The problem with Go was lack of evaluation function that would guide the policy. So it had to be learned simultaneously.

You can leave AlphaGo to play a billion games and then learn a policy that requires little to no search but has almost perfect evaluation (local optimality of minimizing future regret).

Same positional play is exhibited by Komodo, and it requires not that much of depth searching, while currently AlphaGo rolls out a whole game for every move.

60 years ago: "The ENIAC uses so much more energy and takes up more space than a human to multiply numbers, I want to see a calculator multiply faster than a human running on a 5V watch battery before I draw conclusions"