Why we’re all so obsessed with deep learning

Machine Learning   |   
Published June 8, 2014   |   
Derrick Harris

Summary: Deep learning is all the rage among the tech scene right now, and that’s more a result of its utility than because it sounds cool. Some questioned the feasibility of the Secret Service’s requested “sarcasm detector,” but deep learning could help there, too.

You might have noticed the flurry of activity lately around deep learning. It’s an approach to data analysis centered around stacks of artificial neural networks that, for lack of a more succinct definition, can teach themselves to understand complex patterns and the many little features that comprise the data they’re on which they’re trained. It’s the talk of the town among media types, entrepreneurs and computer scientists not just because it sounds so cool, but mostly because it works.

We’ve covered many of its early applications already — recognizing what’s in pictures, who’s in pictures, how words are related in text and what people are saying. A lot of the research being done in universities, which then gets trained on massive amounts of web data inside places like Google, Microsoft and Facebook, is already making its way into consumer services and even commercial software near you. Google is using neural networks to understand and improve data center efficiency. Some believe deep learning could also be used to analyze time-series data for algorithmic trading models or better understand medical records.

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