I wonder if you could creatively combine this model with search algorithms to advance the state of the art in computer chess? I wouldn't be surprised to see such a bot pop up on tcec in a couple years.
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NNUE already tries to distill a subtree eval into a neural net, but it’s optimized for CPU rather than GPU.
What you’re discussing sounds like intuition with checking, which is pretty close to how humans with a moderate degree of skill behave. I haven’t known enough Chess or Go masters to have any claim on how they think. But most of us don’t want an opponent at that level and if we did, we would certainly find a human, or just play against ourselves.
If you want a computer that plays like a human, you will probably need to imitate the way that a human thinks about the game. This means for example thinking about the interactions between pieces and the flow of the game rather than stateless evaluations.