If you like funky Argentine funky indie pop? Bandalos Chinos are the dogs bollocks
Friends?
Discovery, by Daft Punk (☞ﾟヮﾟ)☞
If someone don't know, it's an album name, alternatively known with music0video movie "Interstella 5555: The 5tory of the 5ecret 5tar 5ystem", basically a music-video for whole album, bit anime.
I don't talk to people I just grab my music straight from the game files and random youtube videos that I don't use youtube but I randomly remember stuff sometimes or find out about something and use yt-dlp or just pipetube or whatever I have. and then use vlc or any random file player for that matter.
[ stretches ]
Alright... I guess it's time for another one of my "I will listen to your song" posts
Here we go https://lemmy.world/post/50708959
EDIT: Just noticing plenty folks are sharing stuff in here anyway. Whoops. Egg meet face. =3
Browsing the top 10 on sites like Redacted or Orpheus became my preferred way of discovering new music.
If you like the Beatles and trippy/weird song lyrics, check out Klaatu
My playlist hasn't been updated since the late 90s.
This has to do with the death of music journalism in general. A lot of curation function was done through magazines and online publications, many of which are now gone or much smaller than they used to be: Pitchfork, Paste, NME, Rolling Stone and so on. Now curation is done through niche influencers.
By the way I do some curation on Youtube with an emphasis on Austin based indie and folk music. You can check out my Youtube of live music videos:
Best music discovery I’ve had was a thread on the something awful forums maybe 2 decades ago. People would post their favorites or ones they wanted similar artists to, and folks would chime in with suggestions. I discovered so much music in that thread, stuff that has become my core favorites. I learned about Chromeo in that thread (back when Needy Girl was new) and they have been in my top 5 or 10 ever since.
I do enjoy the Apple Music suggestions, but finding new is so much slower and more hit or miss.
There should be a site for community driven music suggestions similar to that old thread. Especially nowadays when so much is independent and obscure.4
I have all my tv shows curated for me via tunblr gifsets
I've been finding new music as last year I discovered a group that shares 50 songs a year, that's been running since 2009. I actually already knew about it as artists I already follow are involved with the group, I just somehow never connected the dots until recently. This shit is gonna last me ages
My bandcamp findings dump this year so far :3
My last Bandcamp Friday haul: -Fabiola Mendez -Pateka -Catpack -Work Money Death -Genevieve Artadi -Tres Leches (Hiatus Kaiyote) -Jazzbois -Manela
One of my favourite bands. Solo albums by Louis and Genevive (the duo behind Knower) are also fire. Knower - Knower forever
Love Louis Cole and everyone even remotely associated with him. Genevieve Artadi, Moonchild, Jacob Mann, Thundercat, Ben Wendel, MonoNeon… and then going from those guys also lead into a lot of other great music.
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]".
Everything a computer does may as well be magic to 99.9% of people.
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.
True. But even that can be tackled in recommendation algorithms (or attempted). The main issue I see is that the companies that produce them don't have their goals aligned with yours and rerank results to benefit their bottom line. That said, I've gotten much better recommendations for books, music and games from people online and friends than from any such system. Worst case the recommendation is not great and that is still an opportunity to talk to the person who recommended it.
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.
There collaborative filtering algorithms do tend to have a popularity bias. The other downside is that these algorithms also don't help new music and musicians get found.
Yes, though I'd argue that's the same downside :D
I've worked in recommender systems for news specifically myself for a couple years so if anyone has some questions that aren't too identifiable, AMA I guess
We had a system that combined your reading history (from a tracking pipeline that already existed similar to google analytics) (though it could have just as easily been sent from the front-end with the request for recommendations as we didn't precompute anything) with several scoring systems (from simple things like popularity score per article which ignores your history, to multiple complex pretrained models that use your history to calculate a score optimising for some variable), all of which can be weighed and then the scores are added/multiplied and sorted and bam, out rolls your personal list of recommendations.
We could easily tone down (even turn negative) the populatity bias, but it turned out that it was just a strong predictor for what people wanted to read (measured in both click through rate and dwell time on the clicked page), so we're not entirely sure whether news is just different (if you spent a couple of minutes per day scrolling past headlines you'll have seen everything from today, and clicked what you cared about, and left again) or we weren't really catering to the crowd that would be helped by getting non-popular recommendations, because they're drowned out by the crowd that's just looking for whatever's popular.
Anyway, AMA
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.
But this only gets you some of the larger bands. Many of the bands I listen to have no wikipedia article or even much of an online presence outside of instagram or facebook to announce gigs and shows
This is kinda genius. I'm gonna try it lol
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/
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.
Same. Over the last decade that was one of my main main ways of finding new music. Don't really had friends with similar tastes and record labels luckily all had official accounts. Plus promotion accounts who upload music from certain genres. There are definitely genres I found via the algorithm.
Listen to Fantastic Planet by Failure, you're welcome
Omg I love ELO! Jungle is one of my favourite songs by them :3
Fun bar trivia fact: ELO is the band with the greatest number of top ten hits without ever having had a number one hit.
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
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.
I recommend these 3 bands:
Mr. Bungle Grim Salvo Viagra Boys
Word to the wise every Mr. Bungle album is different so start with California for something easy and stable.
Big Url is the only AI I trust to recommend me music.
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.
I do this for cartoons. If you tell me about a cartoon I haven’t heard of my immediate reaction is to download it.
I have almost 600 cartoon series, none older than late 80s.
Dungeon synth
Seeing who's playing with bands you like can be an inspiration. That's how I found Slothrust, years ago.
Neil Cicierega's Mouth Albums are all fire.
Triple-Q makes some real solid bangers.
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
Community Rules
You must post before you leave
Be nice. Assume others have good intent (within reason).
Block or ignore posts, comments, and users that irritate you in some way rather than engaging. Report if they are actually breaking community rules.
Use content warnings and/or mark as NSFW when appropriate. Most posts with content warnings likely need to be marked NSFW.
Most 196 posts are memes, shitposts, cute images, or even just recent things that happened, etc. There is no real theme, but try to avoid posts that are very inflammatory, offensive, very low quality, or very "off topic".
Bigotry is not allowed, this includes (but is not limited to): Homophobia, Transphobia, Racism, Sexism, Abelism, Classism, or discrimination based on things like Ethnicity, Nationality, Language, or Religion.
Avoid shilling for corporations, posting advertisements, or promoting exploitation of workers.
Proselytization, support, or defense of authoritarianism is not welcome. This includes but is not limited to: imperialism, nationalism, genocide denial, ethnic or racial supremacy, fascism, Nazism, Marxism-Leninism, Maoism, etc.
Avoid AI generated content.
Avoid misinformation.
Avoid incomprehensible posts.
No threats or personal attacks.
No spam.
Moderator Guidelines
