Facebook trains A.I. to 'see' using 1 billion public Instagram photos

Whereas many AI models are trained on carefully labelled datasets, Facebook said SEER learned how to identify objects in photos by analyzing random, unlabeled and uncurated Instagram images. This AI technique is known as self-supervised learning. "The future of AI is in creating systems that can learn directly from whatever information they're given -- whether it's text, images, or another type of data -- without relying on carefully curated and labeled data sets to teach them how to recognize objects in a photo, interpret a block of text, or perform any of the countless other tasks that we ask it to," Facebook's researchers wrote in a blog post. "SEER's performance demonstrates that self-supervised learning can excel at computer vision tasks in real-world settings," they added. "This is a breakthrough that ultimately clears the path for more flexible, accurate, and adaptable computer vision models in the future."