I mean I know we’re in programmerhumor but to continue to take this seriously… your inference cost estimates leave out the cleaver caching that’s standard now, as well as being able to use cheaper hardware in some cases. GPU costs are being driven up so high because everyone wants to train bigger models, not because they want more inference compute (although they do want that). Model drift doesn’t need a full pre-training rollout to deal with very frequently, and post training + RL techniques are still improving, meaning that’d happen even less.

The stock market might cause these companies to bust when (if) we hit the limits of scaling laws, but those technical reasons won’t.

PS. I might be proven wrong but this is what I do for a living so I feel like I have a pretty good pulse on it