On this episode of Bit of A Tangent, we discuss the emerging field of self-supervised machine learning. This is an immensely exciting area of active research in machine learning and AI - one which most people haven’t even heard about yet! We build up to the intuition for the topic by covering supervised and unsupervised learning; autoencoders and dimensionality reduction, and exploring how these techniques could be applied to Gianluca’s Quantified Self n=1 sleep quality dataset. We culminate in a detailed discussion of the state-of-the-art Contrastive Predictive Coding model, and how it allows us to learn about the structure of the world, without tonnes of labelled training data!