AlphaGo uses neural networks trained on human play to generate candidate moves, and then Monte Carlo Tree Search to evaluate them deeply. The neural nets are a

AlphaGo uses neural networks trained on human play to generate candidate moves, and then Monte Carlo Tree Search to evaluate them deeply. The neural nets are a strong player by themselves. AlphaGo primarily refutes this essay, rather than supports it. Prior to AlphaGo we had many Monte Carlo bots, but none of them approached professional level of play, much less world-class play. A strategy other than brute force was required to get there. --- AlphaGo's loss in game four is interesting, by the way; I'm not sure how you would fix it in their model. It appears that it lost because it failed to predict the (creative, unusual) wedge move in the neural nets, did not spend enough time evaluating it in MCTS, didn't give a strong response to it (which was available through MCTS if it had looked), and didn't understand afterwards that it was now dramatically losing the game and played some very strange moves.