First, I want people in computer vision and NLP to actually look at the data sets their algorithms apply to. Ask a physicist to tell you some facts about physical reality, and they will rattle off a lengthy list of concepts, like conservation of energy, isotropy of spacetime, Ohm's law, etc etc. As a vision scientist to tell you some things about visual reality, and my guess is they won't have much to say. Sure, a vision scientist can talk a lot about algorithms, machine learning techniques, feature sets, and other computational tools, but they can't tell you much about what's actually in the images. The same problem is true with NLP people to a lesser degree; they can talk about parsing algorithms and optimization procedures for finding MaxEnt parameters, but they can't tell you much about the actual structure of text.

So, yes, I expect the approach to produce new techniques, but not because it supplies some kind of new mathematical framework. It suggests a new set of questions.