Maybe I’m a bit oldschool, but until ML becomes self-aware it won’t be able to replace a drummer, mixer or any other kind of musician. Anything related to ML and music which I’ve seen so far basically caused the same two reactions: “WTF? They can do that with ML? This is awesome!” “Ok, to be honest I wouldn’t listen to this if I didn’t knew it was produced by ML”

Yes, there are many use cases here. If we're talking composing something entirely by itself, start to finish, the technology is nowhere near there (at least by my subjective music taste standards). We may not need self-awareness to get there, but we'll probably need something closer to AGI.

But I could think of many ways existing ML could help producers and composers while they're working. They can present possibilities and alternatives that the composer can choose from; they can find interesting combinations and permutations and patterns; they can potentially learn from your workflow and save you time in the future, etc.

I kind of have some ideas of how to develop applications like these. Maybe I should pursue them; although I currently work in a totally unrelated field.

I have been working in this space [0] for a number of years, and I agree, it's becoming extremely promising.

[0] https://sonicmultiplicities.audio

Where may one find good datasets for this sort of research? I'm interested in making AI musicians.

There is no such dataset out there. This way of thinking is a very self-limiting approach.

In my case, I built my own, through 10 years of organic instrumental input for the system to chomp through.

That's how you apply machine learning to the discipline of music.

The skill of making music well enough that I can trust a machine to emulate my style is unfortunately absent in me. Your response is not only patronizing but also loaded with false premise.

It's also apparently wrong: https://magenta.tensorflow.org/datasets

Thanks for your contribution.

That's too bad that it's absent in you. Maybe you should try to be a musician first, before trying to master AI-assisted music-making.

You say that I am applying a false premise and that I am apparently wrong -- but what kind of nonsense have those datasets output that comes even close to what I [0] have?

Also, you strongly misunderstand the value of having to build your own dataset of actual human input to achieve anything good in AI-assisted music-making. Good musical AI does not simply seek to mimic a dataset. That's such a pedantic oversimplification of this noble, difficult task that those of us who actually care about this issue face.

This problem cannot be solved like an object detection problem. You have a lot to learn before you start trying to insult those of us who have devoted much of our lives to the "problem" of AI in music.

This is art, buddy. Stay away from it if you are going to treat it like a mindless AI researcher at some institution.

[0] https://sonicmultiplicities.audio