“People used to just work in computer vision or image processing, but now there’s a lot interdisciplinary work to connect these things together,” says Fidler, who is an assistant professor at U of T Mississauga’s department of mathematical and computational sciences and a faculty member at the Vector Institute for Artificial Intelligence.
U of T News recently caught up with Fidler to find out more about her work and her thoughts on where AI is headed in 2019.
Where do you see AI research headed over the next 12 months – what are the trends you’re keeping an eye on?
There’s actually been a lot of work in designing simulations where you can train these embodied agents – so I think this will be a new big thing, where people make more sophisticated simulators and train more sophisticated algorithms.
A lot of computer vision people have started working in simulated environments where you use vision as a sort of auxiliary task needed to solve a more complex problem.
There’s a lot of internal teams working on stuff like that, but I want to contribute with some AI tools.
U of T is basically a pioneer in deep learning – we have Geoff Hinton and there’s so many renowned faculty working on various AI fields, particularly machine learning and deep learning.
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