The road ahead

In January 2016, DeepMind announced the release of AlphaGo (for more information refer to: Mastering the Game of Go with Deep Neural Networks and Tree Search, by D. Silver, Nature 529.7587, pp. 484-489, 2016), a neural network to play the game of Go. Go is regarded as a very challenging game for AIs to play, mainly because at any point in the game, there are an average of approximately 10¹⁷⁰ possible (for more information refer to: http://ai-depot.com/LogicGames/Go-Complexity.html) moves (compared with approximately 10⁵⁰ for chess). Hence determining the best move using brute force methods is computationally infeasible. At the time of publication, AlphaGo had already won 5-0 in a 5-game competition against the current European Go champion, Fan Hui. This was the first time that any computer program had defeated a human player at Go. Subsequently, in March 2016, AlphaGo won 4-1 against Lee Sedol, the world's second professional Go player.

There were several notable new ideas...