Canada’s Future Bets on AI
Over the last few years, Canada has been stuck in an awkward position in regards to artificial intelligence (AI) — while the world leading AI experts like Geoffrey Hinton, Yoshua Bengio are all “made in Canada”, there is no Canadian grand strategy to make AI one of the key sectors of the future.
Well then, things are getting changed.
Just a week after Canada unveiled a budget of $125 million to launch Pan-Canadian Al Strategy, a new independent institute for AI, Vector Institute, opened in downtown Toronto yesterday with funding from the federal and Ontario governments and private sectors.
The new Toronto-based AI institute will mainly specialize in the transformative fields of the machine learning and deep learning with attracting and retaining top-tier AI graduates and researchers worldwide. Meanwhile, Geoffrey Hinton, the “godfather” of deep learning and the head of Google’s AI lab in Toronto, returned to Canada as the chief scientific advisor of Vector Institute.
“The Vector Institute will confirm Canada’s world-leading position in the field of deep learning artificial intelligence. Consequently, it will spur economic growth in Canada by attracting talent and investment, supporting scale-up firms and enabling established firms to be best-in-class adopters of artificial intelligence,” said Ed Clark, the CEO of TD Bank and Chair of the Vector Institute Board of Directors.
The whole grant opening sends a strong signal with Canada’s determination in transferring academic reputation into the economic development. It has been reflected on the government’s funding as Ontario invests $50 million in the Vector Institute while part of Canada’s $125 million Pan-Canadian Al Strategy also backs the institute.
“We will harness these cutting-edge technologies to improve everyday life in Ontario, while also attracting the world’s best talent to our province,” said Kathleen Wynne, the Premier of Ontario. She was invited to speak for the opening. “These investments strengthen our position as a global leader in the innovation economy, which is critical to creating more well-paying jobs and shared prosperity for the people of Ontario.”
Transformation of economic model
Both speakers repeatedly put emphasis on the relationship between AI and economy. Considering the inactive innovation economy in Canada over the last few years, AI could be their best shot.
Despite the academic lead in technology, Canada has excessively relied on traditional two industries — crude oil and export. Both industries are likely to stray into an economic slump once oil prices are falling or the U.S. Trump administration is being critical of the US-Canada trade deal.
But things got a little different when AI is getting hot.
AI is opening new ways to disrupt the industry by training machine learning models with massive labelled data. With the help of AI, the civilization is experiencing an earth-shaking change, from self-driving vehicles to better medical diagnoses.
Meanwhile, AI is playing a critical role helping optimize traditional industries, such as energy and oil, as solution provider to boost effectiveness and productivity. IBM Watson’s new AI application tool — the cognitive oil field cognitive system, is a good example. It is being piloted by several oil producers to make exploration and development more productive, efficient and safer. Canada’s oil industry gets benefit from the technological solution.
Finance is another big field where AI has a big potential in application. The integration of Finance and technology, so-called “Fintech”, is using massive data and machine learning model to offer customized financial advice and automated asset allocation.
On the other hand, AI has a big potential of commercialization.
Canada is not a good place for B2C (business to customer) business due to a small marketplace and lack of industrialization, which is why despite Canada has been pursuing innovation economy in last ten years, it was not working effectively at all. When countries like the U.S. or China are skyrocketing because of Internet, Canada was lagged behind. Canadian companies were ended with acquisition, defunct, or being away from the country.
Cognos, for example, was an Ottawa, Ontario-based company making business intelligence and performance management software. Founded in 1969, it was acquired by IBM in 2008 instead of being an independent company. So were Algorthimics, Varicent and Clarity. They were the best data-driven companies in Canada during 2000s, but ended being acquired as well.
However, AI is a kind of B2B (business-to-business) business. The innovation economy can be boosted through the collaboration with clients and partners in different fields.
Private companies have recognized the transformational potential of deep learning and machine learning in fields as diverse as health care, finance, insurance, education, retail, advanced manufacturing, energy, construction and transportation. More than 30 companies have committed a combined total of over $80 million over ten years to support the Vector Institute.
Canada is catching up.
Over the last 20 years, Canada has been providing invaluable talents and research achievements for the success of this wave of AI boom. Toronto and Montreal have played a big role in the rise of deep learning and output thousands of AI talents to worldwide companies and institutes. Suddenly, Canada has become a hotbed for new talents.
However, the country was losing their best AI talents, including Geoffrey Hinton with his startup DNN Research, acquired by Google in 2013. Other Canadian startups like Ross Intelligence, an artificial intelligence system for legal research, have also left for California.
“Canadian companies last year acquired only 18 AI startups, out of 658 that were acquired globally,” said Dr. Alan Bernstein, the president and chief executive of Canadian Institute for Advanced Research (CIFAR).
As Silicon Valley became the new heaven for top-tier AI researchers, Canada realized how bad the situation was.
“We need to keep people here, to let people think of Canada when they looking for chance, development, leadership,” said John Terry, the mayor of Toronto.
Since last year, Canada institutes and universities started to attract worldwide AI talents by deploying different strategies in education.
Yoshua Bengio, the top scientist in artificial neural networks and deep learning, launched a startup incubator, Element AI, in helping build companies emerged from Canadian universities like University of Montreal and University of McGill last year.
Meanwhile, University of Montreal launched a deep learning summer school last summer, aimed at graduate students and industrial engineers and researchers who already have some basic knowledge of machine learning (and possibly but not necessarily of deep learning) and wish to learn more about this rapidly growing field of research. With a strong AI faculty led by Dr. Bengio, the summer school raised a big attention in academia.
While Canadian institutes are doing an excellent job in hoarding AI researchers, some Canada-based AI companies are performing strongly in AI innovation. D-Wave, a Canadian AI startup for example, is the world’s first quantum computing company by using the deepest insights of physics and computer science to achieve breakthrough approaches to computation to address some of the most complex challenges in science, business and government. Google and NASA are D-Wave long-term partners since 2013.
MindBridge AI, another Canadian AI startup, represents the latest progress of how AI is revolutionizing financial crime investigations. Just two weeks ago, the Bank of England announced the collaboration with MindBridge AI.
At this year, the government of Canada made a step forward, announcing $125 million Pan-Canadian Artificial Intelligence Strategy for research and talent that is going to cement Canada’s position as a world leader in AI. The program will be administered through CIFAR that has made fundamental advances in AI since 1987.
$125 million might not be enough to support AI research for a long time, but it is a great start. Dr. Yuxi Li, a Chinese Canadian researcher, said he was impressed with the generous support from federal government.
“More energy has been injected to generate more excellent talents and research achievements, exemplified by Element AI established in late 2016 in Montreal and Vector Institute launched today,” said Dr. Li.
AI ecosystem is built in Canada.
It might take few years to see how influential the government-backed AI institute is, but local Canadians are expecting a new AI eco-system built up.
“I was excited to see that Canadian government and schools are putting more resource to the AI field to support projects and train talents,” said Elva Wu, the associate venture capitalist of Istuary Innovation Group, a Canadian technology incubation platform helping cultivate innovation into businesses. “Supported and cultivated by the vector institute, there will be more AI startups in Canada, and we as a local VC would love to see that.”
Besides, students from universities of Montreal and Toronto expressed their willingness to stay in Canada dedicated to machine learning. As the result of interviews with several machine learning researchers from University of Toronto, most of them agree Vector Institute will strengthen the connection between industry and academia. With the investment from the industry, institutes can better perform in retaining and training talents, and vice versa.
In Canada, Chinese is the largest group of international students, and their attitude is important to Canada’s innovation economy, considering Chinese are usually great researchers. They usually choose Silicon Valley or Boston rather than Toronto and Montreal. However, thanks to the Trump administration and his restrict immigrant policy, Chinese and many other foreign researchers lean to Canada. Two Iranian researchers joined Dr. Hinton’s Google AI lab in Toronto after expelled from U.S. customs, according to rumors.
“I was planning to leave for Silicon Valley after graduation, but I might change my thoughts,” an anonymous Chinese international student researcher shared the thoughts on his future career path. “Trump keeps downplaying the importance of technology, AI and globalization. Meanwhile, Canada is investing heavily on AI. It will generate many opportunities here.”
The good news is with more tech conglomerates coming to Canada investing in AI labs, Canadian researchers might have no reasons to leave for Seattle or Silicon Valley. The two most competitive tech giants in deep learning research, Google and Microsoft, have respectively backed AI research in Canada, giving local students the opportunity to work with smart brains without coming to the U.S. Google is also one of the sponsors of Vector Institute with $5 million funding in next 10 years.
5 years later, will Canada have its own AI-centered Silicon Valley? Well, not a dream anymore.
Original Article from Synced China | Localized by Synced Global Team|Author: Tony Peng
