“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,” reported Cade Metz in Wired last week . “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.” For more on Facebook’s research, check out “How Facebook’s AI Researchers Built a Game-Changing Go Engine” in the MIT Technology Review last week.
Smart Go’s Anders Kierulf also recently published a blog post on “Go at Facebook”, saying that “As long as Facebook and Google stick with trying to find general solutions to general problems, I don’t think top Go programs like Zen and Crazy Stone have anything to worry about. But once these giants decide to beat the strongest human players and are willing to focus on Go-specific solutions, it will get interesting.” Check out also his explainer on Monte Carlo Tree Search and his post about the impact of the Swift programming language on his go programs.