In 2017, Uber decided that if it was going to come out on top in the crowded autonomous vehicle field, it needed help making its self-driving cars smarter and less expensive. The California-based global transportation company headed straight to Toronto, Ontario.

With research centres already devoted to driverless car technology in Pittsburgh and San Francisco, what did Toronto offer Uber that it didn't already have?

Ontario leads the AI revolution

"Leadership in artificial intelligence," says Raquel Urtasun, the University of Toronto computer scientist Uber tapped to head its new Advanced Technology Group. “Toronto, and Canada, for the past two decades have been at the forefront of AI, and that's the expertise we're bringing to Uber.”

Urtasun, who also holds a Canada Research Chair in machine learning (teaching computers how to think) and computer vision (helping computers perceive videos and photos), is a star in the field – and a big catch for Uber.

Her research at the university is focused on making self-driving cars an affordable reality by programming inexpensive sensors to be smarter. If successful, they will replace the laser-based (LIDAR) sensor used in today's self-driving car prototypes, which, at an average cost of US $80,000 per sensor puts autonomous cars – including Uber's – out of the reach of the average consumer.

Urtasun is confident that she, and the growing team of researchers and engineers she's attracting to Uber's new research group, will prevail.

A white Uber self-driving car parked on a Toronto street
Uber has been test driving autonomous cars on Toronto streets since August, 2017

Urtasun's fascination with artificial intelligence began as an undergrad at Spain's Universidad Pública de Navarra. She went on to do her PhD at École Politechnique Fédérale (EPFL) in Lausanne, Switzerland followed by post-doc work at MIT and UC Berkeley before being lured to Toronto four years ago.

"I was drawn by the depth of the AI expertise at the University of Toronto."

That depth is thanks, in large part, to U of T emeritus professor Geoffrey Hinton, a pioneer in the strain of AI known as neural networks, which involves setting up computer systems to mimic the human brain – making it possible for computers to learn. Hinton's work on “neural nets” was recognized and supported early on by the Canadian government.

"Ontario has become a leading centre for AI, particularly in the field of deep learning, because of early funding by the Canadian Institute for Advanced Research and the Natural Sciences and Engineering Research Council of Canada," says Hinton. "That produced world-leading researchers, who today, are training the next generation, with significant financial support from the Canadian and Ontario governments and industry, all of which recognized that we have something really special here."

Ontario invests to keep its AI advantage

Ontario is determined to capitalize on its formidable AI expertise in a bid to become, among other things, a world-leading hub for CV/AV development.

In March, 2017, the Ontario government announced a $50-million investment in Toronto's Vector Institute for Artificial Intelligence. Also supported by the Canadian government and more than 30 corporations – Uber among them – Vector will build on Ontario's outstanding pool of globally recognized AI expertise by training, attracting and retaining more top researchers who will also have the flexibility to work on commercial applications with companies or in their own startups.

And to accelerate the evolution and deployment of self-driving cars, the government has also created the Autonomous Vehicle Innovation Network (AVIN) to develop, test, demonstrate and validate new connected and autonomous vehicle technology.

"It's a very exciting time to be in the auto industry, particularly here in Ontario where we're on the front lines of self-driving car technology," says Urtasun. "That I've fallen in love with Ontario is a bonus."

February 14, 2018
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