There was a time, 7 - 8 - 9 years ago when all the Americans who said they were moving to Canada after 2016—and didn't, decided the next best thing would be to praise Canada from their homes in Silicon Valley, U.S. of A. This included Canadian superiority in AI/machine learning.
They were half right (in AI's case it was the people, not the place).
From Observer, December 30:
Canada was once a haven for ambitious A.I. research. Its breakthroughs have since gone global—and so has its talent.
In the late 1980s, Geoffrey Hinton was a few years into teaching at Carnegie Mellon University in Pittsburgh, Pa., when he became increasingly troubled about the state of the nation he had left his home country of England for a decade prior. Hinton took issue with Ronald Reagan’s foreign policy, particularly the mining of harbors in Nicaragua, and the fact that the A.I. research he was pursuing was largely funded by the U.S. Department of Defense. So when he was presented with an opportunity to head North, he jumped at the chance.
“My wife and I were very fed up with the U.S.,” Hinton told Observer, “and Canada seemed like a good place.” Enticed to Toronto by a strong social system and a generous offer to become a fellow at the Canadian Institute for Advanced Research (CIFAR), a global research organization, Hinton made his way to the country in 1987. He’s largely stayed put ever since, picking up a Nobel Prize for his contribution to A.I. research along the way.
Hinton wasn’t alone. Decades of sustained funding for curiosity-driven research has brought scores of pioneering A.I. researchers to Canada, where a series of breakthroughs laid the foundations for the A.I. products dominating today’s tech industry. Canada built upon this momentum in 2017 when it became the first country to implement a national A.I. strategy, one that congregated much of its innovative work in three A.I. hubs spread out across Toronto, Montreal and Edmonton.
Despite the country’s contributions towards the now-booming technology, many say Canada has failed to reap the rewards of its own innovations. It isn’t just ideas that have been exported to the U.S., but much of the nation’s talent. “It’s this historic Canadian challenge of being often the inventors and pioneers of new technology, but not necessarily seeing the commercial success here,” Cam Linke, head of the Alberta Machine Intelligence Institute (Amii), told Observer.
While attempts to establish competitive A.I. companies in Canada have been largely unsuccessful over the past few decades, a combination of enhanced government funding, bolstered research institutions and changing cultural attitudes is starting to make a gradual impact. The Toronto-based startup Cohere, for example, earlier this year raised $500 million—an unprecedented amount for a Canadian generative A.I. startup—from a mix of Canadian, American and international investors. While conceding that Canada’s A.I. “brain drain” is still an ongoing issue, Nick Frosst, a co-founder of Cohere, told Observer, “I feel the tide is turning.”
Attracting the best researchers in the game....
....MUCH MORE
Some previous posts on the topic:
October 2017 - Questions America Wants Answered: "Is AI Riding a One-Trick Pony?"
From MIT's Technology Review:
Just about every AI advance you’ve heard of depends on a breakthrough that’s three decades old. Keeping up the pace of progress will require confronting AI’s serious limitations.
I’m standing in what is soon to be the center of the world, or is perhaps just a very large room on the seventh floor of a gleaming tower in downtown Toronto. Showing me around is Jordan Jacobs, who cofounded this place: the nascent Vector Institute, which opens its doors this fall and which is aiming to become the global epicenter of artificial intelligence.
We’re in Toronto because Geoffrey Hinton is in Toronto, and Geoffrey Hinton is the father of “deep learning,” the technique behind the current excitement about AI. “In 30 years we’re going to look back and say Geoff is Einstein—of AI, deep learning, the thing that we’re calling AI,” Jacobs says. Of the researchers at the top of the field of deep learning, Hinton has more citations than the next three combined. His students and postdocs have gone on to run the AI labs at Apple, Facebook, and OpenAI; Hinton himself is a lead scientist on the Google Brain AI team. In fact, nearly every achievement in the last decade of AI—in translation, speech recognition, image recognition, and game playing—traces in some way back to Hinton’s work.
The Vector Institute, this monument to the ascent of Hinton’s ideas, is a research center where companies from around the U.S. and Canada—like Google, and Uber, and Nvidia—will sponsor efforts to commercialize AI technologies. Money has poured in faster than Jacobs could ask for it; two of his cofounders surveyed companies in the Toronto area, and the demand for AI experts ended up being 10 times what Canada produces every year. Vector is in a sense ground zero for the now-worldwide attempt to mobilize around deep learning: to cash in on the technique, to teach it, to refine and apply it. Data centers are being built, towers are being filled with startups, a whole generation of students is going into the field....
January 2018 - Take that Toronto: "Beijing to build $2 billion AI research park: Xinhua"
Toronto prides itself on being both a center of A.I. research and a city of the future, what with Google kin Sidewalk Labs hooking up with the city to develop same.
But no one is talking a $2 billion investment....
December 2023 - The Godfather of Artificial Intelligence Has Some Concerns
From Toronto Life, November 16...
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....Previously on Professor Hinton:
2014: "As Machines Get Smarter, Evidence They Learn Like Us"
2015: "Inside Google’s Massive Effort in Deep Learning" (GOOG)
2017: Questions America Wants Answered: "Is AI Riding a One-Trick Pony?"
2018: Artificial Intelligence Chips: Past, Present and Future
2022: Deep Learning Is Hitting a Wall
December 2023 - "France's unicorn start-up Mistral AI embodies its artificial intelligence hopes"
More on Mistral. They are going to have to hire some hyper-brains. Go to Toronto, go to Carnegie Mellon, get beyond ChatGPT and the large language models....
December 8, 2024 - "Canada commits $1.4B to sovereign compute infrastructure as it joins the AI arms race"
