Why does AlphaZero evaluate on the order of 1000 times less moves than Stockfish? According to Deep mind's article, Alpha Zero searches roughly 10,000 moves per decision, while Stockfish is around 10,000,000 moves. I'm aware that Alpha Zero uses Monte Carlo Tree Search while Stockfish uses minimax, but why would this cause 1000 times less moves to be considered?
Very simple. Running a large neural network with floating numbers can’t be quicker than running a simple C++ function on integers.

AI machine learning is not new to chess. There were serious attempts before Google established. Unfortunately, nobody had the determination, skills and resources to do a good job. Nobody wanted to invest money. Before Google's chess journey, the chess engine community believed:


  AI chess will not beat classical programming because neural networks
  (or other models) run much slower.