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"It’s time to stop thinking about Facebook as just a social media company. Between its efforts to deliver internet service with drones, buying Oculus for virtual reality, and its continued pursuit of artificial intelligence, Facebook has quickly become one of the most advanced technology research centers in the world."
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| Photo: Popular Science |
It's not alone: companies like Google and even IBM have similar schemes, and collectively, the developments across the field have accelerated to the point that artificial intelligences will surely shape the way humans interact with computers. In fact, they already do — but quietly, behind the curtains. Facebook has great interest in this technology, servicing 1.5 billion users monthly. The company tackles the problem of emulating general intelligence — that is, getting computers to think less like linear, logical machines, and like us free-form humans — with a multi-prong approach. While the Facebook Artificial Intelligence Research (FAIR) team works on solving generalized AI problems, smaller groups like Language Technology and Facebook M deploy practical features to users.
The birth of artificial intelligence research at Facebook
It all started in 2013. Facebook founder and CEO Mark Zuckerberg, chief technology officer Mike Schroepfer, and other company leadership were taking stock in the company’s accomplishments since launching almost a decade before, and looking to see what would allow them to thrive throughout the next 10 or 20 years.
Facebook had already been using machine learning on its hugely popular social network to decide what users would see on their News Feeds, but it was simple compared to the cutting-edge neural networks of the time.
Some Facebook engineers had also been experimenting with convolutional neural networks (CNNs), a powerful flavor of machine learning that is now popularly used for identifying images. Zuckerberg was impressed by the potential of artificial intelligence, even in its early stages, so he hired an engineer out of Google Brain, Marc’Aurelio Ranzato. Then, he went to the source: the inventor of CNNs, Yann LeCun.
Yann LeCun, who now serves as the director of FAIR, comes from a storied tenure of artificial intelligence research. He began his work in Bell Labs (founded by telephone father Alexander Graham Bell, and known for its experiments across myriad fields in telecommunications and technology) as a researcher starting in 1988, then moving to become a department head at AT&T Labs until developing 2003, when he began to teach at New York University. The modern convolutional neural network is a culmination of work throughout LeCun’s career. Ever wonder how an ATM can read your check? That was LeCun, whose early work included a neural network simulator called “SN” and deployed in 1996...
Assembling The Team The team subsequently tasked with creating the future of Facebook is a small, only about 30 research scientists and 15 engineers in total. Labor is divided over three branches: Facebook AI Research’s main office is in New York City’s Astor Place, where LeCun operates with a team of about 20 engineers and researchers. A similar number staffs the Menlo Park branch, and as of June, FAIR has opened a smaller Paris office of about 5 to collaborate with INRIA, the French Institute for Research in Computer Science and Automation. There are others that work within Facebook on AI deployment, like the Language Technology team; FAIR is the research arm.
These researchers and engineers come from all over the tech industry, and many have previously collaborated with LeCun. High-level artificial intelligence research isn’t an enormous field, and many of LeCun’s pupils have gone on to seed AI startups, which would be absorbed into larger companies like Twitter...
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| Rob Fergus, right, stands among FAIR researchers at Facebook's New York
City office. Fergus' work is concerned with the visual element of
artificial intelligence. Photo: Popular Science |
Rob Fergus, a veteran of NYU and MIT’s Computer Science and Artificial Intelligence Lab, leads the AI research team concerned with vision. His team’s work that can already been seen in the automatic tagging of photos, but Fergus says the next step is video. Lots of video is “lost” in the noise because of a lack of metadata, or it’s not accompanied by any descriptive text. AI would “watch” the video, and be able to classify video arbitrarily.
This has major implications for stopping content Facebook doesn’t want from getting onto their servers—like pornography, copyrighted content, or anything else that violates their terms of service. It also could identify news events, and curate different types of video category. Facebook has traditionally farmed these tasks out to contracted companies, so this could potentially play a role in mitigating costs.
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Source: Popular Science
