While I completely agree with your take, I think everyone has been surprised by how quickly LLMs have become highly useful and extremely powerful, and by how possible it is for relatively smaller models to also be highly useful.
Given that, I would expect that in hindsight OpenAI and Anthropic would spend 40% of what they have on compute if starting over and knowing the actual landscape.
The massive capital allocation was a blind decision and they swung big.
It is still possible that techniques will be developed that create a moat where the massive hardware capex is justified, but US policies of banning competitive GPUs and blocking frontier lab releases makes such things far less likely.
"Escape velocity" for AI is when the open weight models are good enough to help drive the next frontier innovations/techniques. I think we are close to that if not already there, at which point it's a race to commoditization no matter what Altman or Lutnik wish will happen.
Don’t forget it took that huge spend to publish the papers and get to the models we have. It’s not obvious that without them we’d have LLMs springing up out of China or anywhere else.
And the published and non-published works of mankind but no one seems to want to give us any credit.
Perhaps, but things like Sora burned a lot of compute -- a high percentage.