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Google's DeepMind beats Lee Se-dol again to go 2-0 up in historic Go series
"Google stunned the world by defeating Go legend Lee Se-dol yesterday, and it wasn't a fluke — AlphaGo, the AI program developed by Google's DeepMind unit, has just won the second game of a five-game Go match being held in Seoul, South Korea. AlphaGo prevailed in a gripping battle that saw Lee resign after hanging on in the final period ofbyo-yomi ("second-reading" in Japanese) overtime, which gave him fewer than 60 seconds to carry out each move.
"Yesterday I was surprised but today it's more than that — I am speechless," said Lee in the post-game press conference. "I admit that it was a very clear loss on my part. From the very beginning of the game I did not feel like there was a point that I was leading." DeepMind founder Demis Hassabis was "speechless" too. "I think it's testament to Lee Se-dol's incredible skills," he said. "We're very pleased that AlphaGo played some quite surprising and beautiful moves, according to the commentators, which was amazing to see."
The close nature of the game appears to offer validation of AlphaGo's evaluative ability, the main roadblock to proficiency for previous Go programs. Hassabis says that AlphaGo was confident in victory from the midway point of the game, even though the professional commentators couldn't tell which player was ahead.
Until yesterday, the ancient Chinese board game of Go had never been played to a world-class level by an AI. Computer programs have long bested the world's leading human players of games like checkers and chess, but Go's combination of simple rules and intricate strategy has made it a major challenge for artificial intelligence research.
DeepMind's AlphaGo program uses an advanced system based on deep neural networks and machine learning, which has now seen it beat 18-time world champion Lee twice. The series is the first time a professional 9-dan Go player has taken on a computer, with Lee competing for a $1 million prize. AlphaGo's victory today means it leads the series 2-0; Lee had predicted he'd win 5-0 or 4-1 at worst, but he now needs to come out on top in all three remaining games whereas AlphaGo could wrap up the series by Saturday."
"Chess and checkers do not need sophisticated evaluation functions," says Jonathan Schaeffer, a computer scientist at the University of Alberta who wrote Chinook, the first program to solve checkers. "Simple heuristics get most of what you need. For example, in chess and checkers the value of material dominates other pieces of knowledge — if I have a rook more than you in chess, then I am almost always winning. Go has no dominant heuristics. From the human's point of view, the knowledge is pattern-based, complex, and hard to program. Until AlphaGo, no one had been able to build an effective evaluation function."
Match 1 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Match 2 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
https://www.deepmind.com/
Why is Google's Go win such a big deal?
"Google stunned the world by defeating Go legend Lee Se-dol yesterday, and it wasn't a fluke — AlphaGo, the AI program developed by Google's DeepMind unit, has just won the second game of a five-game Go match being held in Seoul, South Korea. AlphaGo prevailed in a gripping battle that saw Lee resign after hanging on in the final period ofbyo-yomi ("second-reading" in Japanese) overtime, which gave him fewer than 60 seconds to carry out each move.
"Yesterday I was surprised but today it's more than that — I am speechless," said Lee in the post-game press conference. "I admit that it was a very clear loss on my part. From the very beginning of the game I did not feel like there was a point that I was leading." DeepMind founder Demis Hassabis was "speechless" too. "I think it's testament to Lee Se-dol's incredible skills," he said. "We're very pleased that AlphaGo played some quite surprising and beautiful moves, according to the commentators, which was amazing to see."
The close nature of the game appears to offer validation of AlphaGo's evaluative ability, the main roadblock to proficiency for previous Go programs. Hassabis says that AlphaGo was confident in victory from the midway point of the game, even though the professional commentators couldn't tell which player was ahead.
Until yesterday, the ancient Chinese board game of Go had never been played to a world-class level by an AI. Computer programs have long bested the world's leading human players of games like checkers and chess, but Go's combination of simple rules and intricate strategy has made it a major challenge for artificial intelligence research.
DeepMind's AlphaGo program uses an advanced system based on deep neural networks and machine learning, which has now seen it beat 18-time world champion Lee twice. The series is the first time a professional 9-dan Go player has taken on a computer, with Lee competing for a $1 million prize. AlphaGo's victory today means it leads the series 2-0; Lee had predicted he'd win 5-0 or 4-1 at worst, but he now needs to come out on top in all three remaining games whereas AlphaGo could wrap up the series by Saturday."
"Chess and checkers do not need sophisticated evaluation functions," says Jonathan Schaeffer, a computer scientist at the University of Alberta who wrote Chinook, the first program to solve checkers. "Simple heuristics get most of what you need. For example, in chess and checkers the value of material dominates other pieces of knowledge — if I have a rook more than you in chess, then I am almost always winning. Go has no dominant heuristics. From the human's point of view, the knowledge is pattern-based, complex, and hard to program. Until AlphaGo, no one had been able to build an effective evaluation function."
Match 1 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
Match 2 - Google DeepMind Challenge Match: Lee Sedol vs AlphaGo
https://www.deepmind.com/
Why is Google's Go win such a big deal?
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