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Assistant Professor Sanja Fidler of the department of mathematical and computational Sciences at the UUֱ�� Mississauga has received the Connaught Innovation Award for her work on AI tools that significantly speed up data annotation.

Machine Learning (ML) is a data-hungry field – a lot of high-quality, labeled data is typically needed to to train high-performing ML models – but manual labeling is a time-consuming task and millions are being spent by each company per year purely on annotation. Fidler's provides A.I. tools to significantly speed up that process without compromising on quality.

“We believe that our platform has the potential to significantly push the down-stream performance in critical domains such as self-driving and health care, and dramatically reduce the development time of a variety of A.I. applications,” Fidler says. “It would further allow quick testing of high-risk ideas without large financial commitments – potentially enabling many more creative ideas to find their way into product.

“Obtaining high quality labeled data fast and at scale can be game changing for the future of A.I. Toronto Annotation Suite aims to make this a reality.”