Deezer says 44% of songs uploaded to its platform daily are AI-generated

> I'm trying to learn music production with a DAW, sometimes I wonder if I'm wasting my time. Part of my reason for trying this was reading how creative endeavors can be therapeutic (I'm dealing with burnout/depression/cptsd).

If you enjoy the process and its outcomes, then it's not a waste of time. If you are forcing yourself to do it or have another motivation for it that is not rooted in genuine interest, then yes, you are wasting your time.

> I feel like AI is making this question of "why do it" or "what is worth doing" even more urgent

This is a spiritual question, so you will have as many answers as there are askers. I found my answer and am happy to share it with you. Why do it? Because I want to. What is worth doing? What I want to do or what gets me to the things I want. Wanting is a very important process, that is often damaged by conditioning. We are told that some things we want are bad and that some things we don't want are good. Or that ego is evil. So many ways this process can go wrong. I think fixing this in oneself is part of becoming an actual adult. Once you know what you want and what you don't want, you no longer are dependent on others telling you what to do or forcing you to do things you shouldn't be doing. Ego is not evil, it's there for a reason. Some people have an overgrown one while others have an underdeveloped one. What is needed is balance. I don't think the pattern recognition machine has anything to do with it. I suspect, that a lot of people who use music as a band aid for personal problems, i.e. people who build their identity around being special due to music making, are the ones who are afraid of AI, but if you just enjoy making music, then what does it matter if music itself is patterned and if a machine can exploit that? It doesn't take anything away from the joy of making music, if you experience it in the first place.

I suppose that my generalization was too broad and that LLMs can be either good or bad at writing tests depending on your workflow and expectations.

I'm closely supervising the LLM, giving it fine-grained instructions — I generally understand the full interface design and most times the whole implementation (though sometimes I skim). When I have the LLM write unit tests for me, it writes essentially what I would have written a couple years ago, except that it tends to be more thorough and add a few more tests I wouldn't have had the patience to write. That saves me quite a bit of time, and the LLM-generated unit tests are probably somewhat better than what I would have written myself.

I won't say that I never see brain-dead mistakes of the "5-vertex square" variety (haha) — by their nature, LLMs tend towards consistency rather than understanding after all. But I've been using Claude Opus exclusively for while and it doesn't tend to make those mistakes nearly as often as I used to see with lower-powered LLMs.

That would be neat, but I really don't see it happening. In software-land, it's my sense that, if anything, AI is working against open source. AI is creating busy work for open source maintainers with a large volume of low quality PRs, and scrapers are burdening those who maintain their own small-scale, public facing infrastructure.

Meanwhile, AI is ingesting their publicly available data to improve itself, with the implicit (if not explicit) goal of making those projects irrelevant (why read the docs, participate in a forum or chat, or submit a PR when you can ask your AI thing to just write the code you want instead?).

Furthermore, if a software developer is of the opinion that AI is "bad" in some way and they want to resist it, I think it would make the most sense to keep their code private. Open source is feeding AI.

Good for users too; I much prefer a curated selection since I don't have time to drink from the firehose