Currently there is much going on with neural networks for chess. With Giraffe, AlphaZero, and its open source adaptation LC0 (Leela Chess Zero), it was shown that, with enough horse power, artificial neural networks are competitive in computer chess.
Currently LC0 uses an MCTS, Monte-Carlo Tree Search, approach with GPU as neural network accelerator for position evaluation.
My own experiments showed that AlphaBeta search is superior to MCTS, but current GPU architectures suffer from host-device latency, so you have to couple tasks to batches to be executed in one run on the GPU, not that conform with the serial nature of AlphaBeta.
With upcoming GPGPU architectures (or ANN accelerators) with less latency there might be AlphaBeta ANN engines possible...