What have we learned from the best chess engines? What rules have they confirmed, modified or rejected in the old chess theory?

• maia-chess

  97 894 1.6 Python

  Maia is a human-like neural network chess engine trained on millions of human games.

  

E.g. a sort of modified Maia could look at those 2 trees and say "if a 2000 player plays the pawn sac they'll play the best move 2 h5 with 5% probability but 2 h4 with 80% probability, so let's recalculate the eval taking that into account".

• Stockfish

  1 99 0.0 C++

  UCI chess engine (by nodchip)

Well the main replies were like "if you can make it 100 elo better than you should be able to pass fishtest w/o any problem". Also I really like this part of the post: "(As a side note, another shogi engine developer (@nodchip on Twitter) is trying out his new shogi evaluation function within Stockfish. The new eval, called NNUE, brought many Elo gains and all the top engines now use it. It was Nodchip's fiddling with Stockfish that led the YaneuraOu developer to make this blog post in first place. https://github.com/nodchip/Stockfish )" and this is indeed what happened - NNUE was made to SF by nodchip. So idk. If you give up at stage of setting up test to fishtest you probably wouldn't be able to bring elo anyway because making it work is much more simple than developing NNUE.

• InfluxDB

  www.influxdata.com featured

  Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.

  

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