That is a staggering amount of possible Go games, no wonder tree search failed to improve without the Convnet pruning.<p>Makes me wonder if Deepmind could learn Go without first learning from the big dataset of expert games to train the convnet to prune the tree.<p>Which implies that Deepmind couldn&#x27;t learn to play Go without first being taught by us (the expert games).<p>So AlphaGo learnt Go from us. It took a human brain to crack the problem of Go and the AI learned from our solutions it did not discover them itself - still a very great breakthrough.<p>Would Lee Sedol have won if he could use MCTS to assist his evaluation ?<p>( Arguably the MCTS is a non-AI component of deepmind &amp; does not learn ).<p>MCTS = Monte Carlo Tree Search, where repeated random playouts evaluate moves by <i>randomly sampling</i> the tree of following (googolplex) possible moves.