Which parts?
The compression method is pretty neat, has useful applications in other contexts as well. Basically the same way you can view types as propositions, you can view them as probabilities as well (which gives you a scheme for representing the bias in any structured data type). This idea works in other contexts too, like "time compression" for pattern-match translation (choosing an order for tests to match the bias in the data you're deconstructing).
It's hard to find time to write about this stuff with my day job though. :T