Comment by salamo

8 months ago

I think this is an interesting finding from a practical perspective. A function which can reliably approximate stockfish at a certain depth could replace it, basically "compressing" search to a set depth. And unlike NNUE which is optimized for CPU, a neural network is highly parallelizable on GPU meaning you could send all possible future positions (at depth N) through the network and use the results for a primitive tree search.

The Stockfish installer is ~45 MB. At 16 bits per parameter, the 270B model would be over 500 MB. The 9B model would be smaller than Stockfish, but you could probably find a smaller chess engine that achieves 2000 ELO.