Sep 7 JDN 2460926

Based on the fact that it only sort of works and yet corps immediately put it in everything, I had long suspected that the current wave of AI was a bubble. But after reading Ed Zitron’s epic takedowns of the entire industry, I am not only convinced it’s a bubble; I’m convinced it is probably the worst bubble we’ve had in a very long time. This isn’t the dot-com crash; it’s worse.

The similarity to the dot-com crash is clear, however: This a huge amount of hype over a new technology that genuinely could be a game-changer (the Internet certainly was!), but won’t be in the time horizon on which the most optimistic investors have assumed it will be. The gap between “it sort of works” and “it radically changes our economy” is… pretty large, actually. It’s not something you close in a few years.

The headline figure here is that based on current projections, US corporations will have spent $560 billion on capital expenditure, for anticipated revenue of only $35 billion.

They won’t pay it off for 16 years!? That kind of payoff rate would make sense for large-scale physical infrastructure, like a hydroelectric dam. It absolutely does not make sense in an industry that is dependent upon cutting-edge technology that wears out fast and becomes obsolete even faster. They must think that revenue is going to increase to something much higher, very soon.

The corps seem to be banking on the most optimistic view of AI: That it will soon—very soon—bring about a radical increase in productivity that brings GDP surging to new heights, or even a true Singularity where AI fundamentally changes the nature of human existence.

Given the kind of errors I’ve seen LLMs make when I tried to use them to find research papers or help me with tedious coding, this is definitely not what’s going to happen. Claude gives an impressive interview, and (with significant guidance and error-correction) it also managed pretty well at making some simple text-based games; but it often recommended papers to me that didn’t exist, and through further experimentation, I discovered that it could not write me a functional C++ GUI if its existence depended on it. Somewhere on the Internet I heard someone describe LLMs as answering not the question you asked directly, but the question, “What would a good answer to this question look like?” and that seems very accurate. It always gives an answer that looks valid—but not necessarily one that is valid.

AI will find some usefulness in certain industries, I’m sure; and maybe the next paradigm (or the one after that) will really, truly, effect a radical change on our society. (Right now the best thing to use LLMs for seems to be cheating at school—and it also seems to be the most common use. Not exactly the great breakthrough we were hoping for.) But LLMs are just not reliable enough to actually use for anything important, and sooner or later, most of the people using them are going to figure that out.

Of course, by the Efficient Roulette Hypothesis, it’s extremely difficult to predict exactly when a bubble will burst, and it could well be that NVIDIA stock will continue to grow at astronomical rates for several years yet—or it could be that the bubble bursts tomorrow and NVIDIA stock collapses, if not to worthless, then to far below its current price.

Krugman has an idea of what might be the point that bursts the bubble: Energy costs. There is a clear mismatch between the anticipated energy needs of these ever-growing data centers and the actual energy production we’ve been installing—especially now that Trump and his ilk have gutted subsidies for solar and wind power. That’s definitely something to watch out for.

But the really scary thing is that the AI bubble actually seems to be the only thing holding the US economy above water right now. It’s the reason why Trump’s terrible policies haven’t been as disastrous as economists predicted they would; our economy is being sustained by this enormous amount of capital investment.

US GDP is about $30 trillion right now, but $500 billion of that is just AI investment. That’s over 1.6%, and last quarter our annualized GDP growth rate was 3.3%—so roughly half of our GDP growth was just due to building more data centers that probably won’t even be profitable.

Between that, the tariffs, the loss of immigrants, and rising energy costs, a crashing AI bubble could bring down the whole stock market with it.

So I guess what I’m saying is: Don’t believe the AI hype, and you might want to sell some stocks.