The Machine is Dreaming

http://googleresearch.blogspot.com/2015/06/inceptionism-going-deeper-into-neural.html
https://photos.google.com/share/AF1QipPX0SCl7OzWilt9LnuQliattX4OUCj_8EP65_cTVnBmS1jnYgsGQAieQUc1VQWdgQ?key=aVBxWjhwSzg2RjJWLWRuVFBBZEN1d205bUdEMnhB
Google gives a neural network acid and asks it to return images. It combines dogs and fish, plants and buildings, birds and insects into a single images to optimize it's memory usage.

Fucking trippy.

http://arxiv.org/abs/1506.03340
Oh God, it's happening and Google's the one behind it!

Teaching machines to read natural language documents remains an elusive challenge. Machine reading systems can be tested on their ability to answer questions posed on the contents of documents that they have seen, but until now large scale training and test datasets have been missing for this type of evaluation. In this work we define a new methodology that resolves this bottleneck and provides large scale supervised reading comprehension data. This allows us to develop a class of attention based deep neural networks that learn to read real documents and answer complex questions with minimal prior knowledge of language structure.

Pretty soon, computers will be able to comprehend a text for us and reading will be outlawed in favor of just asking the machine. Eventually, things will be so bad it will be like http://archive.ncsa.illinois.edu/prajlich/forster.html, except with more consumerism mixed in with the vapidness.