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The deep part of the name comes from the fact that instead of having a single layer that receives the input data and outputs the desired result, we have a series of layers that process data received from the previous layer, extracting higher and higher levels of features. Only the last layer is used to obtain the result, after the data has been transformed and compressed.   Deep neural networks have been succesfully used by various research groups. \cite{Dahl et al} \cite{Dahl}  from Microsoft presented a paper about using deep neural nets for speech recogntion. pretty impressive demo with an application that recognized spoken English, translated the text to Chinese and then spoke the translation with the original speakers voice. In the same year, Google developed a system that, from 10 million YouTube thumbnails, learned by itself to recognize cats (and 22.000 other categories of objects). In December 2013, Facebook opened a new research lab, led by Yann LeCunn from New York University, one of the foremost researchers in deep learning.