In Canada's AI renaissance, Vancouver has been the forgotten city.
The lower mainland is catching up with Montreal, Toronto and Edmonton as its universities and entrepreneurs bring some west coast savvy to the artificial intelligence race. And in British Columbia, that means computer vision, Cascadia and the confidence of Hollywood North.
Vancouver is home to 130 AI startups, as well as four major investor groups, four incubators and four public research labs focused on AI. The hometown companies include Vision Critical, an OMERS-funded venture focused on consumer patterns; Finn.ai, which is applying AI to day-to-day banking; and Generation R Consulting, which is based at the University of British Columbia and pioneered an AI ethics assessment tool for Technical Safety BC, an organization that oversees the safe installation of technical systems and equipment across the province.
The word is out, and investors are in. In 2017, Vancouver’s own Kindred closed a $35.4 million Series B funding round led by Chinese investor Tencent. In the past month alone, Mitsubishi invested $5.8m in Spare, an AI-enabled platform for on-demand mobility and smart transportation networks and Fujitsu opened its global AI headquarters, Fujitsu Intelligence Technology, in Vancouver.
RBC added to the ecosystem this week with the official opening of a Borealis AI lab where 20 researchers are hard at work. It’s run by Greg Mori, a computer vision specialist and former head of computing science at Simon Fraser University.
Mori said the research at such universities on ethical issues like AI bias and “explainability” is working its way into the commercial development of AI in Canada. Borealis is thought to be the largest AI initiative by a Canadian company, with other labs in Montreal, Toronto, Waterloo and Edmonton.
Mori noted that Vancouver is rare among cities to have two world-class computing science schools, at SFU and UBC. Moreover, “there’s an interplay here between universities and industries that’s really important,” he said at the opening of the Borealis lab in Yaletown.
With more than 300 graduate and 2,000 undergraduate students, SFU is ranked among the world’s top 50 computing science schools, and among Canada’s top 5 based on citations per faculty member.
UBC’s main AI research organization, Centre for AI Decision-making and Action, involves more than 50 researchers across five faculties. Its Computer Vision and Robotics research group created Scale-invariant feature transform (SIFT), a widely-used feature detection algorithm in computer vision.
There’s even a new player in town: Northeastern University is adding a Vancouver location to its expanding global campus network, planning graduate programs and work integrated learning opportunities that support B.C.’s rapidly growing expertise in AI and data visualization.
Mori has been developing the Vancouver lab since last September, with a particular focus on computer vision, his academic specialty. It’s a subfield of machine learning that trains computers to see, process, and understand images such as videos and photographs, to identify and distinguish objects – a cat versus a dog, for instance – and even track motion to predict outcomes, such as the likelihood of a player taking a shot in basketball.
The computer vision movement is building on Vancouver’s natural ties with the Seattle area – Microsoft, Amazon, Boeing – and the larger Cascadia region that reaches down to Silicon Valley. It’s also deeply rooted in the lower mainland’s history in video games, moviemaking and post-production, which earned it the nickname of “Hollywood North.”
Vancouver is the world’s largest economic cluster for visual effects and animation, with more than 60 studios, including Sony Picture Imageworks, Industry Light & Magic (ILM), DHX Media and Image Engine, which was behind Drogon’s iconic attack on the loot train in season seven of Game of Thrones. The city is also thriving with video game clusters built around Electronic Arts, Microsoft and Nintendo Education.
As visual media transitions to virtual and augmented realities – and brings with it new orders of data that can feed AI applications – the digital power to transform entire industries may be profound. It’s part of the logic of the federal government’s $153-million commitment to a Digital Technology Supercluster that is projected to generate more than $5 billion in economic output and 13,500 new jobs over the next decade.
Canada could use that kind of integration between academic research and commercial application in AI:
- While Canada was third in the world (after the US and China) for AI scholars with academic publications, we were ninth for patents filed
- We ranked last out of 10 countries for AI deployment, with just 31% of adopters claiming success compared to 51% globally
- Only 17% of Canadian businesses reported using AI technologies over the last year – a number that has barely changed since 2014, when it was 16%, according to the 2018 Deloitte survey of 1,000 Canadian citizens and 2,500 businesses found
- 67% of those firms spent less than $5 million on AI in the 2017-2018 fiscal year
- Only 8% of companies planned to increase AI spending by more than 20% in upcoming year
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