Facebook Builds The ‘World’s Best’ Artificial Intelligence Lab Content User Generated

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.

Dave Gershgorn/ Popular Science Yann LeCun, director of FAIR at Facebook, mainly works out of the company’s New York City offices, so he can also continue to teach at NYU.

“I expect you to build the best research lab in AI in the world.”

“I started talking with Schroepfer and Mark, and I guess they liked what I told them,” LeCun said in an interview with Popular Science. “And then they tried to convince me to run it…When someone like Mark comes to you and says ‘Oh, okay, you pretty much have carte blanche. You can put together a world-class research lab and I expect you to build the best research lab in AI in the world.’ I’ll say,’Hmm, interesting challenge.’”

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.

Dave Gershgorn/ Popular Science From left, Leon Bottou, Yann LeCun, and Rob Fergus work in their corner Facebook’s New York City office.

But that’s not to say that there hasn’t been progress made. Right now, LeCun is excited about work on a “memory” network that can be integrated into present convolutional neural networks, giving them the ability to retain information. He likens the new mode of memory retention to short term and long term memory in the brain, governed by the hippocampus and cerebral cortex respectively. (LeCun actually detests CNNs being compared to brains, instead preferring a model of a black box with 500 million knobs.)

The memory module allows researchers to tell the network a story, and then have it answer questions about the story later.

For the story, they used J.R.R. Tolkein’s Lord of the Rings Well, not the entire book, but short summaries of major plot points. (“Bilbo took the ring.”) When asked questions about where the ring was at certain points in the story, the AI would be able to answer in short, correct answers. This means it “understands” relationships between objects and time, according to CTO Mike Schroepfer, who stressed this technology’s ability to help Facebook show you what you want to see with higher accuracy.

“By building systems that understand the context of the world, understand what it is you want, we can help you there,” Schroepfer said at a developer presentation in March. ”We can build systems that make sure all of us spend time on the things we care about.”

The FAIR team is developing this context around a project called “Embed the World.” To help machines better understand reality, the FAIR team is teaching them to represent the relationships between everything in vectors: images, posts, comments, photos, and video. The neural network is creating an intricate web of content that groups like pieces of media, and distances different ones. There’s a helpful video to visualize this: