It’s official: Lee Se-dol has lost his first two Go games against AlphaGo, the computer program from Google’s DeepMind. Going into the match, Lee said he was confident, predicting victory in all 5 games. So when he lost the first game, he was shellshocked: “I didn’t expect to lose,” he said.”Even when I was behind, I still didn’t imagine that I’d lose. I didn’t think that it would be able to play such an excellent game.”
He’s now 0-2 out of 5 against AlphaGo, with $1 million on the line.
As Lee sat in front of the press after the second loss, he looked visibly shaken. “Yesterday I was surprised but today it’s more than that — I am speechless,” he said. Lee rocked back and forth slightly while DeepMind founder Demis Hassabis described the program’s confidence through the game, fidgeting as the cameras snapped hundreds of photos. He has a day to think about his strategy before game 3 on Saturday
I can understand how for some, a person losing a board game to a computer might seem inconsequential; after all, the best minds in Chess were beaten by computers decades ago. But this isn’t Chess. Go, a roughly 3,000 year old game (called as weiqi in China, igo in Japan, and baduk in Korea), is staggeringly more complex than other strategy board games. It’s estimated that there are some 10761 possible games of Go (compared with 10120 for Chess)—more than the number of atoms in the known universe. This means that even the most powerful computers on the planet can’t calculate ahead to conclusively determine the best move to play. Human players rely on a mix of skill, instinct, and imagination.
I know quite well how much of a challenge it is to program a machine to mimic the art of play. After all, my dad wrote the first commercial Go program. Continue reading “Defeating The Ultimate Nemesis: Google’s AlphaGo A.I. Takes 2-0 Lead In Go Match Against Lee Se-dol”
