Ask HN: Why aren't generative music ML models as popular as image and LLMs

While there will be some dispute for years to come, the capabilities and potential of image generation models, and Large Language models, appear to be far beyond dispute. But the noise (sic) heralding ML models that generate music is comparatively low. I find this to be both interesting and counter-intuitive, as the quality of Machine Learning models are often tied to the availability of a large volume (can't help it...) of curated data.

Very few domains readily offer data as well curated as the corpus made available by many centuries of music. Music generation models shouldn't be too far off LLMs in terms of sophistication.

So what has happened in this area? Might it simply be the case that the field is overlooked because it's a little more difficult to demonstrate the state of the art in print and social media? Or are there other, more technical reasons (copyright for one)?