representation and just do linear decoding we discover that we can decode lots of different parameters of the image like how fast it's moving what the starting angle is we can also look at things about principal components of the identity so you it sort of fits with this idea again that by virtue of learning good predictions you learn good representations that are useful for lots of things which is kind of what you need to have in an unsupervised or a semi-supervised learning sort of setting we also did a face-recognition version