This lecture covers the AMP algorithm for spiked matrix estimation, focusing on the generic denoiser function and the algorithm's implementation for different signal distributions. It includes the derivation of the AMP equations for spiked matrix estimation and the comparison with Bayes-optimal estimators. The lecture also discusses the application of AMP to low-rank matrix factorization and GLM models, detailing the update functions and joint distributions used in the structured model.