It doesn't seem that this approach "knows" the actual music. The article doesn't seem to explain how track embedding vectors are produced, but it mentions that user-action signals are of the same length, which makes me doubt track embeddings have any content-derived (rather than metadata-derived) information. Maybe I'm wrong, of course.
I doubt that any recommendation system is capable of providing meaningful results in absence of the "awareness" about the actual content (be it music, books, movies or anything else) of what it's meant to recommend.
It's like a deaf DJ that uses the charts data to decide what to play, guessing and incorporating listeners' profiles/wishes. It's better than a deaf DJ who just picks whatever's popular without any context (or going by genre only), but it's not exactly what one looks forward to when looking for a recommendation.
I doubt that any recommendation system is capable of providing meaningful results in absence of the "awareness" about the actual content (be it music, books, movies or anything else) of what it's meant to recommend.
It's like a deaf DJ that uses the charts data to decide what to play, guessing and incorporating listeners' profiles/wishes. It's better than a deaf DJ who just picks whatever's popular without any context (or going by genre only), but it's not exactly what one looks forward to when looking for a recommendation.