Ages ago I was a sequencer geek (Impulse Tracker!) while also noodling around with guitar, and I noticed something strange: I made music I liked a lot more when I composed on guitar and transposed onto the sequencer afterwards. After a lot of experimentation, I realized that the constraints on what my hands could do on guitar were (of course) having a huge impact on what I tried to do when composing -- and struggling with the constraint was helping me make music I liked more.
I like a vision for practical machine learning where we spend less time on plumbing and more time thinking about the kinds of constraints (e.g. through input encoding) that enable "creativity" on the part of the machine.