Well, part of this is that some of these are just "solved problems". For example, once you have arithmetic coding, you never have to worry about the actual bitw

Well, part of this is that some of these are just "solved problems". For example, once you have arithmetic coding, you never have to worry about the actual bitwise encoding again (anything on top of that is just speed optimization). That reduces the problem to modeling and probability estimation. There's an inherent limit at the entropy of the source, and usually it is not too hard to get within a few percent of that entropy (as near as we are able to model it). After that, you can do increasingly complex things, but for rapidly diminishing returns. For example, there are definitely lossless audio compressors that can make things smaller than FLAC, but usually only by a percent or two, and they are an order of magnitude or more slower. To me, a lot of the interesting research at this point is exploring the compression/speed trade-off. That's what makes LZMA interesting (it dominates bzip2 on both axes). Google has also done some interesting work in this space. This matters when your goal is to save network transmission time: if you're only sending the data once, anything you do has to be faster than just sending more data on the wire.