This video is made using a visualisation technique applied to a neural network trained to recognise a broad range of images. Each frame is recursively fed back to the network starting with a frame of random noise. Every 100 frames (4 seconds) the next layer is targeted until the lowest layer is reached.
Based on the work by Google researchers Alexander Mordvintsev, Christopher Olah and Mike Tyka. See googleresearch.blogspot.it/2015/07/deepdream-code-example-for-visualizing.html for more information.
