I wish "Deep Learning" had been called "Compositional Function Approximation". It is a mouthful, but it would have avoided a very large amount of criticism that misses the point.
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Replying to @wirrbel
I know very few researchers that have ever argued that the current methods of machine learning can carry us all the way. I am seeing mostly anti hype, but it is possible that outside of academia, the world looks different.
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Replying to @Plinz
Maybe I am missing out on academic context. In the industries, it seems that DL is an almost universally accepted Holy Grail. It sometimes feels like people (like John in accounting) doubt your competence if you aren't building a deep learning model.
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I am not so critical of deep learning per se (and fairly enthusiastic about the advances in computing related to it.) I feel like important discussions don't happen anymore: Biases, cost functions for the business, feature engineering, robustness, and limits of predictive power.
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As always, the people who matter tend to be the ones less prone to confusion, because they attempt to deeply understand what they are talking about.
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