Inside Facebook's AI Machine Backchannel

When asked to head Facebook's Applied Machine Learning group -- to supercharge the world's biggest social network with an AI makeover -- Joaquin Quiñonero Candela hesitated. It was not that the Spanish-born scientist, a self-described "machine learning (ML) person," hadn't already witnessed how AI could help Facebook. Since joining the company in 2012, he had overseen a transformation of the company's ad operation, using an ML approach to make sponsored posts more relevant and effective. Significantly, he did this in a way that empowered engineers in his group to use AI even if they weren't trained to do so, making the ad division richer overall in machine learning skills. But he wasn't sure the same magic would take hold in the larger arena of Facebook, where billions of people-to-people connections depend on fuzzier values than the hard data that measures ads. "I wanted to be convinced that there was going to be value in it," he says of the promotion. Despite his doubts, Candela took the post. And now, after barely two years, his hesitation seems almost absurd.