You're making a conceptual mistake here, comparing a chess tool to its operator. Deterministic tools produce superior results compared to models in many areas, so we allow models to use tooling.
The correct analogy here is Fable as a second tier player assisting a SuperGM in running stockfish, then assessing its output to identify promising variations.
There might be a limit somewhere that prevents the bitter lesson being axiomatic - for instance where simulations for anything can be exhaustive - so that judgement isn't needed any more as an arbiter. But while there are problems sufficiently complex or large to require a breadth models don't currently have, greater scale and compute will continue to convert to better decision making, and the bitter lesson will remain true (true enough).
The correct analogy here is Fable as a second tier player assisting a SuperGM in running stockfish, then assessing its output to identify promising variations.
There might be a limit somewhere that prevents the bitter lesson being axiomatic - for instance where simulations for anything can be exhaustive - so that judgement isn't needed any more as an arbiter. But while there are problems sufficiently complex or large to require a breadth models don't currently have, greater scale and compute will continue to convert to better decision making, and the bitter lesson will remain true (true enough).