This isn't a problem that can be solved with more data. It's a function of model architecture, and as OpenAI has demonstrated, larger models generally perform better even if normal people can't run them on consumer hardware.

But there is still a lot of room for more clever architectures to get around that limitation. (e.g. Shortformer)

I think it's both - we have a lot of architectural improvements that we can try now and in the future, but I don't see why you can't take the output of generative art models, have humans rate them, and then use those ratings to improve the model such that its future art is likely to get a higher rating.