Facebook explores AI and deep learning to analyze data and behavior
December 16, 2013
LeCun, a professor at NYU’s Courant Institute of Mathematical Sciences, is a pioneer in this growing field. In the 1980s, LeCun proposed one of the early versions of the back-propagation algorithm, the most popular method for training artificial neural networks.
He is also one of the leading scientists in “deep learning”—a branch of machine learning in which researchers aim to emulate humans’ auditory and visual systems. Deep learning methods are used for a wide variety of applications—including speech and image recognition—by companies such as Google, NEC, Microsoft, IBM, and Baidu.
LeCun’s recent research projects include the application of such “deep learning” methods to visual scene understanding, visual navigation for autonomous ground robots, driverless cars, and small flying robots, speech recognition, and applications in biology and medicine.
LeCun will oversee the development of deep-learning tools that can help Facebook analyze data and behavior on its massively popular social networking service — and ultimately revamp the way the thing operates, Wired reports.
“With deep learning, Facebook could automatically identify faces in the photographs you upload, automatically tag them with the right names, and instantly share them with friends and family who might enjoy them too. Using similar techniques to analyze your daily activity on the site, it could automatically show you more stuff you wanna see.”