Shares “Nobel Prize of Computing” with Colleagues at the University of Montreal and the University of Toronto

Yann LeCun, a professor at New York University’s Courant Institute of Mathematical Sciences, has been awarded the ACM A.M. Turing Award for his breakthroughs in artificial intelligence and, specifically, deep learning and convolutional neural networks—the foundation of modern computer vision, speech recognition, speech synthesis, image synthesis, and natural language processing.

LeCun, also vice president and chief AI scientist at Facebook and founding director of NYU’s Center for Data Science, shares the prize, given by the Association for Computing Machinery (ACM), with Yoshua Bengio, a professor at the University of Montreal, and Geoffrey Hinton, a professor emeritus at the University of Toronto and a vice president and engineering fellow at Google.

The trio, whom ACM called the “Fathers of the Deep Learning Revolution” in its announcement, developed conceptual foundations for the field. Working together and separately, they identified phenomena through experiments and contributed engineering advances that revealed the practical advantages of deep neural networks.

“Artificial intelligence is now one of the fastest-growing areas in all of science and one of the most talked-about topics in society,” said ACM President Cherri M. Pancake. “The growth of and interest in AI is due, in no small part, to the recent advances in deep learning for which Bengio, Hinton, and LeCun laid the foundation. These technologies are used by billions of people. Anyone who has a smartphone in their pocket can tangibly experience advances in natural language processing and computer vision that were not possible just 10 years ago. In addition to the products we use every day, new advances in deep learning have given scientists powerful new tools—in areas ranging from medicine, to astronomy, to materials science.”

The ACM A.M. Turing Award, often referred to as the “Nobel Prize of Computing,” carries a $1 million prize, with financial support provided by Google, Inc., which will be shared equally among the winners. It is named for Alan M. Turing, the British mathematician who articulated the mathematical foundation and limits of computing.

“Deep neural networks are responsible for some of the greatest advances in modern computer science, helping make substantial progress on long-standing problems in computer vision, speech recognition, and natural language understanding,” said Jeff Dean, Google Senior Fellow and senior vice president, Google AI. “At the heart of this progress are fundamental techniques developed starting more than 30 years ago by this year’s Turing Award winners, Yoshua Bengio, Geoff Hinton, and Yann LeCun. By dramatically improving the ability of computers to make sense of the world, deep neural networks are changing not just the field of computing, but nearly every field of science and human endeavor.”

The use of multi-layer artificial neural networks as a tool to help computers recognize patterns and simulate human intelligence had been introduced in the 1980s. But between the late 1990s and mid 2000s, LeCun, also a professor at NYU's Center for Data Science, Hinton, and Bengio were among a small group who remained committed to this approach.

“Though their efforts to rekindle the AI community’s interest in neural networks were initially met with skepticism, their ideas recently resulted in major technological advances, and their methodology is now the dominant paradigm in the field,” ACM said in announcing this year’s prize.

The term “neural networks” refers to systems composed of layers of computing elements called “neurons” that are simulated in a computer. These “neurons” influence one another via weighted connections. By changing the weights on the connections (i.e., “training” the network), it is possible to change the computation performed by the neural network. LeCun, Hinton, and Bengio recognized the importance of building deep networks using many layers—i.e., “deep learning.”

LeCun’s development of convolutional neural networks has helped to make deep learning trainable for practical tasks—he was the first to train such a system to read images of handwritten digits. Today, convolutional neural networks are used in a wide variety of applications, including autonomous driving, medical image analysis, voice-activated assistants, and information filtering.

LeCun, Bengio, and Hinton will formally receive the 2018 ACM A.M. Turing Award at ACM’s annual awards banquet on Saturday, June 15, in San Francisco.

Additional Media Contact:

Jim Ormond

ACM

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ormond@hq.acm.org

Yann LeCun Bio

Yann LeCun is Silver Professor of Computer Science at New York University’s Courant Institute of Mathematical Sciences, founding director of NYU’s Center for Data Science, and vice president and chief AI scientist at Facebook. He received a Diplôme d'Ingénieur from the Ecole Superieure d'Ingénieur en Electrotechnique et Electronique (ESIEE), and a PhD in computer science from Université Pierre et Marie Curie. His honors include being a member of the US National Academy of Engineering; Doctorates Honoris Causa, from IPN Mexico and École Polytechnique Fédérale de Lausanne (EPFL); the Pender Award, University of Pennsylvania; the Holst Medal, Technical University of Eindhoven & Philips Labs; the Nokia-Bell Labs Shannon Luminary Award; the IEEE PAMI Distinguished Researcher Award; and the IEEE Neural Network Pioneer Award. He was also selected by Wired magazine for “The Wired 100--2016’s Most Influential People” and its “25 Geniuses who are Creating the Future of Business.” LeCun is a co-director (with Yoshua Bengio) of the Learning in Machines and Brains program of the Canadian Institute for Advanced Research (CIFAR). LeCun, an affiliated faculty member in the Department of Electrical and Computer Engineering at NYU’s Tandon School of Engineering and an associated faculty member in NYU’s Center for Neural Science, is also a co-founder and former Member of the Board of the Partnership on AI, a group of companies and nonprofits studying the societal consequences of AI.

About the ACM A.M. Turing Award

The A.M. Turing Award (amturing.acm.org) was named for Alan M. Turing, the British mathematician who articulated the mathematical foundation and limits of computing, and who was a key contributor to the Allied cryptanalysis of the Enigma cipher during World War II. Since its inception in 1966, the Turing Award has honored the computer scientists and engineers who created the systems and underlying theoretical foundations that have propelled the information technology industry.

About ACM

ACM, the Association for Computing Machinery (www.acm.org), is the world’s largest educational and scientific computing society, uniting computing educators, researchers and professionals to inspire dialogue, share resources and address the field’s challenges. ACM strengthens the computing profession’s collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.

About the NYU Courant Institute of Mathematical Sciences

New York University’s Courant Institute of Mathematical Sciences is a leading center for research and education in mathematics and computer science. The Institute has contributed to domestic and international science and engineering by promoting an integrated view of mathematics and computation. Faculty and students are engaged in a broad range of research activities, which include many areas of mathematics and computer science as well as the application of these disciplines to problems in the biological, physical, social, and information sciences. The Courant Institute has played a central role in the development of applied mathematics, analysis, and computer science, and its faculty has received numerous national and international awards in recognition of their extraordinary research accomplishments. For more information, visit http://www.cims.nyu.edu/.