generative deep learning deepdream deepdream is an artistic image-modification technique that uses the representations learned by convolutional neural networks it was first released by google in the summer of as an implementation written using the caffe deep-learning library (this was several months before the first public release of tensorflow it quickly became an internet sensation thanks to the trippy pictures it could generate (seefor examplefigure )full of algorithmic pareidolia artifactsbird feathersand dog eyes-- byproduct of the fact that the deepdream convnet was trained on imagenetwhere dog breeds and bird species are vastly overrepresented figure example of deepdream output image the deepdream algorithm is almost identical to the convnet filter-visualization technique introduced in consisting of running convnet in reversedoing gradient ascent on the input to the convnet in order to maximize the activation of specific filter in an upper layer of the convnet deepdream uses this same ideawith few simple differenceswith deepdreamyou try to maximize the activation of entire layers rather than that of specific filterthus mixing together visualizations of large numbers of features at once alexander mordvintsevchristopher olahand mike tyka"deepdreama code example for visualizing neural networks,google research blogjuly licensed to