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/)