I spent today at Texas A&M University, where I spoke to the Physics Department. I took a risk and talked entirely about modeling astrophysics data, including even inferring the Kepler flat-field! Nick Suntzeff (TAMU) introduced me with a discussion of astro-statistics and its importance in the future of astrophysics, which made me feel a bit better about choosing such a technical topic. I particularly emphasized that making measurements in astrophysics problems—where we can't do controlled experiments—usually requires building a hybrid model that includes both data-driven components (for the parts of the problem that are complicated but we don't particularly need to understand), and causal-physical components (for the parts where we hope to gain some understanding). My examples were XDQSO, Kepler, Comet Holmes and the kitten, and the Solar System force law. On the first example, all I really said is that a whole lot of bad data can be as good as a small amount of good data, when you have a good noise model. On the last point, all I really said was that we have no idea how to scale up for Gaia.