The Brute Force of AlphaGo


David Silver, Google DeepMind:

The search base at Go is too enormous and too vast for a brute force approach to have any chance of succeeding… The search process itself is not based on brute force, more on something akin to imagination…. Humans are not able to make the precise tree-based computation that computers are able to perform. Humans have a limitation in the number of Go games they are able to process in a lifetime… It is at least conceivable that AlphaGo could, given enough processing, given enough training, given enough search power, reach a level that’s beyond any human.

Define “Brute Force”?


The machine knew the move wouldn’t make sense to all those humans. Yes, it knew. And yet it played the move anyway, because this machine has seen so many moves that no human ever has…. drawing on all its other training with millions of moves generated by games with itself, it came to view Move 37 in a different way. It came to realize that, although no professional would play it, the move would likely prove quite successful. “It discovered this for itself,” Silver says, “through its own process of introspection and analysis.” Is introspection the right word? You can be the judge.

Define “Introspection”? Maybe a better term to use is “Brute Force”?