A Sad Victory
I recently watched the documentary AlphaGo, directed by Greg Kohs. The film tells the story of the refinement of AlphaGo—a computer Go program built by DeepMind—and tracks the match between AlphaGo and 18-time world champion in Go Lee Sedol.
Go is an ancient Chinese board game. It was considered one of the four essential arts of aristocratic Chinese scholars. The goal is to end the game having captured more territory than your opponent. What makes Go a particularly interesting game for AI to master is, first, its complexity. Compared to chess, Go has a larger board, and many more alternatives to consider per move. The number of possible moves in a given position is about 20 in chess; in Go, it’s about 200. The number of possible configurations of the board is more than the number of atoms in the universe. Second, Go is a game in which intuition is believed to play a big role. When professionals get asked why they played a particular move, they will often respond something to the effect that ‘it felt right’. It is this intuitive quality why Go is sometimes considered an art, and Go players artists. For a computer program to beat human Go players, then, it would have to mimic human intuition (or, more precisely, mimic the results of human intuition).