Sanja Fidler has a back-of-the-envelope way to track Toronto’s rapid emergence as a global centre for artificial intelligence, or AI: the number of machine learning graduate students who are jumping at offers to do their research at the University of Toronto.
“You typically have some ratio of ‘accepts’ because there is MIT, Stanford and Berkeley and we all compete for the same people,” says Fidler, an assistant professor at U of T Mississauga's department of mathematical and computational sciences and a founding member of the Vector Institute for AI research.
“But this year almost everyone accepted.”
The flood of interest reflects both U of T’s growing global reputation in the booming field of AI and the degree to which Canada’s strategy of investing in AI research through initiatives like Vector, a partnership between U of T, government and industry, is helping to attract and retain top talent.
That includes top researchers like Fidler, who specializes in computer vision and applied machine learning. She will be speaking at U of T Thursday as part of an AI career event with Santa Clara, Calif.-based Nvidia, a Vector partner that designs graphics processing units, or GPUs, which are often used to handle the intense computations necessary for AI applications.
“I do a lot of things connecting computer vision with natural language – so moving towards robots that are not only going to see but also communicate with people in natural ways,” Fidler says.
“The grand vision is we want to teach a robot how to do anything in a household – make coffee, clean your room. Maybe watch TV with you?”
Read the full story at U of T News.