。

Then the display flipped to three cherries in a row, and played a bright, celebratory chime.

然后显示屏翻转成一排三颗樱桃，并演奏出明亮的庆祝铃声。

A jackpot.

中奖了。

But there wasn’t a player in that chair.

但那张椅子上没有一个球员。

Everyone else was crammed around the other machines down the row, still feeding in their tokens.

其他人都挤在这一排的其他机器周围，仍在输入他们的代币。

Still hoping.

还是希望。

Still waiting.

仍在等待。

It’s a decent model for the American economy right now: a room full of people playing the slots, trying to get rich, and the jackpot hits for an empty seat.

对于目前的美国经济来说，这是一个不错的模式：满屋子的人都在玩老虎机，试图致富，而头奖则为空座位而中。

Most people are trying to do everything the economy asks of them.

大多数人都在努力做经济要求他们做的一切。

They’re working and spending and paying more for gas and to borrow money.

他们在工作、消费、支付更多的汽油费和借钱。

But the economic winnings keep showing up somewhere else.

但经济上的胜利不断出现在其他地方。

So where are they going?

那么他们要去哪里呢？

There is a lot of debate, huge debates, over what is going on and why.

关于正在发生的事情以及原因，存在着很多争论，巨大的争论。

What’s causing the rise in Treasury yields (the thing that prices our economy!)?

是什么导致国债收益率上升（这就是我们经济的定价！）？

What’s causing inflationary pressures?

是什么造成了通胀压力？

What’s causing the economy to do anything, really?

究竟是什么导致经济发生变化？

Huge debates, with people saying no it’s AI spending, it’s the sheer amount of debt, it’s the war, it’s Uncle Phil in Chicago, he actually controls the economy from an old Nintendo 64.

激烈的争论，人们说不，这是人工智能支出，这是巨额债务，这是战争，这是芝加哥的菲尔叔叔，他实际上通过一台旧的任天堂 64 控制着经济。

It’s everything, all at once.

这就是一切，同时发生。

It’s oil, AI, and Treasuries, because they are feeding into each other.

这是石油、人工智能和国债，因为它们相互促进。

It’s a Triangle (a Bermuda Triangle as Coby Weiss puts it) - three points on a map.

这是一个三角形（科比·韦斯所说的百慕大三角）——地图上的三个点。

Oil pushes up rates: the war with Iran has throttled oil shipping, diesel has spiked to record prices, and everything that rides on a truck or train or ship or plane costs more.

石油推高了运费：与伊朗的战争抑制了石油运输，柴油价格飙升至创纪录水平，卡车、火车、轮船或飞机上的所有物品的价格都更高。

That’s a big part of why the Fed has had to hike interest rates

这是美联储不得不加息的一个重要原因

The government happens to owe the size of the entire economy right now in debt, so when rates go up, so does their interest bill, the fastest-growing thing in the budget.

政府目前恰好欠下整个经济规模的债务，因此当利率上升时，他们的利息支出也会随之增加，而利息支出是预算中增长最快的部分。

The government covers that by selling more Treasuries, the thing that prices our economy at the same time the AI industry is borrowing unprecedented sums from the same pool of money.

政府通过出售更多的国债来掩盖这一点，国债对我们的经济进行定价，同时人工智能行业正在从同一个资金池中借入前所未有的资金。

Two giant borrowers, one pool of money, the sheer demand can push up long-term rates even more.

两个巨大的借款人，一个资金池，纯粹的需求可以进一步推高长期利率。

And they shrug at any change in rates!

他们对利率的任何变化都耸耸肩！

The government borrows to pay bills.

政府借钱来支付账单。

AI borrows to build, and that requires a ton of power.

人工智能借用构建，这需要大量的力量。

AI needs energy , in a world where energy is really expensive.

人工智能需要能源，在一个能源非常昂贵的世界里。

Data centers need a huge amount of power, and when the grid can’t deliver it, they burn it.

数据中心需要大量电力，当电网无法提供电力时，他们就会烧毁电力。

Oracle is trucking natural gas to data centers .

甲骨文正在用卡车将天然气运往数据中心。

AI doesn’t really move the price of oil but it can’t turn on without it, which brings us back to Point 1.

人工智能并没有真正改变石油价格，但如果没有它，它就无法启动，这让我们回到了第一点。

So that’s the triangle.

这就是三角形。

And who has to deal with it?

谁必须处理它？

People.

人们。

People have to deal with the higher borrowing costs and the higher energy costs and the uncertainty about what AI will do to them.

人们必须应对更高的借贷成本和能源成本，以及人工智能会对他们做什么的不确定性。

And no one wants to slow down because AI investment is a huge share of both the economy and the stock market, bolstering household wealth, so if the party stops, it reverberates across the entire economy.

没有人愿意放慢脚步，因为人工智能投资在经济和股市中都占有巨大份额，可以增加家庭财富，所以如果聚会停止，它会波及整个经济。

It’s a form of shrugflation (can’t help a portmanteau) – usually, money gets expensive and people borrow less, right?

这是耸肩通货膨胀的一种形式（无法帮助混合词）——通常，钱会变得昂贵，人们借钱会减少，对吗？

Gas gets expensive, you drive less.

汽油变得昂贵，你开车更少。

That’s the whole thing.

这就是全部事情。

But right now, a war has made energy expensive and the Fed can’t do anything about that, because you can’t go to a Strait and say listen buddy I’m hiking rates over here.

但现在，战争使能源变得昂贵，美联储对此无能为力，因为你不能去海峡说，听着，伙计，我要在这里加息。

All you can do is make borrowing cost more.

你所能做的就是提高借贷成本。

And the two biggest borrowers in the economy hear that and just sort of …

经济中最大的两个借款人听到这个消息，有点……

shrug?

耸耸肩？

The government borrows at whatever rates are.

政府以任何利率借款。

The AI companies feel like they have to keep borrowing in order to survive, what Tracy Alloway calls the “existential imperative to borrow.”

人工智能公司觉得他们必须不断借贷才能生存，特雷西·阿洛韦称之为“借贷的生存必要性”。

What does this look like across the economy?

整个经济形势如何？

Let’s start with oil.

我们先从石油开始吧。

At a finance conference a couple of months ago, the FT quoted a banker who said “Does anyone really care if the Strait of Hormuz is open?” perhaps a defining quote of this era.

在几个月前的一次金融会议上，英国《金融时报》援引一位银行家的话说“有人真的关心霍尔木兹海峡是否开放吗？”也许是这个时代的定义性引言。

And to this bankers credit, no. The government seems to be only complicating the situation and AI doesn’t seem worried, at all.

值得银行家称赞的是，答案是否定的。政府似乎只是让情况变得更加复杂，而人工智能似乎根本不担心。

The only people who care are people .

唯一关心的是人。

I had the honor of moderating a panel on consumer sentiment at the Chicago Federal Reserve.

我有幸担任芝加哥联储消费者信心小组的主持人。

The panel was extraordinarily brilliant and the room was full.

面板非常明亮，房间里挤满了人。

One of the panelists talked about how consumers are getting “double squeezed” because they have to absorb both (1) high diesel prices through a higher cost of goods and (2) high gas prices to even go get those goods.

一位小组成员谈到消费者如何受到“双重挤压”，因为他们必须通过更高的商品成本来承受（1）高柴油价格和（2）高汽油价格才能购买这些商品。

The room nodded along.

房间里的人也跟着点头。

And they nodded because people care .

他们点头，因为人们关心。

On October 9th, the University of Michigan’s consumer sentiment index came in at 46.3, the second-lowest reading in its history (the lowest was in May of this year).

10月9日，密歇根大学消费者信心指数为46.3，为历史第二低（最低为今年5月）。

Its measure of how people feel about their current conditions is the lowest ever recorded 1 .

它衡量人们对当前状况的感受的指标是有记录以来最低的 1 。

People expect prices to rise 4.7% over the next year (not great for the Fed).

人们预计明年物价将上涨 4.7%（对美联储来说不太好）。

I’ve been inadvertently watching where all that diesel goes.

我无意中观察了所有柴油的去向。

A big portion of my current road trip has been driving.

我目前公路旅行的很大一部分都是开车。

I drove from Albuquerque to Durango (and back), and from Oklahoma City to Tulsa.

我开车从阿尔伯克基到杜兰戈（然后返回），然后从俄克拉荷马城开车到塔尔萨。

All three of these adventures happened between 10pm and 2am.

这三起冒险事件都发生在晚上 10 点到凌晨 2 点之间。

So during those hours, it’s me and a bunch of truck drivers.

所以在那些时间里，只有我和一群卡车司机。

You can see the hidden machinery of the country so clearly.

你可以如此清楚地看到这个国家隐藏的机器。

Trucks hauling other trucks, hauling cars, hauling horses, hauling food, hauling anything and everything.

卡车拖着其他卡车、拖着汽车、拖着马、拖着食物、拖着任何东西。

There are so many of them - on my 90 minute drive from OKC to Tulsa, which started at 12am, I saw about 100 trucks cruising along the interstate.

其中有很多卡车 - 在我从上午 12 点出发从俄克拉何马城到塔尔萨的 90 分钟车程中，我看到大约 100 辆卡车沿着州际公路行驶。

All of them carrying the economy behind them.

他们所有人都以经济为后盾。

All of them are incredibly reliant on diesel.

所有这些都非常依赖柴油。

High energy costs trace back to the war with Iran.

高能源成本可以追溯到与伊朗的战争。

Since the war started, shipping through the Strait of Hormuz (what a fifth of the world’s oil usually goes through) has been throttled.

自战争爆发以来，通过霍尔木兹海峡（世界上五分之一的石油通常经过该海峡）的运输受到限制。

Saudi Arabia had a side chute that lessened the blow, with a pipeline across the country into the Red Sea, but drones took that down too.

沙特阿拉伯有一条侧滑道，可以减轻打击，并有一条穿过该国进入红海的管道，但无人机也将其击落。

For about two weeks, the main road and a detour were both closed.

大约两周时间，主要道路和一条绕道都被封闭。

The pipeline is running again, below capacity, and the Strait is running at 80% capacity, but only unrefined crude oil is getting through (and Iran is stepping up attacks on tankers).

管道再次以低于容量的速度运行，海峡以 80% 的容量运行，但只有未精炼的原油通过（伊朗正在加大对油轮的攻击力度）。

Renting a supertanker to carry oil from the Persian Gulf to Asia now costs about $1.4 million a day according to Bloomberg.

据彭博社报道，目前租用一艘超级油轮将石油从波斯湾运往亚洲的费用约为每天 140 万美元。

Pre-war, it was about $30,000.

战前，大约是 30,000 美元。

A logistics guy summarized it beautifully for the WSJ – “chaos increases prices.” Our entire economy is truly an oil guzzling machine, as both gasoline and diesel come from oil, with things going all places all the time, across trucks and trains and tractors and ships.

一位物流人员为《华尔街日报》做了精彩的总结——“混乱导致价格上涨。”我们的整个经济确实是一台耗油机器，因为汽油和柴油都来自石油，卡车、火车、拖拉机和船舶一直在各个地方运转。

If it gets more expensive to get things places, things are going to get more expensive!

如果把东西送到地方变得更贵，那么东西就会变得更贵！

Diesel hit a record $6.53 a gallon in September, up 77% in a year, according to the Wall Street Journal.

据《华尔街日报》报道，9 月份柴油价格创下每加仑 6.53 美元的历史新高，一年内上涨 77%。

So governments are trying to free up fuel reserves.

因此，各国政府正在努力释放燃料储备。

The G7 agreed to release 100 million barrels of diesel and crude from their reserves over four months.

七国集团同意在四个月内从其储备中释放 1 亿桶柴油和原油。

That’s only about a day of what the world uses, according to the New York Times .

据《纽约时报》报道，这大约只相当于全世界一天的用量。

We use SO MUCH FUEL.

我们使用大量燃料。

And the thing about reserves is that they…

关于储备金的问题是它们......

tend to run out.

往往会用完。

Expensive fuel makes everything more expensive, which creates inflationary pressures, which is the Federal Reserve’s problem.

昂贵的燃料使一切变得更加昂贵，从而产生通货膨胀压力，这就是美联储的问题。

To combat this, the Fed raised rates on September 16th, for the first time since 2023.

为了应对这一问题，美联储于 9 月 16 日加息，这是 2023 年以来的首次。

But the Fed can’t go march down to the Strait of Hormuz and broker a peace deal.

但美联储无法前往霍尔木兹海峡并促成和平协议。

They can’t direct ships through.

他们无法指挥船只通过。

All they really can do is make borrowing more expensive for everybody, so that way, people slow down, spend a little less, the economy therefore slows down, and hopefully, inflation slows down.

他们真正能做的就是让每个人的借贷成本更高，这样一来，人们就会放慢脚步，减少支出，经济就会放缓，通胀也有望放缓。

And we were recently reminded the importance of the Fed’s role in setting expectations like this!

最近我们被提醒美联储在设定这样的预期方面的作用的重要性！

The Nobel memorial prize in economics went to Robert Hall and Michael Woodford for work showing that what households and businesses expect is a big part of what holds an economy steady.

诺贝尔经济学奖颁给了罗伯特·霍尔和迈克尔·伍德福德，他们的研究表明家庭和企业的期望是保持经济稳定的重要因素。

Shaping those expectations is a big part of setting policy.

塑造这些期望是制定政策的重要组成部分。

Fed Chair Warsh has put aside forward guidance , one of the tools his predecessors used to steer those expectations.

美联储主席沃什搁置了前瞻性指导，这是他的前任用来引导这些预期的工具之一。

So we have an energy shock, people expecting prices to rise almost 5% over the next year, and a Fed Chair that is trying to pull back on some element of signaling where it’s going.

因此，我们面临着能源冲击，人们预计明年物价将上涨近 5%，而美联储主席正试图收回某些表明物价走向的因素。

Expectations matter.

期望很重要。

How people feel matters!

人们的感受很重要！

The expectations are already in action.

期望已经付诸行动。

Cleveland Fed President Beth Hammack spoke at NABE , a conference I was attending, and she mentioned that a retailer in her district told her that they’re planning to raise prices by more than their costs went up, because they figure more inflation is coming from somewhere – and that’s how inflation becomes self-fulfilling.

克利夫兰联储主席贝丝·哈马克 (Beth Hammack) 在我参加的 NABE 会议上发表讲话，她提到她所在地区的一家零售商告诉她，他们计划将价格提高到超过成本上涨的水平，因为他们认为更多的通胀来自某个地方 — — 这就是通胀自我实现的方式。

So it’s the beginning of the loop in a way — what people expect to happen can be what happens, which is why it’s important to discuss people as a part of this triangle.

因此，从某种程度上来说，这是循环的开始——人们期望发生的事情也可能会发生，这就是为什么将人作为这个三角形的一部分进行讨论很重要。

Oil prices and the 10-year Treasury yield are also moving more closely than at any time in 35 years, according to CBOE, which means that yields are driven heavily by whatever is going on with oil.

CBOE 表示，油价和 10 年期国债收益率的走势也比 35 年来任何时候都更加接近，这意味着收益率在很大程度上受到石油状况的影响。

Which is a problem for the one industry that needs to both (1) borrow a bunch of money and (2) use a bunch of energy.

对于需要（1）借入大量资金和（2）使用大量能源的行业来说，这是一个问题。

AI is a ghost of sorts, haunting most rooms, with people telling stories about it that sound like the scary ones that we tell over a campfire.

人工智能就像一个幽灵，困扰着大多数房间，人们讲述的关于它的故事听起来就像我们在篝火旁讲述的可怕故事一样。

It has made the future look bright for some, but certainly, not for all, at least not yet (if ever?)

它让一些人的未来看起来一片光明，但当然不是所有人，至少现在还没有（如果有的话？）

But the price of the companies making an AI product keep getting bid up.

但制造人工智能产品的公司的价格不断上涨。

Instinct, a personal AI assistant (these assistants are an agent, AI that has access to the computer) has an interesting product but they make $0.

本能地，个人人工智能助理（这些助理是一个代理，可以访问计算机的人工智能）有一个有趣的产品，但他们赚 0 美元。

They have about 100,000 users or so.

他们大约有 100,000 名左右的用户。

They, naturally, raised $1 billion on a $10 billion valuation (most of which they plan to spend on compute, the thing that powers the AI, which is in increasingly shrinking supply.)

当然，他们以 100 亿美元的估值筹集了 10 亿美元（他们计划将大部分资金用于计算，即为人工智能提供动力的东西，而人工智能的供应量正在日益萎缩。）

And of course this product that makes $0 raised one billion dollars!

当然，这款赚 0 美元的产品筹集了 10 亿美元！

The venture capitalists that wrote the checks were probably like wow, I can text it and it can text my friend and we can all get dinner Tuesday at 7:30pm and also I have a meeting right now what is it about oh it’s this other AI company wow I love this assistant give them one billion no actually…

写支票的风险投资家可能会说，哇，我可以给它发短信，它也可以给我的朋友发短信，我们都可以在周二晚上 7:30 吃晚饭，而且我现在正在开会，这是关于什么的哦，这是另一家人工智能公司，哇，我喜欢这个助手，给他们 10 亿，不，实际上……

make it two billion.

使其达到20亿。

This is the shrug in its purest form and the race is on.

这是最纯粹的耸肩形式，比赛开始了。

Carl Benedikt Frey, an economist at Oxford, told the NYT that, “these companies are essentially in an AI arms race.

牛津大学经济学家卡尔·贝内迪克特·弗雷 (Carl Benedikt Frey) 告诉《纽约时报》，“这些公司本质上是在进行人工智能军备竞赛。

If they don’t invest, they are acknowledging defeat.”

如果他们不投资，就等于承认失败。”

Crypto’s original theory was “what if we had peer-to-peer transactions and there wasn’t a financial middleman” and within a little over a decade, the technology had evolved into a way to talk about the speculative value of a picture of a monkey – “ape holders can use multiple slurp juices on a single ape.”

Crypto 最初的理论是“如果我们进行点对点交易并且没有金融中间人会怎样”，在十多年的时间里，这项技术已经发展成为一种谈论猴子图片投机价值的方式——“猿猴持有者可以对一只猿猴使用多次吸食汁液。”

And in AI, one company set out to redefine Hollywood filmmaking and now they help people make, in Ryan Broderick’s words , “hyperrealistic One Piece character that can promote your crypto scam on Instagram.”

在人工智能领域，一家公司着手重新定义好莱坞电影制作，现在他们帮助人们制作，用 Ryan Broderick 的话来说，“超现实的海贼王角色，可以在 Instagram 上宣传你的加密骗局。”

One might say it’s the singularity of SCAMMING!

有人可能会说这是诈骗的奇点！

The scamingularity, if you will!

骗局，如果你愿意的话！

It’s not totally clear to me why everything becomes sloppy and scammy.

我不太清楚为什么一切都会变得草率和欺骗。

Survival of the scammiest?

最骗子的生存？

Market forces, an economy that rewards growth at any cost, at any price, and preys on people’s gaps in understanding those forces?

市场力量，一个不惜一切代价、不惜一切代价奖励增长的经济体，并利用人们对这些力量的理解差距？

How it has always been and how it will always be?

过去如何，将来如何？

Bloomberg has one answer here .

布隆伯格对此有一个答案。

When something gets cheap, the people with the lowest standards tend to be first movers on the product.

当某样东西变得便宜时，标准最低的人往往是该产品的先行者。

So a cybersecurity firm found that phishing pages built on free AI app builders are up more 4x in two years because now everyone can will a scam into existence by typing “ Chat make me a bank website make it look really real and perfect.” Reports found a training manual in an abandoned scam compound (scampound?) in Cambodia, where it’s advised that stories can be made up, but have to “show genuine feeling.” The human touch.

因此，一家网络安全公司发现，基于免费人工智能应用程序构建器构建的网络钓鱼页面在两年内增加了 4 倍，因为现在每个人都可以通过输入“聊天让我成为一个银行网站，让它看起来非常真实和完美”来将骗局变成现实。报道在柬埔寨的一个废弃的骗局（骗子？）中发现了一本培训手册，其中建议故事可以编造，但必须“表现出真实的情感”。人情味。

Scammed.

被骗了。

Utopia is always the pitch, but slop is usually the final product.

乌托邦永远是球场，但斜坡通常是最终产品。

And AI’s original theory is just as lovely as crypto’s was.

人工智能的原始理论和加密货币的理论一样可爱。

“We will all live in a utopia and write poetry all day because AI runs our lives for us and everything will be free :) and that will be awesome” is a beautiful idea and I hope it comes true?

“我们都将生活在乌托邦中，整天写诗，因为人工智能为我们管理我们的生活，一切都将是免费的:)，这将是一个很棒的想法，我希望它能实现吗？

Like genuinely, I hope that the visions come to fruition (perhaps not in the form of one billion AI assistants, but you know.) We should want a better world for those that come after us, always.

我真诚地希望这些愿景能够实现（也许不是以十亿个人工智能助手的形式，但你知道。）我们应该永远为我们的后人创造一个更美好的世界。

And we have always been dreaming of this world.

而我们一直都梦想着这个世界。

John Maynard Keynes wrote Economic Possibilities for Our Grandchildren in 1930, a vision of a universe where he thought that his grandchildren would live in an economy so productive and so rich that they would only work 15 hours a week.

约翰·梅纳德·凯恩斯 (John Maynard Keynes) 于 1930 年撰写了《我们的孙子们的经济可能性》(Economic Possibilities for Our Grandchildren)，书中描绘了这样一个愿景：他认为他的孙子们将生活在一个生产力如此高、富裕到每周只工作 15 个小时的经济体中。

Keynes said that the extra time that comes from having solved “the economic problem” would be used to solve a person’s “real, his permanent problem” which is “how to live wisely and agreeably and well.”

凯恩斯说，解决“经济问题”带来的额外时间将用于解决一个人“真正的、永久的问题”，即“如何明智、愉快和良好地生活”。

That’s not really happening.

这并没有真正发生。

Keynes grandchildren are, according to BlackRock’s read of the Fed’s Beige Book “trading down” while living through “the divide between the capital-spending economy and the consumer economy is becoming more pronounced.”

根据贝莱德对美联储褐皮书的解读，凯恩斯的孙子们正在“降价”，同时生活在“资本支出经济和消费经济之间的鸿沟正变得更加明显”。

An economy with extraordinary wealth, increasingly concentrated among older folks and already rich folks.

一个拥有非凡财富的经济体，越来越多地集中在老年人和已经富有的人身上。

Median net worth for families under 35 is down 23% since 2022.

自 2022 年以来，35 岁以下家庭的净资产中位数下降了 23%。

For families 75 and older, it’s up nearly 40%.

对于 75 岁及以上的家庭来说，这一数字增加了近 40%。

But the gap really isn’t young versus old — it’s ownership versus not.

但差距实际上并不在于年轻与年老，而在于拥有与否。

If you rent, your median net worth is about $10,000.

如果您租房，您的净资产中位数约为 10,000 美元。

If you own, it’s over $450,000.

如果您拥有，则价值超过 450,000 美元。

A utopia for some, but not for all.

对某些人来说是乌托邦，但不是所有人。

And AI is only complicating things more, mostly due to the wealth it’s creating for these two specific groups who “tend to be more invested in the stock market,” according to reporting from the Wall Street Journal.

据《华尔街日报》报道，人工智能只会让事情变得更加复杂，这主要是因为它为这两个“往往会更多地投资于股市”的特定群体创造了财富。

Most of the big ideas that have made society richer and more convenient over the last couple of decades, the ones nudging us toward perhaps some strip mall version of utopia, have made some people radically wealthy and have made most people’s lives a bit easier.

在过去的几十年里，大多数让社会变得更加富裕和更加便利的伟大想法，那些推动我们走向也许是某种商业街版本的乌托邦的想法，让一些人变得非常富有，也让大多数人的生活变得更加轻松。

But is the wealth evenly distributed?

但财富分配均匀吗？

And can AI complicate that even more?

人工智能会让事情变得更加复杂吗？

Owen Zidar and Eric Zwick went on Odd Lots to talk about their excellent new book the Everywhere Millionaire and they note that in 2001, the value add per worker to a company was about $34k, which went up to $52k in 2021.

欧文·齐达尔 (Owen Zidar) 和埃里克·兹威克 (Eric Zwick) 在 Odd Lot 上谈论了他们出色的新书《无处不在的百万富翁》，他们指出，2001 年，公司每名员工的附加值约为 3.4 万美元，2021 年将增至 5.2 万美元。

Owners got $15k of that $18k increase.

业主获得了 18,000 美元涨幅中的 15,000 美元。

The worker got $3k of the gains that the worker created.

该工人获得了其创造的收益中的 3,000 美元。

$3k!

3000 美元！

That is the economy now, as I wrote about last time .

正如我上次所写的，这就是现在的经济。

This is not an economy for workers.

这不是工人的经济。

This is an economy for capital owners.

这是资本所有者的经济。

And AI, at least the way it’s working now, and is enriching a few people very quickly, while threatening those who have the least cushion to fall.

人工智能，至少是现在的运作方式，正在迅速丰富少数人的财富，同时威胁到那些最没有缓冲能力的人。

It allows workers to automate tedious tasks (or themselves) and has polluted the Internet, our digital commons, our shared space that is owned by the public, with a lot of junk.

它允许工作人员（或他们自己）自动执行繁琐的任务，并用大量垃圾污染了互联网、我们的数字公共空间、我们公共拥有的共享空间。

Convenience while a select few reap the gains, across any industry, is not a utopia.

在任何行业中，少数人获得便利的同时获得收益，这都不是乌托邦。

To be fair, jobs themselves haven’t gone anywhere.

公平地说，工作本身并没有消失。

The people who study the impact that AI has on the labor force say that the scary forecasts are usually mostly wrong.

研究人工智能对劳动力影响的人们表示，可怕的预测通常大多是错误的。

As Ernie Tedeschi wrote in a recent Stripe Economics piece, when factories got electricity in the 1920s, people predicted mass unemployment — but factory jobs grew for another 50 years.

正如 Ernie Tedeschi 在最近的 Stripe Economics 文章中所写，当工厂在 20 年代通电时，人们预测会出现大规模失业，但工厂就业机会又持续增长了 50 年。

Postings for software engineers are up over the last two years, even though AI can now write code.

尽管人工智能现在可以编写代码，但过去两年软件工程师的职位数量有所增加。

So the fight so far isn’t really about if there is work but rather, who gets paid for that work.

因此，到目前为止，争论的焦点并不是是否有工作，而是谁能从这项工作中获得报酬。

And that’s the whole thing.

这就是全部事情。

People don’t really want AI on these wildly unequal terms.

人们并不真正想要在这些极其不平等的条件下使用人工智能。

80% of voters think it’s very or somewhat likely that AI will cause widespread job loss, almost 2/3rds think AI could be a threat to humanity itself, and most folks want the government to do the job that the taxpayer pays them for and to regulate it, according to David Shor at Blue Rose Research.

Blue Rose Research 的 David Shor 表示，80% 的选民认为人工智能很可能或在某种程度上可能会导致广泛的失业，近 2/3 的人认为人工智能可能对人类本身构成威胁，大多数人希望政府做纳税人付钱给他们的工作并对其进行监管。

And it’s all moving very fast.

而且这一切都进展得非常快。

As Vernor Vinge wrote back in 1993, “The Coming Technological Singularity: How to Survive in the Post-Human Era” and admitted that “sometimes I think I’d be more comfortable if I were regarding these transcendental events from one thousand years remove…

正如弗诺·文奇 (Vernor Vinge) 在 1993 年所写的《即将到来的技术奇点：如何在后人类时代生存》中所言，他承认，“有时我想，如果我考虑这些距今一千年的超验事件，我会感觉更自在……

instead of twenty.” Thirty years later, living in some form of the said-transcendental events, he does appear to be correct about many things 2 , including the philosophical battle that comes with it.

而不是二十个。”三十年后，生活在某种形式的上述超验事件中，他在许多事情上似乎确实是正确的 2 ，包括随之而来的哲学斗争。

Technological progress is never easy, and this one is no different.

技术进步从来都不是一件容易的事，这次也不例外。

But the AI buildout needs people to really like it!

但人工智能的扩展需要人们真正喜欢它！

Somebody has to buy what it makes!

总得有人买它生产的东西！

According to Stijn Van Nieuwerburgh’s paper on the AI buildout, the AI industry needs to bring in about 9% of GDP in AI revenue by 2032 for the investment to pay off.

根据 Stijn Van Nieuwerburgh 关于人工智能建设的论文，到 2032 年，人工智能行业需要将约占 GDP 9% 的人工智能收入纳入投资才能获得回报。

Greg Ip asks :

叶格雷问：

Is it plausible that Americans will spend as much of their income on this one technology as they do on food?

美国人在这项技术上花费的收入是否可能与在食品上花费的收入一样多？

Roughly twice what the nation pays for all forms of energy or all computers and software?

大约是国家为各种形式的能源或所有计算机和软件支付的费用的两倍？

Seven times what consumers spend on phone, streaming, and internet services combined?

消费者在电话、流媒体和互联网服务上的支出总和是七倍吗？

Jared Bernstein pointed out that both Amazon and Google would have to build two brand new AI-specific Amazon and Googles, on top of the existing Amazon and Google that already rake in a bunch of cash, in the next 10 years, in order to justify some of these valuations.

Jared Bernstein 指出，未来 10 年，亚马逊和谷歌都必须在现有的已经赚到大笔现金的亚马逊和谷歌之上，建立两个全新的人工智能专用亚马逊和谷歌，以证明其中一些估值的合理性。

They would have to build a second, AI-only version of themselves within the next decade, just as profitable and successful as the companies that took 30 years to build the first time around.

他们必须在未来十年内打造第二个纯人工智能版本，与那些花了 30 年打造第一版的公司一样盈利和成功。

And then there’s who is supposed to be buying.

然后就是谁应该购买。

As Torsten Slok at Apollo has written about, tech has a really rosy vision for its future, but the other silos in the economy, the ones that would pay for this tech, do not see such a rosy future.

正如阿波罗公司的托斯顿·斯洛克（Torsten Slok）所写，科技对其未来有着非常美好的愿景，但经济中的其他孤岛，即那些为这项技术买单的人，却看不到如此美好的未来。

As he writes, this “raises the question of who exactly will be writing all those checks to buy AI services.”

正如他所写，这“提出了一个问题：到底谁将开出所有这些支票来购买人工智能服务。”

That’s the other thing that a lot of people talk about but no one really seems to know how to answer?

这是很多人谈论的另一件事，但似乎没有人真正知道如何回答？

If you displace the entire labor force, is it going to be like 10 guys buying stuff via Meta Muse from each other forever?

如果你取代了整个劳动力，是否会像 10 个人永远通过 Meta Muse 互相购买东西一样？

And that’s the AI industry?

这就是人工智能行业吗？

Maybe - I was in St. Louis at FREDCon recently, where we talked about agentic AI and how we might have to write research for the AI agents to read because no one is going to want to read anymore because their agent is going to summarize it for them and then they will put that into a report that other people’s agents will summarize and that’s the future.

也许 - 我最近在圣路易斯的 FREDCon 上，我们讨论了智能体人工智能，以及我们如何编写研究供人工智能智能体阅读，因为没有人愿意再阅读，因为他们的智能体会为他们总结它，然后他们会将其放入其他人的智能体将总结的报告中，这就是未来。

I mentioned that I thought about it when I wrote, that maybe I have started writing for the machine.

我提到我写的时候就想过，也许我已经开始为机器而写了。

But…

但是……

hardly anyone is really paying for AI, much less using agents read various Substacks like this one.

几乎没有人真正为人工智能付费，更不用说使用代理来读取像这样的各种子堆栈了。

About half of Americans have tried a chatbot, according to Pew .

据皮尤研究中心称，大约一半的美国人尝试过聊天机器人。

Two banks checked their customers’ statements and found that only 2 or 3 in every 100 households actually pay for one.

两家银行检查了客户的账单，发现每 100 个家庭中只有 2 到 3 个真正支付了费用。

And even with that, the companies are already making more money than anyone thought they would be at this point.

即便如此，这些公司目前赚到的钱已经比任何人想象的还要多。

So you can see how much room they really do have to grow and make a ton of money.

所以你可以看到他们确实有多大的发展空间并赚很多钱。

As Ip notes , OpenAI and Anthropic are growing at double-digits each quarter.

正如 Ip 指出的那样，OpenAI 和 Anthropic 每个季度都以两位数的速度增长。

Exactly how fast depends on who is counting.

到底多快取决于谁在数。

These companies don’t report sales the way a normal business does.

这些公司不像正常企业那样报告销售额。

They report a “run rate” meaning they take revenue from a recent month and multiply it by 12.

他们报告“运行率”，这意味着他们将最近一个月的收入乘以 12。

A few weeks ago, the run rate going around for OpenAI was $70 billion a year.

几周前，OpenAI 的运行费约为每年 700 亿美元。

Recently, the Financial Times reported that the number OpenAI gave investors was closer to $50 billion (the stock market HATED this).

最近，英国《金融时报》报道称，OpenAI 给投资者的金额接近 500 亿美元（股市对此深恶痛绝）。

How do you lose $20 billion?

你怎么会损失200亿美元？

A lot of AI gets sold through the big cloud companies, so Anthropic, which sells through Amazon and Google, counts the full price of those sales as its own revenue.

许多人工智能产品都是通过大型云公司销售的，因此通过亚马逊和谷歌销售的 Anthropic 将这些销售的全部价格算作自己的收入。

OpenAI only counts the share it keeps.

OpenAI 只计算它保留的份额。

The $70 billion was OpenAI’s number redone via Anthropic’s way (that they didn’t deny when it first was floated?) and if you’re confused, so is everyone else.

700 亿美元是 OpenAI 通过 Anthropic 的方式重做的数字（这个数字第一次提出时他们没有否认吗？），如果你感到困惑，其他人也一样。

OpenAI expects to burn almost $280 billion by 2030 .

OpenAI 预计到 2030 年将消耗近 2800 亿美元。

They are holding off on going public, but Anthropic did file their IPO prospectus , which was leaked.

他们正在推迟上市，但 Anthropic 确实提交了 IPO 招股说明书，但招股说明书被泄露。

They made $4.6 billion in revenue and spent about $12.65 billion (half of this is compute and infrastructure costs) - and they have over $500 billion in cloud, computing, and infrastructure obligations!

他们的收入为 46 亿美元，支出约为 126.5 亿美元（其中一半是计算和基础设施成本），而且他们的云、计算和基础设施义务超过 5000 亿美元！

They are expected to go public at a $2T valuation, which would make them in the top 10 most valuable public companies in the United States, despite their revenue being extremely tiny.

他们预计将以 2T 美元的估值上市，这将使他们跻身美国十大最有价值的上市公司之列，尽管他们的收入极小。

Maybe this will all work out.

也许这一切都会解决。

Maybe these companies will find a moat and the data centers will get paid back.

也许这些公司会找到护城河，数据中心也会得到回报。

Maybe the neolabs, the new AI labs that “lack products, markets or revenue” and who have in the past six months, have raised “$24 billion, nearly 5x as much as OpenAI and Anthropic did in the years up to the launch of ChatGPT” according to the FT , will turn into real businesses.

据英国《金融时报》报道，neolabs，即“缺乏产品、市场或收入”的新人工智能实验室，在过去六个月中筹集了“240亿美元，几乎是 OpenAI 和 Anthropic 在 ChatGPT 推出前几年筹集的资金的 5 倍”，将转化为真正的业务。

Maybe it won’t become a commodity, something like oil and natural gas.

也许它不会成为一种商品，就像石油和天然气一样。

Maybe.

或许。

Chris Wood at Jefferies thinks that’s exactly where this is going.

杰富瑞 (Jefferies) 的克里斯·伍德 (Chris Wood) 认为这正是事情的发展方向。

A commodity is a product that isn’t really differentiated, so you can only compete on price.

商品是一种没有真正差异化的产品，所以你只能在价格上竞争。

He wrote this week that AI is headed there, because Chinese companies are giving away models that anyone can download and run for free.

他本周写道，人工智能正朝着这个方向发展，因为中国公司正在赠送任何人都可以免费下载和运行的模型。

If customers can get nearly the same thing for nearly nothing, the American companies can’t charge enough to pay back what they borrowed to build it.

如果客户几乎可以免费获得几乎相同的东西，那么美国公司就无法收取足够的费用来偿还他们为建造它而借来的资金。

He calls the likeliest ending “massive capital destruction” which is a polite way of saying financial implosion, which sure.

他将最有可能的结局称为“大规模资本破坏”，这是金融内爆的一种礼貌说法，这是肯定的。

The likeliest case for any sort of implosion is a slow unwind, sort of scraping the AI gum off the bottom of the economy’s shoe.

任何形式的内爆最有可能的情况是缓慢的放松，有点像刮掉经济鞋底上的人工智能口香糖。

As Ernie Tedeschi wrote

正如厄尼·特德斯基所写

AI capex being more & more financed by interest-rate sensitive means like corp bonds means you should at once be 1) less worried about an out of control “bubble” as there are more breaks that can prevent overheating, 2) more concerned about investment crowd out, eg less housing.

人工智能资本支出越来越多地通过公司债券等利率敏感方式融资，这意味着您应该立即 1) 更少担心失控的“泡沫”，因为有更多的突破可以防止过热，2) 更担心投资挤出，例如住房减少。

Not everyone thinks that China is the reason for this either – Ara Kharazian at Ramp says that the American companies are doing it to each other, cutting prices to win customers.

并非所有人都认为中国是造成这种情况的原因——Ramp 的 Ara Kharazian 表示，美国公司正在互相这样做，通过降价来赢得客户。

Either way, what they can charge seems to be falling while what they owe is…

不管怎样，他们能收取的费用似乎在下降，而他们所欠的费用却是……

not.

不。

There’s also a whole world where everyone just develops their own models, which can disrupt the whole party.

还有一个世界，每个人都在开发自己的模型，这可能会扰乱整个团队。

Latham & Watkins , a gigantic law firm, bought their own Nvidia GPU servers and started customizing AI models in-house, which keeps their clients data inside their own systems and gives them options if OpenAI and Anthropic raise their prices.

Latham & Watkins 是一家大型律师事务所，购买了自己的 Nvidia GPU 服务器，并开始在内部定制 AI 模型，这将客户的数据保留在自己的系统中，并在 OpenAI 和 Anthropic 提高价格时为他们提供选择。

AI is bigger than any investment, ever, and the companies building it are spending far more than they are making.

人工智能比任何投资都更大，而构建人工智能的公司的支出远远超过他们的收入。

So far the big boys have been able to pay for it because of who they are, not what they’re building.

到目前为止，大公司之所以能够支付这笔费用，是因为他们是谁，而不是他们正在建造什么。

And that’s kind of the general feeling?

这就是普遍的感觉吗？

As Carlyle wrote in their Rules of Relevance , “more than 80% of anticipated AI capex through 2032 is expected to require external financing” noting that “lenders are effectively underwriting a handful of investment-grade counterparties rather than the economics of the hardware itself.”

正如凯雷在其《相关性规则》中所写，“到 2032 年，预计人工智能资本支出的 80% 以上预计需要外部融资”，并指出“贷款人实际上是在为少数投资级交易对手提供担保，而不是为硬件本身的经济性提供担保。”

It was luck that the companies best suited to building out AI happened to be immensely profitable quasimonopolists.

幸运的是，最适合开发人工智能的公司恰好是利润丰厚的准垄断者。

They could finance the first leg of the buildout internally without having to meet external ROIC tests.

他们可以在内部为第一阶段的扩建提供资金，而无需满足外部投资回报率测试。

Though they are now issuing debt, that debt is backed by the hyperscalers’ non-AI cash flows, not the AI itself.

尽管他们现在正在发行债务，但这些债务是由超大规模企业的非人工智能现金流支持的，而不是人工智能本身。

In other words, the AI capex boom has been possible because the technology has never had to prove its profitability.

换句话说，人工智能资本支出的繁荣之所以成为可能，是因为该技术从未需要证明其盈利能力。

That wasn’t the case with the TMT or other prior booms, which went bust when the capex ran too far ahead of the prospective profits.

TMT 或其他先前的繁荣时期的情况并非如此，当资本支出远远超出预期利润时，它们就会破产。

What that means is lenders see Amazon and Google and say, “okay sure, they can make big money loans because they are Amazon and Google!” But even these companies are spending a lot of money.

这意味着贷款人看到亚马逊和谷歌后会说：“好吧，当然，他们可以发放大额贷款，因为他们是亚马逊和谷歌！”但即使是这些公司也花费了大量资金。

Capex, which is shorthand for what the companies are spending on long-lasting stuff like data centers, is starting to outrun how much money they are making.

资本支出是公司在数据中心等持久设施上的支出的简写，它开始超过他们赚的钱。

The big 5 are expected to spend about $800 billion this year, roughly double last year.

预计五巨头今年将支出约 8000 亿美元，大约是去年的两倍。

For the first time, that is about as much cash as their businesses generate.

这是第一次，这与他们的业务产生的现金一样多。

Goldman Sachs has them spending more than they bring in this year and next.

高盛让他们今年和明年的支出超过收入。

So the companies are buying a ton of chips, on borrowed money.

因此，这些公司正在借钱购买大量芯片。

GPUs, the chips that stack to make servers, which stack to make data centers, depreciate quickly, in about 2 to 3 years.

GPU，即堆叠起来制造服务器的芯片，堆叠起来构成数据中心的芯片，在大约 2 到 3 年内就会迅速贬值。

And each one is being swamped by new chips — Epoch AI estimates that there are about 20 million AI chips in data centers worldwide right now, a number that has been doubling roughly every nine months, which would put it near 200 million by the end of 2028, according to the NYT .

每个芯片都被新芯片淹没——据《纽约时报》报道，Epoch AI 估计，目前全球数据中心内约有 2000 万个人工智能芯片，这个数字大约每 9 个月就会翻一番，到 2028 年底，这一数字将接近 2 亿。

That’s so many chips!

这么多筹码！

They depreciate so quickly!

贬值这么快！

The other big investment booms were physical infrastructure like fiber from the Internet buildout and railroads from the railroad buildout.

其他重大投资热潮是实体基础设施，例如互联网建设中的光纤和铁路建设中的铁路。

As Hanno Lustig put it, “rails last a lot longer than GPUs.”

正如 Hanno Lustig 所说，“导轨的使用寿命比 GPU 长得多。”

If a chip is worthless in three years (unlike railroads) the money borrowed ends up outliving the thing that it paid for.

如果一块芯片在三年内变得一文不值（与铁路不同），那么借来的钱最终会比它所支付的东西寿命更长。

The first big wave of these chips turns five and six years old between 2027 and 2029, and we will certainly find out more then.

这些芯片的第一波浪潮将在 2027 年至 2029 年之间出现五六年，届时我们肯定会发现更多信息。

Fed Chair Warsh was asked at his September press conference why long-term rates keep rising.

美联储主席沃什在 9 月份的新闻发布会上被问及为什么长期利率持续上升。

He said well, (1) the economy is strong and (2) there is competition for capital because “the so-called hyperscalers are out in the market raising funding” and (3) geopolitics.

他说得好，（1）经济强劲，（2）存在资本竞争，因为“所谓的超大规模企业正在市场上筹集资金”，（3）地缘政治。

That’s the entire triangle.

这就是整个三角形。

Fed Governor Christopher Waller said that the bond market is doing “some of the work” of rate hikes for the Fed, by slowing down the parts of the economy that are sensitive to rates, which are like houses and cars, not data centers.

美联储理事克里斯托弗·沃勒(Christopher Waller)表示，债券市场正在为美联储加息做“部分工作”，方法是放慢经济中对利率敏感的部分，比如房屋和汽车，而不是数据中心。

He thinks the AI spending pressure could last two to three years, and the productivity payoff is a few years out.

他认为人工智能支出压力可能会持续两到三年，而生产力回报则需要几年时间。

So.

所以。

You know.

你知道。

The government’s fiscal year ended September 30th, and it spent $7.4 trillion and took in $5.4 trillion, which is a $2 trillion gap, over $200 billion larger than last year, and the third largest EVER in dollar terms behind the two pandemic (pandemic!!) years.

政府的财政年度截至 9 月 30 日，支出 7.4 万亿美元，收入 5.4 万亿美元，缺口达 2 万亿美元，比去年多出 2000 亿美元以上，按美元计算是继两次大流行（大流行！！）年份之后的第三大缺口。

The debt is now about the size of the entire economy .

目前债务规模相当于整个经济的规模。

And people don’t want as much US debt as they used to, at least not at the old prices 3 , especially foreign buyers, who would much rather buy the shiny and beautiful AI stocks.

人们不想要像以前那样多的美国债务，至少不以旧价格计算 3 ，尤其是外国买家，他们更愿意购买闪亮而美丽的人工智能股票。

As Brad Setser said, “it feels like the world is very high on US equity.” According to the FT , “overseas investors bought a net $188 billion of US debt securities in the second quarter, down from $314 billion in the first.” Some central banks are pulling back in other ways too.

正如布拉德·塞瑟（Brad Setser）所说，“感觉世界对美国股市的依赖度很高。”据英国《金融时报》报道，“第二季度海外投资者净购买了 1,880 亿美元的美国债务证券，低于第一季度的 3,140 亿美元。”一些央行也在以其他方式退出。

The Netherlands moved their gold closer to them, citing “increasing geopolitical unrest.”

荷兰将黄金移至离他们更近的地方，理由是“地缘政治动荡加剧”。

And that’s the thing, it’s not just the US that is wrestling with all these problems.

事情就是这样，不仅仅是美国在应对所有这些问题。

The IMF put out its big twice-a-year report this week , and it said that wealthy countries are on track to borrow 5.2% of their economies this year, the most since 2021, when we were in a PANDEMIC.

国际货币基金组织本周发布了一年两次的大型报告，报告称富裕国家今年有望借入其经济的 5.2%，这是自 2021 年大流行以来的最高水平。

Everyone’s shrugging!

每个人都耸耸肩！

And the IMF said that “growth is being reallocated across countries” depending on how exposed they are to the war and how exposed they are to AI.

国际货币基金组织表示，“增长正在各国之间重新分配”，具体取决于各国受战争影响的程度以及受人工智能影响的程度。

In April, 54 countries produced 95% of the world’s growth.

4月份，54个国家贡献了全球95%的增长。

Now it’s 32.

现在是32了。

Global debt is sitting at about 310% of global GDP.

全球债务约占全球 GDP 的 310%。

Japan especially is a point of pain, with the 10-year yield there going north of 3% , which is extremely unusual.

日本尤其是一个痛点，其 10 年期国债收益率高达 3%，这是极其不寻常的。

They held rates near zero for a very long time, which supported the yen-carry trade that some people like Ed Yardeni think is causing little explosions across the entire debt market.

他们在很长一段时间内将利率维持在接近于零的水平，这支持了日元套利交易，埃德·亚德尼等一些人认为日元套利交易在整个债务市场上几乎没有引起爆炸。

But Debt is no longer cheap.

但债务不再便宜。

Money is no longer free.

金钱不再是免费的。

Real rising interest rates are something that not many people have too much experience with.

真正的利率上升并不是很多人有太多经历的。

Rates have not been this high in a long time.

利率已经很久没有这么高了。

The 10-year Treasury is at its highest since 2002.

10年期国债处于2002年以来的最高水平。

For my dad, rates were this high when he bought a house in the 1980s, but they’ve dropped meaningfully since then, which allowed the baby boomers to benefit from easy money and a rising stock market.

对于我父亲来说，他在 20 世纪 80 年代买房时的利率非常高，但此后利率大幅下降，这使得婴儿潮一代受益于宽松的货币政策和不断上涨的股市。

That could all be changing.

这一切可能正在改变。

When the 10-year climbs, it hurts people.

当10年攀升时，会伤害人们。

As Heather Long pointed out , mortgage rates go up, auto loans go up, personal loan rates go up, refinancing gets harder, banks have to hedge, credit cards get more expensive.

正如希瑟·朗指出的那样，抵押贷款利率上升，汽车贷款上升，个人贷款利率上升，再融资变得更加困难，银行必须进行对冲，信用卡变得更加昂贵。

It’s a ripple effect, at the same time that workers quite literally have to work harder than ever to afford ground beef and coffee (the work-time-to-caffeine ratio is at the highest it’s been in modern times, according to UBS .)

这是一种连锁反应，与此同时，工人们实际上必须比以往任何时候都更加努力地工作才能买得起碎牛肉和咖啡（根据瑞银的数据，工作时间与咖啡因的比率达到了现代最高水平。）

For a long time, the economy didn’t seem to care too much about interest rates.

长期以来，经济似乎并不太关心利率。

But now, it might, because increasingly, not even AI can really hide from the bond market.

但现在，可能会出现这种情况，因为人工智能也越来越无法真正躲过债券市场。

The bond market is already jittery.

债券市场已经紧张不安。

Bonds are a beacon of truth.

债券是真理的灯塔。

That matters for the AI buildout and the $10.3 trillion (!) in expected financing it needs by 2032, but it also matters for the Treasury market.

这对于人工智能的建设及其到 2032 年所需的 10.3 万亿美元的预期融资至关重要，而且对于国债市场也很重要。

And every other market.

以及其他所有市场。

Private non-residential fixed investment and residential investment have both shrunk in comparison to AI, which has exploded upwards.

与人工智能的爆发式增长相比，私人非住宅固定投资和住宅投资均出现萎缩。

So is AI borrowing literally crowding out everybody else, the Treasury included?

那么，人工智能借贷真的会排挤其他所有人，包括财政部吗？

FT Alphaville ran the numbers and said probably not , pointing to economic strength and geopolitics instead.

英国《金融时报》阿尔法维尔报道了这些数据，并表示可能不会，而是指出了经济实力和地缘政治。

Tracy Alloway cites Matt King in her Bloomberg piece, who said “the issue is less the volume of current borrowing than the desire.” She summarizes it as:

特雷西·阿洛韦在彭博社的文章中引用了马特·金的话，他说“问题不在于当前的借贷量，而在于人们的愿望。”她总结为：

One broad way of looking at the current bond environment is as a place where issuers who feel they have no choice but to borrow are running headfirst into buyers who feel they have a rapidly-expanding array of investment options.

看待当前债券环境的一种广泛方式是，那些认为自己别无选择只能借钱的发行人正在迎头撞上那些认为自己拥有迅速扩大的投资选择的买家。

Basically, the borrowers feel like they have to borrow no matter what, and the buyers get to be picky.

基本上，借款人觉得无论如何他们都必须借钱，而买家则变得挑剔。

The two biggest issuers appear to be willing to sell bonds at any price, which is the shrug in action.

两个最大的发行人似乎愿意以任何价格出售债券，这就是耸肩行动。

The AI companies are borrowing so much money (and the most money ever) at the same time that the government is borrowing even more, to the point that BlackRock wrote “heavy sovereign borrowing is increasingly competing with extraordinary private financing needs, particularly from AI, pushing prospective capital demand toward levels rarely seen outside crises.”

人工智能公司借了如此多的钱（也是有史以来最多的钱），同时政府借的钱甚至更多，以至于贝莱德写道，“巨额主权借款正日益与非凡的私人融资需求（尤其是来自人工智能的需求）竞争，将潜在的资本需求推向危机之外罕见的水平。”

Outside a CRISIS?

危机之外？

And maybe this is a CRISIS!

也许这就是一场危机！

The economy is reliant on a technology that the creators of said technology seemingly can’t control (OpenAI keeps hacking into the government ) with no real moat and depreciating physical infrastructure and unproven demand at the prices needed to pay it back, while again, spending more money than any money has ever been spent ever, counting for 25% of US GDP growth and 8% of total GDP and more than ⅓ of the stock market, at the same time that we face a war that seems endless, pushing up the cost of oil, the foundation for any economy (and the AI buildout) and a government that is borrowing also a lot of money for bigger and weirder projects.

经济依赖于一种技术，而该技术的创造者似乎无法控制（OpenAI 不断侵入政府），没有真正的护城河，物理基础设施不断贬值，需求也未经证实，需要偿还它的价格，同时，我们花费的钱比以往任何时候都多，占美国 GDP 增长的 25%、GDP 总量的 8% 和股市的 1/3 以上，同时我们面临着一场似乎无休无止的战争，推高了石油的成本是任何经济体（以及人工智能建设）的基础，而政府也为更大、更奇怪的项目借了很多钱。

So the fight over money is a big fight, but the fight over real stuff has already mostly happened.

因此，关于金钱的斗争是一场大斗争，但关于实物的斗争已经大部分发生了。

You can see it in what’s getting built.

您可以在正在构建的内容中看到它。

In August, spending on data center construction was up 73% from a year earlier.

8月份，数据中心建设支出同比增长73%。

Factory construction was down about 20%.

工厂建设下降约20%。

Home building was down about 5%.

房屋建筑下降约 5%。

So - the data center buildout was up about $9 billion year to date through July of this year, and private construction (so homes and apartments and shopping centers) fell $46 billion over the same time period.

因此，截至今年 7 月，数据中心建设增加了约 90 亿美元，而同期私人建设（住宅、公寓和购物中心）则减少了 460 亿美元。

President Hammack made this point in her speech too.

哈马克总统在讲话中也阐述了这一点。

Oil isn’t the whole inflation story and the AI buildout likely has something to do with it.

石油并不是通货膨胀的全部，人工智能的发展可能与此有关。

Data centers are bidding up the price of computer and electrical parts, and those same parts go into aviation, electricity production, and construction – kind of everything, you know.

数据中心正在抬高计算机和电气部件的价格，而这些部件又进入了航空、电力生产和建筑行业——几乎所有领域，你知道。

This kind of pressure relies on the Fed to start hiking rates – to slow it all down, right?

这种压力依赖于美联储开始加息——以减缓一切，对吗？

But who does higher rates slow down?

但更高的利率会减慢谁的速度呢？

Not the big boys.

不是大男孩。

Everyone else around the big boys.

其他人都在大男孩身边。

So the AI buildout helps lead to inflationary pressures, and it’s the borrower most likely to just…

因此，人工智能的建设有助于导致通胀压力，而借款人最有可能……

shrug.

耸耸肩。

Torsten Slok at Apollo calls this “Dutch disease” — a rate-insensitive boom draining capital, power, and labor from the sectors that are rate sensitive, like housing and autos.

阿波罗公司的托斯顿·斯洛克（Torsten Slok）将其称为“荷兰病”——一种对利率不敏感的繁荣，从住房和汽车等对利率敏感的行业中抽走资本、电力和劳动力。

He says the only solution is expanding the supply of chips and power, which the industry is trying to do, but the shrug isn’t as easy as it used to be.

他表示，唯一的解决方案是扩大芯片和电力的供应，业界正在努力做到这一点，但耸耸肩并不像以前那么容易了。

Everyone is starting to raise an eyebrow.

每个人都开始扬起眉毛。

Shrugs can’t last forever.

耸肩不可能永远持续下去。

And the bond market is getting increasingly wary about all this - credit default spreads, which you can think of as like car insurance for bonds, are getting more and more expensive because the AI companies are becoming riskier and riskier drivers.

债券市场对这一切越来越警惕——信用违约利差（你可以把它想象成债券的汽车保险）变得越来越昂贵，因为人工智能公司的风险越来越大。

Oracle is a potential canary in the coal mine here according to Bloomberg (and it’s VERY important to note that some of this volatility is happening because yields in general are going up).

据彭博社报道，甲骨文是煤矿中潜在的金丝雀（值得注意的是，这种波动之所以发生，是因为收益率总体上在上升）。

Oracle’s credit default swaps, so the cost to insure Oracle’s debt, hit a record high.

甲骨文的信用违约掉期，因此为甲骨文债务提供保险的成本创下了历史新高。

Oracle is one notch above junk, and Larry Ellison just…

甲骨文比垃圾公司高一级，而拉里·埃里森只是……

keeps spending money.

不断花钱。

The Ellison family put $17 billion into Paramount’s purchase of Warner Bros.

埃里森家族斥资 170 亿美元，派拉蒙收购了华纳兄弟。

(and that combined entity has $80 billion in debt)!

（合并后的实体负债 800 亿美元）！

As Campe Goodman says, “you have to consider your total Larry Ellison risk.”

正如坎普·古德曼所说，“你必须考虑拉里·埃里森的总体风险。”

But if Oracle does get downgraded to junk OR OpenAI, one of its biggest customers (the whole circular financing thing), goes sideways, people are going to have to sell Oracle bonds, which would be not so good, creating ripple effects throughout the market - quite literally , as this map of revenue dependency across the AI ecosystem from the FT shows.

但如果甲骨文确实被降级为垃圾级，或者其最大客户之一的 OpenAI（整个循环融资的事情）陷入困境，人们将不得不出售甲骨文债券，这将不太好，从而在整个市场产生连锁反应——毫不夸张地说，正如英国《金融时报》上这张人工智能生态系统收入依赖图所示。

The big cloud companies report something called “remaining performance obligations” which is money customers have signed contracts for but haven’t paid yet.

大型云公司报告了所谓的“剩余履约义务”，即客户已签署合同但尚未支付的款项。

For Microsoft, Amazon, Alphabet, and Oracle - that backlog went from about $0.5 trillion in early 2024 to over $2 trillion now, per Jefferies.

Jefferies 表示，对于微软、亚马逊、Alphabet 和甲骨文来说，积压的订单从 2024 年初的约 5 万亿美元增至现在的超过 2 万亿美元。

That looks like guaranteed money, at least on paper.

这看起来像是有保证的钱，至少在纸面上是这样。

But a lot of it is owed by the AI labs.

但其中很大一部分是人工智能实验室欠的。

Anthropic’s $500+ billion in infrastructure obligations is somebody else’s backlog.

Anthropic 超过 5000 亿美元的基础设施债务是其他人的积压订单。

So the lenders are counting on the cloud companies, the cloud companies are counting on the labs, and the labs are counting on…

因此，贷款人指望云公司，云公司指望实验室，实验室指望……

people?

人？

To eventually pay for all of this?

最终要为这一切付出代价吗？

Who, per Anthropic’s filing, aren’t locked into long-term contracts and could cut spending.

根据 Anthropic 的文件，他们没有签订长期合同，可以削减开支。

Nearly a quarter of its revenue last year came from two customers!

去年其收入的近四分之一来自两个客户！

Jefferies says that it can “no longer be assumed” the models will ever be profitable, and sees a “2008 real estate credit angle” to this boom .

杰富瑞 (Jefferies) 表示，“不能再假设”这些模型将永远盈利，并从“2008 年房地产信贷角度”看待这一繁荣。

A Barclays trader says he hasn’t seen a “credible framework as to where this money is going to come from.”

巴克莱银行的一位交易员表示，他还没有看到“关于这笔钱从何而来的可靠框架”。

And the risk is getting spread around.

而且风险正在四处扩散。

The FT reported that SpaceX is trying to raise $40 billion in debt to buy Nvidia chips.

英国《金融时报》报道称，SpaceX 正试图筹集 400 亿美元的债务来购买 Nvidia 芯片。

Investors who were pitched on it earlier said that they got “a short two-page deal memo with pictures of outer space and an arrow pointing out that the company was going to build data centres “somewhere in the universe”.

早些时候参与该项目的投资者表示，他们收到了“一份简短的两页交易备忘录，其中有外太空的图片和一个箭头，指出该公司将在“宇宙的某个地方”建立数据中心。

As one of them put it “How are we supposed to take that to the IC?” (the investment committee, the people who have to say yes to an investment.) But because SpaceX’s debt is rated investment grade, insurance companies and pension funds are allowed to buy it, despite the whole “we are going to space :p moon data centers” thing.

正如其中一位所说，“我们该如何将其提交给 IC？” （投资委员会，那些必须对投资说“是”的人。）但由于 SpaceX 的债务被评为投资级，因此保险公司和养老基金可以购买它，尽管有“我们要去太空：月球数据中心”的说法。

Nvidia is working on the other end of these loans.

英伟达正在研究这些贷款的另一端。

The FT reported that Nvidia has talked to insurers about covering the losses if one of its smaller customers defaults and the chips can’t be resold for enough to pay back the loan.

据英国《金融时报》报道，英伟达已与保险公司讨论，如果其一个较小的客户违约并且芯片无法转售以支付足够的费用来偿还贷款，那么英伟达将承担损失。

Jensen Huang wants chips treated like an “investable asset class” like airplanes.

黄仁勋希望将芯片视为像飞机一样的“可投资资产类别”。

So the company selling the chips is helping to arrange the loans to buy the chips, and now the insurance on the loans to buy the chips.

所以销售芯片的公司正在帮助安排购买芯片的贷款，现在又为购买芯片的贷款提供保险。

And Blue Owl, which leases 140 data centers to the big tech companies, said this week it wants more insurance money to do it.

向大型科技公司租赁 140 个数据中心的 Blue Owl 本周表示，希望获得更多保险资金来实现这一目标。

According to their co-CEO, Doug Ostrover:

他们的联合首席执行官 Doug Ostrover 表示：

We are not managing enough capital.

我们管理的资本不足。

We’re realizing that if we had a bigger pool of capital, meaning insurance capital, we could provide really unique solutions.

我们意识到，如果我们拥有更大的资本池，即保险资本，我们就可以提供真正独特的解决方案。

Spreading risk doesn’t make it smaller!

分散风险并不会降低风险！

It moves it to whoever is on the other side of the trade, and here, it’s insurers and pension funds, which is to say, people’s annuities and retirements.

它将资金转移给交易另一方的人，这里指的是保险公司和养老基金，也就是说，人们的年金和退休金。

And the insurers are already getting full.

保险公司已经满员了。

Zach Ablon at Goldman Sachs said on the firm’s podcast that earlier this year about 15 insurers were putting in big orders for 30-year AI bonds, but by June, that had been cut in half.

高盛 (Goldman Sachs) 的扎克·阿布隆 (Zach Ablon) 在该公司的播客上表示，今年早些时候，约有 15 家保险公司下了 30 年期人工智能债券的大订单，但到 6 月份，这一数量已减少了一半。

They are, he said, “clearly losing their appetite for this risk.”

他说，他们“显然对这种风险失去了兴趣。”

Ostrover also pointed out something really bleak, as the FT summarized:

奥斯特洛弗还指出了一些非常黯淡的事情，正如英国《金融时报》所总结的那样：

Ostrover said that even if the infrastructure was worth “zero” at the end of the leases, its investors would make double-digit returns.

奥斯特罗弗表示，即使基础设施在租约结束时价值“为零”，其投资者也将获得两位数的回报。

“You can make 10 to 12 per cent [without relying on the terminal value].

“你可以赚取 10% 到 12%（不依赖最终价值）。

We think that’s a really compelling investment.”

我们认为这是一项非常有吸引力的投资。”

So the investors will be okay, but what about the communities stuck with these huge, expensive sheds?

所以投资者不会有什么问题，但是那些被这些巨大而昂贵的棚屋困住的社区怎么办？

As we know - they are really expensive.

众所周知——它们真的很贵。

Bloomberg got a cost breakdown for a single one, a one-gigawatt data center in Texas, from the real estate firm Cushman & Wakefield.

彭博社从房地产公司戴德梁行 (Cushman & Wakefield) 那里获得了德克萨斯州一个 1 吉瓦数据中心的成本明细。

About $30 billion at the high end.

高端约为 300 亿美元。

Half of that is the chips and servers, but the developer has to set aside nearly $3 billion just in case things cost more than planned (which they will).

其中一半是芯片和服务器，但开发商必须拨出近 30 亿美元，以防成本超出计划（他们会的）。

Bloomberg also did the math on what 4 of the big companies are spending this year (Meta, Amazon, Microsoft, and Alphabet) - enough to cut a $5,500 check to every household in the United States.

彭博社还计算了 4 家大公司（Meta、亚马逊、微软和 Alphabet）今年的支出——足以为美国每个家庭削减 5,500 美元的支票。

A lot of communities are saying no. Heatmap counted at least $260 billion of data center projects canceled so far this year after local opposition, half of it in the last three months.

很多社区都说不。根据 Heatmap 统计，今年迄今为止，因当地反对而取消的数据中心项目至少有 2600 亿美元，其中一半是在过去三个月内取消的。

And the ones that do get built end up hitting a totally different wall.

而那些确实建成的最终却撞上了完全不同的墙。

Even if the money keeps coming and the investors start taking baths in gold or whatever, there is a physical limit, which is how the triangle really connects.

即使资金不断涌入，投资者开始沐浴黄金或其他什么，也存在物理限制，这就是三角形真正的连接方式。

Energy (and trust) is the foundation of an economy.

能源（和信任）是经济的基础。

There is not enough energy for all the power that these big boys want.

没有足够的能量来满足这些大男孩想要的所有力量。

The CEO of Eaton , which makes electrical equipment, said that 342 gigawatts of data centers have been announced, and only 50 gigawatts are operating today.

生产电气设备的伊顿公司首席执行官表示，已宣布建设 342 吉瓦的数据中心，但目前只有 50 吉瓦正在运行。

As the CEO said, that’s 6 to 7 times what exists!

正如首席执行官所说，这是现有的 6 到 7 倍！

As Goldman Sachs wrote, “the physical grid could emerge as the ultimate constraint.

正如高盛所写，“物理网格可能成为最终的限制。

4 ”

4”

But some of those gigawatts are like ghostwatts?

但其中一些千兆瓦就像幽灵瓦一样？

The Wall Street Journal reported that developers shopping for data center sites ask several utilities for power, so the same data center gets counted a couple of times.

《华尔街日报》报道称，购买数据中心站点的开发商会向多家公用事业公司索要电力，因此同一个数据中心会被计算多次。

Only about a quarter (!) of the requests seem “high confidence” (meaning, a real request) and so now, the utilities are like “you’re going to have to enter a binding commitment with us before we build ANYTHING.” As Exelon’s Jeanne Jones put it, “if we build out the grid and then that data center walks away, someone’s got to pay for it.”

只有大约四分之一（！）的请求看起来“高度可信”（意思是真正的请求），所以现在，公用事业公司就像“在我们建造任何东西之前，您必须与我们签订具有约束力的承诺”。正如 Exelon 的 Jeanne Jones 所说，“如果我们建立了电网，然后数据中心却消失了，就必须有人为此付出代价。”

And of course, someone is everyone else, the people that can’t just shrug all these problems away.

当然，有些人就是其他人，那些不能对所有这些问题不屑一顾的人。

Oracle is running head first into these energy problems in New Mexico.

甲骨文正在新墨西哥州率先解决这些能源问题。

It gave force majeure notice (meaning they were like if this thing is late due to things outside our control, we get to delay paying rent) on its New Mexico data center.

它在新墨西哥州数据中心发出了不可抗力通知（这意味着如果由于我们无法控制的事情导致事情延迟，我们可以推迟支付租金）。

The project is waiting on power (waiting on a gas pipeline, which got delayed more than half a year after regulators kept denying permits) and is facing local opposition – 65% of New Mexicans don’t want big data centers at all.

该项目正在等待电力（等待天然气管道，由于监管机构不断拒绝许可，该项目被推迟了半年多），并面临当地的反对——65% 的新墨西哥人根本不想要大型数据中心。

Bloomberg reported that Oracle is starting to truck (diesel) natural gas to data centers in Utah and Texas and may do the same in New Mexico.

彭博社报道称，甲骨文正开始向犹他州和德克萨斯州的数据中心运送（柴油）天然气，并可能在新墨西哥州采取同样的做法。

Trucked gas costs about 4x as much as pipeline gas, but these data centers HAVE to turn on to be useful 5 .

卡车运输天然气的成本约为管道天然气的 4 倍，但这些数据中心必须开启才能发挥作用 5 。

Diesel hauling natural gas to a data center.

柴油机将天然气运送到数据中心。

Oil, AI, and borrowed money, all while the people who live there ask for it to not happen.

石油、人工智能和借钱，而居住在那里的人们却要求这一切不要发生。

The whole triangle in one picture.

整个三角形在一张图片中。

Almost half of the earnings growth in the stock market comes from AI investment, across “chipmakers, tech hardware suppliers, industrial firms, and utilities” which has fed into a booming stock market and into household wealth.

股市收益增长的近一半来自人工智能投资，涉及“芯片制造商、科技硬件供应商、工业公司和公用事业公司”，这些投资促进了蓬勃发展的股市和家庭财富。

Corporate profits jumped almost 60% this spring, but more than half of American companies made less money than the year before, according to Aswath Damodaran .

阿斯瓦斯·达莫达兰 (Aswath Damodaran) 表示，今年春天，企业利润增长了近 60%，但超过一半的美国企业盈利低于前一年。

BCA Research charted how much profit Wall Street expects from big companies over the next year.

BCA Research 绘制了华尔街预计明年大公司利润多少的图表。

It’s up 31% since January, most of that is tech, and everything outside of tech, communications, and energy adds up to about zero.

自 1 月份以来上涨了 31%，其中大部分是科技股，科技、通信和能源以外的所有因素加起来大约为零。

The market is at all time highs and 75% of those stocks are trading below their 50-day moving average, meaning, they aren’t doing great.

市场正处于历史高位，其中 75% 的股票交易价格低于 50 日移动平均线，这意味着它们的表现不佳。

But those other 25% are doing fantastic .

但另外 25% 的人却表现得非常出色。

Since June, more than half of stocks have fallen at least 20% according to Morgan Stanley.

摩根士丹利的数据显示，自 6 月份以来，超过一半的股票已下跌至少 20%。

Not too unlike “computer terminals printing out market prices while the world blows up,” as Annie Dillard wrote .

正如安妮·迪拉德（Annie Dillard）所写，这与“世界崩溃时计算机终端打印出市场价格”没什么不同。

Part of this is because one company’s AI spending is another company’s sales.

部分原因是一家公司的人工智能支出是另一家公司的销售额。

When Microsoft buys chips, that money shows up as Nvidia’s profit – the whole circular financing thing, right?

当微软购买芯片时，这笔钱就会显示为英伟达的利润——整个循环融资的事情，对吗？

So the money goes around in a small circle of companies.

所以钱在一小部分公司里流动。

And that teeny circle is the entire economy, kind of.

这个小圆圈可以说是整个经济。

That’s the worry that everyone keeps harping on, this feeling that everywhere you turn, there is AI and it has to be there, or else everything explodes into little pieces.

这就是每个人都在喋喋不休的担忧，这种感觉，无论你走到哪里，都有人工智能，而且它必须在那里，否则一切都会爆炸成小碎片。

If the AI spend stops and the debt has to be paid back –on top of a stock market that is overexposed to AI, with most other companies in it struggling and increasingly so, with SpaceX’s IPO and Alphabet’s public stock sale and Anthropic’s planned IPO, there will be a glut of share supply.

如果人工智能支出停止，债务必须偿还——再加上股市过度暴露于人工智能，大多数其他公司都在苦苦挣扎，而且随着 SpaceX 的 IPO、Alphabet 的公开股票发售以及 Anthropic 计划的 IPO，股票供应将会过剩。

And when there is too much supply of something, the price of it has to go down, which, if you follow the loop means, household wealth could fall too.

当某种东西的供应过多时，它的价格就必须下降，如果你遵循这个循环，这意味着家庭财富也会下降。

Add it all up, and you get what Jim Chanos, summarizing Paul Kedrosky in a recent interview , called a boom that checks all four boxes, pointing out that “major booms are either credit-related, government-related, technology-related, or real-estate-related” and AI is the first in a long time that checks all four boxes.

把所有这些加起来，你就得到了吉姆·查诺斯（Jim Chanos）在最近的一次采访中总结保罗·克德罗斯基（Paul Kedrosky）所说的满足所有四个框的繁荣，并指出“主要繁荣要么与信贷相关，与政府相关，要么与技术相关，要么与房地产相关”，而人工智能是很长一段时间以来第一个满足所有四个框的繁荣。

And that’s where the risk comes from.

这就是风险的来源。

There comes a point in an economy where you have to ask – how much is too much?

经济发展到了某个阶段，你不得不问——多少才算太多？

Usually this is answered by a bubble bursting, too much money going into places where it isn’t needed.

通常，这个问题的解决办法是泡沫破裂，太多资金流向不需要的地方。

Right now, because so much of this AI money is borrowed (from all pockets of markets, across all banks and insurers and private credit), it’s extremely risky.

目前，由于大部分人工智能资金都是借来的（从各个市场、所有银行、保险公司和私人信贷），因此风险极高。

So if this many people are paying for it and everyone keeps writing these Substacks about what’s happening, why doesn’t someone slow it down?

因此，如果有这么多人为此付费，并且每个人都在不断地写这些子堆栈来了解正在发生的事情，为什么没有人放慢速度呢？

The Trump administration has every incentive to boost AI as much as possible and to regulate as little as possible because it’s the thing holding up the stock market.

特朗普政府有充分的动力尽可能地推动人工智能发展，并尽可能少地进行监管，因为这是支撑股市的因素。

The Atlantic reported that Trump “has expressed worry to those close to him that a halt to AI expansion could send the economy into a recession.”

《大西洋月刊》报道称，特朗普“向与他关系密切的人表示担心，停止人工智能扩张可能会导致经济陷入衰退。”

“Whoever wins AI, WINS!” is the current messaging announced aloud on the casino floor (while having the companies sign a document where they pinky promise to self-regulate (and where the United States is spelled wrong, an omen for a not-too distant future)).

“谁赢得了人工智能，谁就获胜了！”这是目前在赌场大厅大声宣布的信息（同时让这些公司签署一份文件，其中他们小指承诺自我监管（美国拼写错误，这是不久的将来的预兆））。

The president recently posted that the White House considers anyone who says “Artificial Intelligence” instead of “Super Intelligence” to be “THE ENEMY!” So that’s probably all we are going to get from the government for now, a semantic war.

总统最近发帖称，白宫认为任何说“人工智能”而不是“超级智能”的人都是“敌人！”所以，这可能就是我们现在能从政府那里得到的一切，一场语义战争。

Meanwhile, Axios reported that the AI companies are planning for “ the day after” if something goes badly wrong.

与此同时，Axios 报道称，如果出现严重问题，人工智能公司正在为“后天”做好准备。

They expect some sort of cyberattack on banks, the Internet, or power and water systems.

他们预计银行、互联网或电力和供水系统会受到某种网络攻击。

And Sam Altman , who runs OpenAI, told Politico that “the world should accept some bad things happening for the benefits of this technology.”

OpenAI 的运营者萨姆·奥尔特曼 (Sam Altman) 告诉 Politico，“世界应该接受一些坏事的发生，以利用这项技术。”

It feels like everyone is just pointing fingers when it does come to regulation.

当谈到监管时，感觉每个人都只是互相指责。

Treasury Secretary Scott Bessent told Axios “I believe that we have to be prepared for every occasion, but on the other side, this alarmism without solutions by some of the AI community, that’s not leadership.”

财政部长斯科特·贝森特 (Scott Bessent) 告诉 Axios：“我相信我们必须为每种情况做好准备，但另一方面，这种危言耸听而没有一些人工智能社区的解决方案，这不是领导力。”

SOMEONE HAS TO DO SOMETHING!!

必须有人做点什么！！

The Vanderbilt Policy Accelerator (I am a Senior Fellow there) launched their version of something, a good something, called the AI Governance Project that provides blueprints for how AI gets governed, who gets the benefits, and who pays for all the stuff happening.

范德比尔特政策加速器（我是那里的高级研究员）推出了他们的版本，一个很好的东西，称为人工智能治理项目，该项目为人工智能如何治理、谁获得好处以及谁为所有发生的事情买单提供了蓝图。

So there are solutions, but the solutions would require rules, and one of the reasons no one wants rules is The Race.

所以有解决方案，但解决方案需要规则，而没有人想要规则的原因之一就是竞赛。

If we slow down, China won’t, seems to be the thinking.

人们的想法似乎是，如果我们放慢脚步，中国就不会。

But China is thinking about things a bit differently.

但中国的想法有点不同。

As Kyle Chan writes :

正如凯尔·陈（Kyle Chan）所写：

Most new public-facing A.I.

最新的面向公众的人工智能

models must be registered with the government and pass a battery of tests before they can be released.

模型必须在政府注册并通过一系列测试才能发布。

China has created extensive rules requiring labeling of A.I.-generated content and limiting how humanlike A.I.

中国制定了广泛的规则，要求对人工智能生成的内容进行标记，并限制人工智能生成的方式。

chatbots can operate .

聊天机器人可以操作。

Of course, the answer China lands on for all of that is the Party controlling everything.

当然，中国对这一切的答案是党控制一切。

A state-backed paper, the Global Times, called the CEO of Anthropic Dario Amodei’s call to slow down AI a “Cold War playbook” targeting China specifically in order to make them fall behind.

一家政府支持的报纸《环球时报》称 Anthropic 首席执行官达里奥·阿莫迪 (Dario Amodei) 放慢人工智能速度的呼吁是专门针对中国的“冷战剧本”，目的是让他们落后。

So that’s all happening at the state level, power versus power, as it’s been since we started organizing ourselves into little villages and factions thousands of years ago (not to diminish this in the slightest, but it’s history repeating itself.) As Chang Che wrote in the excellent There Is No A.I.

所以这一切都发生在国家层面，权力与权力之间，就像我们几千年前开始把自己组织成小村庄和派系一样（不是要丝毫削弱这一点，而是历史在重演。）

“Race”

“比赛”

For years, the powers in Silicon Valley and D.C. have conjured an image of China barrelling toward superintelligence.

多年来，硅谷和华盛顿的势力一直在塑造一种中国正在快速走向超级智能的形象。

The irony of this is twofold.

这具有双重讽刺意义。

First, Chinese A.I.

首先，中国人工智能。

policy remains focussed primarily on diffusion: how to drive A.I.

政策仍然主要关注扩散：如何推动人工智能。

into public and commercial life.

进入公共和商业生活。

(It’s rare to hear a Chinese leader mention the risks of runaway, self-improving A.I.) Second, as Matt Sheehan, a researcher at Carnegie focussed on global technology issues, recently observed on Ezra Klein’s podcast, in the years in which Chinese A.I.

（很少听到中国领导人提到失控、自我改进的人工智能的风险）其次，正如卡内基研究全球技术问题的研究员马特·希恩（Matt Sheehan）最近在埃兹拉·克莱因（Ezra Klein）的播客中观察到的那样，在中国人工智能发展的这些年里，

companies caught up to the American frontier, they also had to accommodate their own government, home to “the world’s strictest, most comprehensive, most burdensome A.I.

当公司赶上美国边境时，他们还必须适应自己的政府，因为政府是“世界上最严格、最全面、最繁重的人工智能的所在地”。

regulations.”

规定”。

So nobody at the top is stopping it, it seems.

所以看起来高层没有人阻止它。

And the cost of that lands on people.

而其成本落在了人们身上。

An economy that shrugs at prices ultimately shrugs at people.

对价格不屑一顾的经济最终也会对人们不屑一顾。

The worry here is that technology costs more than promised, makes life worse for everyone who doesn’t have it , and makes the people who do have it less than they were.

这里令人担忧的是，技术的成本比承诺的要高，使所有没有技术的人的生活变得更糟，并使拥有技术的人的生活变得更糟。

And that’s the other side of all this.

这就是这一切的另一面。

What often gets lost inside the triangle is the value of people in an economy that keep telling them that they suck.

在三角关系中，人们常常会迷失的是，在一个不断告诉人们自己很糟糕的经济体中，人们的价值是什么。

AI could have been something as a complement to humans, something that could challenge us and help us, but instead, as is the Law of Slopnomics, it’s turned into a way to make hot girls and more work and more noise and more more more more more but all of this, theoretically, is for US.

人工智能本来可以作为人类的补充，可以挑战我们并帮助我们，但相反，正如懒惰经济学定律一样，它变成了一种让辣妹、更多工作、更多噪音以及更多更多更多更多更多的方式，但从理论上讲，所有这一切都是为了美国。

So why isn’t it centered on us?

那么为什么它不以我们为中心呢？

Why is it marketed as the Job Destroyer and Human Killer 1000 Bot when it could be so different?

为什么它在市场上被称为“工作毁灭者”和“人类杀手 1000 机器人”，而它可能有如此大的不同？

(we all know why, but you know, why?) And for the stuff it’s touching, does it actually work?

（我们都知道为什么，但你知道为什么吗？）对于它所触及的东西，它真的有效吗？

As Greg Ip writes, two doctoral students at Harvard found “AI’s boost to projects was small and statistically insignificant.” The reason was “users were spending much more time reviewing, commenting on, and changing pull requests.”

正如格雷格·叶（Greg Ip）所写，哈佛大学的两名博士生发现“人工智能对项目的推动很小，而且在统计上微不足道。”原因是“用户花费了更多的时间来审查、评论和更改拉取请求。”

Take healthcare.

以医疗保健为例。

AI is also making healthcare more expensive, at least according to insurers.

至少保险公司认为，人工智能还使医疗保健变得更加昂贵。

The Blue Cross Blue Shield Association says hospitals’ use of AI was responsible for about $1 billion in additional costs for its companies over the last two years.

蓝十字蓝盾协会表示，过去两年，医院对人工智能的使用为其公司带来了约 10 亿美元的额外成本。

Using AI tools, hospitals collect more information about patients, which enables them to submit bigger claims.

使用人工智能工具，医院可以收集更多有关患者的信息，从而使他们能够提交更大的索赔。

By adding a secondary diagnosis for things like anemia, the hospitals were able to collect $12,000 more per case (the insurers are one side of the fight here, so take it with a grain of salt).

通过对贫血等疾病进行二次诊断，医院可以为每个病例多收取 12,000 美元（保险公司是这场斗争的一方，所以对此持保留态度）。

Benefit costs could go up by more than 11% for employers next year.

明年雇主的福利成本可能会上涨 11% 以上。

When asked if the technology will save money, one economist said that “a huge share of cost” will be freed up by, as the NYT writes , “replacing the people that handle claims processing.” Another person described where this goes: “it’s bots fighting bots, agents fighting agents, a horrible dystopic future nobody wants to live in.” And another man summarized it well - “I don’t think there is anything intrinsically different in A.I.

当被问及这项技术是否会节省资金时，一位经济学家表示，正如《纽约时报》所写，“取代负责索赔处理的人员”将节省“很大一部分成本”。另一个人描述了这一切的发展方向：“这是机器人与机器人的战斗，特工与特工的战斗，这是一个没人愿意生活在的可怕的反乌托邦未来。”另一位男士总结得很好——“我不认为人工智能有什么本质上的不同。

that will escape the market forces.”

这将逃脱市场力量。”

OpenAI has dots now, that are a team, a bunch of dots (Dots are what OpenAI calls its new assistants that work around the clock, and soon you’ll be able to have a bunch of dots on demand).

OpenAI 现在有了点，这是一个团队，一堆点（Dots 是 OpenAI 所说的全天候工作的新助手，很快你就可以按需拥有一堆点）。

The AI assistant land is going to get increasingly crowded as the companies try to spur up more and more demand for their products.

随着各公司试图刺激对其产品越来越多的需求，人工智能助手领域将变得越来越拥挤。

They will read your mind.

他们会读懂你的想法。

The magic of dots is when they bring you work done the way you would do it, sometimes before you even think to ask.

点的魔力在于它们让你按照你想要的方式完成工作，有时甚至在你想到提出要求之前就完成了。

With dots alongside you, ambitious ideas and projects you haven’t had the time or support to pursue start to feel achievable.

伴随着点点滴滴，那些你没有时间或支持去追求的雄心勃勃的想法和项目开始感觉可以实现。

And this seems to be the future?

这似乎就是未来？

Little guys doing little tasks for everyone?

小家伙为每个人做小任务？

I think this is plausible but it could crater the parts of our economy that rely on an enormous amount of friction.

我认为这是有道理的，但它可能会破坏我们经济中依赖大量摩擦的部分。

Torsten Slok at Apollo pointed out that the average checking account pays about a tenth of a percent, and you can clearly get a higher rate elsewhere.

Apollo 的 Torsten Slok 指出，支票账户的平均利率约为十分之一，而且你显然可以在其他地方获得更高的利率。

The business model of a bank is essentially predicated on most people never bothering to move their money to somewhere they can make a little more money.

银行的商业模式本质上是基于大多数人从不费心将钱转移到可以赚更多钱的地方。

If everyone’s AI assistant moved their money out, he wrote, that “would be a problem for the entire financial system.”

他写道，如果每个人的人工智能助手都将资金转移出去，“这将给整个金融体系带来问题”。

There are good parts to this.

这其中有好的部分。

Patrick Collison, who runs Stripe looks at it and sees good news.

Stripe 的运营者帕特里克·科里森 (Patrick Collison) 看到了好消息。

Companies have always made money off people not paying attention, he says.

他说，公司总是从人们不注意的情况下赚钱。

Today, “people who forget to cancel subscriptions subsidize those who don’t.” If your AI assistant never forgets to cancel anything, ever, the companies will have to start competing with a better product.

如今，“忘记取消订阅的人会为那些没有取消订阅的人提供补贴。”如果你的人工智能助手永远不会忘记取消任何事情，那么公司将不得不开始与更好的产品竞争。

This all “hinges on the assumption that personal agents will be on the consumer’s side.” So the same situation, from two different angles.

这一切“都取决于个人代理人将站在消费者一边的假设。”所以同样的情况，从两个不同的角度来看。

Jamie Dimon said that JPMorgan is “not going to allow just any outside agent to come in.” So the banks see this too.

杰米·戴蒙 (Jamie Dimon) 表示，摩根大通“不会允许任何外部代理人介入”。所以银行也看到了这一点。

But these AI assistants pollute the commons for individual gains.

但这些人工智能助手为了个人利益而污染公共资源。

It creates negative externalities for the humans that don’t have a bot to manage the pounding requests of an AI agent.

它给没有机器人来管理人工智能代理的冲击请求的人类带来了负面的外部性。

One person posted that her restaurant team scrambled to fill a client’s last minute requests, and she realized the requests “were likely made by an AI agent and that the human client might not have personally cared.

一个人发帖称，她的餐厅团队忙于满足客户最后一刻的请求，她意识到这些请求“很可能是由人工智能代理提出的，而人类客户可能并不关心。

This felt bad!” One man’s AI assistant asked Resy for a table about 200 times an hour, until Resy s hut down his account.

这感觉很糟糕！”一名男子的人工智能助理每小时向 Resy 索要一张桌子大约 200 次，直到 Resy 关闭了他的账户。

Going back to the worker, the human ecosystem, the people underlying the technology who often do not get credited or paid (especially in the case of the models getting trained on stolen work), there is a big worry that AI is going to make us dumb.

回到工人、人类生态系统、技术背后的人们，他们经常得不到认可或报酬（特别是在模型接受窃取工作的训练的情况下），人们非常担心人工智能会让我们变得愚蠢。

One of the worst case scenarios here is that everyone uses AI to get stuff done but forgets how to do stuff.

最糟糕的情况之一是每个人都使用人工智能来完成工作，但忘记了如何做事情。

It’s not good enough to replace people entirely, but it makes people “meat proxies” by any other name, a vessel for technology rather than humanity.

它不足以完全取代人类，但它使人们以任何其他名字成为“肉类代理人”，成为技术而不是人类的容器。

We see this happening in a microcosm at MIT , where study groups are disappearing and students are using AI on problem sets and are losing confidence.

我们看到这种情况发生在麻省理工学院的一个缩影中，那里的学习小组正在消失，学生们在问题集上使用人工智能并失去了信心。

Students worry about overreliance and losing themselves in the machines.

学生们担心过度依赖机器并迷失自己。

In response, MIT is starting to do more oral exams and semester portfolios and in-classroom work in order to rethink education during this time of enormous change.

作为回应，麻省理工学院开始进行更多的口试、学期作品集和课堂作业，以便在这个巨大变革的时期重新思考教育。

They encourage people to think beyond dollars and cents, that people are sometimes more important than output, and that “however sociable or responsive AI systems become, they cannot substitute for the relationships and practices necessary to grow and mature as a human being.” Their posture is not anti-AI, but rather towards figuring out how to “provide students with appropriate AI learning experiences from the time they arrive at MIT through graduation” in the service of the “betterment of humankind.”

他们鼓励人们超越美元和美分进行思考，认为人有时比产出更重要，并且“无论人工智能系统变得多么社交或反应灵敏，它们都无法取代作为人类成长和成熟所必需的关系和实践。”他们的立场并不是反对人工智能，而是想弄清楚如何“为学生从进入麻省理工学院到毕业提供适当的人工智能学习体验”，以服务于“人类的进步”。

There is a name for that spark!

那火花有一个名字！

Tyler Cowen recently wrote about Polanyi knowledge, which is “knowledge of time and place, inarticulable knowledge, custom and habit, and many other particularities.” Contextual knowledge, human knowledge, or as Michael Polanyi describes it, “ we know more than we can tell.” Cowen says there is no way to “bring an AI into your office and have it figure out how that office works.”

泰勒·考恩（Tyler Cowen）最近写了一篇关于波兰尼知识的文章，它是“关于时间和地点的知识、难以言喻的知识、习俗和习惯，以及许多其他特殊性”。情境知识，人类知识，或者正如迈克尔波兰尼所描述的那样，“我们知道的比我们能说的还要多。”考恩表示，没有办法“将人工智能带入你的办公室并让它弄清楚办公室是如何运作的”。

And what are these market forces pointing us to?

这些市场力量向我们指出了什么？

And how have we responded to them in the past?

我们过去是如何回应他们的？

Thomas Pynchon wrote an essay in 1984 (of course) titled Is It O.K.

托马斯·品钦 (Thomas Pynchon) 在 1984 年（当然）写了一篇题为“Is It OK”的文章。

To Be A Luddite?

成为勒德分子？

In it, he talks about the push and pull between literature and science, that we have enormous flows of data encircling us at any time (reminding us that time itself is a loop), that anything and everything is at the tip of our fingers.

在其中，他谈到了文学与科学之间的推拉关系，我们随时都有巨大的数据流围绕着我们（提醒我们时间本身就是一个循环），一切都在我们的指尖。

He walks through the history of those that fought back against technology, known as the Luddites, often confused as those who hated progress but really, were fighting back against “the machines coming more and more to be the property of men who did not work, only owned and hired” and the “concentration of capital each machine represented” alongside “the ability of each machine to put a certain number of humans out of work - to be “worth” that many human souls.” The Luddites did not hate technology.

他回顾了那些反抗技术的人的历史，这些人被称为“勒德分子”，他们常常被误认为是那些讨厌进步的人，但实际上，他们是在反抗“机器越来越成为那些不工作、只拥有和雇佣的人的财产”，以及“每台机器所代表的资本集中度”以及“每台机器让一定数量的人失业的能力——“值得”那么多人类的灵魂。”勒德分子并不讨厌技术。

They hated what it was doing to their lives.

他们讨厌这对他们的生活造成的影响。

They did not hate the product, they hated the application, and the inequality that festered as a result.

他们并不讨厌产品，而是讨厌应用程序，以及由此加剧的不平等。

Towards the end of the piece, Pynchon wonders about the future.

在作品的结尾，品钦对​​未来感到好奇。

That perhaps the computer will do good.

也许计算机会有好处。

That it will “cure cancer, save ourselves from nuclear extinction, grow food for everybody, detoxify the results of industrial greed gone berserk - realize all the wistful pipe dreams of our days.” He mentions the challenge of the convergence of “artificial intelligence, molecular biology, and robotics” by name.

它将“治愈癌症，使我们免于核灭绝，为每个人种植粮食，消除工业贪婪的疯狂结果——实现我们这个时代所有渴望的白日梦。”他点名提到了“人工智能、分子生物学和机器人技术”融合所面临的挑战。

He ends with Byron’s lines for King Ludd, an acknowledgement of the problems present and the problems to come.

他以拜伦写给路德王的台词作为结尾，承认当前的问题和未来的问题。

And today, we are having the same conversation that he had over 40 years ago.

今天，我们正在进行与他 40 多年前相同的对话。

We will likely have it in another 40 years.

再过 40 年我们可能就会拥有它。

There is always going to be a tense relationship between humans and machines, because the makers of the machines want to make enormous profits.

人与机器之间总是存在着紧张的关系，因为机器的制造者想要赚取巨额利润。

Enormous profits require paying no people for anything, just selling the products, seemingly to other makers of machines, who also seek enormous profits.

巨额利润要求不向任何人支付任何费用，只需将产品出售给其他同样寻求巨额利润的机器制造商。

But who funds the makers, at the end of the day?

但归根结底，谁为制造商提供资金？

Who is truly the bed rock of the economy?

谁才是真正经济的基石？

The human souls, as Pynchon posits: the ones who put in the work to make each component of the machines possible.

正如品钦所假设的那样，人类的灵魂：那些付出努力使机器的每个组件成为可能的人。

Those human souls do not hate technology, they hate what technology is doing to them.

这些人类灵魂并不讨厌技术，他们讨厌技术对他们所做的事情。

But growth at any cost, whoever wins, does not allow for the foresight to examine “a human soul.” As Pynchon wrote, “to insist on the miraculous is to deny to the machine at least some of its claims on us.”

但无论谁获胜，不惜一切代价的增长，都不允许有远见来审视“人类的灵魂”。正如品钦所写，“坚持奇迹就是否认机器至少对我们的一些要求。”

What kind of growth, and to what end?

什么样的增长，达到什么目的？

An AI data centre in a hollowed-out post-industrial community might provide 30-odd jobs and create numerical growth on a Treasury spreadsheet but does it materially address the lack of meaning, purpose or agency many feel in their lives?

空心化的后工业社区中的人工智能数据中心可能会提供 30 多个就业机会，并在财政部电子表格上创造数字增长，但它是否能实质性地解决许多人感到生活中缺乏意义、目的或机构的问题？

Pope Leo has also pointed this out , how at risk we are of losing humanity within this technology (in a tweet!):

教皇利奥也指出了这一点，我们在这项技术中失去人性的风险有多大（在一条推文中！）：

In this era of artificial intelligence, it is becoming urgent to distinguish human art from what machines produce.

在这个人工智能时代，区分人类艺术和机器创作变得越来越紧迫。

There is an ontological difference, even before an aesthetic one, between art and what a machine can generate through statistical calculation based on millions of images created by others.

艺术与机器通过基于他人创建的数百万图像的统计计算所生成的东西之间存在本体论差异，甚至在美学差异之前就存在。

Algorithms lack the spark of humanity.

算法缺乏人性的火花。

For this reason, the Church wishes to renew an alliance with artists and cultural institutions to safeguard our humanity.

因此，教会希望与艺术家和文化机构重新结盟，以维护我们的人性。

That’s the thing that gets lost inside the triangle.

这就是三角形内丢失的东西。

The things that can’t be priced, at least yet now, perhaps not ever.

那些无法定价的东西，至少现在是这样，或许永远都不会。

People will try their best to commoditize that which cannot be sold, that which cannot be automated into bytes and bits, and perhaps, they will be successful, or perhaps, we will stop and ask what we are doing this all for.

人们会尽最大努力将无法出售的东西商品化，将无法自动化的东西商品化为字节和比特，也许他们会成功，或者也许我们会停下来问我们所做的这一切是为了什么。

The slot machine from Vegas haunts me.

维加斯的老虎机一直困扰着我。

It’s a metaphor for where we are.

这是我们所处位置的隐喻。

Most people in the economy are putting in the work – paying higher prices, taking on higher interest rates – but the jackpot isn’t for them.

经济中的大多数人都在投入工作——支付更高的价格，承担更高的利率——但头奖并不适合他们。

Wealth instead sits inside a self-referential loop, where hyperscalers borrow billions to buy chips from chipmakers, inflating stocks and GDP, while consumers report that they are near rock bottom.

相反，财富处于一个自我参照的循环中，超大规模企业借入数十亿美元从芯片制造商那里购买芯片，导致股市和 GDP 膨胀，而消费者则报告称他们已接近谷底。

And who should be winning?

谁应该获胜？

In the old, imperfect math of the American dream, the answer was supposed to be people .

在美国梦的古老而不完美的数学中，答案应该是人。

James Truslow Adams, the original American Dreamer , described it not as “a dream of motor cars and high wages merely” but more as people being able to become the fullest version of themselves, where each person can reach “the fullest stature of which they are innately capable, and be recognized by others for what they are.”

最早的美国梦想家詹姆斯·特鲁斯洛·亚当斯将其描述为“不仅仅是汽车和高工资的梦想”，而更多的是人们能够成为最完整的自己，每个人都可以达到“他们与生俱来的最充分的地位，并得到他人的认可”。

The promise wasn’t that everyone would have ten yachts, but it was a promise that if you worked hard, you’d get an honest shake at it all.

这个承诺并不是每个人都会拥有十艘游艇，而是一个承诺，如果你努力工作，你就会得到诚实的回报。

A home maybe, some savings, dignity, space to help your kids, our next generation, grow up to be better than we are today.

也许是一个家，一些储蓄，尊严，空间来帮助你的孩子，我们的下一代，成长为比今天更好的人。

I kept running into that all week.

我整个星期都不断遇到这个问题。

The point of the Chicago Fed panel was to talk about why it matters how people feel about the economy.

芝加哥联储小组的目的是讨论为什么人们对经济的看法很重要。

We often write off these feelings saying “well they’re still spending so can’t be feeling that bad!” We conflate money and happiness so often, spending with contentment.

我们经常忽略这些感受，说“好吧，他们还在花钱，所以感觉不会那么糟糕！”我们常常把金钱和幸福混为一谈，心满意足地花钱。

We throw pennies into the fountain to try and beget some luck, a donation to some unknown figure, somewhere, money in exchange for happiness.

我们把硬币扔进喷泉里，试图获得一些运气，向某个地方的某个不知名的人物捐款，用金钱换取幸福。

I’ve been rereading Annie Dillard’s work, and Wendell Berry’s, mourning them and the prose we often sacrifice for efficiency.

我一直在重读安妮·迪拉德和温德尔·贝瑞的作品，哀悼他们以及我们经常为了效率而牺牲的散文。

Writing is similar to the way a person is constructed.

写作类似于一个人的构造方式。

You have the bones of the piece and you have the connective tissue between paragraphs, and somewhere in there, you should have a heart.

你有整篇文章的骨架，有段落之间的结缔组织，在其中的某个地方，你应该有一颗心。

The thing we try to protect most in writing is a heart, the thing we try to protect most in each other should be our heart.

我们在文字中最想守护的是一颗心，我们在彼此身上最想守护的应该是我们的心。

Annie Dillard, writing about a total eclipse said the same thing in a different way:

安妮·迪拉德（Annie Dillard）在一篇关于日全食的文章中用不同的方式说了同样的事情：

Significant as it was, it did not matter a whit.

尽管它很重要，但一点也不重要。

For what is significance?

有何意义？

It is significance for people.

对于人们来说是有重要意义的。

No people, no significance.

没有人，就没有意义。

This is all I have to tell you.

这就是我要告诉你的一切。

And I think that is the question that we don’t really know how to answer with AI.

我认为这是我们真正不知道如何用人工智能回答的问题。

Is the end goal here just…

这里的最终目标只是……

agents talking to agents and 8 billion people on some form of UBI?

特工与特工和 80 亿人就某种形式的 UBI 进行对话？

Or will this article sound foreign and far away to those perhaps 5 years or 100 years into the future to people, living in a renovated data center, that have a brain chip that holds a file titled “2020s: What Various Word Engineers Of Yesteryear Got Wrong About the Today” that contains these here words?

或者，对于 5 年或 100 年后的人们来说，这篇文章听起来是否陌生、遥远？生活在翻新的数据中心中，他们的大脑芯片中保存着一个名为“2020 年代：过去的各种单词工程师对今天的错误”的文件，其中包含这些单词？

Are we ushering in a utopia?

我们正在迎来一个乌托邦吗？

Or will it be a slow and arduous future, where not much changes but where things get better and better, but slowly, and often not before they get worse?

或者这会是一个缓慢而艰巨的未来，没有太大变化，但情况会变得越来越好，但缓慢，而且往往不是在变得更糟之前？

A cab driver in Vegas started asking me what I thought about AI, and as we were driving, a Zoox scooted by, lights twinkling.

维加斯的一位出租车司机开始问我对人工智能的看法，当我们开车时，一辆 Zoox 疾驰而过，灯光闪烁。

My driver was retired, driving because he was bored and wanted some cash, and he scoffed at the Zoox.

我的司机退休了，开车是因为他很无聊，想要一些现金，他对 Zoox 嗤之以鼻。

“I can’t stand those things,” he said.

“我无法忍受这些事情，”他说。

I asked him if it’s impacted his driving.

我问他这是否影响他的驾驶。

“Of course,” he said.

“当然，”他说。

How did he handle it?

他是怎么处理的？

“I mostly handle it by being a better person.

“我主要通过成为一个更好的人来处理这件事。

That’s my hope, I guess.

我想这就是我的希望。

That by being a good person, people will keep wanting to be around people.”

通过做一个好人，人们会一直想要与人相处。”

This is a reader-supported publication.

这是一本由读者支持的出版物。

To receive new posts and support my work, consider becoming a free or paid subscriber.

要接收新帖子并支持我的工作，请考虑成为免费或付费订阅者。

Joanne Hsu, who runs the Michigan survey, summarized it all so well – sentiment is one person, one vote.

负责密歇根州调查的乔安妮·许 (Joanne Hsu) 总结得很好——情绪就是一个人一票。

The data is dollar-weighted, and dollars are clearly doing fine.

该数据是按美元加权的，美元显然表现良好。

But the people behind some of them are not doing so fine.

但其中一些背后的人却做得不太好。

I don’t think I share his same optimism , but I do share the concerns

我不认为我和他一样乐观，但我确实有同样的担忧

To be fair, the buyers are still buying.

公平地说，买家仍在购买。

When the government borrows money, it holds an auction, and investors bid for the chance to lend to it.

当政府借钱时，它会举行拍卖，投资者竞标以获取贷款给它的机会。

A few weeks ago, the government sold $39 billion of 10-year debt, and had nearly 3x as many bids as it needed.

几周前，政府出售了 390 亿美元的 10 年期债券，投标数量几乎是所需数量的 3 倍。

They’ll buy it, especially if they get over 5%!

他们会买的，尤其是当他们获得超过 5% 的收益时！

China has the opposite problem.

中国则面临着相反的问题。

The Financial Times went to Ulanqab, a city in Inner Mongolia, with 89 data centers built or planned, one of them going into an abandoned high school (a bit on the nose).

英国《金融时报》前往内蒙古乌兰察布市，那里已建成或规划了 89 个数据中心，其中一个数据中心建在一所废弃的高中（有点近）。

Electricity in that area costs about half of what it does in Beijing, and China can put a data center up in 12 to 18 months, against the 18 to 24 we have in the US.

该地区的电费约为北京的一半，而且中国可以在 12 至 18 个月内建成一个数据中心，而美国则需要 18 至 24 个月。

What it can’t get is enough chips to fill them, because the best ones are American and Washington restricts how much can be sold to China.

它无法获得足够的芯片来填补它们，因为最好的芯片是美国的，而华盛顿限制了可以向中国出售的数量。

So America has the chips and is short on power.

所以美国有筹码，但缺实力。

China has the power and is short on chips.

中国有实力，但缺芯片。

As Bloomberg noted, “If Oracle powered just 100 megawatts — about 4% of its ultimate 2.45-gigawatt footprint — with CNG deliveries, each large trailer would only provide about 40 minutes of electricity”

正如彭博社指出的那样，“如果 Oracle 通过 CNG 输送仅提供 100 兆瓦的电力（约占其最终 2.45 吉瓦足迹的 4%），那么每辆大型拖车只能提供约 40 分钟的电力”

Capexistential crisis, scamingularity, debtacenters, luddite…

资本存在危机、诈骗、债务中心、勒德分子……

you were on a roll there

你在那里很开心

Firstly, everything you produce is worthy of our time and attention.

首先，你创造的一切都值得我们花时间和关注。

Secondly I can’t help but draw a parallel to the amount of money being borrowed by companies and governments to the amount of credit card debt that consumers carry.

其次，我忍不住将公司和政府借入的资金数额与消费者承担的信用卡债务数额进行类比。

It seems everyone needs massive amounts of credit to function in today’s economy.

似乎每个人都需要大量信贷才能在当今的经济中发挥作用。

Don’t get me wrong, I believe that credit is good and necessary to stimulate growth and fund new businesses.

不要误会我的意思，我相信信贷是好的，而且对于刺激增长和为新业务提供资金是必要的。

Is there any chance that the government will ever pay down the nation debt or does the increasingly expanding interest on that debt become just the cost of doing business?

政府是否有机会偿还国家债务，或者债务利息的不断增加是否只是做生意的成本？