Jordan Jacobs and Tomi Poutanen are co-founders and co-CEOs of Layer 6 AI. Richard Zemel is a machine learning professor at the University of Toronto. Geoffrey Hinton is a University of Toronto professor emeritus and VP engineering fellow at Google. Ed Clark is a former TD Bank CEO and is business adviser to the Premier of Ontario.
A new form of Artificial Intelligence is about to transform our world. The impact AI will have is often compared to the advent of the Internet. Others say AI will be as transformative as the discovery of electricity.
We are already seeing extraordinary changes. Now, anyone with a smartphone can have real-time universal language translation, for free. Soon, self-driving cars and trucks will be ubiquitous, with Tesla, Google, Uber, Apple and many traditional car companies competing to provide the self-driving fleets that are expected over the next five to 10 years. Similarly, the application of AI technologies will make health care proactive, predictive and personalized. Over the coming years, AI will touch every industry, from finance to farming, from aerospace to manufacturing. Countries that lead in AI research and application are expected to see a doubling of their economic growth rates.
Amazingly, the technology at the heart of these breakthroughs, Deep Learning, was largely developed in Canada. In fact, many of the world’s AI leaders in both academia and at the world’s most advanced technology companies – Google, Facebook, Apple, Open AI – came through the machine learning lab in the computer science department at the University of Toronto as PhD students, postdoctoral fellows or faculty.
While we should celebrate the alumni who have gone on to lead the world at companies and institutions elsewhere, we should also strive to keep many of our best students in Canada, where they can contribute to Canada’s rich technology ecosystems.
When we asked AI research leaders why they leave, their top concern was rarely compensation. They want to perform world-leading research and solve meaningful problems. To do so effectively requires collaborative efforts of a critical mass of scientists and engineers, significant computer resources and, most importantly, access to data. Why? Because for a machine to “think” intelligently, it must be trained with lots of data.
Deep Learning is a type of machine learning that makes use of layers of artificial neurons to mimic the way our brains work. Like our brains, machines learn by processing huge volumes of sensory and other data and deciding which information is relevant for a particular outcome. The recent advances in AI are the result of improvements in computing power and ever-growing datasets. Large U.S. and other foreign companies have enormous troves of data, and open it to their AI teams to use for research.
To date, there are not enough graduates to entice those companies to add research labs in Toronto. Key companies say that if we graduated more data scientists trained in machine learning, they would open labs here.
Some large companies have recently moved their AI divisions to Toronto, including Thomson Reuters and General Motors, with the intention of hiring hundreds of data scientists. Many of Canada’s largest companies have also stated a desire to hire thousands more data scientists in the coming years. Demand for talent already far outstrips supply, and the gap will only grow.
There is one solution that will help keep the best minds in Canada, solve the current and future talent gap for domestic businesses, lure investment from foreign data-rich companies, and ensure Canada leads future AI breakthroughs: We must build a world-leading AI Institute in Toronto. We are leading an effort to make this happen.
The goals of the institute are to: 1) be a world-leading centre for AI research; 2) graduate the most machine-learning PhDs and masters students globally; and 3) become the engine for an AI supercluster that drives the economy of Toronto, Ontario and Canada. The institute would be independent and affiliated with the University of Toronto but open to researchers from other schools. Collaboration agreements with other universities would strengthen AI capability throughout Canada.
Critically, institute researchers will be encouraged to collaborate with research teams from a broad set of companies, and launch their own business startups, working with stellar programs and organizations such as Creative Destruction Lab, MaRS, Velocity, Communitech, the forthcoming NextAI, and other excellent domestic incubators.
Creating the institute will ensure Toronto tops the list of global destinations for researchers looking to establish academic careers, for students seeking AI educations or companies building and looking to staff AI labs. Current global geopolitics make Canada especially attractive.
What is required to make this vision a reality?
Significant funding: Foreign AI research is supported by enormous funding. For example, Open AI in Silicon Valley (led by a U of T graduate) has a $1-billion (U.S.) commitment from its backers, including Tesla and SpaceX founder Elon Musk. To compete, a very significant funding commitment is necessary to signal our intention to lead in AI research over the long term and to attract the world’s leading minds – faculty, post-docs and grad students.
Industrial partnerships: AI is a field of science with extensive immediate applications. An academic research institute will support the hiring needs of domestic companies and attract significant foreign investment as companies build AI labs in Toronto.
One modern facility: Current University of Toronto machine-learning researchers are spread across many departments in disparate buildings already at capacity. The institute faculty and students must be brought together in one modern facility that supports its expansion and facilitates interaction with industry and other researchers from across Canada and around the world.
We say we want to be an innovation nation. Let’s seize this special opportunity to lead the world.Report Typo/Error
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