Articles like this are why I come back to HN. Interesting technically, kinda novel and fun. Got me thinking about datasets that may be sitting on old HDD, got TBs of old video and audio from projects of past. Blogs like this help point the way.. Now if only I had the time..
the spectrograms are 128x173 (128 mel frequency bins by 173 time frames)
the encoder is downsampling 4 stages of stride 2 convolutions so it halves dimensions 4 times
0: 128 x 173
1: 64 x 87
2: 32 x 44
3: 16 x 22
4: 8 x 11
Then i used 4 separate channels.
This was somewhat arbitrary due to the local training constraint. This would be a hyper parameter worth tuning if I had time to dig into this more.
I trained this a few month ago and don't remember exactly what I tried before I arrived here, but I only ran the whole process 2 or 3 times because of how long it took to train.
Hope this answers your question!
I wouldn't exactly say it's trying to solve a problem. It's to explore and see what happens which is what music is all about. It's also a unique niche model I haven't seen before.
Decomposing sounds from (fully produced?) tracks into underlying components, and then giving the user the option to synthesize them with different parameter settings. I think.
I was trying (and failing) to do this the other day. It’s a really interesting problem space and I love to see someone with a more solid foundation give it a try.
I always roll my eyes when I see LLM weirdos talk about getting models to run on "old" hardware and finding out it's hardware that's still better than what most people have access to.
It doesn't make it any less impressive to those who know what hardware requirements for LLMs usually is/are but for those with no idea it usually ends up reinforcing bitterness towards it as they feel annoyed that their own hardware is somehow worse and yet are unable to upgrade because of said LLMs stealing all the hardware in the world all while RAM/memory/storage manufacturers manipulate the market(s) against them.
The Geforce GTX 1060 launched 10 years ago with a MSRP of $249. It spend 5 years and 4 months as the #1 card according to the Steam Hardware Survey. That makes it hard to feel that it is fair to accuse it of still being better than what most people have access to, unless you are asserting that most people have access to no GPU at all, which is likely accurate, but not likely to be accurate here, nor in any sort of enthusiast circumstance. If you lump the Intel Xe built in graphics (started with the 11th gen Core Is) and the Intel UHD (launched with 8th gen Core Is) together, the combined group would come in 6th place, with the 5 places above that in commonness for people who are actively playing steam games all being considerably faster than the Geforce GTX 1060 or Geforce GTX 1660 cards.
Interestingly, now the #1 GPU is the GeForce RTX 4060 Mobile version, which I believe is the first time the top has been a laptop chip instead of desktop chip.Items #2 and #3 on the list are the 2 generation old RTX 3060, followed by the 1 generation newer RTX 4060. 4th and 5th are RTX 5070 and RTX 3050.
> but for those with no idea it usually ends up reinforcing bitterness towards it as they feel annoyed that their own hardware is somehow worse
I don't think "those with no idea" spend much time thinking about their hardware at all. They respond to marketing and peer-pressure influences, but most of them are not upgrading phones or laptops because they can't run AI on it.
Most people I know have been wanting upgrade cycles to slow down for quite some time, now. I think that those people will survive deferred retail therapy for a few years.
If you are curious I used a NVIDIA GeForce GTX 1660 SUPER
So to be exact, it came out 7 years ago (I upgraded at some point on this desktop a long time ago and didn't remember the exact year) (I updated the article to reflect this now)
This cost $230 new and you can get one now for $100 which I don't think is too out of reach.
This is a really really fun sounding project - ironically, because there are no audio samples provided at all. I would have thought a music producer creating samples for music would naturally let you listen to what they were making.
That I didn't get from the text.
0: 128 x 173 1: 64 x 87 2: 32 x 44 3: 16 x 22 4: 8 x 11 Then i used 4 separate channels.
This was somewhat arbitrary due to the local training constraint. This would be a hyper parameter worth tuning if I had time to dig into this more.
I trained this a few month ago and don't remember exactly what I tried before I arrived here, but I only ran the whole process 2 or 3 times because of how long it took to train. Hope this answers your question!
It doesn't make it any less impressive to those who know what hardware requirements for LLMs usually is/are but for those with no idea it usually ends up reinforcing bitterness towards it as they feel annoyed that their own hardware is somehow worse and yet are unable to upgrade because of said LLMs stealing all the hardware in the world all while RAM/memory/storage manufacturers manipulate the market(s) against them.
Interestingly, now the #1 GPU is the GeForce RTX 4060 Mobile version, which I believe is the first time the top has been a laptop chip instead of desktop chip.Items #2 and #3 on the list are the 2 generation old RTX 3060, followed by the 1 generation newer RTX 4060. 4th and 5th are RTX 5070 and RTX 3050.
I don't think "those with no idea" spend much time thinking about their hardware at all. They respond to marketing and peer-pressure influences, but most of them are not upgrading phones or laptops because they can't run AI on it.
Most people I know have been wanting upgrade cycles to slow down for quite some time, now. I think that those people will survive deferred retail therapy for a few years.
If you are curious I used a NVIDIA GeForce GTX 1660 SUPER So to be exact, it came out 7 years ago (I upgraded at some point on this desktop a long time ago and didn't remember the exact year) (I updated the article to reflect this now)
This cost $230 new and you can get one now for $100 which I don't think is too out of reach.