Lee Sedol beat Google's artificial intelligence computer Sunday for the first time in four tries in the ancient Chinese board game Go, giving humans back a bit of pride over the learning technology machine.
The computer's AlphaGo program resigned roughly five hours into the game against the Korean Go grandmaster in
Seoul on Sunday, Wired reported. The win, though, was more of a consolation prize since Sedol was playing the computer in a best-of-five match.
The computer's dominance surprised many because of the complexity of the game as compared to chess. For example, the opening move in Go presents a player with some 361 options compared to
20 in chess, according to the British Go Association.
"AlphaGo's dominance in the first three games was notable because no machine had previously beaten a top human player at Go — and because some technologies at the heart the system are already used inside Google and other big-name Internet companies," Wired noted.
"AlphaGo highlights the enormous power of these technologies and points the way forward for the AI techniques that have driven its success this week — techniques that are poised to reinvent everything from scientific research to robotics. And yet, as Lee Sedol showed today, machines are by no means infallible," the tech site continued.
Many experts believed that artificial intelligence computers were between five and 10 years away from handling something as complex as the
Go board game, according to Bloomberg Business. Google is currently using such technology for such thing as automatically writing e-mails, recommending YouTube videos, and helping cars drive themselves.
Demis Hassabis, co-founder of the DeepMind artificial intelligence system, told Bloomberg that the he hopes the computer and program will show that its problem-solving ability can help, not beat, humans in a wide variety of ways.
"Healthcare is one of the main things we're looking at next," he said. "The system and techniques that we’re using for AlphaGo should be useful for anywhere, any kind of problem where there's lots and lots of data and you’re trying to understand the structure in that data and make some kind of decision."
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