Facebook taught a computer vision system how to supervise its own learning process


As impressively capable as AI systems are these days, teaching machines to perform various tasks, whether its translating speech in real time or accurately differentiating between chihuahuas and blueberry muffins. But that process still involves some amount of hand holding and data curation by the humans training them. However the emergence of self supervised learning (SSL) methods, which have already revolutionized natural language processing, could hold the key to imbuing AI with some much needed common sense. Facebook's AI research division (FAIR) has now, for the first time, applied SSL to computer vision training. "We've developed SEER (SElf-supERvised), a new billion-parameter self-supervised computer vision model that can learn from any random group of images on the internet, without the need for careful curation and labeling that goes into most computer vision training today," Facebook AI researchers wrote in a blog post Thursday.

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