AlphaGo is setting a new stage for the future of AI
It truly is a great time for artificial intelligence (AI) and more so for us as we have front row seats into the beginnings of the advancement of AI. On March 9th, 2016 Googles DeepMind AlphaGo program beat South Korea’s Lee Se-dol in Go, one of the most complex strategy board games in our world.
AlphaGo is a computer program that was developed by DeepMind, acquired by Google in 2014, to be able to play Go. It became the first Go AI to beat a professional human in 2015.
The game of Go was created in China more than two thousand years ago. The rules of the game allow players to take turns to place black or white stones on a board in an attempt to capture the opponent’s stones or take over territory, empty space, for points. It is regarded as an immensely complex game and according to Google Go has more possible positions than the number of atoms in the universe.
On March 9th, 2016, AI took a step forward when AlphaGo defeated Lee Se-dol, a 9th dan rank South Korean professional Go player considered one of the worlds best players. At the age of 18 Lee became the second best go player, internationally, and has been world champion 18 times. He has 5 games against AlphaGo with a $1 million winning prize. Unfortunately on March 10th he lost his second match against AlphaGo. AlphaGo also won against the European champion Fan Hui, including 499 other matches.
According to the team behind AlphaGo, the program learns by watching other players and learns different patterns, even being able to understand which patterns are good and bad. While games such as chess and checkers are considered simple Go is far more complicated. Many professionals predicted it would take some 10 years for advancement of this kind, so it came as a surprise when AlphaGo beat Lee. Mastering Go has been a challenge for AI, FaceBook is also working on an AI that can play Go, according to Mark Zuckerberg its getting close to being top human players.
Its ability to learn and improve by watching other players, learning from mistakes, and analyzing millions of possible movies sets a new stage for AI.