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Stable-Audio-Demo

stability-ai.github.io

81–90 of 249 posts

Re: Stable-Audio-Demo

#81
Just a few days ago I was down voted for stating AI will be better in creating music than human would be: https://news.ycombinator.com/item?id=39273380#39273532

Now this is released and now I feel I got grist to my mill.

Sure it still kind of sucks, but it's very impressive for a _demo_. Remember that this tech is very much in it's infancy and it's very impressive already.

Re: Stable-Audio-Demo

#82

Earlier quoted context omitted.

> If you require licensing fees for training data, you kill open source ML. And likely proprietary ML as well, hopefully. (To be clear, I think AI is an absolutely incredible innovation, capable of both good and harm; I also think it's not unreasonable to expect it to play a safer, slower strategy than the Uber "break the rules to grow fast until they catch up to you" playbook.) I'm all for eliminating copyright. Unt…

> "How much of the work will you use?" - All of it That depends on the interpretation of "use", and it would be interesting to read what lawyers think. You learned the language largely from speech and copyrighted works. (All the stories, books, movies, etc. you ever read/heard) When you wrote this comment did you use all of them for that purpose? Is the case of AI different? To be clear that's a rhetorical question -…

Principles applied to human brains are not automatically applicable to AI training. To the best of my knowledge, there's no particular law that says a human brain is exempt from copyright, but it empirically is, because the alternative would be utterly unreasonable. No such exemption exists for AI training, nor should it.

Ideas/works/etc literally live rent-free in your head. That doesn't mean they should live rent-free in an AI's neural network.

Changing that should involve actually reducing or eliminating copyright, for everyone, not giving a special pass to AI.

Re: Stable-Audio-Demo

#83
post #54

Earlier quoted context omitted.

> If you require licensing fees for training data, you kill open source ML. kill open source ML -> decrease speed of improvements for some open source ML

Sadly not. Making something illegal has social effects, not just legal effects. I’ve grown tired of being verbally spit on for books3. One lovely fellow even said that he hoped my daughter grows up resenting me for it. It being legal is the only guard against that kind of thing. People will still be angry, but they won’t be so numerous. Right now everyone outside of AI almost universally despises the way AI is traine…

US copyright has limited reach. There are models trained in China, where the IP rules are... not really enforced. It would be an interesting world where you use / pay for those models because you can't train them locally.

Re: Stable-Audio-Demo

#84

Earlier quoted context omitted.

If you require licensing fees for training data, you kill open source ML. That’s why it’s important for OpenAI to win the upcoming court cases. If they lose, they’ll survive. But it will be the end of open model releases. To be clear, I don’t like the idea of companies profiting off of people’s work. I just like open source dying even less.

That makes no sense. OpenAI must lose and it must not be possible to have proprietary models based on copyrighted works. It's not fair use because OpenAI is profiting from the copyright holders work and substituting for it while not giving them recompense. The alternative is that any models widely trained on copyrighted work are uncopyrightable and must be disclosed, along with their data sources. In essence this is…

For what it’s worth, I agree with your second paragraph. But it would take legislation to enforce that. For now, it’s unclear that OpenAI will lose. Quite the opposite; I’ve spoken with a few lawyers who believe OpenAI is on solid legal footing, because all that matters is whether the model’s output is infringing. And it’s not. No one reads books via ChatGPT, and Dalle 3 has tight controls preventing it from generating Pokémon or Mario.

All outcomes suck. The trick is to find the outcome that sucks the least for the majority of people. Maybe the needs of copyright holders will outweigh the needs of open source, but it’s basically guaranteed that open source ML will die if your first paragraph comes true.

Re: Stable-Audio-Demo

#85
Music is perfect for AI generation using trained models, because artists have been copying each other for at least the past 100 years and having a computer do it for you is only notionally different. Sure a computer can never truly know your pain, but it can copy someone else's.

Re: Stable-Audio-Demo

#86

As with Stable Diffusion, text prompting will be the least controllable way to get useful output with this model. I can easily imagine midi being used as an input with control net to essentially get a neural synthesizer.

For music perhaps. For sound effects I think text prompting is the rather good UI.

Re: Stable-Audio-Demo

#87
post #45

This is right into the "uncanny valley" of music. It definitely sounded "like music", but none of it is what a human would produce. There's just something off.

Here is a silly song I generated using suno.ai, which I have found to be incredibly impressive (at least, a small percentage of its outputs are very good, most are bad). I think it's good enough that most humans wouldn't realise it's AI generated. https://app.suno.ai/song/8a64868d-9dd3-46db-91af-f962d4bec8b...

Wow. I’m guessing it’s generating MIDI or something rather than synthesizing audio from scratch? Even so, the quality of the score is leaps and bounds better than any of the long-form audio on the Stable Audio demo page (either Stable Audio itself or the other models). The audio model outputs seem to take a sequence of 1 to 3 chords, add a barebones melody on top, and basically loop this over and over. When they deviate from the pattern, it feels unplanned and chaotic and they often just snap back to the pattern without resolving the idea added by the deviation. (Either that or they completely change course and forget what they were doing before.) Yes, EDM in particular often has repetitive chord structures and basic melodies, but it’s not that repetitive. In comparison, from listening to a few suno.ai outputs, they reliably have complex melodies and reasonable chord progressions. They do tend to be repetitive and formulaic, but the repetition comes on a longer time scale and isn’t as boring. And they do sometimes get confused and randomly set off in a new direction, but not as often. Most of the time, the outputs sound like real songs. Which is not something I knew AI could do in 2024.

Re: Stable-Audio-Demo

#88

Earlier quoted context omitted.

If you require licensing fees for training data, you kill open source ML. That’s why it’s important for OpenAI to win the upcoming court cases. If they lose, they’ll survive. But it will be the end of open model releases. To be clear, I don’t like the idea of companies profiting off of people’s work. I just like open source dying even less.

> If you require licensing fees for training data, you kill open source ML. And likely proprietary ML as well, hopefully. (To be clear, I think AI is an absolutely incredible innovation, capable of both good and harm; I also think it's not unreasonable to expect it to play a safer, slower strategy than the Uber "break the rules to grow fast until they catch up to you" playbook.) I'm all for eliminating copyright. Unt…

It’s not so clear cut. Many lawyers believe all that matters is whether the output of the model is infringing. As much as people love to cite ChatGPT spitting out code that violates copyright, the vast majority of the outputs do not. Those that do, are quickly clamped down on — you’ll find it hard to get Dalle to generate an image of anything Nintendo related, unless you’re using crafty language.

There’s also the moral question. Should creators have the right to prevent their bits from being copied at all? Fundamentally, people are upset that their work is being used. But "used" in this case means "copied, then transformed." There’s precedent for such copying and transformation. Fair use is only one example. You’re allowed to buy someone’s book and tear it up; that copy is yours. You can also download an image and turn it into a meme. That’s something that isn’t banned either. The question hinges on whether ML is quantitatively different, not qualitatively different. Scale matters, and it’s a difference of opinion whether the scale in this case is enough to justify banning people from training on art and source code. The courts’ opinion will have the final say.

The thing is, I basically agree with you in terms of what you want to happen. Unfortunately the most likely outcome is a world where no one except billion dollar corporations can afford to pay the fees to create useful ML models. Are you sure it’s a good outcome? The chance that OpenAI will die from lawsuits seems close to nil. Open source AI, on the other hand, will be the first on the chopping block.

Re: Stable-Audio-Demo

#89
post #68

Earlier quoted context omitted.

Chrome isn't open source, chromium is. Best not to confuse the two.

Chrome and Chromium are virtually identical except for Google services, which aren't required to do anything with the browser except for installing Chrome extensions that can alternatively be sideloaded, so this is nitpicking.

It's essential nitpicking

Re: Stable-Audio-Demo

#90
post #68

Earlier quoted context omitted.

Chrome isn't open source, chromium is. Best not to confuse the two.

Chrome and Chromium are virtually identical except for Google services, which aren't required to do anything with the browser except for installing Chrome extensions that can alternatively be sideloaded, so this is nitpicking.

Jumping in to defend parent comment, there’s nothing Open Source about Google Chrome and it’s highly relevant in this context because they are notorious for putting technologies and tracking in there that many people find objectionable.
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