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Learning in Machines and Brains

Principal Investigator:
  • Yoshua Bengio, Université de Montréal
Team Members:
  • Yann Lecun, Facebook AI Research
  • Francis Bach, Inria
  • Aaron Courville, Université de Montréal
  • Nando de Freitas, University of Oxford
  • James DiCarlo, Massachusetts Institute of Technology
  • David Fleet, University of Toronto
  • Brendan Frey, University of Toronto
  • Surya Ganguli, Stanford University
  • Zaid Harchaoui, Inria
  • Aapo Hyvarinen, University of Helsinki
  • Hugo Larochelle, Université de Sherbrooke
  • Honglak Lee, University of Michigan
  • Christopher Manning, Stanford University
  • Roland Memisevic, Université de Montréal
  • Andrew Ng, Stanford University
  • Bruno Olshausen, University of California, Berkeley
  • Ruslan Salakhutdinov, University of Toronto
  • Mark Schmidt, University of British Columbia
  • Eero Simoncelli, New York University
  • Josef Sivic, Inria
  • Ilya Sutskever, OpenAI
  • Richard Sutton, University of Alberta
  • Antonio Torralba, Massachusetts Institute of Technology
  • Pascal Vincent, Université de Montréal
  • Yair Weiss, The Hebrew University of Jerusalem
  • Max Welling, University of Amsterdam
  • Christopher Williams, The University of Edinburgh
  • Richard Zemel, University of Toronto

Project Overview

The program in Learning in Machines & Brains (formerly known as Neural Computation & Adaptive Perception) is revolutionizing the field of artificial intelligence, and creating computers that think more like us – that can recognize faces, understand what is happening in a picture or video, and comprehend the actual meaning of language. The result will be computers that are not only powerful but intelligent, and that will be able to do everything from conduct a casual conversation to extract meaning from massive databases of information.

The program is co-directed by Yoshua Bengio of the Universite de Montreal and Yann LeCun of New York University. The program helping to revolutionize the field of artificial intelligence and create computers that can think more like people ­– that can recognize faces, understand what is happening in a picture or video, and comprehend the meaning of language. Research by members of the program has helped usher in a new generation of powerful AI, and members work closely with top technology firms including Google, Facebook and Microsoft.