Deep learning

Machine learning with neural networks of many layers, which learn hierarchical representations from raw data rather than hand-engineered features.

Depth is what lets a network learn features at multiple levels of abstraction - edges, then textures, then objects - without a human defining them. The cost is data, compute, and opacity: a deep network learns its own feature space, which is why interpretability is hard.