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Ask HN: AI for Music Discovery

17 points by noashavit 2y ago

Are there any AI tools for music discovery by genre/related artists/combination of genres and artist the user likes (that last one would be ideal)? Spotify's DJ is alright, but it tends to loop through the same artists, at least for me. I'm looking for totally new artist discovery based on preferences / filters

martinky24 2y ago
Why's it gotta be AI based? Try out https://www.music-map.com https://www.music-map.com
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gnabgib 2y ago
There's https://cosine.club/ https://cosine.club/ which finds music by similarity
- noashavit 2y ago
  Thanks for sharing, I do love electronic music :-)
- 4d4m 2y ago
  This is such a lovely site. Found so many similar songs to the ones I've released over the past year. The UX/UI is wonderful as well. Ty!!!
  - gnabgib 2y ago
    I thought so too. The developer posted on HN two weeks ago[0].. I hope they expand it (with mix/remix/remakes you can have dozens of versions of one track) [0]: https://news.ycombinator.com/item?id=40074246 https://news.ycombinator.com/item?id=40074246
diggum 2y ago
Oo! An opp to share a project I built! Please check out ottomusic.ai or the original demo I built at demo.ottmomusic.ai. We were one of the first AI-powered, prompt-based music recommendation service, and I still think far better than Spotify or Amazon’s recent drops. (For users of the demo site, you can get a Spotify link to the generated playlist in the console. Shhh.)
- noashavit 2y ago
  I just requested access to the beta :-)
adrianmsmith 2y ago
https://www.last.fm/ https://www.last.fm/ has the ability to play "radio" via a Spotify Premium account. It can either track your existing Spotify account as you listen to stuff and learn what you like, or you can just start using it and skip what you don't like and it learns pretty quickly. It's not AI though, and hasn't changed much in the last few years, but works well, and a lot of people I know (myself included) consider it the best music recommendation system that we know of currently. Certainly leagues ahead of Spotify's recommendations!
drakonka 2y ago
Not sure that it's "AI-based" in the way you mean, but this is why I've stuck with YT Music for years. It's gotten good at guessing what I'll like, and creating auto-playlists to match different moods which are a good mix of tracks I already know and love and new material. I keep hoping they'll take it further - it is literally the one thing I want Google to use all my personal data (listening history) for.
grobgambit 2y ago
These all largely bullshit IMO. The best recommendations are from humans who love music and you also share their taste in music. Once every few years an amazing recommendation bubbles to the surface on Youtube for me but compared to a music lover's top 100 for a certain year? It isn't even close. There is no reason you need algorithmic efficiency in this domain. 1000 recommendations might even be objectively less enjoyable than 10 recommendations since it will cause you to not explore any single recommendation all that much. Most of my favorite albums were not 1st listen instant favorites. Actually, quite the opposite. A great album to me is also going to be out of sample and not in the training data of what I have liked in the past. That is a large part of its greatness.
- noashavit 2y ago
  I agree, human recommendations would be the best, but those aren't always available

17 points by noashavit 2y ago

martinky24 2y ago

Why's it gotta be AI based? Try out https://www.music-map.com https://www.music-map.com

deleted 2y ago
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deleted 2y ago
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gnabgib 2y ago

There's https://cosine.club/ https://cosine.club/ which finds music by similarity

noashavit 2y ago
Thanks for sharing, I do love electronic music :-)
4d4m 2y ago
This is such a lovely site. Found so many similar songs to the ones I've released over the past year. The UX/UI is wonderful as well. Ty!!!
- gnabgib 2y ago
  I thought so too. The developer posted on HN two weeks ago[0].. I hope they expand it (with mix/remix/remakes you can have dozens of versions of one track) [0]: https://news.ycombinator.com/item?id=40074246 https://news.ycombinator.com/item?id=40074246

diggum 2y ago

Oo! An opp to share a project I built! Please check out ottomusic.ai or the original demo I built at demo.ottmomusic.ai. We were one of the first AI-powered, prompt-based music recommendation service, and I still think far better than Spotify or Amazon’s recent drops. (For users of the demo site, you can get a Spotify link to the generated playlist in the console. Shhh.)

noashavit 2y ago
I just requested access to the beta :-)

adrianmsmith 2y ago

https://www.last.fm/ https://www.last.fm/ has the ability to play "radio" via a Spotify Premium account. It can either track your existing Spotify account as you listen to stuff and learn what you like, or you can just start using it and skip what you don't like and it learns pretty quickly. It's not AI though, and hasn't changed much in the last few years, but works well, and a lot of people I know (myself included) consider it the best music recommendation system that we know of currently. Certainly leagues ahead of Spotify's recommendations!

drakonka 2y ago

Not sure that it's "AI-based" in the way you mean, but this is why I've stuck with YT Music for years. It's gotten good at guessing what I'll like, and creating auto-playlists to match different moods which are a good mix of tracks I already know and love and new material. I keep hoping they'll take it further - it is literally the one thing I want Google to use all my personal data (listening history) for.

grobgambit 2y ago

These all largely bullshit IMO. The best recommendations are from humans who love music and you also share their taste in music. Once every few years an amazing recommendation bubbles to the surface on Youtube for me but compared to a music lover's top 100 for a certain year? It isn't even close. There is no reason you need algorithmic efficiency in this domain. 1000 recommendations might even be objectively less enjoyable than 10 recommendations since it will cause you to not explore any single recommendation all that much. Most of my favorite albums were not 1st listen instant favorites. Actually, quite the opposite. A great album to me is also going to be out of sample and not in the training data of what I have liked in the past. That is a large part of its greatness.

noashavit 2y ago
I agree, human recommendations would be the best, but those aren't always available