The really cool application of this, which they allude to at the end of the paper, is multi dimensional indexes. For example right now kNN for similarity search (think recommender systems) is usually done with some form of K-D tree or projection method. This has a bunch of downsides, including memory usage. If we can "learn" that index directly, that would be really fancy.