The AI bubble is 17 times the size of the dot-com frenzy — and four times the subprime bubble, analyst says
AI is not just in a bubble, but one 17 times the size of the dot-com bubble, and even four times bigger than the 2008 global real-estate bubble.
RE: Large language models: one study shows that the task-completion rate at a software company ranged from 1.5% to 34%, and even for the tasks that were completed 34%, that level of completion could not be consistently reached. Another chart, previously circulated by Apollo economist Torsten Slok based on Commerce Department data, showed the AI adoption rate at big companies now on the decline. He also showed some of his real-world tests, like asking an image maker to create a chessboard one move before white wins, which it didn’t come close to achieving.
LLMs, he argues, already are at the scaling limits. “We don’t know exactly when LLMs might hit diminishing returns hard, because we don’t have a measure of the statistical complexity of language. To find out whether we have hit a wall we have to watch the LLM developers. If they release a model that cost 10x more, likely using 20x more compute than the previous one, and it’s not much better than what’s out there, then we’ve hit a wall,” he says.
“So, in summary; you can’t create an app with commercial value as it is either generic (games etc), which won’t sell, or it is regurgitated public domain (homework), or it is subject to copyright. It’s hard to advertise effectively, LLMs cost an exponentially larger amount to train each generation, with a rapidly diminishing gain in accuracy. There’s no moat on a model, so there’s little pricing power. And the people who use LLMs the most are using them to access compute that costs the developer more to provide than their monthly subscriptions,” he says.
“The danger is not only that this pushes us into a zone 4 deflationary bust on our investment clock, but that it also makes it hard for the Fed and the Trump administration to stimulate the economy out of it. This means a much longer effort at reflation, a bit like what we saw in the early 1990s, after the S&L crisis, and likely special measures as well, as the Trump administration seeks to devalue the US$ in an effort to onshore jobs,” he says.
Conclusion: the economy is already at stall speed and will fall into recession as wealth effects plateau, then reverse, just as they did in the dot-com bubble in 2001.