[Mehdi2277]

The recommender system mention is very valuable use case that I've seen at some of the largest ml using companies in the world. If you have a recommendation system on millions or much higher pool of content you will need an ANN index. I would expect google image search is using an ANN index. Facebook definitely uses ANN indices. Spotify is where Annoy comes from. They're pretty key at tiktok.

Whether you use locality sensitive hashing or something else is a separate question. Personal experience is graph based ANN indices (hnsw is one nice one) have tended to a bit better, but LSH is competitive so I wouldn't strongly be against a design decision choosing it. One downside I've seen with some ann index libraries is a lot of them don't support incremental updates/deletions and force you to build the index as a batch job. That's fine in some use cases, but breaks others. LSH based approach spotify uses doesn't support incremental updates, but that's not because LSH can't support it just Annoy wasn't designed for it.