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naraburns  nihil supernum  1yr ago (text post)   33253 thread views

Culture War Roundup for the week of February 20, 2023

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How does traditional machine learning even begin to address these problems? One way would be to say, feed it the sheet music for Beethoven's Fifth, and then show it as many recordings of that piece as you can until it figures out that the music lines up with the notation. Then do that for every other piece of music that you can. This would be a pretty simple, straightforward way of doing things, but does anyone really think that you could generate reasonably accurate sheet music to a recording it hadn't heard, or would you just get some weird agglomeration of sheet music it already knows? After all, this method wouldn't give the computer any sense of what each individual component of the music actually does, just vaguely associate it with certain sounds.

Why wouldn't it? I imagine there would be issues where it gets stuff weirdly wrong like Stable Diffusion's famously mangled hands or ChatGPT's famously incompetent arithmetic, but I'd expect such a trained model to generally get the sheet music right. No idea how it would compare to a typical real trained human musician at this - my guess would be that it would be similar to how Stable Diffusion can get you images that clearly look very close to something a human artist might draw based on the prompt, just with bizarre artifacts like the aforementioned hands (and eyes, and continuous objects disappearing/getting misaligned when hidden behind stuff, and hair blending into clothes, and clothes blending into skin, and...). I think existing machine learning tools show that the upper limit of precision and accuracy of "vaguely associate it with certain sounds" is (potentially) very high.

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