Innovative Machine Learning Training Method Opens New Possibilities for Artificial Intelligence
From AZoRobotics: As a result of a new machine learning algorithm formulated by engineering researchers Parham Aarabi (ECE) and Wenzhi Guo (ECE MASc 1T5) at University of Toronto, smartphones may soon be able to provide users with honest answers.
The researchers prepared an algorithm that was capable of learning directly from human instructions, instead of an existing set of examples, and surpassed conventional techniques of training neural networks by 160%.
But more astonishingly, their algorithm also surpassed its own training by 9% - it learned to identify hair in pictures with better reliability than that enabled by the training, signifying a major leap forward for artificial intelligence. Cont'd...
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Boston Dynamics Webinar - Why Humanoids Are the Future of Manufacturing
Join us November 18th for this Webinar as we reflect on what we've learned by observing factory floors, and why we've grown convinced that chasing generalization in manipulation—both in hardware and behavior—isn't just interesting, but necessary. We'll discuss AI research threads we're exploring at Boston Dynamics to push this mission forward, and highlight opportunities our field should collectively invest more in to turn the humanoid vision, and the reinvention of manufacturing, into a practical, economically viable product.
