OAKLAND, CA – Deep learning has been broadly acclaimed for its advanced pattern recognition abilities that are primed for working with data at scale. It can detect non-linear patterns with quantities of variables that make it difficult, if not impossible, for humans to do so. Deep Learning's strengths are recognizing patterns and translating them into predictions with high accuracy rates. Critiques of Deep Learning take issue with how its achievements are produced. Deep Learning needs an inordinate amount of training data to generate reliable results.