It seems like they all do the loop eventually.

I liked Tidal's recommendations.

I went back to last.fm, music stores, friends recommendations, and music/TV scores(a lot of good movie sound folks are amazing musicians).

I've heard good things about Tidal (https://tidal.com) but it's not open source afaik.

> In the age of machine learning, I'm really surprised there aren't superhuman music recommendation algorithms.

Because music is extremely hard to quantify. What do you quantify it on? See https://everynoise.com/ (the mess on the page is quantifying by just three or four out of 17 IIRC parameters) and their small doc on it: https://everynoise.com/EverynoiseIntro.pdf

And doing that at scale across hundreds of millions of users quickly becomes prohibitively expensive. So companies simplify, and reach for simpler solutions, unfortunately.

This is true for most things that have recommendation engines.

I still pay for Spotify, but nowadays 99% of my music consumption are local FM radios, plus mainstream webradios [radioParadise, FIP, BBC6, NTS]. I sometimes Shazam things, but rarely have the time to listen them back on Spotify. My attention time is limited by other things [:those stupid real-life stuff every normal person was praising in the old times: kids, family, work, burnout, failing cars, gardenning. And sleep!]

And then what’s the next comeback, you boomer? BBS? Tabletop roleplaying-games? Reading books? #comeOooon

Recommending new material involves risk. Once these companies go big and mature, they hate risk. They hate risk in hiring (taking a chance in people) and they certainly hate risk in algorithms.

> Can anyone recommend a music discovery service that isn't garbage?

I enjoy using last.fm, although it's not their focus these days. Sign up, connect it to Spotify or whatever you use (incl. a long list of players of local music), after a day or so it'll learn what you like and you can create playlists with suggestions and export them, or browser around recommended artists etc.