• yoriaiko@lemmy.blahaj.zoneEnglish
    9·
    1 day ago

    Discovery, by Daft Punk (☞ﾟヮﾟ)☞

    If someone don’t know, it’s an album name, alternatively known with music-video movie “Interstella 5555: The 5tory of the 5ecret 5tar 5ystem”, basically a music-video for whole album, bit anime.

  • KoboldCoterie@pawb.socialEnglish
    73·
    3 days ago

    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]”.

    • strawberry_enjoyer42@lemmy.blahaj.zoneOPEnglish
      13·
      3 days ago

      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.

      • john_lemmy@slrpnk.netEnglish
        3·
        2 days ago

        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.

    • NightFantom@slrpnk.netEnglish
      13·
      3 days ago

      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.

      • 8uurg@lemmy.worldEnglish
        1·
        2 days ago

        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.

        • NightFantom@slrpnk.netEnglish
          2·
          2 days ago

          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

    • doleo@lemmy.oneEnglish
      31·
      3 days ago

      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.

  • CriticalMiss@lemmy.worldEnglish
    2·
    2 days ago

    Browsing the top 10 on sites like Redacted or Orpheus became my preferred way of discovering new music.

  • dwightb@lemmy.worldEnglish
    2·
    2 days ago

    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:

    https://youtube.com/@dwightbsaustinmusicarchive

  • 4grams@awful.systemsEnglish
    2·
    2 days ago

    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

  • Skankboot@sh.itjust.worksEnglish
    14·
    3 days 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.

    https://youtu.be/_v0iGBBiXBI

    • Baŝto@discuss.tchncs.deEnglish
      3·
      2 days ago

      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.

  • 58008@lemmy.worldEnglish
    8·
    3 days ago

    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.