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Seeing who’s playing with bands you like can be an inspiration. That’s how I found Slothrust, years ago.
Youtube’s algo has been pretty good at giving me artist/song recommendations… admittwdly after over a decade of liking and subscribing to a ton of bands on the platform. Brought me IDLES and Viagra Boys first LPs before anyone else, and just this week turned me on to Vancouver band PISS. They’re fucking raw, take heed of the lead’s warning before they start.
Here, have some extra heavy THALL
I unironically get mine from Neuro Sama Karaoke.
My experience has generally been that any song recommendations by the algorithm are completely wrong. Even when I build the playlist with a certain vibe and then request suggestions from the algorithm, it will go into left field and pick the most awful choices to fill out the list.
You would think that, with all this data they are keen to collect, they would have some level of understanding of vibes. Not direct understanding, obviously, but I would have thought them capable of cross-referencing various listening profiles to suggest better music.
It’s legit one of the things I could see AI actually being good at and used ethically for. I guess the fact that it’s not used for better taste profiling is a small mercy, considering the technology would be used for more nefarious stuff elsewhere if it was any good.
A prime example: the song “The Hoodin’ of Miss Fannie Deberry” by Kenny Rogers is decidedly different from the rest of his catalog. No matter how hard I try to get Spotify to find songs with similar vibes, I can’t escape Kenny Rogers and general country tunes. It’s maddening.
Any given song radio will trap you in a decade of music/genre, and pay no attention to the vibe of a song.
It has gotten slightly better recently with making custom playlists for me, but once my hyper-focus changes, I’m sure it will be out of sync with me again. Frontier Psychiatrist Radio slaps, but I’m still trapped in the '90s-'00s.
This has also been my experience (hence the meme). I’ve taken to finding music via human recommendations, as well as finding music that is related to another artist (for example, songs featuring another artist, or recommendations from artist, like their inspirations and stuff).
Another thing I’ve taken to is listening to artists’ entire discographies, which has been really great for me so far.
Oh, and internet radios are cool. Especially really niche and indie ones.
I know it wasn’t exactly hard to predict any of it, but I still think it’s notable that this song came out months before names like Marimar Martinez, Renee Good, Alex Pretti, Ruben Ray Martinez, and others were in the news - https://www.youtube.com/watch?v=ehAciON3IdE
I tried using Spotify’s AI DJ… I am getting old, I want to discover something new, but I have no idea how to do it, AI DJ promised to try to challenge me with new music… I tried switching songs and modes for half an hour, never heard a single song that would be on my playlists or by a band that is on my playlists. The Spotify AI DJ is just a really fancy shuffle button and is absolute garbage.
I use gnoosic.com, it finds really niche bands.
I’m ashamed that I’ve been using Spotify for years, but some of my favourite artists are ones that came from the generated playlists after the music I picked ran out. And not huge names or slop, but actual real independent “local” (from my country) artists.
In the last year or so I’ve found very little. I don’t know if that’s me getting more settled in my way, or if the algorithm is worse.
Part of the phenomenon was not trying to find new music, but just letting it play while I was doing something until something made me go “wait, who is that?”
Neil Cicierega’s Mouth Albums are all fire.
Triple-Q makes some real solid bangers.
I just listened to Mouth Moods this morning, it still slaps!
Ok online randos, recommend something like https://www.youtube.com/watch?v=6HYHdkEYdQE Please
is different, but maybe it will hit for you. https://www.youtube.com/watch?v=Soy4jGPHr3g&list=RDSoy4jGPHr3g&start_radio=1
though, if you like the instrumentals in what you posted you might like Fake Type. https://www.youtube.com/watch?v=Bs_AuDacuWw
last edit:
https://open.spotify.com/album/0nw2WMM6g8LsE0LzbXN03L This album gets close but I lean more for swing.
Don’t forget music blogs and reviewers (which may technically fall under “randos”). In this age of bland algorithmic recommendations, going back to reading articles and reviews written by someone with similar musical tastes has once again become my favorite way to discover new music.
Oh yeah, I bet that’s a good way too! I’ve never considered that before tbh. Maybe I’ll look into it.
Music discovery algorithms don’t have to be AI slop. Some of them used to work effectively peer to peer based on likes.
You like songs, as does everyone else. The algorithm compares the songs you liked to what other people liked, finds people who liked a high percentage of the things you did, and recommends you other songs that they liked, and vice versa. Basically “Many people who liked [song you like] also liked [song you maybe haven’t heard]”.
I said “via algorithms and AI slop”, two seperate ways of finding music, “AI slop” meaning Spotify-style playlist nonsense.
Also, algorithms create feedback loops, where popular things get recommended more, even among specific niches.
I can recommend Listenbrainz as a recommendation service.
Sadly once you like one song that’s been on the radio once, it starts spiralling into other songs (often good even) you know from the radio and 0 other songs. With things that kind of come in sets (like “songs that played often on X channel in the 90s”) it becomes quickly a game of complete the set rather than discovering new music you’d also like.
this is my annoyance too
With respect, that’s a bit like saying twitter doesn’t have to be a far right hate speech enabler. What something is, and what something could be, I’m afraid in this case are irreconcilable.
Skylight (2012? mayb 2013) by AtomA
I mostly use bandcamp tags, which works better than you’d expect.
Anyway, you should check out Carcosa.
Carcosa… The King in Yellow?
Well, the Canadian metal band, who probably named themselves after the book.
ok then, enjoy the guitarists with the best phrasing :
