Even so, that doesn’t take away from my point. Traditional specialized models can do these things already, for much cheaper and without expensive optimization. What traditional models cannot do is the toy aspect of LLM, and that is the only usecase I see for this technology going forward.

Lets say you are right and these things will be optimized, and in, say, 5 years, most models from the big players will be able do things like reading small text in an obscure image, draw a picture of a glass of wine filled to the brim, draw a path through a maze, count the legs of a 5 footed dog, etc. And in doing so finished their last venture capital subsidies (bringing the actual cost of these to their customers). Why would people use LLMs for these when a traditional specialized model can do it for much cheaper?