[dimatura]

One thing that strikes me about almost every AI-generated track (from academic or commercial generators), is that even if it's often "competent" - in that it has reasonable melodies, chord progressions, etc - is how average it is. Mediocre, taking the term literally. In a way that also highlights cliches and crutches that are common in human-made music. Somewhat reminiscent of GPT text that drones on and on in a grammatically correct way but conveys little of interest. This is of course not unexpected, given how these models are trained. I wonder if this will have an effect of pushing (human) musicians to be more experimental - to move away from the conventions that are now just a click away for anyone.

[chefandy]

Yeah-- in a professional workflow, at best, these tools are for getting ideas rather than creating output that will be used directly. Lots of folks use them for actual creation because they're just so enamored with the ability to create vaguely technically competent output from text, but they're all pretty much a bee-line to mediocre, and overcoming mediocrity is absolutely the most difficult part of working with AI output. The same is true with text, as you mentioned, and image generators. As Charles Eames said, "The details are not the details. They make the design." Well, these tools suck with details, and details convey character, perspective, message, meaning, etc. Surely the tooling will improve this in years to come, but it certainly hasn't yet.