I gave the Bayesian inference lectures in the morning, and spent time chatting in the afternoon. In my lectures, I argued strongly for passing forward probabilistic answers, not just regularized estimators. In particular, many methods that are called "Bayesian" are just regularized optimizations! The key ideas of Bayes are that you can marginalize out nuisances and properly propagate uncertainties. Those are important ideas and both get lost if you are just optimizing a posterior pdf.