Download Making artificial intelligence an everyday reality

CASE STUDY 1 — DEEP LEARNING
Making artificial
intelligence an
everyday reality
Yoshua Bengio, CIFAR Senior
Fellow and co-director is among
the many research leaders of the
program who are committed to
developing a new generation of
Deep Learning experts through an
annual summer school supported
by CIFAR.
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DEEP LEARNING
One of the most exciting areas of artificial intelligence
(AI) research focuses on “deep learning,” in which
digital neural networks extract meaning from vast
amounts of data with incredible speed and efficiency.
From Google searches among millions of images to
the voice-recognition features on Android phones,
deep learning breakthroughs that originated with
CIFAR are now reshaping technology.
Dr. Geoffrey Hinton
ARTIFICIAL INTELLIGENCE PIONEER,
GOOGLE/UNIVERSITY OF TORONTO;
FORMER DIRECTOR, CIFAR
DISTINGUISHED FELLOW
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IN THE MID-1970s, when UK-born computer scientist Geoffrey
Hinton joined the small community of researchers investigating
artificial intelligence, most of his peers were moving away from the
long-held vision of developing AI modelled on the human brain. But
the young investigator could not shake his fascination with how our
networks of neurons function, and especially how we learn to perceive patterns. He continued to focus on neural networks as a model
for computer intelligence, inventing techniques that improved their
ability to recognize patterns dramatically.
For many years Dr. Hinton’s work was outside the mainstream
of AI research, but he carried on as part of an informal network of
like-minded researchers. That network was strengthened when he
helped CIFAR create a specialized research program devoted to
Neural Computation & Adaptive Perception, now named Learning
in Machines & Brains. As director, Dr. Hinton led a handpicked
team of computer scientists, engineers, neuroscientists, biologists,
physicists and psychologists who focused their collective knowledge on exploring the full potential of what came to be called “deep
learning.”
Today CIFAR’s pioneers of deep learning represent the forefront
of AI research, as they build on their success in creating multi-layered neural networks that can process higher levels of abstraction
– and, more significantly, that can do so without human supervision.
Their work is being incorporated into everything from advanced
search applications to self-driving cars to computers with the ability
to carry on meaningful conversations. “With just a half-a-million-dollar-a-year investment from CIFAR, Hinton’s consortium of free
thinkers…have changed the face of the community that once spurned them. …In other
words, deep learning is now mainstream. ‘We
ceased to be the lunatic fringe,’ Hinton says.
‘We’re now the lunatic core.’”
Daniela Hernandez
WIRED MAGAZINE
Not surprisingly, the extraordinary potential of deep learning has
attracted innovation-driven companies that understand how fundamental research insights can be transformed into valuable applications. Today Dr. Hinton divides his time between the University of
Toronto and Google, where he is a Distinguished Researcher. His
CIFAR colleague Dr. Yann LeCun, who is now co-director of the
CIFAR program, has a similar dual role as a senior researcher at New
York University and Director of AI Research at Facebook. And CIFAR
fellow Dr. Andrew Ng, a professor of computer science at Stanford
University, is also Chief Scientist at Baidu Research.
In short, an area of inquiry that was once on the fringes of
AI is now at the heart of a technological revolution. And across
a research community that spans both academe and high-tech
leaders, there is wide acknowledgement of the vital role CIFAR
has played in making it all possible. As Dr. LeCun summed up in
a Toronto Star interview: “CIFAR had a huge impact in forming a
community around deep learning. We were outcast a little bit in the
broader machine learning community; we couldn’t get our papers
published. This gave us a place where we could exchange ideas.”
“The interest of large companies
in artificial intelligence is really
focused today on deep learning,
which was basically a CIFARfunded conspiracy.”
Dr. Yann LeCun
SENIOR FELLOW AND CO-DIRECTOR,
CIFAR PROGRAM IN LEARNING IN
MACHINES & BRAINS
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“When people said it’s irrelevant how the brain works, they
were just utterly and obviously wrong… That’s where
CIFAR, with its fundamental idea of getting the best
researchers together to exchange ideas, was crucial to
the development of deep learning.”
- Dr. Geoffrey Hinton
Using the deep learning approach,
Senior Fellow Yoshua Bengio and
Fellow Pascal Vincent developed
a neural network that allows a
computer to recognize emotion
in a human face--something that
has been difficult for computers
until now.
In 2015, the Creative Destruction Lab at the Rotman School of
Management presented CIFAR with their “Ideas” award, which
recognizes organizations that have had an impact on Canada’s
competitiveness through advancing new ideas in science and technology. CIFAR received the award for its role in supporting research
that greatly advanced artificial intelligence, in particular the deep
learning approach pioneered by CIFAR fellows Geoffrey Hinton
(University of Toronto, Google), Yann LeCun (Facebook, New York
University), Yoshua Bengio (University of Montreal) and others.
In their announcement, the Rotman School stated that “Although
there is now clear evidence that developments in this field are delivering significant economic impact and therefore research is able to
attract broad support from a wide range of industries and government funding agencies, CIFAR provided critical support for many
years when this line of scientific inquiry was considered peripheral,
risky, and unexciting among experts in the field.”
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