Crazy Stone beat Go grandmaster Norimoto Yoda, but with a caveat: the computer started with a four-stone advantage.
A.I. has been making humans feel dumb in the past two decades. We’ve lost at playing checkers, chess, Jeopardy!, and all sorts of other boardgames. Silicon brains haven’t been able to master the ancient game of Go until recently, thanks to advances in deep neural networks.
…In playing Go, the grandmasters often rely on something that’s closer to intuition than carefully reasoned analysis, and building a machine that duplicates this kind of intuition is enormously difficult. But a new weapon could help computers conquer humans much sooner: deep learning. Inside companies like Google and Facebook, deep learning is proving remarkably adept at recognizing images and grasping spacial patterns—a skill well suited to Go. As they explore so many other opportunities this technology presents, Google and Facebook are also racing to see whether it can finally crack the ancient game.
As Facebook AI researcher Yuandong Tian explains, Go is a classic AI problem—a problem that’s immensely attractive because it’s immensely difficult. The company believes that solving Go will not only help refine the AI that drives its popular social network, but also prove the value of artificial intelligence. Rob Fergus, another Facebook researcher, agrees. “The goal is advancing AI,” he says. But he also acknowledges that the company is driven, at least in a small way, by a friendly rivalry with Google. There’s pride to be found in solving the game of Go.
Computers are great at calculations and storing facts. With deep neural networks, computers have the ability to learn and derive answers. Also, they edge ever closer to having intuition and “gut feeling” – something Grandmaster Yoda relies on in a game of Go.
Next A.I. frontier: emotions?