If you'd like an essay-formatted version of this thread to read or share, here's a link to it on pluralistic.net, my surveillance-free, ad-free, tracker-free blog:

pluralistic.net/2025/09/27/eco…

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A week ago, I turned that book into a speech, which I delivered as the annual Nordlander Memorial Lecture at Cornell, where I'm an AD White Professor-at-Large.

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This was my first-ever speech about AI and I wasn't sure how it would go over, but thankfully, it went great and sparked a lively Q&A.

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One of those questions came from a young man who said something like "So, you're saying a third of the stock market is tied up in seven AI companies that have no way to become profitable and that this is a bubble that's going to burst and take the whole economy with it?"

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I said, "Yes, that's right."

He said, "OK, but what can we do about that?"

So I re-iterated the book's thesis: that the AI bubble is driven by monopolists who've conquered their markets and have no more growth potential.

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They are desperate to convince investors that they can continue to grow by moving into some other sector, e.g. "pivot to video," crypto, blockchain, NFTs, AI, and now "super-intelligence."

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Further: the topline growth that AI companies are selling comes from replacing most workers with AI, and re-tasking the surviving workers as AI babysitters ("humans in the loop"), which won't work.

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Finally: AI *cannot* do your job, but an AI salesman can *100%* convince your boss to fire you and replace you with an AI that *can't* do your job, and when the bubble bursts, the money-hemorrhaging "foundation models" will be shut off.

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Then we'll lose the AI that can't do your job, *and* you will be long gone, retrained or retired or "discouraged" and out of the labor market, and *no one* will do your job.

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AI is the asbestos we are shoveling into the walls of our society and our descendants will be digging it out for generations:

pluralistic.net/2025/05/27/ran…

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The only thing (I said) that we can do about this is to puncture the AI bubble *as soon as possible*, to halt this before it progresses any further and to head off the accumulation of social and economic debt.

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To do that, we have to take aim at the *material basis* for the AI bubble (creating a growth story by claiming that defective AI can do your job).

"OK," the young man said, "but what can we *do* about the crash?" He was clearly very worried.

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"I don't think there's anything we can do about that. I think it's already locked in. I mean, maybe if we had a different government, they'd fund a jobs guarantee to pull us out of it, but I don't think Trump'll do that, so --"

"But what can we *do?*"

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We went through a few rounds of this, with this poor kid just repeating the same question in different tones of voice, like an acting coach demonstrating the five stages of grieving using nothing but inflection.

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It was an uncomfortable moment, and there was some decidedly nervous chuckling around the room as we pondered the coming AI (economic) apocalypse, and the fate of this kid graduating with mid-six-figure debts into an economy of ashes and rubble.

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I firmly believe the (economic) AI apocalypse is coming. These companies are not profitable. They can't be profitable. They keep the lights on by soaking up hundreds of billions of dollars in other people's money and then lighting it on fire.

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Eventually those other people are going to want to see a return on their investment, and when they don't get it, they will halt the flow of billions of dollars. Anything that can't go on forever eventually stops.

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This isn't like the early days of the web, or Amazon, or any of those other big winners that lost money before becoming profitable.

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Those were all propositions with excellent "unit economics" - they got cheaper with every successive technological generation, and the more customers they added, the more profitable they became.

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AI companies have - in the memorable phraseology of Ed Zitron - "dogshit unit-economics." Each generation of AI has been vastly more expensive than the previous one, and each new AI customer makes the AI companies lose *more* money:

pluralistic.net/2025/06/30/acc…

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This week, no less than the *Wall Street Journal* published a lengthy, well-reported story (by Eliot Brown and Robbie Whelan) on the catastrophic finances of AI companies:

wsj.com/tech/ai/ai-bub…

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The *WSJ* writers compare the AI bubble to other bubbles, like Worldcom's fraud-soaked fiber optic bonanza (which saw the company's CEO sent to prison, where he eventually died), and conclude that the AI bubble is *vastly* larger than any other bubble in recent history.

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The data-center buildout has genuinely absurd finances - there are data-center companies that are collateralizing their loans by staking their giant Nvidia GPUs as collateral.

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This is wild: there's pretty much nothing (apart from fresh-caught fish) that loses its value faster than silicon chips.

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That goes *triple* for GPUs used in AI data-centers, where it's normal for tens of thousands of chips to burn out over a single, 54-day training run:

techblog.comsoc.org/2024/11/25/sup…

Talk about sweating your assets!

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That barely scratches the surface of the funny accounting in the AI bubble. Microsoft "invests" in Openai by giving the company free access to its servers.

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Openai reports this as a ten billion dollar investment, then redeems these "tokens" at Microsoft's data-centers. Microsoft then books this as ten billion in revenue.

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That's par for the course in AI, where it's normal for Nvidia to "invest" tens of billions in a data-center company, which then spends that investment buying Nvidia chips.

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The the same chunk of money being energetically passed back and forth between these closely related companies, all of which claim it as investment, as an asset, or as revenue (or all three).

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