Yes, but pruning (not considering everything) is as old as game tree search. Previous Go AIs used MCTS as well. What's new in AlphaGo is a more sophisticated ap

Yes, but pruning (not considering everything) is as old as game tree search. Previous Go AIs used MCTS as well. What's new in AlphaGo is a more sophisticated approach to scoring game boards - policy networks that help the AI prune even more aggressively, and a value network that's used to "guess" the winner in lieu of searching to endgame. Note that guessing the winner is just a special case of an evaluation function. For any game, if you could consistently search to the end, your evaluation function is always a -1/1 corresponding to lose/win. AlphaGo is still using MCTS - just a more sophisticated form.