This is an interesting and informative article but to be a bit meta I'm concerned when I see articles like this on HN because they don't usually do a great job of summarising the work that has been done in a certain area before the advent of deep neural nets. This is important because very often, especially when it comes to generative art, the standard approaches used before deep neural nets could do thins that modern deep neural nets cannot do, in particular when it comes to structured generation.

For example, alorithmic music is the subject area of generating music with algorithmic approaches, not necessarily using a computer. The wikipedia page seems to be a bit poor in detail but it lists a number of different approaches most of which are not machine larning approaches:

https://en.wikipedia.org/wiki/Algorithmic_composition

I'm by no means an expert but that's the point. When a non-expert reads an article like the one above, I fear they may get an impression that neural nets are the first approach ever to generate music, or that they are the best approach ever to generate music, or anyway some kind of misunderstanding that is natural to draw from incomplete information.

The thing to try and keep in mind is that computer scientists, and other scientists and creative people, had been able to do amazing things with the tools they had in their disposal long before the advent of deep neural nets. And that there are many such tools that are not deep neural nets. Somehow these amazing things flew under the radar of technies - until deep neural nets came along and suddendly everyone is amazed that "wow, neural nets can do X!". Well, what else can do X? That's something worth trying to find out.