Mengye Ren (U. of Toronto) - Steps Towards Making Machine Learning More Natural

Steps Towards Making Machine Learning More Natural

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Over the past decades, we have seen machine learning making great strides in AI applications. Yet, most of its success relies on training models offline on a massive amount of data and evaluating them in a similar test environment. By contrast, humans can learn new concepts and skills with very few examples, and can easily generalize to novel tasks. In this talk, I will highlight three key steps towards making machines learning more human-like, and these steps will unlock the next generation of technologies. The first step is to make machines learn new concepts continually and incrementally using limited labeled data. The second step is to develop flexible representations that can generalize well to novel concepts under different contexts. Finally, I'll show how to make abstract and compositional reasoning given visual inputs. I'll then conclude with an outlook of future directions towards building a more general and flexible AI.

Host: Sanjay Krishnan