That's what I use to get more in-depth than the tiny amount of new releases Spotify features in its official playlists.

The really aggravating thing is that we know they have the tech to do better. There was that demo of a 2D embedding of genre-space that actually did a pretty decent job of grouping similar-sounding songs together, but their recommendations all seem to be based off of what was popular at the same time, or what came from the same label.

E.g. when I ask for recommendations for a song like "Mellon Collie and the Infinite Sadness," I should get "Avril 14th," not "Bullet with Butterfly Wings."

Not nit-picking, just piqued my curiosity about how you would connect those artists.

I would listen to those two songs in a row and be completely satisfied by the transition.

I've worked and interviewed for companies that do music analysis to find moods, atmospheres, similar timbres, chords and structure to mix and match automated playlists for business needs (restaurants, cafés, retail stores and so on), would like to see what kind of similarity scores they could get between the songs you mentioned.

I found a lot of the release radar and other recommendations are spot on and I end up liking a lot of the songs it suggests.

I think I read something about that which turned me off instantly.