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Most artificial intelligence is still built on a foundation of human toil. Peer inside an AI algorithm and you’ll find something constructed using data that was curated and labeled by an army of human workers.
Now, Facebook has shown how some AI algorithms can learn to do useful work with far less human help. The company built an algorithm that learned to recognize objects in images with little help from labels.
The Facebook algorithm, called Seer (for SElf-supERvised), fed on more than a billion images scraped from Instagram, deciding for itself which objects look alike. Images with whiskers, fur, and pointy ears, for example, were collected into one pile. Then the algorithm was given a small number of labeled images, including some labeled “cats.” It was then able to recognize images as well as an algorithm trained using thousands of labeled examples of each object.
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