AlphaGo as a proof of concept for businesses Information Age

Last month, Google DeepMind's AlphaGo programme famously defeated professional Go player, Lee Sedol, in what has been described as a breakthrough for artificial intelligence research. Unlike previous gaming computers, such as IBM's chess-playing Deep Blue which defeated Garry Kasparov in 1997 and IBM's Watson which won Jeopardy! in 2011, AlphaGo implements a fundamentally different type of AI search algorithm that leverages neural networks trained with a combination of supervised and reinforcement learning. Previous game-playing computers relied heavily on deterministic search techniques custom built for a narrow problem domain. For example, IBM's Deep Blue, though expert at chess, would have to be entirely reprogrammed to play checkers. The novelty of AlphaGo's search algorithm lies in its use of deep neural networks, a method of programming that does not rely on any specific domain information.