A Look Inside Facebook’s AI Machine – AI Trends


(L-R) Joaquin Candela, Director of Engineering for Applied Machine Learning; Manohar Paluri, Applied Computer Vision Team Lead; Rita Aquino, Technical Product Manager; and Rajen Subba, Engineering Manager. Photo by Stephen Lam

By Steven Levy, Wired

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.

How absurd? Last month, Candela addressed an audience of engineers at a New York City conference. “I’m going to make a strong statement,” he warned them. “Facebook today cannot exist without AI. Every time you use Facebook or Instagram or Messenger, you may not realize it, but your experiences are being powered by AI.”

Last November I went to Facebook’s mammoth headquarters in Menlo Park to interview Candela and some of his team, so that I could see how AI suddenly became Facebook’s oxygen. To date, much of the attention around Facebook’s presence in the field has been focused on its world-class Facebook Artificial Intelligence Research group (FAIR), led by renowned neural net expert Yann LeCun. FAIR, along with competitors at Google, Microsoft, Baidu, Amazon, and Apple (now that the secretive company is allowing its scientists to publish), is one of the preferred destinations for coveted grads of elite AI programs. It’s one of the top producers of breakthroughs in the brain-inspired digital neural networks behind recent improvements in the way computers see, hear, and even converse. But Candela’s Applied Machine Learninggroup (AML) is charged with integrating the research of FAIR and other outposts into Facebook’s actual products—and, perhaps more importantly, empowering all of the company’s engineers to integrate machine learning into their work.

Because Facebook can’t exist without AI, it needs all its engineers to build with it.

My visit occurs two days after the presidential election and one day after CEO Mark Zuckerberg blithely remarked that “it’s crazy” to think that Facebook’s circulation of fake news helped elect Donald Trump. The comment would turn out be the equivalent of driving a fuel tanker into a growing fire of outrage over Facebook’s alleged complicity in the orgy of misinformation that plagued its News Feed in the last year. Though much of the controversy is beyond Candela’s pay grade, he knows that ultimately Facebook’s response to the fake news crisis will rely on machine learning efforts in which his own team will have a part.

But to the relief of the PR person sitting in on our interview, Candela wants to show me something else—a demo that embodies the work of his group. To my surprise, it’s something that performs a relatively frivolous trick: It redraws a photo or streams a video in the style of an art masterpiece by a distinctive painter. In fact, it’s reminiscent of the kind of digital stunt you’d see on Snapchat, and the idea of transmogrifying photos into Picasso’s cubism has already been accomplished.

“The technology behind this is called neural style transfer,” he explains. “It’s a big neural net that gets trained to repaint an original photograph using a particular style.” He pulls out his phone and snaps a photo. A tap and a swipe later, it turns into a recognizable offshoot of Van Gogh’s “The Starry Night.” More impressively, it can render a video in a given style as it streams. But what’s really different, he says, is something I can’t see: Facebook has built its neural net so it will work on the phone itself.

Read the source article in Wired.

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Just a figment of your imagination.