It's not about specialized vs generalized models - it's about how models are trained. The chess engine that beat Kasparov is a specialized model (it only plays chess), yet it's the bitter lesson's example for the smarter way to do AI.
Chess engines are better at chess than LLMs. It's not close. Perhaps eventually a superintelligence will surpass the engines, but that's far from assured.
Specialized AI are hardly obsolete and may never be. This hypothetical superintelligence may even decide not to waste resources trying to surpass the chess AI and instead use it as a tool.
I think your point that AI would refuse to play chess is interesting. To humans, chess is a strategic game. To a mathematician, chess is an exceedingly hard game, (pretty sure it is EXP complete, but I'm not fully familiar with Np/Exp completeness). To an AI, it seems like the AI will side with the mathematicians. AI is like "bro you can't even figure out if P=NP so how am I going to, you want me to waste power to solve an unsolvable problem?"
From Wikipedia, Garry Kasparov said it was a pleasure to watch AlphaZero play, especially since "its style was open and dynamic like his own".
People can't define AI because they don't want to consider AI as a subset of exponentially difficult algorithms, but they do want to consider AI as a generator of stylistic responses.
It's not about specialized vs generalized models - it's about how models are trained. The chess engine that beat Kasparov is a specialized model (it only plays chess), yet it's the bitter lesson's example for the smarter way to do AI.
Chess engines are better at chess than LLMs. It's not close. Perhaps eventually a superintelligence will surpass the engines, but that's far from assured.
Specialized AI are hardly obsolete and may never be. This hypothetical superintelligence may even decide not to waste resources trying to surpass the chess AI and instead use it as a tool.