While deep learning was inspired by the human brain, the two work very differently. Deep learning requires much more data than humans, but once trained on big data, it will outperform humans by far for a given task, especially in dealing with quantitative optimization (like picking an ad to maximize likelihood of purchase, or recognizing a face out of a million possible faces). While humans are limited in the number of things they can pay attention to at once, a deep-learning algorithm trained on an ocean of information will discover correlations between obscure features of the data that are
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