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Re:The neural network of the Stockfish chess engine by stabbles on Wednesday January 13, 2021 @09:04AM (#25762050)
The Stockfish mentality is: not everybody owns a GPU and Stockfish should be available for everybody and perform well [1]. So they went for a CPU micro-arch optimized neural net, which is great. Maybe this is ultimately not the best for tournaments.

What I would find interesting is if they could give engines an energy budget instead of a time limit. Maybe that makes CPU vs GPU games more interesting & fair.

[1] https://github.com/official-stockfish/Stockfish/issues/2823

Re:The neural network of the Stockfish chess engine by kohlerm on Wednesday January 13, 2021 @09:22AM (#25762242)
IMHO they did this because that was the only incremental way to improve strength. They always relied an a fast search with a relatively simplistic eval function. For this approach alpha beta search works well. What is not clear whether it works well for the Leela approach. All attempts so far at least have not been successful(could be for other reasons, such as training approach). SF strength seems to be their well optimized search function. Rewriting that would IMHO be equivalent to creating a new chess engine. That being said I still think that the success of SF NNUE is very remarkable.
Re:The neural network of the Stockfish chess engine by yters on Wednesday January 13, 2021 @11:42AM (#25764453)
They should also give an energy budget of human vs computer.