In the future, the pictures we take could move. Here's how

To estimate motion, the team trained a neural network with thousands of videos of waterfalls, rivers, oceans, and other material with fluid motion. The training process consisted of asking the network to guess the motion of a video when only given the first frame. After comparing its prediction with the actual video, the network learned to identify clues--ripples in a stream, for example--to help it predict what happened next. Then the team's system uses that information to determine if and how each pixel should move.