Can a radically open culture help Facebook catch up to Google and Microsoft—and build the world's most powerful ad platform?
Facebook is known for a variety of mantras embedded in its culture, often spelled out on signs at its offices or recited by CEO Mark Zuckerberg and other executives: "Code wins arguments," "Move fast and break things," or "Done is better than perfect."
A sign on the wall at the company's New York office perfectly sums up the approach Yann LeCun brings to his leadership of Facebook's nascent efforts in the field of artificial intelligence and machine learning: "Always be Open." Artificial intelligence has become a vital part of scaling Facebook. It's already being used to recognize the faces of your friends in photographs, and curate your newsfeed. DeepText, an engine for reading text that was unveiled last week, can understand "with near-human accuracy" the content in thousands of posts per second, in more than 20 different languages. Soon, the text will be translated into a dozen different languages, automatically. Facebook is working on recognizing your voice and identifying people inside of videos so that you can fast forward to the moment when your friend walks into view.
Facebook wants to dominate in AI and machine learning, just as it already does in social networking and instant messaging. The company has hired more than 150 people devoted solely to the field, and says it's tripled its investment in processing power for research—though it won't say how much that investment is.
If the mobile cloud was the previous era of computing, the next will be the era of AI, says Jen-Hsun Huang, the CEO of Nvidia, one of the world’s largest makers of graphics processors and a partner in Facebook’s open-source hardware design. "It is the most important computing development in the last 20 years, and Facebook and others are going to have to race to make sure that AI’s a core competency."
Yet Facebook, which only seriously entered the field less than three years ago, will need more than money to compete, since it's one of technology’s hottest fields right now. "They were a late comer," says Pedro Domingos, a professor of computer science at the University of Washington and the author of The Master Algorithm. "Companies like Google and Microsoft were far ahead." They've been building intelligent software since well before Mark Zuckerberg announced plans to program an intelligent butler that would control his home.
Microsoft, which has been working on machine learning since 1991, has several hundred scientists and engineers in dozens of research areas related to the field. Google Assistant, the centerpiece of that company's deep learning efforts, is on the way to becoming the front-end brain for most of its apps and services. Chinese search giant Baidu poached the head of Google's deep learning project, Andrew Ng, back in 2014. OpenAI, a nonprofit, has $1 billion in funding from Tesla founder Elon Musk and other tech heavyweights. Amazon CEO Jeff Bezos, speaking at the Code conference, said his company has been working on AI behind the scenes for four years and that it already has a thousand people dedicated to its voice recognition ecosystem. Apple and Uber have also invested heavily in artificial intelligence, and are competing to attract the same pool of talent.
All of this is riding on a wave of striking innovation in the field, some of which came from LeCun himself—widely considered one of the most accomplished scientists in the field—during his pre-Facebook days. And Facebook has rapidly gone from not having a formal research lab of any kind to housing two of them. Facebook’s Artificial Intelligence Research program (FAIR), headed by LeCun, focuses on fundamental science and long-term research. Then there’s the Applied Machine Learning (AML) division, led by Spanish-born Joaquin Candela, a longtime machine learning expert who, among other things, created a course on the topic at the University of Cambridge. His team finds ways to apply the science to existing Facebook products.
The two divisions are separate, with both LeCun and Candela reporting to Facebook CTO Mike Schroepfer. The challenge is figuring out how to make the two groups work together, with long-range scientific research feeding into near-term business goals. One obvious way to make that happen: Get the two teams sitting next to each other. "They have to have personal relationships," says LeCun. "And they have to collaborate really closely."
At Facebook, they not only sit next to one another but near the very top of the organization—just feet from Zuckerberg's and Schroepfer's offices, in fact—a sign of how valuable AI and machine learning has become to the company.
But just because you sit next to someone doesn't make the task of capitalizing on deep science any easier. To understand how LeCun and Candela plan to make it work, you have to first understand where LeCun and Candela came from.
Facebook’s Artificial Intelligence Research Lab
There’s a big blue thumbs-up logo taped to the front door of Yann LeCun’s office in the computer science department at New York University. LeCun, one of the world’s foremost experts in deep learning, didn’t put it there. Wearing a navy blue polo shirt with a small image of Einstein stitched above the word "THINK" on a recent Wednesday, he laughs and says that when it was announced two and a half years ago that he was joining Facebook, someone put it there, and he just never took it down....MUCH MORE
