For the latter, I have a very hard time believing we’ve squeezed most of the juice out of compression already. Surely there’s an absolutely massive amount of low-rank structure in all that redundant data. Yeah, I know these companies already use inverted indices and various sorts of trees, but I would have thought there are more research-y approaches (e.g. low rank tensor decomposition) that if we could figure out how to perform them efficiently would blow the existing methods out of the water. But IDK, I’m not in that industry so maybe I’m overlooking something.