It's best to say that alphago uses neural networks, which are extremely general. The same way planes and cars both use internal combustion engines. ICEs are extremely general. They produce mechanical energy from gas, and are totally uncaring whether you put them into a plane or a car. The body of the plane is necessary, but isn't really the interesting part.
Likewise NNs are uncaring what application you put them into. Give them a different input and a different goal, and they will learn to do that instead. Alphago gave it's NN's control over a monte carlo search tree, and that turned out to be enough to beat Go. They could plug the same AI into a car and it would learn to control that instead.
Note that even without the monte carlo search system, it was able to beat most amateurs, and predict the moves experts would make most of the time.
I'm not sure that's correct. MCTS has well known weaknesses, and isn't even a predictive algorithm. MCTS on it's own couldn't get anywhere near beating the top Go champion, that requires deepminds neural networks.
Likewise NNs are uncaring what application you put them into. Give them a different input and a different goal, and they will learn to do that instead. Alphago gave it's NN's control over a monte carlo search tree, and that turned out to be enough to beat Go. They could plug the same AI into a car and it would learn to control that instead.
Note that even without the monte carlo search system, it was able to beat most amateurs, and predict the moves experts would make most of the time.