Amen. AI boosters look at currently high profit margins on inference and blindly accept claims that these inference profit margins will continue. Of course those margins depend on historically massive R&D spend on training. The moment that training stops, AI returns to a commodity market and the inference profits end. Big labs are trying as hard as possible to keep the gravy train running but they can all see it won't last forever, hence the rush for IPO & regulating away open models.
Boosters are right that AI is a historically impactful product, but big labs will be unable to meaningfully profit from ushering in the AI era just like Netscape failed despite ushering in the internet era.
>AI boosters look at currently high profit margins on inference
Name a company with a currently high profit margin on inference. I can't.
OpenAI and Anthropic's valuations are as high as they are because investors hope that they will create AI that is much much more powerful than the AI they have now. The fact that they already have a substantial revenue stream helps, but it helps mainly by lending credibility to the hope that they might create something much much more powerful.
(You, Mike and I agree that selling the inference of models that are not much better than liberally-licensed open-weights models will be a low-margin business.)