Meet the world's leading pioneers advancing deep learning research in the 'Silicon Valley of Deep Learning'.

Speakers

• Yoshua Bengio

  Full Professor

  Université de Montréal

• Yann LeCun

  Director of AI Research

  Facebook

• Geoffrey Hinton

  Professor

  University of Toronto

• Aaron Courville

  Assistant Professor

  University of Montreal

• Roland Memisevic

  Chief Scientist

  Twenty Billion Neurons

• Bryan Russell

  Research Scientist

  Adobe Research

• Lisha Li

  Principal

  Amplify Partners

• Herke van Hoof

  Post-Doctoral Fellow

  McGill University

• Alex Acero

  Senior Director of Siri

  Apple

• Shyam Thyagaraj

  Managing Director in Technology

  Accenture

• Eric Humphrey

  Research Scientist

  Spotify

• Joan Bruna

  Assistant Professor

  New York University

• Ira Kemelmacher-Shlizerman

  Assistant Professor/Researcher

  Allen School of Computer Science/Facebook

• David Sadek

  Vice President, Research & Technology

  Thales

• Richard Zemel

  Co-Founder & Director of Research

  Vector Institute

• Jasper Snoek

  Research Scientist

  Google Brain

• David Duvenaud

  Assistant Professor

  University of Toronto

• Sanja Fidler

  Assistant Professor

  University of Toronto

• Gaurav Kumar Singh

  ML & Deep Learning Researcher, Autonomous Vehicles

  Ford Motor Company

• Hugo Larochelle

  Research Scientist

  Google Brain

• Raquel Urtasun

  Head

  Uber ATG/University of Toronto

• Kyunghyun Cho

  Assistant Professor of Computer Science and Data Science

  New York University

• Andrea Lodi

  Professor

  École Polytechnique de Montréal

• Jianchao Yang

  Lead Research Scientist

  Snap Inc

• Michael Gschwind

  Chief Engineer, Machine and Deep Learning

  IBM

• Greg Diamos

  Senior Researcher

  Baidu

• Joelle Pineau

  Associate Professor

  McGill University

• More Speakers Coming Soon

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Get to know the speakers

“Today’s models can be trained on huge quantities of data, but that’s not enough,” says Bengio, who together with LeCun and Google’s Geoffrey Hinton is one of the original musketeers of deep learning. “We need to discover learning algorithms that can take better advantage of all this unlabeled data that’s sitting out there.”

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Yann LeCun once built an AI chip called ANNA. But he was 25 years ahead of his time. He and several other researchers designed this chip to run deep neural networks—complex mathematical systems that can learn tasks on their own by analyzing vast amounts of data—but ANNA never reached the mass market.

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There are some estimates that five percent of all AI talent within the private sector are currently employed by Google. Perhaps no one among that rich talent pool has as deep a set of perspectives as Geoff Hinton. He has been involved in AI research since the early 1970s, which means he got involved before the field was really defined.

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Researchers have developed a machine learning algorithm that can turn audio clips into realistic, lip-synced videos. A video shows former US president Barack Obama apparently speaking on a number of subjects including terrorism, though the clips were artificially generated using existing video addresses.

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Computer scientists from the University of Toronto have created a software program that helps users avoid fashion faux pas. Raquel Urtasun and Sanja Fidler, along with colleagues in Spain, designed an algorithm that analyzes a person’s photograph to determine whether the wearer’s outfit is stylish. It also suggests ways to improve the ensemble and the subject’s overall appeal.

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"A Deep and Autoregressive Approach for Topic Modeling of Multimodal Data". In this paper Hugo Larochelle explores how to successfully apply and extend DocNADE to multimodal data, such as simultaneous image classification and annotation.

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