I don't think the recommendation engines behind Spotify, Youtube Music, etc compare to the recommendations I got from last.fm over the years. The algorithmic ones seem to have a bunch of issues that bug me as a long time music listener and someone with a large music library.

- their memory is short as hell so you can listen to something for a while, stop and then it'll suggest it to you later as something to "discover"

- they are way too biased towards recently listened music and will replay things over and over if you're not actively managing your queues.

- because they're so based on what you have listened to (recently) they suggest things that are extremely obvious music no one is "discovering"

- they suggest the "top" songs from artists, albums, etc, it's very hard to get it to play a "deep cut"

- if you have a large library you'll inevitably hit playlist song limits and other things silently. Each service handles this differently, Youtube Music seemingly kicks things out of my library or liked playlists each time I add something else.

I've literally just gotten in the habit of never using the autoplay features and just starting whole albums from start to finish again because the algorithms annoy me so much. Youtube Music has been getting worse about it too where now it often ignores the music you chose to start a playlist and starts playing things you've listened to recently regardless of it doesn't match the genre/vibe at all.

That's because the recommendation engine that Last.fm used back in the day was made the incredibly expensive way: the entire corpus was hand-tagged and cross-linked by humans atop an enormous CDDB. Last.fm, Audioscrobbler, and MusicBrainz (the association engine) were all linked together.

One really annoying example of YTM's algorithm is it (or whoever works on it) doesn't understand that a genre can have diverse sounds and instruments, so it will recommend songs that all sound the same.

Like if I start listening to house music, it will just recommend 100 songs that have organ 2 [0], even though house music is more diverse than that. Then it forces me to thumbs down the music, which also isn't what I want to do, because I have no idea what effect it's having on my recommendations. Is it just going to stop recommending house music altogether? Is it going to stop recommending songs with organ 2? Is it smart enough to understand that I just want less and not none? I do like organ 2, I just don't want to drown in it when I'm trying to find new music.

Or I will thumbs up a phonk song and it it just floods me with phonk remixes of pop songs.

Last.fm, on the other hand, seemed to have some way of towing a line of different enough without going too far. Both YTM and Spotify algos just do cookiecutter similarity.

[0]: https://www.youtube.com/watch?v=Iq61C8gndjM

Great summaries. I also have a real affection for my last.fm discovery, and I think it had everything to do with "deep discovery" going deep into the related artists pages. It really shaped my relationship to music and my love of music discovery and I sometimes find I don't click with people whose idea of discovery is The Algorithm(TM).

I tried to import my music life into Google Music, uploading my lifetime of libraries there. When they wound that down I just lost trust in online services and now do it through Nextcloud, which honestly is pretty awesome imo. There's no algorithmic suggestion for better or worse, but none of the "who ordered that" style assumptions imposed on you by the system like those you outlined above.

I switched to Apple Music to save some money and I find the curation and the recommendations to be significantly better than Spotify.

Cannot call lastfm algorithm advanced in any sense. Just opened Amon Tobin page: "similar artists: Kid Koala and DJ Kush", which is an impressively shallow understanding of the last 20 (!!) years of his life, and this happened with almost every artist on the platform, because the average sum of tastes of every listener does not exist in reality. E.g. in the case of Amon Tobin, Kid Koala is the average of similarities between early albums and recent releases, which is just not true, his music cannot be averaged throughout his career. I love my Web 2.0 youth, but the average similarity algorithm doesnt deserve praise. Its not better, its nostalgia and lack of faang-style unlimited greed which confused with better quality

Edit: of course spotify-style recommendations are much much worse, I just mean that lastfm doesnt have good algorithm either because artists are not consistent in releases. What is an average between electronic cult classic "The last resort" and every other Trentemoller album in strict indie rock style? This average does not exist

I'm 90% sure that music labels pay to "put their thumbs on the scales" with these recommendation algorithms in order to push their "hot" artists. I wonder how many of these problems are a result of that.

The other frustration I’ve noticed is that they key in very heavily on artist and specific “genre” designation as what feeds the recommendation, which is actually quite bad for anyone who likes experimental work.

I understand that if your recommendations are based on “people who like this also tend to like that” then you’re right in the strike zone. But that approach is basically agnostic to any property of the music itself. Suppose there’s a rock band that released a specific song where they’re experimenting with a new style that has an atypically (for them) funky/jazzy influence. If I say I want more songs like that I mean songs that fuse rock/jazz/funk, not more songs that fans of [rock band] are into.

I still think for new music discovery Pandora’s approach remains the best if you really curate a station for yourself. Apple Music has been good for creating very listenable playlists though, and their new AI playlist generator has been very fun. Surprisingly, YouTube also seems to have some secret sauce where they recommend a lot of interesting stuff that I’ve genuinely never encountered before. I suspect this is because there’s a lot more amateur and experimental artists on there doing weirder stuff and it’s able to find audiences for those in ways that the music-focused services have less visibility into since their catalog is so focused on stuff from the recording industry.