Code Watch: Using deep neural networks as programming assistants

How can programmers benefit from the “the year of Neural Nets”? Statistical machine learning techniques have been surging in popularity in academic settings for years, but 2015 was a watershed in terms of industry awareness and deployment. It was not long ago when the term “Deep Neural Networks” seemed about as dubious an explanation as “Applied Phlebotinum,” but now, Google’s open-source release of TensorFlow was the source of celebration and rewriting of business plans. (Although the consensus seems to be that Theano may hold multiple advantages.) It’s important to understand that neural networks are not on the threshold of replacing traditional programming techniques, much less general intelligence. Neural networks do not do any symbolic processing and are neither “logical” nor “creative.” Neural networks are “universal approximators,” meaning that they can…

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