3 ms·

No "expansion of copyright" is needed in music, the requirements in the US are already onerous enough for the entirely original human-written and performed Blur

No "expansion of copyright" is needed in music, the requirements in the US are already onerous enough for the entirely original human-written and performed Blurred Lines to be deemed a copyright violation for consciously emulating the "feel" of a Marvin Gaye baseline. The people that need to change this status quo - like it or loathe it - are the people that want to profit from spamming streaming services with zero-effort derivatives of popular music (people that do it for fun or use 'AI' tools for post production or loop-variation will continue to be fine). I have a lot less sympathy with them than the many artists who've lost court cases for 'inspiration', and if they're relying on the whole "models learn just like people" canard they're going to be in a weaker position than usual, because not only is that deemed insufficient for people, but it's unambiguously untrue that machines "listen" like humans do (they're bulk processing files, not experiencing consonance or dissonance in the ear) or that they "perform" as opposed to stochastically transferring elements of style. Even the most cliched blues going has human reasons for note choice and intonation other than "weighted average of other blues with overlapping description"

ben_w 3y ago
> Even the most cliched blues going has human reasons for note choice and intonation other than "weighted average of other blues with overlapping description" From what I've heard about human cognition, we come up with a word-based justification after we decide what to do, it just that the research involved a brain scanner to find this out because it doesn't (usually[0]) feel like this is what's going on on the inside. So the real reason may well be "weighted average of other blues with overlapping description", followed (not preceded!) by a language model producing some convincing words that can communicate the mental state to other humans. IMO, the main difference between AI and humans right now, is that humans can do human things with far fewer examples. AI has the speed advantage that lets them read all the words in the world, listen to all the music ever recorder, watch all the videos ever filmed… but are so stupid[1] that they need to, too. [0] I do sometimes notice this in my own brain: I can have a fully-formed sentence before my inner dialogue tries to (for a lack of a better word for the internal voice) "speak" it — if I then try to skip the inner voice because I've already had the thought and turning into an imagined voice is clearly a waste of time, the part of me which is the inner voice is, for lack of a better word, frustrated. [1] Stupid on this particular axis. Intelligence isn't fantastically well defined even in humans, is badly defined cross-species, and doesn't have a singular definition at all for machines, so it is perfectly valid to consider intelligence to be a question of "what can it do?" rather than "how fast does it learn?", for which many current AI (there's no G, so narrow AI that only plays chess is fine) "smarter than humans".
- notahacker 3y ago
  IMO, the main difference between AI and humans right now, is that humans can do human things with far fewer examples. AI has the speed advantage that lets them read all the words in the world, listen to all the music ever recorder, watch all the videos ever filmed… but are so stupid[1] that they need to, too. I mean, if humans need to listen to far fewer examples to create music than an LLM needs to parse sound files, they're obviously not doing the same thing, are they? Similarly, it's unambiguously false that a human blues is the weighted average of the sound files of other blues. There are structures which are essentially identical to those used by other artists for reasons of easy improvisation, there are selections of notes played over the top which are a function of fundamental musical properties of consonance and dissonance, scale runs the instrument is suited to as well as licks that may have been directly borrowed, but the final output is dependent heavily on the actual capabilities of the artist to play and singer, which obviously aren't simply lifted from their favourite artists' recordings. Even if it's highly derivative which it almost certainly is, it's not remotely the same progress as a matrix generating a sound file from a combination of other tagged sound files and the input "12 bar blues with Stevie Ray Vaughan guitar work and BB King vocals"
  - ben_w 3y ago
    > I mean, if humans need to listen to far fewer examples to create music than an LLM needs to parse sound files, they're obviously not doing the same thing, are they? If I need much longer to run a marathon than an athlete, is that because my body is not doing the same things as the athlete, or just because it's doing all the same things but doing them worse? If a (clinical) moron tries to learn a song, and it takes a lifetime, why? (Do we even understand human brains well enough to answer that? Not my field). > there are selections of notes played over the top which are a function of fundamental musical properties of consonance and dissonance, scale runs the instrument is suited to as well as licks that may have been directly borrowed How do you learn what these things are? What do "consonance and dissonance" mean in terms of why they make you feel the way they do, and why can't an AI learn those things from examples? The qualia, that AI hopefully doesn't have but we can't tell because we don't have a test for that? Danse Macabre (Camille Saint-Saëns) was rejected at the time for how it sounded. The early cultural rejection of Blues seems to me like it was more probably racist excuses than artistic preferences, which is why I'm picking a non-Blues example. > reasons of easy improvisation … [all the other things in the previous quote, I hope this is a fair cut] … the final output is dependent heavily on the actual capabilities of the artist to play and singer, which obviously aren't simply lifted from their favourite artists' recordings. If I put the AI into a robot (or simulated) body, and the limits of that body constrained the capabilities of the output, those limit themselves make it OK? Constrain it to MIDI rather than a full waveform? This doesn't seem like it would change the answer, to me.

ben_w 3y ago

> Even the most cliched blues going has human reasons for note choice and intonation other than "weighted average of other blues with overlapping description" From what I've heard about human cognition, we come up with a word-based justification after we decide what to do, it just that the research involved a brain scanner to find this out because it doesn't (usually[0]) feel like this is what's going on on the inside. So the real reason may well be "weighted average of other blues with overlapping description", followed (not preceded!) by a language model producing some convincing words that can communicate the mental state to other humans. IMO, the main difference between AI and humans right now, is that humans can do human things with far fewer examples. AI has the speed advantage that lets them read all the words in the world, listen to all the music ever recorder, watch all the videos ever filmed… but are so stupid[1] that they need to, too. [0] I do sometimes notice this in my own brain: I can have a fully-formed sentence before my inner dialogue tries to (for a lack of a better word for the internal voice) "speak" it — if I then try to skip the inner voice because I've already had the thought and turning into an imagined voice is clearly a waste of time, the part of me which is the inner voice is, for lack of a better word, frustrated. [1] Stupid on this particular axis. Intelligence isn't fantastically well defined even in humans, is badly defined cross-species, and doesn't have a singular definition at all for machines, so it is perfectly valid to consider intelligence to be a question of "what can it do?" rather than "how fast does it learn?", for which many current AI (there's no G, so narrow AI that only plays chess is fine) "smarter than humans".

notahacker 3y ago
IMO, the main difference between AI and humans right now, is that humans can do human things with far fewer examples. AI has the speed advantage that lets them read all the words in the world, listen to all the music ever recorder, watch all the videos ever filmed… but are so stupid[1] that they need to, too. I mean, if humans need to listen to far fewer examples to create music than an LLM needs to parse sound files, they're obviously not doing the same thing, are they? Similarly, it's unambiguously false that a human blues is the weighted average of the sound files of other blues. There are structures which are essentially identical to those used by other artists for reasons of easy improvisation, there are selections of notes played over the top which are a function of fundamental musical properties of consonance and dissonance, scale runs the instrument is suited to as well as licks that may have been directly borrowed, but the final output is dependent heavily on the actual capabilities of the artist to play and singer, which obviously aren't simply lifted from their favourite artists' recordings. Even if it's highly derivative which it almost certainly is, it's not remotely the same progress as a matrix generating a sound file from a combination of other tagged sound files and the input "12 bar blues with Stevie Ray Vaughan guitar work and BB King vocals"
- ben_w 3y ago
  > I mean, if humans need to listen to far fewer examples to create music than an LLM needs to parse sound files, they're obviously not doing the same thing, are they? If I need much longer to run a marathon than an athlete, is that because my body is not doing the same things as the athlete, or just because it's doing all the same things but doing them worse? If a (clinical) moron tries to learn a song, and it takes a lifetime, why? (Do we even understand human brains well enough to answer that? Not my field). > there are selections of notes played over the top which are a function of fundamental musical properties of consonance and dissonance, scale runs the instrument is suited to as well as licks that may have been directly borrowed How do you learn what these things are? What do "consonance and dissonance" mean in terms of why they make you feel the way they do, and why can't an AI learn those things from examples? The qualia, that AI hopefully doesn't have but we can't tell because we don't have a test for that? Danse Macabre (Camille Saint-Saëns) was rejected at the time for how it sounded. The early cultural rejection of Blues seems to me like it was more probably racist excuses than artistic preferences, which is why I'm picking a non-Blues example. > reasons of easy improvisation … [all the other things in the previous quote, I hope this is a fair cut] … the final output is dependent heavily on the actual capabilities of the artist to play and singer, which obviously aren't simply lifted from their favourite artists' recordings. If I put the AI into a robot (or simulated) body, and the limits of that body constrained the capabilities of the output, those limit themselves make it OK? Constrain it to MIDI rather than a full waveform? This doesn't seem like it would change the answer, to me.