The great minds behind intelligent machines

A white line drawing of a human brain on a blue background with parts of a circuit board drawn around it

The great minds behind intelligent machines

How three Canadian researchers in artificial intelligence are helping to change how we make decisions, from our money to our health
September 27, 2017

The world is poised for a new revolution. Research in artificial intelligence is already changing how we assess risk and make decisions in everything from medicine to the financial markets. As machines get smarter, we will increasingly turn the difficult work of analysis over to computers that can make better predictions than humans. Canadian labs are home to trailblazers in this field. At the Université de Montréal, Yoshua Bengio is breaking new ground in understanding the principles of machine learning techniques, which will give to computers the ability to predict behaviours by analyzing large amounts of data. At the University of Toronto, Geoffrey Hinton investigates ways of using artificial neural networks, which mimic the behaviour of the human brain. These are just two of the country’s powerhouse minds in AI. Across the country researchers are breaking barriers in this exciting field with the help of CFI funding. In this collection, read about three of them.

  • What if your stove could learn that you have a tendency to forget the pot of rice on the burner, and alert you when it thinks you’re about to repeat that bad habit? For seniors wanting to continue living safely on their own for as long as possible, it could be a life saver. Assistive devices developed by Bruno Bouchard and his team at the Université du Québec à Chicoutimi use sensors and artificial intelligence (AI) to predict the behaviour of users, especially in potentially dangerous situations such as cooking. We talked to Bouchard to find out how applying artificial intelligence to...
  • Machine learning — which is essentially designing computer methods that can learn patterns in data — can help computers predict things such as the incidence of disease in a given population, or assessing the credit risk of somebody applying for a mortgage. But like human learning, machine learning is only as good as the information the machine is exposed to. Sandra Zilles, Canada Research Chair in Computational Learning Theory and a researcher at the University of Regina is making machine learning more efficient by improving the way computers are exposed to sample information. We talked...
  • When it comes to the many ways artificial intelligence will shape the future, self-driving vehicles are likely to be among the most transformational. And the University of Toronto’s Raquel Urtasun is at the forefront of that movement. Before she was head of Uber’s Advanced Technologies Group and co-founder of the Vector Institute for Artificial Intelligence, both in Toronto, she was leading U of T’s CFI-funded laboratory for autonomous driving. We talked to her about how AI will change transportation everywhere. What excites you most about your research? The potential impact we can...