Facebook's giving away servers for AI: So what does it get in return? Facebook is distributing 22 high-powered GPU servers to 15 research groups across nine European countries. Just east of the Belgium capital, Brussels, Marian Verhelst's microchip research group at the University of Leuven anxiously awaits a large shipment of supercomputing servers from Facebook's Silicon Valley headquarters. Verhelst, an assistant professor of electrical engineering at the university known as KU Leuven, plans to employ the deep-learning potential of these computers to help develop more advanced processors. As part of a global research partnership to stimulate artificial-intelligence research into deep learning, Facebook is donating 22 GPU-accelerated computer servers to researchers in nine countries across Europe.
Image recognition, determining all the objects within a photo, is something Facebook's AI does with relative ease. The company's approach to machine learning is called deep learning, a popular route to AI also followed by Google and others. Deep learning employs algorithms to recognize patterns, learn from those patterns and complete sophisticated tasks. For Facebook, it could be tagging friends. For Google, it may be creating a program that plays the game Go well enough to beat human champions.
Over 25% of Facebook engineers are using a piece of software to help them leverage artificial intelligence (AI) and machine learning (ML), according to a blog post by one of the company's engineers. FBLearner Flow, as the software is known, is filled with algorithms developed by Facebook's AI/ML experts that can be accessed by more general engineers across the company to build different products. "FBLearner Flow [is] capable of easily reusing algorithms in different products, scaling to run thousands of simultaneous custom experiments, and managing experiments with ease," wrote Facebook software engineer Jeffrey Dunn, in a blog post on Monday titled "Introducing FBLearner Flow: Facebook's AI backbone." AI involves creating computers and computer software that are capable of intelligent behaviour, while machine learning can be defined as a field of study of that gives computers the potential to learn without being explicitly programmed. "FBLearner Flow is used by more than 25% of Facebook's engineering team," wrote Dunn.
Facebook is set to get an even better understanding of the 700 million people who use the social network to share details of their personal lives each day. A new research group within the company is working on an emerging and powerful approach to artificial intelligence known as deep learning, which uses simulated networks of brain cells to process data. Applying this method to data shared on Facebook could allow for novel features and perhaps boost the company's ad targeting. Deep learning has shown potential as the basis for software that could work out the emotions or events described in text even if they aren't explicitly referenced, recognize objects in photos, and make sophisticated predictions about people's likely future behavior. The eight-person group, known internally as the AI team, only recently started work, and details of its experiments are still secret.
Current deep learning technology is not enough for computers to understand language, a major figure in the field said today. The ability to learn the way people learn through observation and experience is what Facebook will use to teach chatbots and computers to carry on a conversation like a human, said Yann LeCun, the head of Facebook's artificial intelligence (AI) research lab. LeCun spoke about AI and steps being taken to make virtual assistant M stop relying on human training at the 2016 Wired Business Conference, as Wired reported. People have been a part of decisions made by Facebook's M since the bot debuted last year, before the launch of the company's bot platform. Facebook has begun research on ways to make machines understand language more independently.