One, a ubiquitous restoration model. Find degraded copies of music in the wild, old YouTube's, transcodes, vinyl rips, bad masters, half destroyed tapes... Pair them with modern pristine lossless encodes of the same music, train. Then use that model on music we don't have pristine copies of.
The second is similar but more specific. There are so many stems floating around from popular music. My idea is to compare individual stems against the results from MVS/Spleeter(same song, same instrument). This would surely stand a chance of pushing that tech forward, so we can treat the FFT artefact heavy sound of new efforts.
Thirdly, from a creative point of view, I wanna do the equivalent of image to image on my tracks... But I actually want it to hallucinate in the manner of the early deep dream images, I want to be able to play with that space..
I can knock out musak to spek in minutes already, gen music is just reducing low effort to nearly no effort, preventing people with needs from networking with creators.... Uhh.. but I think that's a very general issue with Gen AI away from the corporate/entrepreneurial dev space