A brute force approach for Go doesn't work. It doesn't work for humans (deep reading skills) and doesn't work for computers. The Monte Carlo approach was the f

A brute force approach for Go doesn't work. It doesn't work for humans (deep reading skills) and doesn't work for computers. The Monte Carlo approach was the first one that allowed Go AIs to scale with the hardware. This was at least two years ago. AlphaGo went way beyond that. It actually learned more like how a Go player does. It was able to examine and play a lot of games. That's why it was able to beat a 2p pro, and within less than half a year, challenge a 9p world-class player at least on even terms. The big thing isn't that AlphaGo is able to play Go at all at that level, but that learned a specific subject much faster than a human.