Self-supervised learning is a means for training computers to do tasks without humans providing labeled data (i.e., a picture of a dog accompanied by the label “dog”). It is a subset of unsupervised learning where outputs or goals are derived by machines that label, categorize, and analyze information on their own then draw conclusions based on connections and correlations.