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 AI researchers at the top of the field, 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. 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.

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 AI researchers at the top of the field, 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. 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.

Artificial intelligence (A.I.) could become a game-changer for multiple industries. Powerful algorithms may soon be able to quickly sift through reams of data and information, delivering quantifiable insights for tasks such as enhancing guidance systems for self-driving cars, assisting physicians in diagnosing patients, or helping farmers implement plans that simplify the management and protection of their crops. Technology giants in the U.S. like IBM and Microsoft are exploring business opportunities where A.I. could have the most impact, but an ecosystem for this type of R&D is already thriving in Canada. Our neighbor to the north has produced several pioneers in A.I. Prominent computer scientists like Geoffrey Hinton, Ph.D., and Yoshua Bengio, Ph.D., started their careers in Toronto laying the groundwork for various A.I. oriented fields. Hinton, an engineering fellow at Google and professor emeritus of computer science at the University of Toronto, is considered a pioneer in training neural networks with multiple layers, a computing technique that provides A.I. with greater recognition capabilities.