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Artificial Intelligence Community Insights

Canadian AI Needs More Commercial Successes

The Toronto skyline. (Shutterstock)

In the past 18 months, Toronto has become a magnet for artificial intelligence researchers, drawing some of the field’s leading figures to set up labs. There is a news and industry narrative that suggests this brain gain will cement Canada’s largest city among the top tier of global tech centers. But Toronto in fact is headed in a different direction — it’s becoming more of an ivory tower than a economic power.

Toronto has been developing a base of world-class research since the 1980s, including the Canadian Institute for Advanced Research, the University of Toronto and, most recently, the Vector Institute. Now, hardly a month goes by without an international company establishing a new office here. Samsung has opened an AI center. Uber is working on self-driving cars. And LG Electronics just signed a five-year research partnership with University of Toronto.

But where are the stories about Canadian companies commercializing the fruits of this intellectual labor? Too many of our startups are developing AI-based technologies with the aim of being acquired by one of tech’s giant companies or to simply secure another hefty research grant. There’s too little push to create real products that deliver results for real customers and win in global markets.

It’s not the first time we’ve heard of this problem. Canada has a habit of funding basic research then standing by, as foreign companies swoop in to take the intellectual property. Toronto is at risk of falling into the same trap with AI.

The goal has to be commercialization. That’s the only way to create jobs, wealth and a virtuous cycle of reinvestment here in Canada.

Nonetheless, some local AI-centric companies are indeed creating breakthrough products. Deep Genomics is revolutionizing genetic medicine. Wattpad’s software delivers powerful storytelling to a global community of 65 million users. And Kitchener-Waterloo’s Clearpath Robotics automates some of the world’s most dangerous jobs. My company, Rubikloud, is also in this category, building AI-powered systems for the retail industry. But we need more companies like these.

This requires carving out a specialized niche. New York is already a leader in commercializing AI with e-commerce applications. The Letgo app, for instance, allows ordinary New Yorkers to purge clutter, leveraging AI to prepare online ads for things they want to sell just by snapping a picture of them. London, meanwhile, is a center for commercializing AI in financial services.  One important company there is TransferWise, which lowers customer costs for online money transfers and has created an AI-powered “chatbot” that syncs with Facebook.

Toronto’s opportunity could lie in the emerging enterprise AI market, a sector that as yet has no established global center of excellence. Enterprise software forms the backbone of business’s daily operations. These are the programs that customers use to interact with companies, and that firms use to manage inventories, logistics, payroll and the like. For decades, this involved expensive proprietary licenses for programs and row after row of on-site servers.

Enterprise programs had been reliable revenue generators for legacy companies such as IBM, HP and Oracle, which could also make big money from providing the physical infrastructure their customers needed to operate. Now, most of the spoils go to giants such as Microsoft, Google and Amazon. But they don’t offer everything. Properly funded and sufficiently ambitious startups could leapfrog these companies by offering novel business solutions. Nimble startups can take on what the tech giants have been too busy to notice.

Toronto’s AI startups only have two or three years to show they can successfully commercialize products before investors start getting nervous and the venture capital money dries up. A solid first step would be to get better at communicating to markets what’s in our product pipeline. We need to build confidence that the hype will be matched by products.

We also need local government, media, and business to stop measuring success by how much funding is flowing into Toronto’s AI labs. The true indicator is how quickly our companies turn that research into revenues. If that doesn’t begin to happen faster, our ivory tower will soon look like a house of cards.

Kerry Liu is chief executive of Rubikloud, a Toronto-based company applying AI in the retail industry.

 

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