AlphaGo was actually only trained on publicly available amateur (that is, strong amateur) games. After that, AlphaGo was trained by running a huge number of games against itself (reinforcement learning).
A priori, this makes sense: you don't need to train on humans to get a better understanding of the game tree. (See any number of other AIs that have learned to play games from scratch, given nothing but an optimization function.)
A priori, this makes sense: you don't need to train on humans to get a better understanding of the game tree. (See any number of other AIs that have learned to play games from scratch, given nothing but an optimization function.)