In general, training requires far more neural networks requires far more computational power than using them does. However, AlphaGo combines neural networks with a traditional Monte Carlo search. This means that you can improve the performance of a trained AlphaGo by just giving it more processing power. Indeed, with a sufficient amount of processing power, AlphaGo would converge to fully optimal play.