Comment by regularfry

The comparison makes sense in what I am charitably assuming is the case the GP is referring to: we know how to build a tight embedding space from a text corpus, and get out outputs from it tolerably similar to the inputs for the purposes they're put to. That is lossy compression, just not in the sense anyone talking about conventional lossless text compression algorithms would use the words. I'm not sure we can say the same of image embeddings.