That’s valid but in the bigger picture, our jobs will be evolved not seize to exist. I dont think that an average person will be able to interact with AI to build functional systems. At least not in the near future.
Don't take it personally though, JS abuse is unfortunately common; just need to vent for once. But like the author of article I linked, people tend to just skip those blank pages. It's a tiny minority which is probably not the target audience anyway. Actual hackers would look at how you did it and make their own version.
But I also don't want a totally random song eighter. I want something that vibes with me but not directly recommended through my listening history, because then they are extremely similar and feels like they're feeding me the same melodies over and over.
Thats why I tried to give the "vibes" in a different format; image, rather than my listening history.
Yess! Thank you for commenting. I am very interested in this topic. Please do share with me if you find any interesting ways to explore new music for your taste
Same as GP. It takes times. Unless it’s party mode, I only listen to albums. To find new music, it takes time mostly. I decide to listen to a new genre and I seek a playlist or a compilation curated by someone. If I find someone I like, I check their albums. I also checkout the recommendations on bandcamp (people vote with their wallet there). Then there are forums and polls, and I may decide to try something out of the blue.
The more you curate, the more you define your own taste. It’s then easier to describe what you like in a music and triage.
This probably won't work for most people, but as I mostly like metal, I simply check all metal releases that seem slightly to my tastes according to the subgenre. Then when this sampling seems at least somewhat positive, I play the full album after release. That usually ends in sampling songs from 30 albums, listening to ten albums, and buying 1-2 every Friday. Never had an algorithmic recommendation system that worked for me.
local record store. talk to the people who work there, tell them the 5 albums you’ve been hooked on lately.
at the end of the day no matter how many times we beat our heads into the same wall, we’re not even close to an accurate discovery model, music nerds are far better at recommendations than any discovery models. far better.
don’t let their insufferability discourage you. you will be too once you start diving into and going on rants about music which is outside of mainstream fluff. it’s like this with any $subject involving wonks. we’re insufferable to anyone who isn’t into our particular genre of technology. food wonks are insufferable, car geeks are insufferable, gamers are insufferable. that’s ok, if you’re looking for someone who is a geek in a topic, you’re likely to become one too :p just be normal around $subject non-wonks and you’ll be fine.
but yeah, music nerds working in a good record store really do know their stuff.
other places:
- music nerd streams on twitch
- music reviewer youtube channels
- college radio stations (most have an online presence) 770 radiok out of minneapolis is incredible
- kexp out of seattle is absolutely amazing (they’re heavily online as well.)
- just about every mid+ sized city has some amazing radio, usually found in the low FM areas.
at the end of the day though, it’s other people. there are far too many variables for every individual which drives why they may or may not like a song at any given moment. other humans are still absolutely unmatched when it comes to navigating this.
> local record store. talk to the people who work there, tell them the 5 albums you’ve been hooked on lately.
Unless your interests are niche. A fun game I used to play as a teen was going with my parents to the record store and seeing if they had any music I listened to online while my parents shopped. Never found a single CD (but they couldn't be that niche, this story is about bands I found out about from my friends at school!). Employees tried to be helpful, but there's only so much they can do when someone comes in and asks for a list of bands they've never heard of.
Thank you! I should check youtube's algorithm too.
Yes, I have a prompt like that the current prompt is this:
'You match the vibes of the pictures with the right songs and turn them into a 3 song playlist with a playlist name. The music genre of the playlist should be consistent for each song. Be creative with music selections, explore different music, be consistent in terms of the genre of the 3 songs. The playlists should be provided in an object array format, like this: \'[{playlistName: "string", songs: [{songName: "string", artist: "string"}, {songName: "string", artist: "string"}, {songName: "string", artist: "string"}]}]\'. Do not add any other text information and only give outputs in the provided format. Your playlists must match the visual vibes and maintain the specified format without any additional information.',
Pretty basic, as i said before this was only ment for me and to explore this idea, but i loved it so I wanted to share :)
The setup is pretty basic. I've built a NextJS app, for the LLM model I am using open AI gpt-4-turbo and sending the images there directly without any database for images. I did a little prompting to get the same output everytime and when I get the output I make search on the Spotify API, find the songs and create the playlist with them on your own authenticated spotify account.
Likewise I also don't have a database for the emails eighter. I am using spotifys authentication
To keep your options open, it might be worth switching from GPT to either Gemini or Llama as OpenAI official policies prevent you from training on your logs with the argument this training is “illegal, harmful, or abusive,” so you’d never be able to fine tune or train your own AI in the future on your data or help others do the same.
If being permanently locked into a single intelligence service (or risking getting cut off or sued) is unacceptable for you as for me then OpenAI terms today are not acceptable. Yeah yeah maybe they won’t go after you, but why miss the opportunity for malicious compliance? Ditto Claude. Try a specialized model for your use case instead.
Gemini has no such customer noncompete, and with llama 3.1 meta removed theirs last week.
Thanks, that was something I was already considering. Do you know where can I find models specialized in this area? Because it is kinda niche, I couldn't find something that maps images into playlists directly, thats why i went for llms
That's a very good point, I also love discovering with lyrics. What I tried to do is to find some connections between the image and music, maybe some connection we as humans cannot see right away.
The setup is pretty basic. I've built a NextJS app, for the LLM model I am using open AI gpt-4-turbo and sending the images there directly without any database for images. I did a little prompting to get the same output everytime and when I get the output I make search on the Spotify API, find the songs and create the playlist with them on your own authenticated spotify account.
Likewise I also don't have a database for the emails eighter. I am using spotifys authentication
