I see this so much. "This shouldn't work, therefore it won't work." It's like the world is imagined to run on a moral causal framework rather than uncaring quantum mechanics.

I have watched many of his screeds; I think he undercuts his thesis with excess bile.

His core observation is that the unit economics of openAI and anthropic don't actually yield enough profit to pay off the huge debts that these two companies have incurred, and that as a result all the debt they've taken on will have to be written off which will trigger "the hyperscalers" to themselves suffer huge losses (likely wounding google and microsoft and destroying oracle).

He is rather more negative about the utility of LLMs than lots of other people (myself included); but his overall view of

  1. they're not completely trustworthy
  2. they're really expensive to train
  3. it isn't obvious that anyone's willing to pay the full freight for the resulting product
  4. lots of large orgs "that should know better" have gone far down the LLM "AI" road because they're looking for "the next big thing" when they should be pivoting to "mature, stable" companies instead of "hypergrowth" companies.
  5. there's lots of debt and obligations and no obvious way for all of it to be paid off from revenues from openai / anthropic.

seems pretty reasonable. There seem to have been lots of bets placed on the hope that this stuff will continue scaling as it has in the past, if it is given more compute and data, and that bet is one that has yet to have demonstrated itself as correct.

Elsewhere, people have pointed out that many of the "FAANG" companies have shed lots of people and driven lots of profits, largely on the back of internal use of LLM tools. That doesn't necessarily contradict the skepticism that anthropic and openAI will succeed, and given all their obligations, if they fail it'll be a big mess.

But again, big Z doesn't do himself any favors when he rants about "failsons" or whatever.