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Learning in Machines & Brains

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How do we understand intelligence and build intelligent machines?

Artificial Intelligence has created a global industry that touches on every business sector imaginable — from improved security of our banking to innovation in farming, education, law enforcement, health care, space exploration and customer service.

optimal stimuli
How Google sees you and your cat. These “optimal stimuli” for both human and cat faces resulted from training a deep learning network on more than 10 million pictures

The Learning in Machines & Brains program played a major part in the revolution by examining how artificial neural networks could be inspired by the human brain, and developing the powerful technique of deep learning.

Now the program is expanding our understanding of the fundamental computational and mathematical principles that enable intelligence through learning, whether in brains or in machines.

Current AI systems are limited in their ability to understand the world around us. This program attacks those limitations by going back to basic questions rather than focusing on short-term technological advances. This fundamental approach has the dual benefit of improving the engineering of intelligent machines and explaining intelligence.

Neural Network
A deep learning network takes in raw information, such as values for individual pixels, in the top input layer, and processes it through one or more hidden layers, with each layer adding a further level of abstraction.

SELECTED PAPERS

Hinton, G. E., Osindero, S. and Teh, Y. (2006). “A fast learning algorithm for deep belief nets.” Neural Computation, 18, pp 1527-1554. PDF

Y. Bengio and P. Lamblin and D. Popovici and H. Larochelle, “Greedy Layer-Wise Training of Deep Networks,” Neural Information Processing Systems Proceedings (2006). PDF

Salakhutdinov, R. and Hinton, G., “Learning a Nonlinear Embedding by Preserving Class Neighbourhood Structure,” Proceedings of the Eleventh International Conference on Artificial Intelligence and Statistics, 412-419 (2007). PDF

Graves, A., Mohamed, A., Hinton, G. E., “Speech Recognition with Deep Recurrent Neural Networks,” 39th International Conference on Acoustics, Speech and Signal Processing, Vancouver (2013). PDF

Yann LeCun, Yoshua Bengio and Geoffrey Hinton. (2015). “Deep Learning.” Nature, 521, pp 436–444. ABSTRACT

Path to Societal Impact

We invite experts in industry, civil society, healthcare and government to join fellows in our Learning in Machines & Brains program for in-depth, cross-sectoral conversations that drive change and innovation.

Social scientists, industry experts, policymakers and CIFAR fellows in the Learning in Machines & Brains program are addressing complex ethical issues in research and training environments and in the implementation of AI.

Areas of focus:

  • Exploring existing and future societal implications of AI research.
  • Addressing issues in AI research and implementation, including privacy, accountability, and transparency.

Do you want to shape the future of ethical AI? 

Contact: Fiona Cunningham, Director of Innovation

Founded

2004

Renewal Dates

2008, 2014, 2019

Supporters

Alfred P. Sloan Foundation, Bristol Gate Capital Partners, Facebook

Interdisciplinary Collaboration

Computer science, including artificial intelligence, deep learning, reinforcement learning
Neuroscience
Bioinformatics
Computational biology
Statistics
Data science
Psychology

CIFAR Contact

Rachel Parker

Fellows & Advisors

Program Directors

Yoshua Bengio

Program Co-Director
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
IVADO
Mila
Université de Montréal
Canada

Yann LeCun

Program Co-Director

Learning in Machines & Brains
Chief AI Scientist
Facebook Professor
New York University
United States
Fellows

Marc G. Bellemare

Associate Fellow
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
Google Brain
McGill University
Mila
Canada

Léon Bottou

Fellow

Learning in Machines & Brains
Facebook AI Research
New York University
France

Kyunghyun Cho

Fellow
CIFAR Azrieli Global Scholar 2017-2019

Learning in Machines & Brains
New York University
United States

Aaron Courville

Fellow
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
Mila
Université de Montréal
Canada

Emmanuel Dupoux

Fellow

Learning in Machines & Brains
School for Advanced Studies in the Social Sciences (EHESS)
France

Rob Fergus

Associate Fellow

Learning in Machines & Brains
New York University
United States

Chelsea Finn

Fellow

Learning in Machines & Brains
Stanford University
United States

Nando de Freitas

Associate Fellow

Learning in Machines & Brains
University of Oxford
United Kingdom

Alona Fyshe

Fellow
Canada CIFAR AI Chair
CIFAR Azrieli Global Scholar 2016-2018

Learning in Machines & Brains
Pan-Canadian AI Strategy
Amii
University of Alberta
Canada

Surya Ganguli

Fellow

Learning in Machines & Brains
Stanford University
United States

Aapo Johannes Hyvärinen

Fellow

Learning in Machines & Brains
University of Helsinki
Finland

Konrad Kording

Fellow

Learning in Machines & Brains
University of Pennsylvania
United States

Simon Lacoste-Julien

Associate Fellow
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
Mila
Université de Montréal
Canada

Hugo Larochelle

Associate Fellow
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
Google Brain
Mila
Université de Montréal
Canada

Christopher Manning

Fellow

Learning in Machines & Brains
Stanford University
United States

Doina Precup

Fellow
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
McGill University
Mila
Canada

Blake Richards

Fellow
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
McGill University
Mila
Canada

Bernhard Schölkopf

Fellow

Learning in Machines & Brains
ETH Zürich
Max Planck Institute for Intelligent Systems
Germany

Richard S. Sutton

Associate Fellow
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
Amii
DeepMind
University of Alberta
Canada

Raquel Urtasun

Associate Fellow

Learning in Machines & Brains
Uber ATG
University of Toronto
Canada

Pascal Vincent

Associate Fellow
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
Mila
Université de Montréal
Canada

Max Welling

Fellow

Learning in Machines & Brains
University of Amsterdam
The Netherlands

Richard Zemel

Canada CIFAR AI Chair

Pan-Canadian AI Strategy
University of Toronto
Vector Institute
Canada

Joel Zylberberg

Associate Fellow
CIFAR Azrieli Global Scholar 2016-2018

Learning in Machines & Brains
York University
Canada
Advisors

Pieter Abbeel

Advisor

Learning in Machines & Brains
University of California Berkeley
United States

Raia Hadsell

Advisor

Learning in Machines & Brains
DeepMind
United Kingdom

Joelle Pineau

Advisor
Canada CIFAR AI Chair

Learning in Machines & Brains
Pan-Canadian AI Strategy
McGill University
Mila
Canada

Terrence J. Sejnowski

Advisor

Learning in Machines & Brains
Salk Institute for Biological Studies
United States

Sebastian Seung

Advisory Committee Chair

Learning in Machines & Brains
Princeton University
Samsung
United States

Christopher K. I. Williams

Advisor

Learning in Machines & Brains
University of Edinburgh
United Kingdom
CIFAR Azrieli Global Scholars

Stefan Bauer

CIFAR Azrieli Global Scholar 2020-2022

Learning in Machines & Brains
Max Planck Institute for Intelligent Systems
Germany

Kyunghyun Cho

Fellow
CIFAR Azrieli Global Scholar 2017-2019

Learning in Machines & Brains
New York University
United States

Marzyeh Ghassemi

Canada CIFAR AI Chair
CIFAR Azrieli Global Scholar 2020-2022

Learning in Machines & Brains
Pan-Canadian AI Strategy
University of Toronto
Vector Institute
Canada

Andrew Saxe

CIFAR Azrieli Global Scholar 2020-2022

Learning in Machines & Brains
University of Oxford
United Kingdom

Graham Taylor

Canada CIFAR AI Chair
CIFAR Azrieli Global Scholar 2016-2018

Learning in Machines & Brains
Pan-Canadian AI Strategy
University of Guelph
Vector Institute
Canada

Joel Zylberberg

Associate Fellow
CIFAR Azrieli Global Scholar 2016-2018

Learning in Machines & Brains
York University
Canada

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