Slightly off-topic. Now that 1920s jazz music is falling into public domain, has anyone tried to reinvigorate the music using AI and generative adversarial approaches? Pre-1940s music didn't have high-fidelity sound, so the strong bass lines weren't captured. In theory, we could "downgrade" modern recordings to sound like 1920s recordings, then use adversarial techniques to train the machine on how to restore the antique recordings. Anyone know of any work being done in this area?

People who are interested in this application should check synplant[0]. It has a ML technology called "Genopatch" which gives you 2 functionality:

1. you can try to describe a sound with some tags and it will try to generate a sound to capture the feeling of these tags

2.you can feed it with a sound sample and it will try to re-synthesize the sound with its synth engine. Though the end result will usually be just a "re-imagined" version of your input sample.

My guess is the underlying model is not a "deep" model. The main benefit is that the end result is not a wave file, but a list of generated parameters that can be synthesized by the synthplant engine. And now it comes the interesting part: you can tweak these parameters to finetune the generated sound. These parameters have actual meanings (FM ratio, reverb etc.)

[0]: https://soniccharge.com/synplant

Confused. Why not just make the kick drum from a sine? Seconds

This has been done years ago. See https://audialab.com/products/emergent-drums-2/ for instance.

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..

Modeled reverb yet no modeled compressor, hrmm, is compression not used on kick drums (or not a big part of the sound)?

I just wish it had samples! I want to hear it

For a moment I thought Gen AI meant the current generation of kids. It's a fitting moniker

Excellent article! I think it has the right level of detail, one question though: why the shape of the tensor? 4x8x11.

That I didn't get from the text.

someone needs to take care of the snares

I have to admit I don't understand what exactly the problem is we're trying to solve with ML here...?

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.

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.

English adjectives are highly contextual. In this context, the author's clear meaning is in context to the current generative AI boom.

For sure.

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.

> 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.