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A Radical New Technique Lets AI Learn With Practically No Data

Machine learning typically requires tons of examples. To get an AI model to recognize a horse, you need to show it thousands of images of horses. This is what makes the technology computationally expensive — and very different from human learning. A child often needs to see just a few examples of an object, or even only one, before being able to recognize it for life. In fact, children sometimes don’t need any examples to identify something. Shown photos of a horse and a rhino, and told a unicorn is something in between, they can recognize the mythical creature in a picture book the first time they see it. Now a new paper from the University of Waterloo in Ontario suggests that AI models should also be able to do this — a process the researchers call “less than one”-shot, or LO-shot, learning.

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