This is super cool, it feels like going in the direction of the "deep"/high level type of semantic searching I've been waiting for. I like their examples of basically filtering documents for the "concept" of price increases, or even something as high level as a rhetorical question

I wonder how this compares to training/fine tuning a model on examples of rhetorical questions and asking it to find it in a given document. This is maybe faster/more accurate? Since it involves just looking at neural network activation, vs running it with input and having it generate an answer...?