Google has let DeepMind AlphaZero loose with a chess board, and it pretty well destroyed the previous state-of-the-art chess engine (Stockfish 8). 100 games, 28 wins, 72 draws, 0 losses. I guess it wasn't even worth letting a human try to play it. Previous engines relied on brute force tree search algorithms with some pruning and various opening/endgame lookup tables. AlphaZero is DeepMind's deep convolutional neural network tech and was apparently trained only with the rules of chess and 24 hours of self-play, no lookup tables or anything.
The best part for me is that AlphaZero seems to play much more aesthetic or 'human-like' chess, happy to make plenty of material sacrifices because it must have a much more robust understanding of the positional advantages it can gain. On page 6 of the paper the DeepMind team show the openings that AlphaZero started playing at various points in it's self-play development - it's interesting to see some common human openings are played but then discarded as it evidently finds some flaw in them. Hundreds of years of human chess development condensed into a few hours and then completely surpassed...
I've linked to some analysis of one of the games from a youtube channel I watch and the arxiv paper from the DeepMind team:
https://youtu.be/lb3_eRNoH_w
https://arxiv.org/pdf/1712.01815.pdf