Researchers have developed a deep-learning system that can do the very human task of interpreting what's happening in a photo and guessing what's likely to happen next.Better yet, the system, developed by machine-learning researchers at MIT, can express its idea of a plausible future by adding animations to still images, such as waves that would ultimately crash, people who might move in a field, or a train that might roll forward on its tracks. The work could provide a new direction for exploring computer vision by giving machines the ability to understand how objects move in the real world.
The researchers achieved their objective by training two deep networks on thousands of hours of unlabelled video. As the researchers note, annotating video is expensive, but there's no shortage of unlabeled video to begin training machines to read other signals about the world.The model was trained on two million videos from Flickr amounting to 5,000 hours of content covering four main scene types, including golf courses, beaches, train stations, and hospital rooms, consisting mostly of images of babies.
http://www.zdnet.com/article/mits-new-ai-so-smart-it-can-predict-what-happens-next-from-a-still-image/
