[christopheraden]

Ph.D student in Stats here. That we can even sample the full posterior with so much data is interesting in and of itself. The method isn't particularly revolutionary, especially compared to a method Zaiyang Huang and Andy Gelman[1] came up with 8 years ago, but it's practical (for a restricted class of models). Steve Scott spoke to my department about a month ago, describing the problem. It's not a solution that works for all posteriors, but it certainly allows more freedom than restricting oneself to conjugate priors and allows computation on large datasets.

Academics tend to trivialize the implementation (we had some pretty strong critics of his talk in my dept), but some kudos are in order for that, even if the algorithm itself isn't revolutionary.

[1]: http://www.stat.columbia.edu/~gelman/research/unpublished/co...