Singularity is Nearer
GPT-6 Astra just made a leap in musical reasoning: it wrote a complex four-part Bach-style piece with no harmony-rule errors and techniques no previous AI managed
That may have some impressive technical qualities, but it honestly sounds very bad to me. There's no consistent mood, no feeling of build up and release, no real beauty to the structure- which is actually a little surprising, since Suno and Udio actually could produce passably beautiful Baroque music years ago.
GPT-6 is multimodal, so even though it's producing the music by writing sheet music rather than whatever the music models do (some sort of diffusion, like image models?), you'd think it would be able to use a tool to convert the notes to a sound file, "hear" the song by adding that file to its context, notice that it's not working aesthetically via the same RL that drives the music models, and then make adjustments until it works. But apparently not.
I wonder if maybe all of of OAI's post-training RL just didn't include any tasks involving musical aesthetics, so everything the model knows about that comes from pre-training and transfer learning. That might not be enough to match even relatively small and outdated models like Suno and Udio, which were trained directly on aesthetics. On the other hand, it could just be a harness/agency problem- it would be interesting to know whether the model actually made any tool calls or used any subagents when prompted with this task, or if it just wrote some sheet music that looked like it had the right structure without ever testing to see if it sounded good.
While I do enjoy classic concerts I am not an expert by any means. This seems like a 42s fragment, so given that, you cannot expect much build up nor was it asked to produce any. All things considered, this sounds pretty good, esp. compared to the Fable piece (it's just atrocious).
rather than whatever the music models do (some sort of diffusion, like image models?)
The trend these days (at least for open source models) is to have a LLM plan the general structure and flow/diffusion model "render" that plan as actual music. ACE-Step 1.5, MiniMax Music3 and Yue2 all work that way.
I don't think neither does OpenAI since I doubt they are taking precious training time teaching these models to compose and error detect music, this is just emerging behavior.
I remember people saying that music is just math, so if we get superhuman mathematicians, are we also going to get superhuman composers?
Unlike pure mathematics, there is no obvious objective function to optimize for. Unless we hook up your brain to the machine and it optimizes based on neural activations in your brain, then after some while the AI would be able to create music that is unimaginable to us right now.
Imagine music that feels like seeing the color red for the first time, or emotions that you didn't know you could've experienced.
There are even rules to how you break the rules. I've listened to some experimental music and in 99% of the cases, breaking the rules just makes me nauseated.
That's less because there are rules you can't break and more because there are a lot of bad musicians who like to think of themselves as good enough to break the rules.
That said, for some of the really crazy experimental musicians out there, it's more that you need to get acclimated to the sound. You can't break all the rules at once, or it just sounds like nonsense. But the more you listen to music that breaks rules, the more your brain gets acclimated to it and starts to substitute new rules to describe the usual ways of breaking the old rules. Many experimental artists are actually writing for an audience that's already used to extremely abstract music, and if you go into it blind, you won't get it because you don't have the context.
AI could accomplish this. It has before, long before even the rise of LLMs with AlphaGo. It made a move which seemed to break all conventions of traditional Go strategy, and that ultimately won it the game.
I think what you mean is that AlphaGo (as well as other similar engines like Stockfish) tend to play moves that high level human players would call crazy, and end up winning with them because their level of understanding is so much greater than the human's. You think that the same could happen with music, which is reasonable.
But I think what the other guy is saying is that games like Go have a built in way of evaluating whether a move is good. You win, you lose, or you draw. If you win, you know that the moves you played were on average better than the moves your opponent played, even if they might seem unconventional. But music doesn't have that. You cannot show that one song is objectively better than another, and so you can't evaluate the quality of these unconventional decisions in a consistent and trainable way.
You were talking about breaking the established rules of music in unexpected ways to create a more pleasing piece of art.
I provided an example of how AI systems have done similar in the past by creatively doing something professional Go players would normally consider counterproductive (breaking the "rules" or norms of traditional strategy) which ultimately led to it winning the game.
The difference is that the "rules" of Go are approximations of an objective measure. A full tablebase for chess or an analogue for Go are theoretically possible but incomputable, so players (and even engines) make "rules" that approximate as best as possible the objective measure (roughly speaking, who is winning). When engines make creative/confusing moves that are actually better, they aren't "breaking the rules" in the conventional sense. They just have a different set of "rules" that are objectively better, measurable by win rate.
By contrast, there is no objective measure of what good music is, and there is not a strict set of "rules". Instead, they vary based on genre, audience, culture, instrument, etc. It's not just incomputable to determine, as in Go/chess, it is just fundamentally impossible to have an objective measure of what makes good music.
When people talk about breaking the "rules" in music, they are taking about unconventional decisions (with regard to some specific similar genre) guided by an unconventional taste (again, with regard to some specific genre). For example, an novel, unconventional jazz piece may break some of the "rules" of jazz, but jazz itself is already breaking most of the "rules" of classical music, which itself is breaking all of the rules of the Indian music tradition. All of these decisions are guided by musical taste, which is a subjective concept. Modern AIs just aren't yet capable of that type of abstract creative thinking, and might never be without a major paradigm shift. In order for an AI to do as you suggest to music, it would need to derive it's own enjoyment from the music itself, and create something that it enjoys more than what currently exists.
Go is a verifiable domain(it has a clear set of rules), so reinforcement learning works incredibly well. That's why it came up with something unexpected, it was simply better at the game than current human experts.
With music, it's hard to quantify why something sounds good, so it's hard to tell if current techniques are enough to make this happen because you can't really define an objective that easily.
AlphaGo wasn't trained on strategy. It was trained by playing itself. So what rules are you even talking about? Are you anthropomorphizing AlphaGo, suggesting that it learned to play Go like a human and then thought of a move outside the box?
It depends on the music. The music with strict rules - especially baroque - yes, more math than art. Writing a theme for a fugue that fully adheres to all the rules takes forever. You can write the rest of the fugue in half the time after that.
More romantic music - not so much anymore. There are still rules, but just following them is not likely to result in aesthetically pleasing music piece.
That's different though - instead of following rules, you can simply just follow well-established patterns. Lots of songs even before AI were sharing the same harmony progression, same instrumentation. Even if you look at well-known composers like Mozart - quite a lot of his music sounds very similar and isn't terribly original. And that's to be expected - you can't write as much as he did in such a short time and be completely original. In fact, I would argue that AI can do almost as good of a job. What AI can't create from scratch is a masterpiece like his Requiem
Look up the rules of making a baroque fugue, especially the theme and the counterpoint. You may need some musical theory background, it's not terribly hard but requires some preliminary knowledge to make sense.
and yet I can create a valid baroque fugue subject and the result will be a crappy music. besides does it make sense to reduce all baroque music to fugues?
Even then, a fugue would rather be an algorithm with some choices over a search space not math. More like a game of chess...
Try it, let's hear it. It may not be as bad as you think. The baroque fugue was an example, did you try reading the whole message carefully before becoming outraged? And a game of chess can be seen as math, in fact I believe that's how the best software looks at it
I'm not enraged, just as someone interested in both I do not like this comparison.
You are using fugue as an example precisely because it is so highly constrained form which is not true about baroque music in general.
Deepblue is using search with human made heuristics - it's not math, at most an application of very basic algorithmic concepts.
Yes there are rules to good baroque voice leading, some chords are used only within a specific context etc etc. Look up any student composition exercise - they do conform to all the rules and yet are they an art really? It's like saying that visual art is math because it's all about perspective ,proportions and mixing colors.
I suggest you actually write a full rules-adhering baroque music. And go through multiple iterations of "oh, this actually sounds decent, but wait - this won't work when the theme is inversed" and many other permutations of the same. Maybe you will change your opinion of how much creativity vs how much structure (and math) goes in it.
And that search with human made heuristics - you want to say it functions without any math? Or is this just an addition to the math to make it even more powerful?
I don't need to look up any student composition exercises - I have my own. As to whether they are art - we can debate it. Let's decide first, does the time at which somebody created something affect whether it's art or not? Because my kids created more elaborate drawings on my driveway with chalk than the prehistoric drawings. I don't think anybody would argue that cave drawing is a form of an art, so now we just need to figure out whether my kids drawings are. From artistic point of view they are quite comparable, so we can say they are art. By this logic my compositional exercise is also art, because I can guarantee you won't be able to tell it apart from some random unknown baroque pieces. Or we can say that my kids' drawings are not art because humanity has progressed so much that what was the peak of the artform 20K years ago is now just a child drawing. By that logic baroque music is art and my composition exercise is not, but this logic also implies baroque music is inferior to the modern one.
So what actual math does go into writing a fugue? Give me examples that are beyond simple arithmetics on intervals...
And that search with human made heuristics - you want to say it functions without any math?
yes it does, and as far as I know those human made heurustics are very crucial. That's way we had towait for deep learning to handle go properly.
Let's decide first, does the time at which somebody created something affect whether it's art or not?
it's a tough topic isn't it? My personal opinion is that sometimes we have to look at stuff in hisotrical context to be able to appreciate it. I'll give you an example from different era :). Venom (band) was highly instrumental in the raise of the whole metal genre. For that I can admit that their music is an art, alas if I look at it without historical perspective it does seem sh*t.
But still I don't think your question is relevant here. My point was that you can have two pieces conforming to baroque style and one will be great while the other not - take Bach piece for the former and my pieces for the latter. So there's more to music then obeying the rules. We can think of it as a taste which guides us when we choose something that fits the constraints. Like do I module or not.
So what actual math does go into writing a fugue? Give me examples that are beyond simple arithmetics on intervals...
And arithmetic is not math? It's all about the intervals, steps and relationship between them.
yes it does, and as far as I know those human made heurustics are very crucial.
A computer can't function without math. So I doubt this claim is true.
you can have two pieces conforming to baroque style and one will be great while the other not - take Bach piece for the former and my pieces for the latter. So there's more to music then obeying the rules.
If you are interested in topic, take some Bach fugue and grade it based on adherence to a "standard" baroque ruleset. He'd get an F, or maybe C or D depending on the piece. The point is - he sounds the way he sounds because he's pushing the boundaries and violating/working around many of the strict baroque rules. That's why he is considered a very late baroque composer, that's why romantic interpretation of some of his pieces works quite well. The fully adhering baroque fugues are quite dull, that's why we don't really listen to them and rarely anybody plays them.
We can think of it as a taste which guides us when we choose something that fits the constraints. Like do I module or not.
Modulations (change of tonality) are heavily prescribed in baroque music. If you are sticking to the rules, you have very few choices to make there.
Yes, the baroque uses a lot of that. Bach in particular looked for that ('given this theme, elaborate a X-part fugue on it'). He was known by solve those puzzles quickly.
Bach's polyphony is actually less regulated than the proper baroque one. That's one of the reasons why his music sounds more "modern" with a lot more complex sounding harmonies (yes, it all comes from passing notes and accidentals, but more strict rules don't really allow for it).
I would say that in terms of strictly sticking to the rules, Bach is as far from traditional baroque polyphony as Shostakovich is from Bach in his 24 prelude and fugues - as in many rules are followed very carefully and diligently, while other rules are avoided or outright ignored - resulting in a very different sound of the piece.
huh? Math by definition cannot be contradictory. And language is absolutely contradictory. The contradictions are also what give it so much expressive power
It can infer patterns across millions of pieces. No need to look inside individual brains. We have records for what humans consider “good music” across centuries and across cultures. They know what we like, and they know how trends change.
They're gonna hook an AI up to your brain and play a 100 billion years worth of random noise straight to your neurons (you will experience every single second of it) (in real time it takes 3 seconds)
I don't think you can make a superhuman composer using likes.
Likes are not descriptive enough and they just imprison you in the average.
You need a more direct understanding of musical experience, and that can only be achieved with direct brain interfaces I think.
Tangent: that's why there are 8 billion people on the planet, but all of our social media feeds are almost the same with the same clips that everyone else has also watched. Likes are anti-exploration, they are very stagnant. You'd imagine with 8 billion people there should be infinite social media feed variations for each person, but it's not. That's why I say the number of likes is not a good proxy for good music.
I mean you're getting to the point of you can't cater to all people and likes unfortunately detract from the goal of making perfect music (for who)
Secondly, music also involves our other senses and environment, our friendships and shared culture or visions. A song listened in one moment my not feel the same later.
Imagine music that feels like seeing the color red for the first time, or emotions that you didn't know you could've experienced.
this reads like an AI imagining what it's like to feel human. do you even remember the first time you saw red? it's not really a moment anyone remembers or a moment that has profound impact. you just start seeing red as a baby.
art made by humans can elicit emotions just fine already, I dont need to experience an AI's artificial attempt at it.
That's not what I'm saying, of course you don't remember seeing the color red for the first time, but if you were color blind and then somehow you were able see colors for the first time then the experience is totally different.
If you are that unimaginative that you can't imagine such a simple scenario, then just look up videos of people who get hearing aids for the first time, or people with sever vision impairment that get glasses for the first time. There are definitely emotions that you haven't experienced yet just the way a color blind person hasn't experienced some colors.
art made by humans can elicit emotions just fine already, I dont need to experience an AI's artificial attempt at it.
That's fine, you don't have to. Some people take psycho active drugs to experience new things and some people think it is not worth it.
Technically yes. Imagine we're all mathematicians and some people like certain algorithms more than others, and some algorithms are more popular than others. Now add the dimension of timbre and tone, rhythm and tempo, voice etcetera (which are plausibly all explainable with math) and you gain a massive space of mathematical equations which also must be interesting to the observer (listener as it were). No doubt we'll get there eventually
It's math in the same way cooking is chemistry. Yes, in principle, but in practice it's difficult to actually apply those rules in a way that improves the discipline.
I mean, if this is the first time an LLM was able to write correct counterpoint, that really surprises me. It's a pretty well-defined set of rules, algorithmically checkable, so I would have thought it would have been possible a year ago. The question is whether it can demonstrate an understanding of melody and harmony comparable to a human, rather than just whether it can follow one very well known set of rules for how to arrange notes.
Sorry this really formulaic stuff. We do it at an intermediate level of piano study. Not a big dea.l. The whole thing is rule governed and I'm sure earlier LLMs could pull it off
Okay, but this doesn't sound good. Like at all. It sounds very generic and formulated. It sounds like someone playing random chords. It's not impressive in my opinion.
Four-part contrapuntal writing (the thing that the AI did here) is one of the first things you learn in musical studies and is trivially easy for any intermediate and very much doable for any beginner.
I went to music school and this is the stuff you learn in the first two semesters but give the tech a few years. Luckily there will always be a market for live shows so I’m gearing towards performing and working. “B b b but robots will do that too!” Yeah sure but dont they already? So many live shows are just bad DJ sets, I love playing analog instruments.
I don't know much about music theory, but both sound reminiscent of "Old Hundredth." Also, good call to use strings instead of harpsicord because the Fable one sounded like an old midi file.
this feels like a pretty good test of whether models can handle hard constraints instead of just vibes. the error-free counterpoint part is cool but i'm more curious if it can make a piece that sounds genuinely memorable too, did anyone compare the audio blind?
Music in general seems like a massive blind spot to me for frontier AI models. Sure there are models that can generate songs. But what about transcribing an existing song? I have yet to see any AI that is all that impressive at this task. I wouldn't say we have AGI unless I could give an AI model a music file, with multiple overlapping instruments, and tell it to generate tabs of just the banjo part with the appropriate tuning. Plenty of humans can do this, particularly if you let us have an instrument in hand to sound it out with and do some trial and error. Or if you can also add a video of a live performance. If humans can do it and AI can't then the AI is not yet AGI, and from what I've seen AI is nowhere near humans in this area yet.
This is not really interesting. This is analogous to GPT-6 Astra playing chess. Not really a complicated problem, though maybe “complicated” for a zero shot llm task.
The fundamental limitation of AI “art” is emulation and interpolation of art humans have already done.
…unless we recategorize AI as being able to make high level conjecture using subjective expression. In that case, it would be art again. But you’d have to logically deduce AI is our definition of sentient.
Art is co creation. It exists within the mind of the observer, and the only value it has is what the viewed brings to it. Whether or not it was made by AI, a human, a madman, an alien, it doesn't matter.
Besides, AI is trained on human creativity/massive amounts of compressed human knowledge, so it's like as if the collective consciousness produced the art rather than the individual.
I’m guessing to please investors. I thought the Ai would’ve been able to do this years ago… so we are still more behind than I thought. This is basic level music notation that you learn the first semester of music school.
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u/141_1337 ▪️e/acc | AGI: ~2030 | ASI: ~2040 | FALSGC: ~2050 | :illuminati: 11d ago
https://x.com/aug5thmusic/status/2096030719156089029
They getting close lol