They don't have the right to not allow people to learn from it, that's just never been a part of copyright.
This here shows that you are speaking without understanding what you are speaking about.
AI is absolutely trained. It's a process that is quite literally inspired by the way we understood neurons to work in the 1970s.
AI start with a big batch of random numbers. There's a big fancy scientific method used to adjust those numbers in order to cause the system to learn to do some task.
The process creates genuine and novel understanding of the problem space at hand. AI trained to do something simple, like add two numbers, will have a real solution to add two numbers in them once you have finished training them.
With bigger problems, similar understanding certainly exists and in some cases has been proven to exist. However, once you get to the difficult problems with billions of parameters, it's very difficult for us to check that because if we could we would have just written it without needing to use an AI in the first place.
There are lots of researchers who do lots of study and effort to ensure that AI are actually producing real outputs and have genuine understanding of the problems face they are working in. Do not insist that AI has no understanding if you have not taken the time to learn about those techniques.
Stable diffusion has genuine understanding of different images and how to produce them within it. It is not a simple system that reproduces would already exists. It is not a collage tool. It is not incapable of producing novel outputs.
Diffusion models are perfectly capable of producing any image that can possibly exist. It is only a matter of time before someone invents a new style that hasn't been seen before, and someone else is able to find a combination of descriptive words that causes stable diffusion to produce that output.
Or that someone produces a novel combination of words, chucks it into stable diffusion (or some other AI model), and produces a new style of art.
> Art is made with physical motor skills, time and effort. AI is a human made program that uses human made imagery, classified by more humans to generate a shopping list written by another human who want art that requires no effort of aquiring the physical skill needed to make the art. With no physical product, there is no AI art
This is simply not true. Art is incredibly cultural, vaguely defined, and often involves little to no work at all. If someone prompts an AI, gets a result, and sticks it to a wall, calling it art, it is probably able to be considered art.
> If you want to physically copy my art, go for it, I will applaud your skill, but taking my art and shoving it in a program
In short, it appears that you are threatened by the existence of AI and the copyright argument is not actually about copyright, it's about ensuring that the competition does not exist, and that people did not have access to these tools that might make artists less valuable.
This is actually an anti-capitalist argument, rather than an anti-AI one.
That doesn't weaken the argument, IMO, but it does help to know whose ox you're trying to gore.
Apparently it isn't. Now a computer can do it.
> that requires no effort of aquiring the physical skill needed to make the art.
So what? This doesn't matter.
> If you want to physically copy my art, go for it
This is the same thing as if a computer does it.
Why do we need farmers when you can just buy a burger at McDonald's?
My AI art generator works right now, on my PC. If everyone stopped making art, the "normal" way, my AI art generator would still work.
This is a false equivalence to your example, because if farmers stopped farming, then it would not be possible to make burgers.
But, thats usually what happens when someone comes up with a pithy, one off meme response, like you just did, instead of actually responding to the substance of the argument. (I expect any future response from you, to instead not be engaging with the substance, and instead coming up with reasons why the silly analogy still works)
Hasn’t been about the motor skills time and effort for a long long time. Art has been about the idea rather than a fetishization of how much time and skill something takes to build.
> They don’t have the right to not allow people to learn from it, that’s just never been a part of copyright.
Yeah this is true. Stable Diffusion and other neural networks are not “learning” from it they way humans do though, it’s remembering and remixing and interpolating pixels (fixed expression), which is a part of copyright.
BTW compensation is not a very accurate summary of this problem. Machines that borrow someone’s style and copies and remixes without attribution is inherently problematic far beyond artists who live off selling their art, it dilutes both creativity and credit, in addition to undermining people who have to work much harder than the computer to produce images. These AI completely depend on being given human-created art to begin with, and the companies that are making them and using them are already making handsome profits, so it’s reasonable to expect some kind of return in addition to proper credit.
> Available for free online is not a valid justification for copying under copyright law, though, right?
Legal and attribution and licensed are all terms that are usually involved, but the core assertion is more or less correct. eg Images on billboards are protected by copyright in a similar manner. Something displayed on a website does not invalidate the copyright of the author or indemnify the owner of the site (or downstream users) from licensing conditions.
The laion 5b dataset is in the neighborhood of 220TB. (1) That is how much storage space you need to remember the pixels.
The stable diffusion 1.5 checkpoint is 7gb. (2)
1 https://github.com/rom1504/img2dataset/blob/main/dataset_exa...
2 https://huggingface.co/runwayml/stable-diffusion-v1-5/tree/m...
To extend your musical analogy, it's remembering that many songs are in 4/4 time, and that major chords sound appealing.
Also, were you to compress anything, an mp3 or a picture, in a lossy fashion, to that degree of compression (~10^-5), you would no longer have anything resembling the original. The audio would be glitchy noise, and the image would be a scattering of apparently random pixels a few pixels wide.
Here's the thing - I empathize that this is disruptive in a very similar fashion to a tool that does store compressed copies of the work in question. It is capable of doing the same kind of damage. There's a conversation to be had there - but it's just not compression. That's not how the thing works.
'cause those images are not the same. Sports events are just easy to fake, because they're boring - all sports pictures look roughly the same.
Edited to add: There's another lawsuit (a class action - 2), and after a little light reading, I came across section 5: 'Do diffusion models copy?', and my stomach jumped.
What they're doing, to make a point at trial that stable diffusion copies images, is _training images into the model, then using that trained model to prove that stable diffusion is a compression algorithm_.
This is a patent fabrication. If you train a model hard enough, yeah, it will produce the image you trained it on. And become useless for all other images. Congrats, you've just compressed your 7kb image to a 7gb diffusion model.
What scares me about this, is that the average court in the US is absolutely dumb enough to fall for it.
1 - https://www.theverge.com/2023/2/6/23587393/ai-art-copyright-...
Calling people dumb is to be willfully ignorant to the fact that neural networks actually can and really do remember images, not just when overfitting, but also when examples are in a low-density area of the latent space, when it doesn’t have enough neighbors to average with. The machine really is technically a machine intentionally and specifically built to reproduce a weighted combination of it’s inputs, and it really is possible for that weight vector to spike on some specific training examples. This won’t go away by pretending it doesn’t happen, it will go away when people curate training data that is legal to use, and/or when people write software that detects and rejects outputs that are too similar to a training sample, or otherwise guarantee no individual examples can be reconstructed. This is precisely why the project we’re commenting on is interesting, because it takes a step in that direction.
I think it does go without saying that our legal system has made some pretty dumb decisions regarding tech in the past - we read here all the time about the patent system, which is damn close in spirit to copyright.
Again, yes, they can remember an image, but they are not remembering pixels, and it's not compression. The vectors you're referring to are not a smaller version of the data, nor are they a pixel representation or even a close derivative thereof. Sure, there's a connection between the latent space and the pixels, but I don't see how that's the same thing.
For those following along, (1) is the best paper I could find talking about extracting images from SD. I'm open to more resources, and I'm even open to being convinced I'm wrong, but not by intentionally overtraining a model and calling it 'compression'. That's a lie.
To take a step back here, is it really the incidental occasional regurgitating of an existing image that's got everyone on edge, or is that just an easier target than "this is disruptive so I want to make it go away"? I'm not saying it doesn't suck that this is gonna put a ton of people out of jobs; both my parents were professional photographers in the 80s. I get it. But like, let's talk about that. Not some orthogonal strawman.
And hey, just to get it out there. We might disagree but I'm not calling you dumb. I do appreciate your willingness to engage an opposing view - it's part of what keeps me coming back to HN.
Yes, the model is smaller than the total input data. But when it comes to recreating a single image, how many of the weights must be configured 'just-so' recreate an image enough to call it the same image? I'll admit ignorance here - but I also don't think that this is a thing anyone knows for sure. We can only just extract othello piece colors from a simplified, othello-specialized model designed to recognize two colors.
How much of the information from other images must be present to perform this task?
My instinct, given my understanding of how these things work, is that to replicate an image with any recognizable fidelity, you have to overtrain the model enough that you've affected a set of weights much, much larger than the pixel data. The internal representation of these images is concerned with much more visual information than just 'this pixel is this color' - by looking at layered outputs from the inverse type of system (image recognition, which is the core component of these models), you can see that they're encoding layers of shading, lines that map to brushstrokes or object boundaries, foreground, background, all kinds of stuff. A direct representation of an image with all of these would be necessarily huge - and we know this because we have them. Artists use layers in all kinds of image-creation software, and they're always way bigger than the JPEG itself.
I get that this may sound pedantic, but the term 'compression' doesn't seem, to me, that it fits here. Compression, by definition, makes stuff smaller
The assumption that there must be compensation comes from the capitalist society that we live in. Switching to Communism or something else can be a solution to not directly pay people who do works and still have them around.
These days it's both publishers and artists attempting to create RMS's world of a right to read.
Under communism artists would be barred from making art entirely, ordered by the state to work in a place where it is deemed to be productive.
It would seem that it opens you up to the problem of other people deciding whether you're an artist or not and if so whether you're a good artist.
The same of course happens with capitalism, where it's your customers doing it. (Or in the case of books, which are almost never profitable, the VC-like publishers deciding to give you advances.)
So of course the reason modern mixed economies are good is there's more than one set of people that you may be able to convince to fund you.
Sure they would, it would just be "I got paid to do this art/music piece that then someone will use in their product they sell"
Surely that's their labor? Capital is the factor of production that isn't labor (or land if Georgist.)
Artists do not care about the copyright of people being able to learn from their art and reproduce it.
It is not been an issue for decades, because it is a long established standard of copyright. You can't copy a work directly, you can learn from it and reproduce your own sort of stuff.
What's different now is that this is a tool which artists can be replaced by. They not angry that their art has been learned from. Artists are angry that there is a tool which can replace them. And artists are looking for a way to make sure that tool is hampered as much as physically possible.
If it were not learning copyright it would be something else, and whatever that's something else is it would also probably be something with proxy for that core issue.
Imagine we had created an AI which was perfect, it could take your exact description of anything you asked it for and drew that thing.
And then I went and asked it for a picture of Mickey mouse in the style of Disney. Because it's a perfect AI perfectly reproduces it.
Who is in the wrong? I think it's absurd to think the creators of the AI would begin the wrong, because they did their job perfectly. It's a perfect app, it is a tool capable of literally anything.
At the end of the day, it's the person using the tool to violate copyright who is in the wrong, assuming they distribute those images.
And I don't believe the answer here is communism, I believe the answer is the same answer we've had for decades for the same situation. People need to find new jobs and learn new skills and do new things.
And as programmers, it's probably going to happen to us too, about as soon as it happens to artists. Time to consider to start to learn to weld or build homes or something like that.
I don't object that people should learn new skills and find new jobs, my concern is that people who actually put huge effort to produce that "training data" are now left dry. They should be compensated and move on, I'm completely against hampering the abilities of AI in order to preserve the current business structures.
It's greater than zero, otherwise the AI wouldn't exist, but these AI are trained off of 5 billion plus examples.
Examples that required work to collect and sort through. Examples that required millions of dollars worth of compute time to make into something useful.
What is there to compensate them for? These machines are not actually going to make these companies that much money either. The tools are open source. Competition is going to reduce profit on these systems to a very slim margin.
You have to not only compensate for the fact that they aren't involved in actually creating the AI, so they're only getting a fraction of what this thing is worth in the first place. Then you have to consider that there are five billion images in the training set.
The compensation is going to be nothing.
Currently compensating the artists would be like the Pirate Bay compensating the studios for their production costs through the gambling ads they run. No new move would have been ever made if that was the case.
I want my computer to be able to summon images out of the ether if I ask it for a picture of anything I could imagine. I could not imagine a positive system that would value such a small group of individuals over the need of the whole in a situation like this.
This seems much more about the fear of competitions, than about violation of copyright. And yes, that's scary, but unavoidable as tech progresses. I don't think anything good could come from trying to strickten copyright here. The AI is obviously not copying directly, at best it takes a bit of inspiration from other works, something artists themselves do plenty themselves.
Something like UBI might help with the monetary needs eventually. Though the fear part might start getting really interesting in the near future. What do you do with your life when AI is better at it than you? When everything you can create, can be created by the AI faster and better?
Yep, it's all about being compensated and yes copyrights are already very problematic and creativity limiting concept.
People in these industries happen to be the first to face AI revolution but it will come for as all, eventually. UBI might be something but I don't know, it seems like hard times are ahead of us.
as has many other industries that faced automation and become obsolete. The fact that it is AI derived doesn't make it different than Luddites before.
I listened to an interview with an artist who referenced the “three C’s”:
Consent
Credit
Compensation
These seem reasonable to me. The request isn’t to eliminate the technology. It’s that artists should be able to consent to their work being used. Works derived from their work should include credit. And, they should be compensated.
Getting consent of all the authors within that 5 billion images, managing the infrastructure of paying them, would be a Herculean task, and the cost of that task would far outrun the 5 billion spend if you gave a dollar for each image.
That would kill any and all possibility of an open source AI model. The future where this happens would be a very dystopian one.
What I see in the discussion is a results first, truth second thing. This is understandable - in an existential fight, damn the consequences - I'm swinging for my own survival.
What's missing from that analysis though, is that by constricting open source models, you're not by any measure stopping the development or deployment of these models. Google will make one. Microsoft will make one. Apple will make one.
Adobe will make one. Then, in order to use these technologies, you will have to pay. A lot - and it won't be paying the artists. Sure, the initial training night send out a few cents for each work included, a small price for Google to pay to prevent competition. But you're smoking the wrong shit if you think for a second that won't change as soon as the lead is cemented.
So now you're still looking for another job, and you don't even get to play with this new tech and continue making art, because you don't work for Google.
Many are too angry and small minded to see how lucky we are. A tool beyond anything Adobe currently ships today, for free. Could have easily been a AutoCad level subscription (10k+ a year IIRC that would have left you behind if you hadn’t paid.
But here's the thing; I have never 'done art' as a part of my identity, and yet I can listen to them talk about it and understand where they're coming from enough to contribute.
Also, I work in tech and I didn't even make it through basic trig. I have a GED and a set of scattered community college credits that are never going anywhere because of a GPA < 2.
The whole idea that there are 'this type of person' and 'that type of person' and that those are immutable is a horrific and dangerous lie.
But some people have bought it.
These sort of tools are only going to accelerate this trend in my eyes.