Reducing your labeled data requirements (2–5x) for Deep Learning: Deep Mind’s new “Contrastive Predictive Coding 2.0”

CPC 2.0 in action — with only 1% of labeled data, achieves 74% accuracy (from the paper)

Current Deep Learning for vision, audio, etc. requires vast amounts of human labeled data, with many examples of each category, to properly train a classifier to acceptable accuracy.

By contrast, humans only need to see a few examples of a class to begin properly and…