The issue with this is that the machine doesn't learn from itself at all in both scenarios. While "studying" replays isn't half bad idea, it means it could pick up just as many bad tactics and moves as good ones, which would get it nowhere.

Starting off with sourcing few thousand replays is definitely the right thing to do, but it's only the first and smallest step. The machine would still have to play tens of thousands of games to "realise" which moves are superior to others or how to counter a certain move. The "countering" part would probably be extremely hard to overcome because it requires acting against what ghost is suggesting. It creates a massive spiral of checking previous games to guess what the opponent is going to do, and even then all it can act against is the most statistically probable outcome. Anything that the opponent does out of the ordinary instantly throws off the AI because it can't act on statistical probability no more.

Idk to me it seems like all too much for a system to handle at this point. Maybe after 10-20 years this would be possible from a home computer, but now it would require loads and loads of processing power. This sort of AI would have to update its database constantly with no end to it since there are infinite sets of moves that can be done every match.