No music discovery algorithm has satisfied me. All data-driven approaches make predictions based on historical data. Personally I enjoy being exposed to entirely new genres and sounds I've never heard before, instead of variations on genres I've listened to a lot.
My solution: listening to NTS, an eclectic online radio station, where diverse artists create playlists.
I agree that NTS radio is one of the best ways to be exposed to interesting new and old music, obscure stuff, brilliant mixes, etc.
The NTS app is great: for Web, Android, iOS - it's always being steadily improved. A very nice feature to aid discovery/curation is that every track in a tracklist has a 'copy song and artist info' so you can easily search for tracks on your streaming platform. Not sure if this is a subscriber only feature.
I also use the 'identify song' feature in the Google search app on my phone, similar to Shazam.
If the algorithms aren't doing it for you then do yourself a favor and head to https://nts.live
If entirely new things is what you're looking for, you're not really looking for a recommendation algorithm [1]. What these algorithms try to achieve is finding unknown songs that are in the same genre to what people already like.
[1] Technically "random song not in listen history" would work out, if you'd really like to call that a recommendation algorithm.
But I also don't want a totally random song eighter. I want something that vibes with me but not directly recommended through my listening history, because then they are extremely similar and feels like they're feeding me the same melodies over and over.
Thats why I tried to give the "vibes" in a different format; image, rather than my listening history.
My solution: listening to NTS, an eclectic online radio station, where diverse artists create playlists.