This is basically my take - I'm mostly confused by the people up in arms about this (except that it likely makes their work more of a commodity, so I get that fear).

People look at art and make art in that style all the time, now a machine exists that can do that. Why is that unethical? Because they didn't consent for the machine to look at it/learn from it, but they did for humans? I don't think this argument will be able to hold the wave of change that's coming from this new capability. They'd be better off long term learning how to use it.

Nobody creates purely original things in a vacuum, machines won't either.

Automation is okay if it is about taxi drivers or warehouse workers. But when it targets artists some people turn Luddite.

My brother is an artist by the way who does a lot of work with AI, 3D printing and internet. Art will always survive and adapt. If memory serves it took decades before photography was socially accepted among the art world.

The question now is what value can (human) artists bring besides merely producing images of a certain subject in a certain style. Software has just solved that problem, although the buildup was the last 10-20 years (style transfer, and now generative language-based models).

When I think of the value and interestingness of art, there's a lot of intention and meaning in choosing what to draw, the form, etc. For example look at the OG The Death of Socrates and then compare it with the three other paintings of the same scene https://en.m.wikipedia.org/wiki/The_Death_of_Socrates. Obviously the one by David is superior; it's much more interesting to look at, you can see the emotions of the characters, and overall the composition underscores the significance of the philosopher's death, especially in the context of the enlightenment/romantic period. (This is my opinion as a pleb; I'm not an art critic.) These concepts are still beyond what a model can encode in an image as of today.

So although humans are no longer superior in the mechanics of producing images, I think in the higher-level/psychological aspects of "art", there's room for optimism that humans will be able to hang on, for now.

I understand the debate is also around the revenue loss in the commission/fanart/online art scene. And from my experience looking at some of these over the years, I'd still argue the same thing: that IMO the really good series and artists are good because of their ideas and themes, and not their technique. But if their revenue is 90% from drawing lewd fanart, unfortunately it seems like they'll have to adapt and compete, using the skills that humans are dominant in.

And although I'm just an dumb anon on the internet spewing these ideas, I think this is harsh but true. Because the reality is that now, everybody's downloaded the SDv1.4 weights onto their hard drives, and so the cat's out of the bag permanently.

> loss of revenue for...online art scene

I have never used any of those services before. I have never considered using one of the services before because it was always outside my price range.

Now that I have tried stable diffusion and have photo bashed and rendered some concept art for each of the main characters in my novel, I now want to commission an artist to create the 30 or so needed training images so I can ask stable diffusion to spit out my own character in various poses and expressions.

At minimum, that will require a human to render a model sheet of the character from front and back and side and 3/4 and above and below, as well as the emotions on the basic emotions wheel.

If I want the character to be able to wear different outfits, then I will also need to pay for renderings of that character wearing that clothing, all in service of trying to train stable diffusion to be able to remix that character into future images.

Let's also say that I do not have a killer graphics card to be able to train images into a model, luckily, for another $100 fee, the artist will use their existing graphics card to spit out an embedding or a hypernetwork or a VAE or whatever it is that you can use to add custom training to a model and send me that as well as the original set of input photos.

After all of that, I can generate the photos I want...but I will then have to slightly tweak each image so that it has human authorship, even if it's just removing noise and fixing the cursed loops that happen on limbs at times.

In short, I am considering something that is at least $200 for the crappiest cheapest artist out there, multiply that by my six or so main characters, and that is money that I am genuinely considering spending that I would not have even dreamed of entertaining for a moment.

The proof is in the pudding as to whether this thought process will be happening for other stable diffusion users who are able to get images they like, but do not have good rendering skills on their own, weather they too are willing to pay for this or not.

If so, there will instantly become a new type of artist job available, that of the AI art trainer artist.

At the very least, there will be AI art cleanup artists that remove the noise and so-called cursed elements of ai art when used in the concept art stage.

It makes me think a bit of Asimov’s novella Profession: https://en.m.wikipedia.org/wiki/Profession_(novella)

Currently, we (mostly) still need people to make the tapes. That probably won’t be true forever, but it is for now.

In order to "make the tapes", these models will have to solve the much more general problem of reasoning, modeling human cognition, etc. It would be the last problem and a signal of the end of humanity.

I'm less worried about artists' livelihoods at this point; after this problem is solved we'd all become obsolete and just be killed off.

It’s really not that simple. If an artist picks 12 unusual colors to paint a sunset and you copy those exact same colors to also paint a sunset in his style then no that’s not ok.

People on HN have very strong options about this stuff without looking at any of the relevant case law.

I have no idea if that is legal or not, but it is an extremely common practice. For example, that is the scenario when someone on Deviant Art creates fan art of any cartoon.

And why should that be a problem? This is a King Canute and the tide scenario. We may as well bow to reality and admit that it is ok.

Yeah well, remember Napster?

Now it’s so easy to share music, it’s meaningless to try to stop people doing it.

Apply 20 years of law cases and punishment for random people and now…

…everyone pays to stream their music.

Right? Wrong? Eh.

I’m just saying, you are kidding yourself if you think that the Powers That Be will just let people decide copyright isnt a thing anymore because of (insert reason here).

Once there is money involved, there will be court cases, and you know, I’ll be shocked if a combination of “needs bigger GPUs to run” and “legal issues” don’t cause these sorts of models to be locked away behind cloud APIs in the future.

It is what it is. Enjoy it while you can; some things are quite predictable, and:

“Law takes a while to catch up with new technology, but it eventually does, and when it does it favours the status quo”

Is one of those things.

Not always; eg. Uber, but… predictably often.

The models are already locked away behind cloud APIs. Stable Diffusion wasn't supposed to happen; OpenAI thought that nobody else could afford to train a U-Net on CLIP at their scale and give it away for free.

I will point out that the usual copyright maximalists have been pretty silent on the issue of AI art. The biggest opposition to AI is coming from the Free Software community - i.e. the people who want to abolish artists' ownership over their work outright.

The Free Software movement originates in academia and has academic value - they don't care about receiving direct compensation, but attribution is critical, and attribution is what image generation models can't provide.

>OpenAI thought that nobody else could afford to train a U-Net on CLIP at their scale and give it away for free.

I'm surprised here; I thought it only cost like $600k to train SDv1.4. Plenty of wall street folks and programmers have that much money to burn.

I think your example doesn't quite work here. People pay for music now because handing Spotify or whoever ten dollars a month is a easier then torrenting, easier then managing directories of mp3 files and moving them to your phone, and has value adds in the form of discovery.

I feel like a rebuttal could almost be https://www.youtube.com/user/kmmusic without comment.

You don't need to pay to listen to music if you don't want to. The corpus of good music on YouTube for free is probably bigger than what you can listen to in a lifetime. If it isn't already it will be in time.

Napster's model won that war. Effortlessly. If you're paying for your music, you are paying on your terms based on the value you think is being provided to you. It isn't a legal framework making you do it.

No, it was ease of use that won out in the end. It's easier to pay YT Premium than to torrent and manage music locally.

The difference between music and AI art is that music is still made by humans. No one would make the music if we didn't pay them. And the music industry currently has a monopoly on producing new music, so of course they have leverage to get paid for that new music.

However, if models to freely generate good music become ubiquitous like SD did, then there'd be no incentive to pay for music, and these arguments would become less valid.

In order for these models to end up being solely controlled by a couple of big corporations as in your scenario (ex: Google, OpenAI) they have to either be prohibitively expensive to train or to run.

The former is more likely, although in the case of SD, it wasn't the case. It will be interesting to see if music generation ends up being more complex (in terms of model size) than image generation.

The latter is much less likely because it's difficult to stop people from just using AWS. I doubt that a cluster of BFGPUs couldn't generate enough music for a month in a couple of hours.

Surely someone is busy training a model on a million pop songs. Why wouldn't "AI music" work very much like "AI art"?

Not yet though. In the future, for sure.

My point is that Napster-to-SD is not a fair comparison. Napster didn't eliminate or replace human artists, while SD certainly did. Therefore, it's not fair to assume the government can regulate themselves out of this one like they did with Napster. Because even though Napster enabled widespread piracy, the human musicians still had leverage in that they were needed to create new music.

So my answer to the question posed by parent comment of "will SD play out the same way that Napster did?" is "no" because there are fundamentally different economics at play.

Obviously, if a good generative model comes out, the music industry will be in a similar boat to the art industry right now. Google was working on it in 2017 (https://magenta.tensorflow.org/performance-rnn) but I don't know if they've made any progress since.

Spotify won because it's better than The Pirate Bay. The Playlist on Netflix explains why Spotify surpassed TBP and how the record labels still had to surrender even though they "beat" the pirates.

There's a million Stary Night variants and even Warhol's Soup. Shepard Fairey ripped from They Live. A good artist copies but a great artist steals.

I'm going to need to see a source on ripping the same color palette as being illegal.

This reminded me of https://www.reuters.com/article/electronicarts-zynga/update-... , but alas they settled outside of court so we didn't get a precedent on digital palettes in this particular case.

I bet Pantone believes they can copyright a color palette, considering Adobe just pulled their colors out of Photoshop.

Stary Night is in the public domain which is why you see so many near copies in corporate works.

The other is amusing in light of this case: https://www.supremecourt.gov/DocketPDF/21/21-869/213328/2022...