http://www.sciencedirect.com/science/article/pii/S0031320304...
Maybe the patent has interesting twists and turns, but applying known algorithms on previously known architectures doesn't seem like the innovation that they should hand out protection for 17 years.
http://techblog.netflix.com/2014/02/distributed-neural-netwo...
EDIT: The deaded comment below me makes a good point, but they still have labels in the sense of what everyone watched and for how long.
Also the new title is terrible. Oh I guess it's a different article now???
It's actually the multiple layers hidden units that perform non-linear feature extraction and the unsupervised pre-training is simply a means to do this better (theoretically, although we don't really know what's happening as much as it would seem).
Most of the current research shows deep neural nets to be state of the art in image classification and nlp. I don't know that it is the case that deep learning techniques do not work out side this area, it's just there hasn't been much published on it either way. Although I do believe the Kaggle Merck contest was neither of these, and deep learning out performed all other techniques http://blog.kaggle.com/2012/11/01/deep-learning-how-i-did-it...
Many of the recent headline results for deep learning have been supervised such as the image net classification challenge (http://www.image-net.org/challenges/LSVRC/2013/)
It used to be that on the iPad, at least two bottom rows were dedicated to "New Releases" and "Recently Added"...sometimes neither of those rows seem to show up, and so I find myself logging into the web client just to see those listings, and -- I assume this is why they aren't as spotlighted in the iPad app anymore -- there's generally not much new to see. While I like House of Cards, I think Netflix would appeal to me much better if it spent that money on 200 - 300 good recent releases, or holding steady on to some of the great classics (there used to be more Akira Kurosawa and Woody Allen movies on Instant).
