Give you ‘physical’ forever access and doesn’t take up so much space.
Some of us figured this out 20 years ago and never turned back. (I figured it out about the time that I realized I had more music in my mp3 collection than the college radio station I volunteered at in 2000.)
My Cinemageddon account turned 18 earlier this year.
I’m evolving a “music player” system which basically consists of a fleet of individual players, each with a full copy of the music library because, even at today’s storage prices, why not? Storage for 10,000 songs at higher fidelity than a brand new LP vinyl album costs less (adjusted for inflation) than an album of 8 songs did back in the 1980s, and only 2 of those 8 songs were usually any good…
So, have a music player in every bedroom, living room, family room, kitchen, car, patio - turn them on when you want, synchronize them when you want - split off and listen to your own playlist when you want - and every player contains a synchronized backup of all the music so you can just drive off with one, go completely off-grid and never interrupt the playlist. The only network traffic is from your phone interface to choose your playlist or synchronize with players nearby - or across the planet.
This does sound very attractive. I’ve been trying to get a few family members of of Amazon Alexa’s and this is one of the biggest arguments they give me against it. I’d be curious to hear how far your evolution has come with this. I do have a rather large collection of music mostly from the olden days of piracy but would be interested in some doing some ‘updating’ to the library and the possibility of getting some family further away from Amazon.
In theory, it speaks for itself. In practice, this has been an evolving project and I believe my current automatic song end finder for fade outs is not as good as a previous generation that I built most of my collection with. You can edit each passage’s lead in / lead out points separately and it’s not a half bad editor, but it’s still clumsy and very time consuming.
If I were introducing this to a new music collection, I’d fire up an LLM agent, have it read the project documentation, tell it where the player (Pi) is on the network (give it ssh key access, and have the music files in-place on the Pi for it to find), and tell it to go through the database induction / setup process. That may take most of 24 hours on a collection with ~10,000 songs…
Once it’s setup, you should be able to define the kind of music you want to hear at particular times of day by choosing 5 to 8 representative songs, the “Program Director” will then queue up similar songs automatically and play them through.
I’ve just barely got the “multi-room” setup going, it has several rough edges, but once it gets synced up it appears to be working pretty well.
If you like to play with LLMs for coding, this is an interesting project to try them on. I find it’s right about at the threshold of what a model like Claude Opus 5 can handle / make forward progress with. If anything about how it’s working bothers you, feel free to ask your LLM to smooth those rough edges in ways that make sense to you, you can at least maintain your own branch and maybe we can merge together a “best of both” situation someday.
Some of us figured this out 20 years ago and never turned back. (I figured it out about the time that I realized I had more music in my mp3 collection than the college radio station I volunteered at in 2000.)
My Cinemageddon account turned 18 earlier this year.
I’m evolving a “music player” system which basically consists of a fleet of individual players, each with a full copy of the music library because, even at today’s storage prices, why not? Storage for 10,000 songs at higher fidelity than a brand new LP vinyl album costs less (adjusted for inflation) than an album of 8 songs did back in the 1980s, and only 2 of those 8 songs were usually any good…
So, have a music player in every bedroom, living room, family room, kitchen, car, patio - turn them on when you want, synchronize them when you want - split off and listen to your own playlist when you want - and every player contains a synchronized backup of all the music so you can just drive off with one, go completely off-grid and never interrupt the playlist. The only network traffic is from your phone interface to choose your playlist or synchronize with players nearby - or across the planet.
This does sound very attractive. I’ve been trying to get a few family members of of Amazon Alexa’s and this is one of the biggest arguments they give me against it. I’d be curious to hear how far your evolution has come with this. I do have a rather large collection of music mostly from the olden days of piracy but would be interested in some doing some ‘updating’ to the library and the possibility of getting some family further away from Amazon.
So, the music player rename migration is done - I don’t think too much broke in the process.
The source repo is here: https://github.com/MangoCats/Lempi
In theory, it speaks for itself. In practice, this has been an evolving project and I believe my current automatic song end finder for fade outs is not as good as a previous generation that I built most of my collection with. You can edit each passage’s lead in / lead out points separately and it’s not a half bad editor, but it’s still clumsy and very time consuming.
If I were introducing this to a new music collection, I’d fire up an LLM agent, have it read the project documentation, tell it where the player (Pi) is on the network (give it ssh key access, and have the music files in-place on the Pi for it to find), and tell it to go through the database induction / setup process. That may take most of 24 hours on a collection with ~10,000 songs…
Once it’s setup, you should be able to define the kind of music you want to hear at particular times of day by choosing 5 to 8 representative songs, the “Program Director” will then queue up similar songs automatically and play them through.
I’ve just barely got the “multi-room” setup going, it has several rough edges, but once it gets synced up it appears to be working pretty well.
If you like to play with LLMs for coding, this is an interesting project to try them on. I find it’s right about at the threshold of what a model like Claude Opus 5 can handle / make forward progress with. If anything about how it’s working bothers you, feel free to ask your LLM to smooth those rough edges in ways that make sense to you, you can at least maintain your own branch and maybe we can merge together a “best of both” situation someday.