There's certain figures he gives that paint the picture well enough without him having to really even make the argument. For example, in his piece "The More You Buy, The More You Lose"[1], a few paragraphs in, he says: "Hyperscalers will have sunk over $1.3 trillion dollars into generative AI by the end of 2026, and have plans to spend a trillion dollars more next year. On a very rational level, nothing that large language models (LLMs) have done, do or will do in the future can or will ever bring in the more than $2 trillion (or more) in brand new revenue that will be required to make any of this worth it."

He explains some more numbers in the following paragraphs (that aren't needed to make my point), but the problem isn't even that AI can't make any money, it's that the scale of the money spent is so colossal, what they would need to do to actually make it back is insane! They'd need to actually replace most of the workers in the world because that is such a ridiculous, unimaginable amount of money! It outclasses all of their combined revenue significantly, and remember, these companies don't tell us how much money they make from AI (anymore), they bundle it in with other things, and if it was good, you know they'd be shouting it from the rooftops how much they were making.

I also don't take seriously any of his predictions that have dates attached to them - after all, the market can remain irrational longer than you can remain solvent. I don't trust his timing, but the numbers don't lie.

[1] https://www.wheresyoured.at/the-more-you-buy-the-more-you-lo...