This isn't like text classification, the signal many orders of magnitude higher bitrate and so many more corners need to be cut. It's likely going to be nearly impossible or at least not remotely worth it to generate an audio signal that is truly undetectable in the foreseeable future.
Today. Trying to detect AI is like extracting water from puddles in a lake that is quickly drying up. What is the point in the short term if it's impractical in the long term? It will catch some low-hanging fruit in the best case, and will find false positives in the worst.
if the ai picked a bunch of samples and combined them together and mastered using an mcp to a DAW, how is that particularly distinguishable vs a person doing the same thing badly?
i can see how the llm generation pictures of spectrograms is essy to spot, but much less so with tool following.
even worse of you using a vla to have it actually play the guitar and use the recording as a sample.
theres some time and setup to make it happen sure, but somebody put that all in a studio and expose an mcp
You are right, the output of a model that generates music directly is, for now, easy to categorize as AI.
What this big flux of AI generated music online isn't really that. It'a a tiny bit autogenerated stuff and a whole lot of automatically remixed stuff. The reason it can not be easily classified as AI is because quite a bit of human produced music is also that, and you'd just shut out real users.
'Detecting AI' is not a problem that has real solutions, the only avenue is something supply side like synthid. But that harms users too, by introducing further barriers for indie users.