Humans and computers have a long history of competing when it comes to playing board games. From Wolfgang Von Kempelen’s ‘Turk’ (a mechanical chess-playing machine which eventually turned out to be operated by a small human) to the infamous match between IBM’s supercomputer Deep Blue versus human chess genius Garry Kasparov. Another victory can be added to computer wins, as Go world champion Ke Jie has just lost two games of 'Go' against Google's DeepMind AI system AlphaGo.
Go is a 2.500-year-old game that is exponentially more complex than a ‘simple’ game of chess. Rooted in ancient China, the abstract-looking game is believed to be the oldest board game around the block, and is still played today. It consists of two players, one Black and one White, who put their “stones” on the intersections of the board’s lines, with the aim of acquiring more territory than their opponent.
DeepMind CEO and co-founder Demis Hassabis explains: "As simple as the rules are, Go is a game of profound complexity. There are 1,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000,000 possible positions - that’s more than the number of atoms in the universe, and more than a googol times larger than chess".
To “train” AlphaGo played numerous games against itself, did its homework by studying about 100.000 human matches and played many of the world's top players under the pseudonym 'Master' in online matches earlier this year. As it went, it reprogrammed and improved itself, gradually influencing human players to start adapting their gameplay to seemingly unconventional systemized strategies. In a way the story of AlphaGo is yet another analogy to understand our co-evolutionary path with technology; a path to domesticate our habits, our next nature, which eventually will also come to domesticate us.