This lecture covers the application of Belief Propagation in Stochastic Block Models, focusing on simplifying the process, plugging into the model, and solving it step by step. The instructor explains the concept of likelihood, community detection, and the phase diagram of the SBM, providing a detailed analysis of the algorithm's behavior.