AlphaGo represents a general approach to AI

Although I disagree that fooming will be slow, from what I've learned studying it I would say that its approach is not easy to generalize.
AlphaGo draws its power partly due to the step where an 'intuitive' neural net is created, using millions of self-play from another already supervisedly trained net. But the training can be accurate because the end positions and the winning player are clearly defined once the game is over. This allows a precise calculation of the outcome function that the intuitive neural net is trying to learn.
Unsupervised learners interacting with an environment that has open ontologies will have a much harder time to come up with this kind of intuition-building step.