Dr. Alan Bernstein is president and chief executive of CIFAR. Pierre Boivin is president and CEO of Claridge Inc. David McKay is president and CEO of Royal Bank of Canada.

It's not often a new technology comes along with the potential to transform society. Think the steam engine, electricity or silicon chip. Today, the most transformative technology may be artificial intelligence, in particular the branches of deep learning and reinforcement learning, that are not only positioned to change the way we work and live; they're a made-in-Canada success.

Like all disruptive technologies, AI is creating entirely new ways of doing things, from diagnosing disease to driving cars. With a strong research base already built, Canada's goal should now be nothing less than becoming a world leader in AI science and its applications in the marketplace.

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The federal government set that stage this week, with an AI initiative that will lay the foundation for a Pan-Canadian Artificial Intelligence Strategy. Through the Canadian Institute for Advanced Research (CIFAR), the $125-million commitment will help develop three AI institutes in Canadian centres that are already among the best in the world, help our universities recruit and retain scientific talent and train hundreds of graduate students. It will also fund research into the social, legal and ethical implications of deep AI, to build a Canadian brand of technology that serves human needs, concerns and ambitions, not the other way around.

How did we get here? Deep learning and related AI techniques were developed by Geoff Hinton at the University of Toronto, Yoshua Bengio at the University of Montreal, and Yann LeCun at New York University, along with Richard Sutton at the University of Alberta and a host of other researchers supported by CIFAR and its program in Learning, Machines and Brains.

The science makes computers better at seeing patterns and making accurate predictions based on those patterns, using so-called artificial neural networks, in a way analogous to how we think humans learn. If a ball rolls onto the road in front of a car, a good driver would put on the brakes because there is a chance a child will run out onto the road to get it. A smart car, controlled by AI, would come to the same conclusion, only faster.

Or consider this example: As profiled in Nature magazine, a deep AI-based computer program can now recognize skin cancer from images with the same accuracy of a dermatologist. The deep AI algorithm won't put dermatologists out of business. But it will accelerate and improve diagnosis, cut costs and allow doctors more time to spend with patients talking about treatments and cures.

Across many sectors, we're starting to see how AI can change the nature of work itself, away from routine repetitive tasks to more interesting, varied and valuable work, the kind that can make Canadian jobs more secure in a global economy. Used wisely, these tools can also make Canadian companies more competitive, governments more efficient, and social and health services more effective.

But despite our early scientific lead, we're losing ground to the AI superpowers. One indicator of that: Canadian companies last year acquired only 18 AI startups, out of 658 that were acquired globally.

So while our goal should be to ensure that Canada is a global centre for AI science, we also need to push Canadian companies, entrepreneurs and investors to seize the moment. The opportunities go hand in hand.

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Here are three immediate priorities to help get us there:

First, we have to expand Canada's pipeline of talent. We have to keep existing academic talent in Canada, strengthen our academic and skills-training programs in AI and expand our reach with the next generation of AI entrepreneurs. We have to streamline our immigration process for highly skilled individuals and market Canada internationally as a source and destination for AI.

Second, we must build the conditions for entrepreneurs to succeed. Young AI companies need investment capital, computing resources, data, and a community of mentors and fellow entrepreneurs.

Innovative programs like Element AI in Montreal, the Creative Destruction Lab in Toronto, Amii in Edmonton, and NextAI across the country are showing how Canada can be a startup country and a scale-up country. These programs should be expanded, and new ones added, to seed ideas and ensure the best ones stay and flourish in Canada.

Finally, we need to help established businesses take advantage of AI. Research centres in Edmonton, Montreal and Toronto-Waterloo provide an opportunity for Canadian companies to work closely with academics. Government can help build those bridges, not only within Canada but with the world.

Canada has a history of pioneering great science and then allowing that science to be snapped up by others. The investment in AI announced in Budget 2017 opens a new chapter in Canadian technology.

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It's now up to the private sector, working with the research community and government, to develop our made-in-Canada success story.