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Wikipedia rabbitholing is my preferred method. Start on an article about a band or genre you like, then just glance through for influences and subgenres etc., read those articles to find new band names, give 'em a quick listen on whatever platform you use (usually just YouTube for me), and continue the process as needed i.e. if you don’t like what you hear for a given artist, just keep clicking till you find the next one. It sounds like it’d take forever this way, but I’ve found new bands I love within about 10 minutes of clicking, and this is consistently the case. Algorithms have never, ever recommended me anything I actually liked, and this is true for music, games, TV shows and whatever else. They just don’t work on any meaningful level.
Recent metal album I picked up on Bandcamp Friday: Cairiss - Wilderness
I do occasionally hear metal but this is the first of this subgenre I‘ve listened to. Really enjoyed it though, so I‘m open to recommendations
Unfortunately I barely have friends
Found my favourite album by scrolling new releases on Bandcamp: Plantoid - FLARE
music discovery via the internet archive tags
edit because i saw people posting reccomendations: (some random polish 90s punk) https://archive.org/details/Apatia_Odejdz-Lub-Zostan/
I too prefer human music.
Mwahahahaha my evil plan to get more good songs is working >:3
Three things ive been listening too.
• Dragon Mouth by DustMoth (fusking love dustmoth)
• Vestiges of Verumex Visidrome by Gnome
• Area 52 by Rodrigo Y Gabriela
Dungeon synth
Ohhh I’ve read about dungeon synth! Or maybe I watched a video? I can’t remember. I really should give it a try. Thanks!
It’s time for me to recommend some songs I like:
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Heaven Pierce Her - War Without Reason (from Ultrakill, instrumental)
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Sidney Gish - Impostor Syndrome
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Tally Hall - Ruler of Everything
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Miracle Musical - Time Machine
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Lemon Demon - Lifetime Achievement Award
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Jamie Paige & OK Glass - BIRDBRAIN
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Las Robertas had a new album out a few weeks ago, I’m pretty psyched about it.
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.
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 can recommend Listenbrainz as a recommendation service.
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.
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.
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.
That was largely my experience as well. Things like last.FM or listen brains would tend to give more relevant results at first. It certainly didn’t happen overnight or even soon. But the algorithm through YouTube music has gotten really good for me. I have a wide listing range but all of it still pretty niche and eclectic.
But I’m not going to lie that took it a few years to be able to do. I don’t know if they just improved their algorithm in that time. Or if my listening habits have helped it. But I’m pretty happy with the recommendations and things it brings up. The thing I try not to do as a rule of thumb. Is to thumbs down or down vote something. I have found that on tracks I don’t like if I skip them early and often. It picks up on the fact.
Again this may have changed I remember Pandora back in the early 2010s. Up voting the stuff I liked, downvoting the stuff I didn’t. It definitely got to a very narrow feedback loop with extremely poor discovery.
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.
