I edited while you were responding with second para. I think his analysis that existing investors are walking corpses (or economically exhausted/weakened) is substantial. You have new companies going into extreme debt and established companies burning war chests may actually is important, and also valid economic argument ESPECIALLY if you think think AI will be economically transformative. Like current players basically spent $1000 on a screw driver to do $10 of work. Some of them went $1000 into debt, some of them drained $1000, which is much of their savings/warchest. The incumbant players rationalize future has $100 or $1000, or of work, but these companies are going to be vs player buying $1 screw drivers, i.e. the compute deprecation curve makes spending $1000 on screwdrivers in the first place very detrimental/terminal vs future competition. Zitrons argument is broadly there even if there is $1000000 work in the future, companies that spend $1000 on screw drivers balance sheet is working on timescale where there is $100 of work, i.e. the economics is not in favor of incumbents. The economics might still be very favorite for future AI... but not for first round of players who has to recover from grossly overpaying.

He makes very specific predictions about specific companies and they are wrong.

You think we are in a bubble and that AI won't pay off for the companies investing in it.

While I'm sure there will be companies that invest badly the problem with your prediction is that the public hyperscalers (Google, Amazon and MS especially) are already seeing returns from their AI investments.

Look at the revenue growth - that is actual dollars coming through the door.

Here's an exercise you should consider doing: instead of your $1000/$10 numbers, use real numbers for the major software companies investing heavily in AI.