AlphaGo – How Google’s AI Defeated the European Go Champion
I felt compelled to return from my over-long hiatus to share some exciting news: Google DeepMind recently announced that their artificial intelligence program AlphaGo has defeated Fan Hui 2p, three-time European Go Champion, in five games out of five. This is the first time a computer has won against a professional Go player in an even game (without a handicap).
If someone had told me five years ago or even yesterday that a computer program would be capable of winning an even game against a professional Go player in 2016, I would have said it’s impossible, and that is not a word I use often! Remarkably more complicated than chess, developing a competitive Go program has been a major challenge in 21st-century computer science and artificial intelligence studies. The number of possible Go games far exceeds the number of atoms in the observable universe. A brute-force approach to solving Go is unfeasible. Rather than narrow focus on local regions of the board, good gameplay requires accurate assessments of the entire game situation and intuitive judgements, which humans have excelled at — until now.
So, how did Google do it?
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