Since i have read the paper about NeuroChess by Sebastian Thrun i pondered on how to improve his results.

It was obvious that the compute power available in the 90s limited his approach, in training and in inference.

So he had only 120K games for training, a relative small neural network, and could test his approach only with limited search depths.

Recent results with A0 and LC0 show how Deep Learning methods profit by GPGPU, so i think the time has come to give a GPU ANN based engine a try....

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Srdja