In the time around sessions, and on the conference hike (with kangaroos), I had many conversations with Marcus Frean (Wellington) about a generalization of his source finding system. He finds sources in data by looking for anomalies in the "pixel histogram"; his model has no knowledge of astronomy (or anything else) on the inside. We discussed several generalizations in which the model would learn—as it saw more and more data—what kinds of properties that astronomical data have. The idea is that the system should learn that the anomalies (sources) fall into different categories, learn the process that generates each of those categories, and instantiate new categories as required by the data. A system like this would be like a simulation of a hypothesis-generating astronomer! It also would be extremely useful running on any operating astronomical survey; "eyes on the data" are always valuable and usually very expensive. As my reader knows, I think that eyes on the data is the most valuable contribution of massive citizen science projects like the Zooniverse; awesome if we could add some robots into the mix!
At the end of the day (Australian time), during the MaxEnt2013 conference dinner, Gaia launched! It looks right now like the launch was successful. This is potentially the beginning of a new era in observational astrophysics. Congratulations to everyone involved.