A student has built a computer that managed to teach itself chess, and in just three days attained a level of skill comparable with some of the world’s most skilful players.In the last two decades computers have become exponentially more powerful, but the “brute force” method of evaluating 200 million moves per second that Deep Blue employed was still the norm.Caissa instead trained a “neural network” using example situations from real games of chess.Rather than searching through all possible future moves and calculating the best one.
Caissa machine was built with a neural network which was fed 175 million examples of real games. It then evaluated the pieces in play and, contrary to traditional chess machines, predicted which move of the millions of possibilities would be strong and which would be weak.Inspired by the human brain, the network’s nodes change as they are fed information, simulating the human process of learning by experience.
Thanks to recent advances in computer speeds, these neural networks have grown in size and complexity, greatly increasing their power and proficiency.Beyond playing games, Deep Learning Machines have a potential future in image recognition, drug discovery and even customer relations. As a potential step towards powerful artificial intelligence Facebook, Microsoft and Google have all invested in Deep Learning technologies in the past five years.