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What's with the trend towards deeper neural nets?

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I remember from my Russell / Norvig AI textbook that any neural net that can be expressed in N hidden layers can also be expressed in a single hidden layer.

Yet, the trend seems to be towards more layers lately. Why is this? Is it a question of efficiency? Learning speed?

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