SAN FRANCISCO (AP) -- Facebook announced several new hires of top academics in the field of artificial intelligence Tuesday, among them a roboticist known for her work at Disney making animated figures move in more human-like ways. The hires raise a big question -- why is Facebook interested in robots, anyway? It's not as though the social media giant is suddenly interested in developing mechanical friends, although it does use robotic arms in some of its data centers. The answer is even more central to the problem of how AI systems work today. Today, most successful AI systems have to be exposed to millions of data points labeled by humans -- like, say, photos of cats -- before they can learn to recognize patterns that people take for granted.

Facebook announced several new hires of top academics in the field of artificial intelligence Tuesday, among them a roboticist known for her work at Disney making animated figures move in more human-like ways. The hires raise a big question - why is Facebook interested in robots, anyway? It's not as though the social media giant is suddenly interested in developing mechanical friends, although it does use robotic arms in some of its data centers. The answer is even more central to the problem of how AI systems work today. Today, most successful AI systems have to be exposed to millions of data points labeled by humans - like, say, photos of cats - before they can learn to recognize patterns that people take for granted.

Today, most successful AI systems require millions of points of human-labeled data, like photos of cats, to train themselves to recognize faces and objects like people do. Or they have to play games tens of thousands of times, like Google's AlphaGo Zero did.

Facebook is announcing several academic hires in artificial intelligence, including Carnegie Mellon researcher Jessica Hodgins, who's known for her work making animated figures move in more human-like ways. The hires raise a big question -- why is Facebook interested in robots? The answer is central to the problem of how AI systems work today. Today, most successful AI systems require millions of points of human-labeled data, like photos of cats, to train themselves to recognize faces and objects like people do. Or they have to play games tens of thousands of times, like Google's AlphaGo Zero did.