A lot of the graphs in the paper seem to level out as they hit the level of the opponent. It makes me wonder to what extent AlphaGo Zero is merely optimizing to beat flaws in existing opponents' current implementations (even if "existing opponents" == all available opponents' data and algorithms today) rather than generalizable insights into the underlying game. Because wouldn't you expect that unless we are at the theoretical limit of perfect chess that a tabula rasa approach might exceed existing best practice significantly, especially with the massive computation advantage it has?
Not that there's anything wrong with that; AlphaGo Zero supposedly optimized for the "just enough" win rather than the crushing win. It doesn't even mean Stockfish is doomed--I suspect Stockfish could beat it in a future heads up match provided that Zero didn't have time to retrain, but that a retrained Zero (having the benefit of optimizing against a new Stockfish) would be able to supersede it once again.
Not that there's anything wrong with that; AlphaGo Zero supposedly optimized for the "just enough" win rather than the crushing win. It doesn't even mean Stockfish is doomed--I suspect Stockfish could beat it in a future heads up match provided that Zero didn't have time to retrain, but that a retrained Zero (having the benefit of optimizing against a new Stockfish) would be able to supersede it once again.