The GenAI bubble is going to pop. Everyone knows that. To me, the urgent and interesting questions are how widespread the damage will be and what the hangover will feel like. On that basis, I was going to post a link on Mastodon to Paul Krugman’s Talking With Paul Kedrosky. It’s great, but while I was reading it I thought “This is going to be Greek to people who haven’t been watching the bubble details.” So consider this a preface to the Krugman-Kedrosky piece. If you already know about the GPU-fragility and SPV-voodoo issues, just skip this and go read that.

Depreciation · When companies buy expensive stuff, for accounting purposes they pretend they haven’t spent the money; instead they “depreciate” it over a few years. That is to say, if you spent a million bucks on a piece of gear and decided to depreciate it over four years, your annual financials would show four annual charges of $250K. Management gets to pick your depreciation period, which provides a major opening for creative accounting when the boss wants to make things look better or worse than they are.

Even when you’re perfectly honest it can be hard to choose a fair figure. I can remember one of the big cloud vendors announcing they were going to change their fleet depreciation from three to four years and that having an impact on their share price.

Depreciation is orderly whether or not it matches reality: anyone who runs a data center can tell you about racks with 20 systems in them that have been running fine since 2012. Still, orderly is good.

In the world of LLMs, depreciation is different. When you’re doing huge model-building tasks, you’re running those expensive GPUs flat out and red hot for days on end. Apparently they don’t like that, and flame out way more often than conventional computer equipment. Nobody who is doing this is willing to come clean with hard numbers but there are data points, for example from Meta and (very unofficially) Google.

So GPUs are apparently fragile. And they are expensive to run because they require huge amounts of electricity. More, in fact, than we currently have, which is why electrical bills are spiking here and there around the world.

Why does this matter? Because when the 19th-century railway bubble burst, we were left with railways. When the early-electrification bubble built, we were left with the grid. And when the dot-com bubble burst, we were left with a lot of valuable infrastructure whose cost was sunk, in particular dark fibre. The AI bubble? Not so much; What with GPU burnout and power charges, the infrastructure is going to be expensive to keep running, not something that new classes of application can pick up and use on the cheap.

Which suggests that the post-bubble hangover will have few bright spots.

SPVs · This is a set of purely financial issues but I think they’re at the center of the story.

It’s like this. The Big-Tech giants are insanely profitable but they don’t have enough money lying around to build the hundreds of billions of dollars worth of data centers the AI prophets say we’re going to need. Which shouldn’t be a problem; investors would line up to lend them as much as they want, because they’re pretty sure they’re going to get it back, plus interest.

But apparently they don’t want to borrow the money and have the debts on their balance sheet. So they’re setting up “Special Purpose Vehicles”, synthetic companies that are going to build and own the data centers; the Big Techs promise to pay to use them, whether or not genAI pans out and whether or not the data centers become operational. Somehow, this doesn’t count as “debt”.

The financial voodoo runs deep here. I recommend Matt Levine’s Coffee pod financing and the Financial Times’ A closer look at the record-smashing ‘Hyperion’ corporate bond sale. Levine’s explanation has less jargon and is hilarious; the FT is more technical but still likely to provoke horrified eye-rolls.

If you think there’s a distinct odor of 2008 around all this, you’d be right.

If the genAI fanpholks are right, all the debt-only-don’t-call-it-that will be covered by profits and everyone can sleep sound. Only it won’t. Thus, either the debts will apply a meat-axe to Big Tech profits, or (like 2008) somehow they won’t be paid back. If whoever’s going to bite the dust is “too big to fail”, the money has to come from… somewhere? Taxpayers? Pension funds? Insurance companies?

Paul K and Paul K · I think I’ve set that piece up enough now. It points out a few other issues that I think people should care about. I have one criticism: They argue that genAI won’t produce sufficient revenue from consumers to pay back the current investment frenzy. I mean, they’re right, it won’t, but that’s not what the investors are buying. They’re buying the promise, not of more revenue, but of higher profits that happen when tens of millions of knowledge workers are replaced by (presumably-cheaper) genAI.

I wonder who, after the loss of those tens of millions of high-paid jobs, are going to be the consumers who’ll buy the goods that’ll drive the profits that’ll pay back the investors. But that problem is kind of intrinsic to Late-stage Capitalism.

Anyhow, there will be a crash and a hangover. I think the people telling us that genAI is the future and we must pay it fealty richly deserve their impending financial wipe-out. But still, I hope the hangover is less terrible than I think it will be.