AI is bad at music also. Even the state of the art transformer models can't produce more than a few seconds of coherent melodic phrases.
Would we expect a discrete melodic structure to be expressible as averages of prior music? No.
What's more interesting and concerning - listen carefully to the first piano continuation example from AudioLM, notice the similarity of the last 7 seconds to Moonlight sonata: https://youtu.be/4Tr0otuiQuU?t=516
I'm afraid we will see a lot of this with music generation models in the near future.
Having said that, I think the idea of predicting popularity is good - we can use it for filtering already generated chunks during post-training evaluation phase.
I don't think the other two methods you suggest would help here, we want to generate while conditioning on famous pieces, and we don't want to increase temperature if we want to generate conservative, but still high quality pieces.
It's true that we (humans) are less sensitive to plagiarism in the text output, but even for LLMs it is a problem when it tries to generate something highly creative, such as poetry. I personally noticed multiple times a particular beautiful poetry phrases generated by GPT-2 only to google it and find out they were copied verbatim from a human poem.
Another similar possibility might be to do more RL with this data, e.g. using upside-down RL. One can possibly steer this with user feedback as well.
It didn’t get to train on the test set, if that’s what you’re implying, and I find it hard to believe the assertion that continuations are copies of the train set (if that’s your claim).
I guess in retrospect we asked it to continue the music in a likely way, not be novel. And it definitely convinced me enough to be impressive. An NN that composes completely fresh music, whatever that means (I’m sure most modern human music has a hefty dose of cross song sampling), would certainly be a good next goal post.
but yes there is not yet at on-demand button rendering from a text prompt of bitstreams encoding composed performed and mastered music.
We can't produce arbitrary media streams with many "stack layers" of meaning and detail yet, but we can do a lot of specific instrumental transformations...
Vaguely relevant: https://koe.ai/recast/
Unfortunately this is not true. It takes a huge amount of human effort to make MIDI encoded music sound good. The difference between MIDI and raw audio music generation is the same as the difference between drawing a cartoon and producing a photograph.
To clarify, yes MIDI can be expressive, but what's being generated when people say "AI generates MIDI music" is basically a piano roll.
As a clasically-trained pianist who then got into electronica and synthesis, it was mind blowing to me that people could wrangle expression and phrasing from a MIDI sequencer.
The search space is absolutely enormous, though, so I don't dispute that it's very difficult, but I wouldn't go so far as to say that it can't be done. In such a space there are "no wrong answers" so to speak. I have a python script which creates randomized sequences of notes/rhythm and gives each one a different combination of LP/HP filters and random envelopes - it's not music but it takes on a much less mechanical quality by emulating different attacks and timbres over time, even though it's completely random.
I would go so far as to say I'd be genuinely surprised if algorithmic composition and production hasn't been used to some extent significantly greater than "basically a piano roll" in at least some of the past decade's top 40 music on the radio.
There is such a reason - lack of training data. Very few high quality detailed MIDI samples exist to train machine learning models like AudioLM.
For state of the art in MIDI generation, take a look at what https://aiva.ai/ produces (it's free for personal use). There you can compare raw MIDI output to an automatically generated mp3 output (using "VST's and samplers with routing and effects in place, then using some combination of genetic algorithms and other methods to "tweak the knobs" in the search for something pleasing.")
mp3 version will sound much better than raw MIDI, but (usually) significantly worse than music recorded in a studio and arranged/processed by a human.
This reads like someone who knows sheet music and theory but does not listen to music. It’s repetition of short phrases over and over.
I’m not really sure what people expect of general AI trained on human generated outputs. It can’t make up anything anything “net new” only compose based upon what we feed it.
I like to think AI is just showing us how simple minded we really are and how our habit of sharing vain fairy tales about history makes us believe we’re masters of the universe.
AIs state will forever be constrained to the limits of human cognition and behavior as that’s what it’s trained on.
I read published research all year. Circular reasoning. Tautology. It’s all over PhD thesis.
There’s no “global structure” to humanity. Relativity is a bitch.
Seeing the world through the vacuum of embedded inner monologue ignores the constraints of the physical one. It’s exhausting dealing with the mentality some clean room idea we imagine in a hammock can actually exist in a universe being ripped asunder by entropy.
It’s living in memory of what we were sold; some ideal state. Very akin to religious and nation state idealism.
"AI" is just taking `mean()` over our choice of encodings of our choice of measurements of our selection of things we've created.
There is as much "alike humans" in patterns in tree bark.
AI is an embarrassingly dumb procedure, incapable of the most basic homology with anything any animal has ever done; us especially.
We are embedded in our environments, on which we act, and which act on us. In doing so we physically grow, mould our structure and that of our environment, and develop sensory-motor conceptualisations of the world. Everything we do, every act of the imagination or of movement of our limbs, is preconditioned-on and symptomatic-of our profound understanding of the world and how we are in it.
The idea that `mean(424,34324,223123,3424,....)` even has any revelance to us at all is quite absurd. The idea that such a thing might sound pleasant thru' a speaker, irrelevant.
This is a product of i dont know what. On the optimist side, a cultish desire to see Science produce a new utopia. On the pessimisst side, a likewise delusional desire to see Humans as dumb machines.
What a sad state!
> The idea that `mean(424,34324,223123,3424,....)` even has any revelance to us at all is quite absurd.
Most of what I say to anyone is exactly this.
When I'm about to give anyone any information, I look back at all of the relevant past information that I can recall (through word and sensory association, not by logic, unless I have a recollection of an associated internal or external dialog that also used logical rules.) I multiply those by strength of recollection and similarity of situation (e.g. can I create a metaphor for the current situation from the recalled one?). I take the mean, then I share it, along with caveats about the aforementioned strength of recollection and similarity of situation.
This is what it feels like I actually do. Any of these steps can be either taken consciously or by reflex. It's not hidden.
> I think it's deeply depressing that AI has been sold as something even capable of modelling anything humans do
This is a bizarre position. All computers ever do is model things that humans do. All a computer consists of is a receptacle for placing human will that will continue to apply that will after the human is removed. They are a way of crystallizing will in a way that you can sustain it with things (like electricity) other than the particular combination of air, water, food, space, pressure, temperature, etc. that is a person. An overflow drain is a computer that models the human will. An automatic switch/regulator is the basic electrical model of human will, and a computer is just a bunch of those stitched together in a complementary way.
You're no more made of clay & god's breath, as you are sand and electricy.
You're an oozing, growing, malluable organic organism being physiologically dynamically shaped by your sensory-motor oozing. You're a mystery to yourself, and these self-reports, heavily coloured by the in-vogue tech are not science, they're pseudoscience.
If you want to study how animals work, you'd need to study that. Not these impoverished metaphors that mystify both machines and men. No machine has ever acquired a concept through sensory-motor action, nor used one to imagine, nor thereby planned its actions. No machine is ever at play, nor has grown its muscles to be better at-play. No machine has, therefore, learned to play the piano. No machine has thought about food, because no machine has been hungry; no machine has cared, nor been motivated to care by a harsh environment.
An inorganic mechanism is nothing at all like an animal, and an algorithm over a discrete sequence of numbers with electronic semantics, is nothing like tissue development.
What you are doing is not something you can introspect. And you arent really doing that. Rather, you've learned a "way of speaking" about machine action and are back-projecting that onto yourself. In this way, you're obliterating 95% of the things you are.
> these self-reports, heavily coloured by the in-vogue tech are not science, they're pseudoscience.
I simply don't know what you're referring to. If you're referring to retrieving memories through associations, there's mountains of empirical evidence for that. If you're referring to wondering if I remember things, and being unsure of the information I'm recalling when I have less recall of that, or wondering if past situations compare well to current situations, well you got me. It's my personal belief that conscious thought is an epiphenomenon that is a rationalization of decisions already made.
But the rest of this is nonsense. Vivid imagery is not an argument for exceptionalism, no matter how much I say things drip or ooze. This is just association in action. You're trying to create a distinction for life (or rather what you recognize as life) life oozes and has viscera, so using a bunch of words that feel wet and organy can substitute for reason contra the robots.
We're trying to train a full composer AI without allowing to learn about different instrument sections independently at first. The human composer will have a good idea of the different parts and know how to merge them in harmony.
I think we might get better results training separate AI systems on percussions, strings, vocals etc. then somehow create connections between them so they learn together. A band AI if you will.
We could try a BERT for each, with the generator learning to output logical sequences of sounds instead of words.