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Take a look at the chess engine Stockfish: they tossed out years and years of human written heuristics in board evaluation, to a small neural net that does the same but better.

Now consider all the heuristics for inlining, loop unrolling, vectorization etc in compilers, certainly a neural net can be beneficial and possibly easier to maintain than tons of human written heuristics.



We'll have to see. I could definitely see someone spending a lot of time training for a specific algorithmic kernel and microarchitecture and beating the best human results (by a few percent).

I'd be very surprised if that can be extended to a large complex algorithmic system that is amenable to mathematical reformulations (at least within the next 10 years).



My understanding is that stockfish retains and uses its classical evaluation model in addition to the NNUE model


No, they removed the code in Stockfish 16, released June 30, 2023 but it wasn't used for much or made much difference before then, after they introduced the neural net.

https://github.com/official-stockfish/Stockfish/commit/af110...


big +1 - IMHO the future of optimizers (and probably compilers...) are almost certainly ML-based.


Humans designing algorithms by hand will go the way of the dodo bird




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