of becomes clear that in the limit these functions that these language models learn and compute should be quite useful traditionally we approach that as a supervised learning problem right we were gonna like oh let's go build a data set let's go collect you know a bunch of crowd laborers and have them assign ratings to a bunch of different movie reviews that's what the Stanford sentiment tree Bank is but in the limit this kind of unsupervised scalable method of just like fit a probability distribution to strings of language