This is event is co-sponsored by the Department of Computer Science's Distinguished Lecture Series.

Yann LeCun, Facebook AI Research & New York University

TITLE: The Power and Limits of Deep Learning and AI

ABSTRACT: Deep learning is at the root of revolutionary progress in visual and auditory perception by computers, and is pushing the state of the art in natural language understanding, dialog systems and language translation. Deep learning systems are deployed everywhere from self-driving cars to content filtering, search, and medical image analysis. Almost all of the deployed applications of deep learning use supervised learning in which the machine is trained to predict human-provided annotations. While reinforcement learning has been very successful in games and a few real-world applications, it requires an inordinately large number of trials to learn complex concepts. In contrast, humans and animals learn vast amounts of knowledge about the world by observation, with very little feedback from intelligent teachers and very few interactions with the environment. Humans (and many animals) construct complex predictive models of the world that give them "common sense", allowing them to interpret percepts, to fill in missing information, to predict future events, and to plan a course of actions. Enabling machines to learn predictive models of the world is a major obstacle towards significant progress in AI. I will describe a number of promising approaches towards learning predictive models that can handle the intrinsic uncertainty of the natural world, particularly variations of adversarial training.

Yann LeCun is Director of AI Research at Facebook and Silver Professor at New York University, affiliated with the Courant Institute, the Center for Neural Science and the Center for Data Science, for which he served as founding director until 2014. He received an EE Diploma from ESIEE (Paris) in 1983, a PhD in Computer Science from Université Pierre et Marie Curie (Paris) in 1987. After a postdoc at the University of Toronto, he joined AT&T Bell Laboratories. He became head of the Image Processing Research Department at AT&T Labs-Research in 1996, and joined NYU in 2003 after a short tenure at the NEC Research Institute. In late 2013, LeCun became Director of AI Research at Facebook, while remaining on the NYU Faculty part-time. He was visiting professor at Collè ge de France in 2016. His research interests include machine learning and artificial intelligence, with applications to computer vision, natural language understanding, robotics, and computational neuroscience. He is best known for his work in deep learning and the invention of the convolutional network method which is widely used for image, video and speech recognition. He is a member of the US National Academy of Engineering, the recipient of the 2014 IEEE Neural Network Pioneer Award, the 2015 IEEE Pattern Analysis and Machine Intelligence Distinguished Researcher Award, the 2016 Lovie Award for Lifetime Achievement, and a honorary doctorate from IPN, Mexico.