AlphaGo was initially trained to predict the moves that humans would make, using a deep neural network, and given tons of game records. Then it was trained agai

AlphaGo was initially trained to predict the moves that humans would make, using a deep neural network, and given tons of game records. Then it was trained again with reinforcement learning by playing against itself by taking moves based on that probability, and increasing the probability of moves that lead to wins. So when they say it predicted 1 in 10,000 chance, it means it thinks it's really unlikely a human would play that move. Just playing random moves means each move has only 1 361 chance at worst, so that move must strongly violate normal human play patterns.