Explore recent advancements in high-dimensional learning through this lecture by MIT's Ankur Moitra at the Simons Institute's Probability, Geometry, and Computation in High Dimensions Boot Camp. Delve into the origins of factor analysis, examining the rotation problem and generics algorithm. Discover applications in phylogenetic reconstruction and hidden Markov models. Investigate solid genetic reconstruction, distance functions, and Chang's Lemma. Analyze conditional independence, path learning, and orbit retrieval. Gain insights into orbit tensor decomposition and explore future directions in this field.