In an interview, Richard Zemel at the University of Toronto in Canada discusses artificial intelligence (AI) developments he anticipates for the year ahead.
Zemel predicts improved personalization technologies, to the point where digital assistants, and even smartphones, will be able to better understand questions, formulate answers, and become more familiar with users and their behavior.
Related to this is the growing field of fairness in machine learning, which Zemel says involves building machine-learning systems to embody ethical and societal fairness principles.
He also expects educational innovations such as online learning tools customized for individual students, and is especially interested in transfer learning, in which AIs may be able to learn new tasks without much training data.
Another AI area Zemel sees as important is the idea of adding structure to machine-learning systems in the form of capsule networks, and he believes a key issue to resolve concerns the right structure to incorporate.
From U of T News
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