Thanks for added background! I haven’t been monitoring this area very closely so wasn’t aware, but I’d have thought a publication that has been would then be more skeptical and at least mention some of this, particularly highlighting disputes over the efficacy of the Glaze software. Not to mention the others they talked to for the article.
Figures that in a space rife with grifters you’d have ones for each side.
People don’t understand AI. Probably all articles I have read on it by mainstream media were somehow wrong. It often feels like reading a political journalist discussing about quantum mechanics.
My rule of thumb is: always assume that the articles on AI are wrong. I know it isn’t nice, but that’s the sad reality. Society is not ready for AI because too few people understand AI. Even AI creators don’t fully understand AI (this is why you often hear about “emergent abilities” of models, it means “we really didn’t expect it and we don’t understand how this happened”)
That was certainly true in the 90s. Mainstream journalism on computers back then was absolutely awful. I’d say that only changed in the mid-2000 or 2010s. Even today, tech literacy in journalism is pretty low outside of specialist outlets like, say, Ars.
Kind of true. Check the law proposals on encryption around the world…
Technology is difficult, most people don’t understand it, result is awful laws. AI is even more difficult, because even creators don’t fully understand it (see emergent behaviors, i.e. capabilities that no one expected).
Computers luckily are much easier. A random teenager knows how to build one, and what it can do. But you are right, many are not yet ready even for computers
Probably all articles I have read on it by mainstream media were somehow wrong. It often feels like reading a political journalist discussing about quantum mechanics.
Yeah, I view science/tech articles from sources without a tech background this way too. I expected more from this source given that it’s literally MIT Tech Review, much as I’d expect more from other tech/science-focused sources, albeit I’m aware those require scrutiny just as well (e.g. Popular Science, Nature, etc. have spotty records from what I gather).
Also regarding your last point, I’m increasingly convinced AI creators’ (or at least their business execs/spokespeople) are trying to have their cake and eat it too in terms of how much they claim to not know/understand how their creations work while also promoting how effective it is. On one hand, they genuinely don’t understand some of the results, but on the other, they do know enough of how it works to have an idea of how/why those results came about, however it’s to their advantage to pretend they don’t insofar as it may mitigate their liability/responsibility should the results lead to collateral damage/legal issues.
who illegally stole GPLv3 code from an open source program called DiffusionBee for his proprietary Glaze software (reddit link), and when pressed, only released the code for the “front end” while still being in violation of GPL?
Oh, how I wish the FSF had more of their act together nowadays and were more like the EFF or ACLU.
You should check out the decompilation they did on Glaze too, apparently it’s hard coded to throw out a fake error upon detecting being ran on an A100 as some sort of anti-adversarial training measure.
That’s hilarious, given that if these tools become remotely popular the users of the tools will provide enough adversarial data for the training to overcome them all by itself, so there’s little reason to anyone with access to A100’s to bother trying - they’ll either be a minor nuisance used a by a tiny number of people, or be self-defeating.
This is very relatable, between DNS filtering and uBlock Origin (with a couple custom filters) I always forget how user-hostile the internet has become until I use someone else’s device.
Eh, the corporate fucks who decide to make websites this way, I agree with you, but the truth is most people who put up with it just don’t have the faintest idea of how computers work. You’d bring up DNS filtering and custom adblock filter lists and their eyes would glaze over.
It’s a different reason for losing respect for those two sides.
For the site markers, it’s about greed and where they draw the line for what they want their website to look and behave like.
For the users, it’s that they aren’t willing to learn just a little bit to improve their lives a lot. Like on Android, it’s just a matter of installing Firefox and ublock origin. You can further fine tune it from there but that’s enough for me to forget how cancerous the internet has become unless I end up browsing on a different browser (I hate apps with built in browsers).
“New snake oil to give artists a false sense of security” - The last of these tools I tried had absolutely zero effect on the AI, which is not exactly surprising given that there are hundreds of different ways to make use of image data as well as lots of completely different models. You’ll never cover that all with some pixel twisting.
No shit that using your PC for any purpose will consume electricity. A modern GPU can generate an image in a couple of seconds. Or I could just play a video game for an hour, and consume a few thousand times more energy
Yeah, I can’t imagine it’s that different from playing a demanding game. I hear my video card fans spin up harder and sustain that speed for the duration of a play session.
I use pihole at home, but when I take my laptop out and about, I sometimes notice its fan going wild. Shut down the tab I’m reading and it calms down. What the hell are running on these sites?
I remember one time wwhen I was browsing reddit for a few minutes (booted righ before, doing nothing else, fedora os, minimum stuff installed, no unusual activity in the process list, automatic updates disabled) and noticed my fans spinning a lot, so I opened the system monitor to check what was happening. It was showing high cpu usage in a firefox process, and it registered 40bg of downloaded data!
It never happened again, so I guess it was some sort of bug they fixed, but still, it was something so bizarre to see.
My pihole guaranteed that my experience remained pristine. The author didn’t make any money from my visit, but their income loss is a sacrifice I’m willing to make.
Which is really what the whole problem here boils down to.
They don’t even need to detect them - once they are common enough in training datasets the training process will “just” learn that the noise they introduce are not features relevant to the desired output. If there are enough images like that it might eventually generate images with the same features.
To steal an old trope: the tech bros have circled the globe eight times while the government is still putting its boots on. If there’s money to be made via automation, there’s no stopping it (unless we get the guillotines out of mothballs).
The problem with any regulation is that it’s going to have unforeseen knock-on effects. It might cripple an otherwise benign use. This can be mitigated by trying to draft smart bills initially by coordinating with leaders in the field who aren’t corporate backers. And then being able and willing to amend laws as these effects take shape.
Unfortunately this is not how the US congress functions right now and for the foreseeable future. Therefore regulation will likely be sparse and when it is heavy handed, unlikely to be amended unless the knock-on effects are massively bad.
This is cool. I think generative AI is great, but the way it’s being trained right now largely without consent from the artists or subjects is unequivocally unethical. Until the law catches up with the technology, people need ways of protecting themselves.
Until the law catches up with the technology, people need ways of protecting themselves.
I agree, and I wonder if the law might be kicked into catching up quicker as more companies try to adopt these tools and inadvertently infringe on other companies’ copyrighted material. 😅
I don’t see how AI training couldn’t be considered transformative as the whole idea is to consume input, break it down into data, and output something new. The way I’m understanding what you’re saying is like this: Instead of only paying royalties when I try to monetize a cover song, I’d have to pay every time I practiced it.
I don’t understand how you’re separating the the generated artworks from the AI that’s generating the work, but I do see your point. If a company puts out a tool for free I don’t think they should be on the hook for someone using that and creating a product. At the end of it all though, I think whoever has made any hard financial gains should should payout whoever contributed.
How is training AI with art on the web different to a person studying art styles? I’d say if the AI is being monetized in some capacity, then sure maybe there should be laws in place. I’m just hard-pressed to believe that anyone can have sole control of anything once it gets on the Internet.
The real issue comes in ownership of the AI models and the vast amount of labor involved in the training data. It’s taking what is probably hundreds of thousands of hours of labor in the form of art and converting it into a proprietary machine, all without compensating the artists involved. Whether you can make a comparison to a human studying art is irrelevant, because a corporation can’t own an artist, but they can own an AI and not have to pay it.
Human brains clearly work differently than AI, how is this even a question?
It’s not all that clear that those differences are qualitatively meaningful, but that is irrelevant to the question they asked, so this is entirely a strawman.
Why does the way AI vs. the brain learn make training AI with art make it different to a person studying art styles? Both learn to generalise features that allows them to reproduce them. Both can do so without copying specific source material.
The term “learning” in machine learning is mainly a metaphor.
How do the way they learn differ from how humans learn? They generalise. They form “world models” of how information relates. They extrapolate.
Also, laws are written with a practical purpose in mind - they are not some universal, purely philosophical construct and never have been.
This is the only uncontroversial part of your answer. The main reason why courts will treat human and AI actions different is simply that they are not human. It will for the foreseeable future have little to do whether the processes are similar enough to how humans do it.
Now you’re just cherry picking some surface-level similarities.
You can see the difference in the process in the results, for example in how some generated pictures will contain something like a signature in the corner, simply because it resembles the training data - even though there is no meaning to it. Or how it is at least possible to get the model to output something extremely close to the training data - gizmodo.com/ai-art-generators-ai-copyright-stable….
That at least proves that the process is quite different to the process of human learning.
The question is how much those differences matter, and which similarities you want to focus on.
Human learning is similar in some ways, but greatly differs in other ways.
The fact that you’re picking and choosing which similarities matter and which don’t is just your arbitrary choice.
You can see the difference in the process in the results, for example in how some generated pictures will contain something like a signature in the corner
If you were to train human children on an endless series of pictures with signatures in the corner, do you seriously think they’d not emulate signatures in the corner?
If you think that, you haven’t seen many children’s drawings, because children also often pick up that it’s normal to put something in the corner, despite the fact that to children pictures with signatures is a tiny proportion of visual input.
Or how it is at least possible to get the model to output something extremely close to the training data
People also mimic. We often explicitly learn to mimic - e.g. I have my sons art folder right here, full of examples of him being explicitly taught to make direct copies as a means to learn technique.
We just don’t have very good memory. This is an argument for a difference in ability to retain and reproduce inputs, not an argument for a difference in methods.
And again, this is a strawman. It doesn’t even begin to try to answer the questions I asked, or the one raised by the person you first responded to.
That at least proves that the process is quite different to the process of human learning.
Neither of those really suggests that all (that diffusion is different to humans learn to generalize images is likely true, what you’ve described does not provide even the start of any evidence of that), but again that is a strawman.
There was no claim they work the same. The question raised was how the way they’re trained is different from how a human learns styles.
I agree that the training isn’t fundamentally different, but that monetization of the output has to be controlled. The big difference between AI and humans is the speed with which they create - you have to employ an army of humans to match the output of a couple of GPUs. For noncommercial projects this is amazing. For commercial projects, it destroys the artists livelihoods.
But this simply means that training shouldn’t be controlled, inference in commercial contexts should be.
I work in AI and I believe it is different. Society is built to distribute wealth, so that everyone can live a decent life. People and AI should be treated differently in front of the law. Also, non-commercial, open source AI should be treated differently than commercial or closed source models
To me, that’s not an argument for regulating AI, though, because most regulation we can come up with will benefit those with deep enough pockets to buy themselves out of the problem, while solving nothing.
E.g. as I’ve pointed out in other debates like this, Getty Images has a market cap of <$2bn. OpenAI may have had a valuation in the $90bn range. Google, MS, Adobe all also have shares prices that would trivially allow them to purchase someone like Getty to get ownership of a large training set of photos. Adobe already has rights to a huge selection via their own stock service.
Bertelsmann owns Penguin Random-House and a range ofter publishing subsidiaries. It’s market cap is around 15 billion Euro. Also well within price for a large AI contender to buy to be able to insert clauses about AI rights. (You think authors will refuse to accept that? All but the top sellers will generally be unable to afford to turn down a publishing deal, especially if it’s sugar-coated enough, but they also sit on a shit-ton of works where the source text is out-of-copyright but they own the right to the translations outright as works-for-hire)
That’s before considering simply hiring a bunch of writers and artists to produce data for hire.
So any regulation you put in place to limit the use of copyrighted works only creates a “tax” effectively.
E.g. OpenAI might not be able to copy artist X’s images, but they’ll be able to hire artist Y on the cheap to churn out art in artist X’s style for hire, and then train on that. They might not be able to use author Z’s work, but they can hire a bunch of hungry writers (published books sells ca 200 copies on average; the average full time author in the UK earns below minimum wage from their writing) as a content farm.
The net result for most creators will be the same.
Even wonder why Sam Altmann of OpenAI has been lobbying about the dangers of AI? This is why. And its just the start. As soon as these companies have enough capital to buy themselves access for data, regulations preventing training on copyrighted data will be them pulling up the drawbridge and making it cost-prohibitive for people to build open, publicly accessible models in ways that can be legally used.
And in doing so they’ll effectively get to charge an “AI tax” on everyone else.
If we’re going to protect artists, we’d be far better off finding other ways of compensating them for the effects, not least because it will actually provide them some protection.
UBI is needed because most of the jobs people are currently doing are already not needed. They are needed just to redistribute wealth, but most of the jobs are currently already useless (if you work in corporate, public sector or retail you know what I am talking about). In the future more will become useless. Current copyright laws are already outdated and don’t work anymore. Only safe solution for people who want to dedicate their lives to visual art is UBI. Because of the known reasons. Most “artists” are not really doing art, simply a job for entertainment industry that in the future will be done by much fewer people due to technological and organizational changes. As it is already happening now, even before AI.
UBI is a solution for similar situations, that will be even more common in future. We need better solutions to redistribute wealth, from what you call “power brokers” to larger society
I don’t see a problem with it training on all materials, fuck copyright. I see the problem in it infringing on everyone’s copyright and then being proprietary, monetized bullshit.
If it trains on an open dataset, it must be completely and fully open. Everything else is peak capitalism.
Of course not, it’s the artists decision to put it on the internet for free.
Technically that’s the root of the issue. This does not grant a license to everyone who looks at it, but if a license is required to train a model is unclear and currently discussed in court.
The problem is the only way for artists to get people to see and eventually buy their art or commissions is to post some of their work publicly. Historically you would go out on the street and set up a stall, now social media is our digital street. Galleries don’t take everyone, having the ability to even get a meeting with one is difficult without the right connections. Most artists are never successful enough to completely live off their art, if they can make any money at all it is great for them. Then along comes an AI model that takes their work because it’s on the internet scrapes it into its training set and now any chance they had in an over saturated market is even smaller, because hey, I can just do this with AI. This idea that copyright and IP shouldn’t exist at all is kinda absurd. Would you just go through a street art walk, take high res photos of every picture they have on display, not take any business cards, and when they ask what you are doing, go “it’s ok, I’m training an AI data model so people can just make work that looks exactly like this. They shouldn’t have to ever buy from you. Capitalism is a joke. Bye!” The art walk was free, but it was also a sales pitch, because that’s how the art world works. You are hoping to get seen, that someone likes it enough to buy, and maybe buy more.
This idea that copyright and IP shouldn’t exist at all is kinda absurd
I don’t hold this opinion at all.
I’m just saying that there are uses for which you don’t need a license. Say, visiting an art exhibition and then going home and trying to draw similar pictures. Wether AI training falls into this category or instead requires a license is currently unclear.
Btw, two spaces before the line break
Creates the spacing you want.
As an artist who studies data science, I would say doing art and generating art are an entirely different process. AI has no reference outside of the information we give it. It had no real understanding of lighting, spacial awareness. We can tell it every tank is a cat, every flashlight is a pig and it will never question it. If we tell a toddler that every tank is a cat, they may call a tank a cat, but they will never think a that “cat” is a house pet. They will never think that “pig” will oink or be turned into steaks. An AI however would if your language conventions were the same in the prompt.
If you go to the art walk and go home and try to recreate a style, you were inspired. If an AI model is trained on many styles and you tell it “portrait, woman, Van Gogh style, painterly, blue tones” then do you understand what you asked for? Was the ai inspired by Van Gogh? Did the ai study his techniques? No. It broke down his art pixel by pixel, rearranged it in a filter styled overlay over a woman, most likely a young woman-because of algorithmic bias which has been studied- in shades of blue. Humans take the time to study the why, the how. Ai does not. Humans are not just meat robots.
I should say I’m not against AI art. I’m against gathering against consent. If it was opt in, or if there was some type of pay for program that would be fine. Even if it was pennies each month. But the fact that they scrape without consent. Or are now going back and adding it into TOS where it never was before feels scummy. AI art has a place, and is a helpful tool. But it’s not a replacement for artists, it has many flaws still, that might never be worked out.
This idea that copyright and IP shouldn’t exist at all is kinda absurd.
For the majority of human existence, that was the default.
Copyright exists as an explicit tradeoff between the rights of the public to be able to do as they please with stuff introduced into the public sphere, and a legal limitation infringing on the publics liberty for a limited time for the purpose of encouraging the creation of more works for the public benefit. It was not introduced as some sort of inherent right, but as a trade between the public and creators to incentivise them.
Stripping it away from existing artists who has come to depend on it without some alternative would be grossly unfair, but there’s nothing absurd about wanting to change the bargain over time. After all, that has been done many times, and the copyright we have now is vastly different and far more expansive and lengthy than early copyright protection.
Personally, I’d be in favour of finding alternative means of supporting creators and stripping back copyright as a tradeoff. The vast majority of creators earn next to nothing from their works; only a very tiny minority makes a livable wage of art of any form at all, and of the rest the vast majority of profits take place in a very short period of initial exploitation of a work, so we could allow the vast majority to earn more from their art relatively cheaply, and affect the rest to a relatively limited degree, while benefiting from the reduced restrictions.
I agree that copyright lasts far too long, but the idea I can post a picture today, and in a hour it’s in an AI model without my consent bothers me. Historically there was a person to person exchange. But now we are so detached from it all I don’t think we can have that same affordance of no types of protections. I’m not saying one person can solve this. But I don’t see UBI or anything like that ever happening. As a person who has lived on disability most of their life, people don’t like to share their wealth with anyone for any reason. I’ve never been able to sell art for a living and am now going to school for data science. So I know about both ends of this. Just scraping without consent is unethical and many who do this have no idea about the art world or how artist create in general.
I doesn’t need to be full on UBI. In a lot of countries grants mechanisms and public purchasing mechanisms for art already make up a significant proportion of income for artists. Especially in smaller countries, this is very common (more so for literary works, movies and music where language provides a significant barrier to accessing a bigger audience, but for other art too). Imagine perhaps a tax/compulsory licensing mechanism that doesn’t stop AI training but instead massively expands those funding sources for people whose data are included in training sets.
This is not stoppable, not least because it’s “too cheap” to buy content outright.
I pointed out elsewhere that e.g. OpenAI could buy all of Getty Images for ~2% of their currently estimated market cap based on a rumoured recent cash infusion. Financing vast amounts of works for hire just creates a moat for smaller players while the big players will still be able to keep improving their models.
As such it will do nothing to protect established artists, so we need expansion of ways to fund artists whether or not inclusion of copyrighted works in training sets becomes restricted.
Those grants, and public purchases make up a significant portion of income for established main stream artists. If you work on commission only online, or never went to art school those won’t cover you.
These large tech companies become so highly valued at the start because of venture capital and then in 5-10 years collapse under their own weight. How many of these have come up and are now close to drowning after pushing out all competitors? Sorry if I’m not excited about an infusion of cash into a large for profit company that is just gobbling up anything anyone posts online without consent to make a quick buck.
I’m not against AI. I’m against the ethics of AI at the moment because it’s awful. And AI leans into biases it finds and there are not a lot of oversights on this.
If you work on commission only online, or never went to art school those won’t cover you.
There’s no reason it has to stay like that. And most people in that position are not making a living from art as it is; expanding public funding to cover a large proportion of working artists at a better level than today would cost a pittance.
These large tech companies become so highly valued at the start because of venture capital and then in 5-10 years collapse under their own weight. How many of these have come up and are now close to drowning after pushing out all competitors? Sorry if I’m not excited about an infusion of cash into a large for profit company that is just gobbling up anything anyone posts online without consent to make a quick buck.
MS, Apple, Meta, Google etc. are massively profitable. OpenAI is not, but sitting on a huge hoard of Microsoft cash. It doesn’t matter that many are close to drowning. The point is the amount of cash floating around that enable the big tech companies to outright buy more than enough content if they have to means that regulation to prevent them from gobbling up anything anyone posts online without consent will not stop them. So that isn’t a solution. It will stop new entrants with little cash, but not the big ones. And even OpenAI can afford to buy up some of the largest content owners in the world.
The point was not to make you excited about that, but to illustrate that fighting a battle to restrict what they can train on is fighting a battle that the big AI companies won’t care if they lose - they might even be better off if they lose, because if they lose, while they’ll need to pay more money to buy content, they won’t have competition from open models or new startups for a while.
So we need to find other solutions, because whether or not we regulate copyright to training data, these models will continue to improve. The cat is out of the bag, and the computational cost to improving these models keeps dropping. We’re also just a few years away from people being able to train models competitive to present-day models on computers within reach of hobbyists, so even if we were to ban these models outright artists will soon compete with output from them anyway, no matter the legality.
Focusing on the copyright issue is a distraction from focusing on ensuring there is funding for art. One presumes the survival of only one specific model that doesn’t really work very well even today and which is set to fail irrespective of regulation, while the latter opens up the conversation to a much broader set of options and has at least a chance of providing working possibilities.
I don’t see these grants or public funding ever covering a private company for one. And for two, I don’t see AI art ever actually getting to the point where it fully replaces artists. As of right now it is good. But it doesn’t understand space or lighting at all. Because of how AI works I’m not sure it ever will. Because it is trained to make a homogeneous rendering of what you are looking for, even if you use a base image, most people have an image that is lit heavily in the front, but because of this it never is able to render shadows correctly. Unless they hire people who are artist or art critics to finely train the data set, which I doubt they will, then the more you look the more uncanny valley the images get. They also have a hard bias in all of their images they generate. Which is difficult to overcome.
AI is an amazing tool, but it is a poor replacement in total. The people who act like it is a total replacement are like the people who in 2015 told us self driving cars were just one year away, and have been saying it every year since. Maybe when quantum computing becomes the standard for every person AI will be able to. But there is just a fundamental misunderstanding of art, artistic process, how art get made people seem to have.
Open AI might be sitting on Microsoft money, but how many other companies has Microsoft gobbled up over the years? Open AI if it starts to struggle will just fall under the Microsoft umbrella and become part of its massive conglomerate, integrated into it. Where are our AR goggles that we are supposed to all be wearing, Microsoft and Google both had those? So many projects grow and die with multiple millions thrown at them. All end up with crazy valuations based on future consumer usage. As we all can’t even afford rent.
There is also this idea that people wouldn’t willing contribute if just asked. The problem is no one has even asked. Hugging Face is an open source distro people willingly contribute to. And so many people upload images to Creative Commons which could be used. I’ve done it with many of my photos which I have no problem being used in a data set, for commercial use even. But my commercial images, no please. The idea that you can’t train smaller models on the vast array of Creative Commons images and public domain, you absolutely can. You can also ask people to contribute to your data set and give credit to them. A lot of people are angry at lack of credit.
There is no reason for any of this to be private enterprise if they are going to blatantly steal copyright images when sources like Creative Commons exists, not give any credit to the people they steal from, and sometime even steal from places they shouldn’t even have access to.
I don’t see these grants or public funding ever covering a private company for one.
Companies are by far the largest recipients of public funding for art in many countries and sectors. Especially for e.g. movie production in smaller languages, but also in other sectors.
And for two, I don’t see AI art ever actually getting to the point where it fully replaces artists.
I do agree it won’t fully replace artists, but not because it won’t get to the point where it can be better than everyone, but because a huge part of art is provenance. A “better Mona Lisa” isn’t worth anything, while the original is priceless, not because a “better” one isn’t possible, but because it’s not painted by Da Vinci.
But that will only help an even narrower sliver than the artists who are making good money today.
It will take time, but AI will eat far more fields than art, and we haven’t even started to see the fallout yet.
Because it is trained to make a homogeneous rendering of what you are looking for
Diffusion models are not trained “for” anything other than matching vectors to denoising to within your own tolerance levels of matching to what you are looking for. Accordingly, you’ll see a whole swathe of models tuned on more specific types of imagery, and tooling to more precisely control what they generate. The “basic” web interfaces are just scratching the surface of what you can do with e.g. Controlnet and the like. It will take time before they get good enough, sure. They are also only 2 years old, and people have only been working on tooling around then for much less than that.
Open AI might be sitting on Microsoft money, but how many other companies has Microsoft gobbled up over the years? Open AI if it starts to struggle will just fall under the Microsoft umbrella and become part of its massive conglomerate, integrated into it. Where are our AR goggles that we are supposed to all be wearing, Microsoft and Google both had those? So many projects grow and die with multiple millions thrown at them. All end up with crazy valuations based on future consumer usage. As we all can’t even afford rent.
OpenAI is just one of many in this space already. They are in the lead for LLMs, that is text-based models. But even that lead is rapidly eroding. They don’t have any obvious lead for diffusion models for images. Having used several, it was first with the recent release of DallE 3 that it got “good enough” to be competitive.
At the same time there are now open models getting close enough to be useful, so even if every AI startup in the world collapsed this won’t go away.
There is also this idea that people wouldn’t willing contribute if just asked.
That’s fine, but that doesn’t fix the financial challenge.
So what you are saying is open ai should get the public grants for artists to give to artists?
I understand it isn’t trained for anything, I have done training with them. The training leads to homogeneous outcomes. It had been studied as well. You can look it up.
Dall-e 3 still isn’t good enough to be competitive. It is too uncanny valley. I’m not saying people have to be the masters. I don’t know where you get that from, every one who touts this tech always goes to that. It is a tool that can be useful, but it is not a replacement.
Asking and crediting would go a long way to help fix the financial challenge. Because it is a start to adding a financial component. If you have to credit someone there becomes an obligation to that person.
So what you are saying is open ai should get the public grants for artists to give to artists?
No. What in the world gave you that idea? I’m saying artists or companies employing artists should get grants, just like is the case for a large number of grants now. I’m saying I’d like to see more of that to compensate for the effects being liberal about copyright would have.
I understand it isn’t trained for anything, I have done training with them. The training leads to homogeneous outcomes. It had been studied as well. You can look it up.
There is no “the training”. There are a huge range of models trained with different intent producing a wide variety in output to the point that some produces output that others will just plain refuse.
Dall-e 3 still isn’t good enough to be competitive.
Dall-E 3 isn’t anywhere near leading edge of diffusion models. It’s OpenAI playing catch up. Now, neither Midjourney or Firefly, nor any of the plethora of Stable Diffusion derived models are good enough to be competitive with everyone without significant effort either, today, but that is also entirely irrelevant. Diffusion models are two years old, and the pace of the progress have been staggering, to the point where we e.g. already have had plenty of book-covers and the like using them. Part of the reason for that is that you can continue training of a decent diffusion model even on a a somewhat beefy home machine and get a model that fits your needs better to an extent you can’t yet do with LLMs.
Asking and crediting would go a long way to help fix the financial challenge. Because it is a start to adding a financial component. If you have to credit someone there becomes an obligation to that person.
If there is a chance crediting someone will lead to a financial obligation, people will very quickly do the math on how cheaply they can buy works for hire instead. And the vast bulk of this is a one-off cost. You don’t need to continue adding images to teach the models already known thing, so the potential payout on the basis of creating some sort of obligation. Any plan for fixing the financial challenge that hinges on copyright is a lost cause from the start because unless it’s a pittance it creates an inherent incentive for AI companies to buy themselves out of that obligation instead. It won’t be expensive.
I feel like you are one of the people who feel that AI is just going to be the future with no real problems to anyone who matters. We can’t stop it, we can’t regulate it in any way whatever; and people should just move out of the way, give up and if they can’t find a place in the new world, die already. Artists don’t matter, writers don’t matter and anyone impacted by this new system doesn’t matter. The algorithm is all that matters.
Because I don’t use the exact correct wording, I use a short hand that is easier for my brain to remember, and you are pedantic, I can’t know anything about LLMs, machine learning or anything about this. Because I don’t say it has a training set of a large model of images that are tagged in specific ways that they can take out antagonistic images or images that create artifacts and refine the model in appropriate ways. You therefore throw out the idea that bias exists due to tagging systems.
Honestly I don’t care if you don’t think I know anything about this. You are a stranger on the internet and this conversation has gone on too long.
I feel like you are one of the people who feel that AI is just going to be the future with no real problems to anyone who matters. We can’t stop it, we can’t regulate it in any way whatever; and people should just move out of the way, give up and if they can’t find a place in the new world, die already. Artists don’t matter, writers don’t matter and anyone impacted by this new system doesn’t matter. The algorithm is all that matters.
If I thought that, I wouldn’t have emphasised the need to sort out the funding issue, and argued that just regulation will be insufficient to solve it.
I think it will cause a massive degree of upheaval. I don’t think regulation has any hope in hell of preventing upheaval significant enough that unless a solution is found to ensure better distribution of wealth it will cause violence and uprisings and governments to fall. Not necessarily in and of itself, but in accelerating a process of reducing the monetary value of labour.
I can’t know anything about LLMs, machine learning or anything about this.
I’ve not suggested anything of the sort.
How you can interpret anything I’ve written as suggesting I don’t think there will be problems is beyond me.
You therefore throw out the idea that bias exists due to tagging systems.
I am perfectly entitled to type random stuff into google images, pick out images for a mood board and some as reference, regardless of their copyright status, thank you. Studying is not infringement.
It’s what every artist does, it’s perfectly legal, and what those models do is actually even less infringing because they’re not directly looking at your picture of a giraffe and my picture of a zebra when drawing a zebra-striped giraffe, they’re doing it from memory.
And if you think that working with AI does not take effort you either did not try, or don’t have an artistic bone in your body. Randos typing “Woman with huge bazingas” into an UI and hitting generate don’t get copyright on the output, rightly so: Not just did they not do anything artistic, they also overlook all the issues with whatever gets generated because they lack the trained eye of an artist.
Linus Torvalds, the Finnish engineer who in 1991 created the now ubiquitous Unix alternative Linux, didn’t buy into this dogma. Torvalds and others, including Microsoft’s Bill Gates, believed that the culture of open exchange among engineers could coexist with commerce, and that more-restrictive licenses could forge a path toward both financial sustainability and protections for software creators and users.
It’s kind of amazing that this article gets one thing right that most journalists don’t, which is that pushover licenses are more restrictive toward the software’s users than copyleft licenses, while simultaneously ignoring the fact that free software can be sold and the GNU Project actively encourages doing business with free software. However, I worry that by “more restrictive”, this article isn’t talking about passing on freedoms but instead talking about source-available licenses. I think this because it includes Bill Gates and Linus Torvalds in the same class, the former who was the CEO of a company that started the Shared Source Initiative, which was a source-available licensing program for Windows. Meanwhile, Linus Torvalds is a veteran of free software.
A little confusing, but I’ll give them the benefit of the doubt here. They’ve got the history right for the most part.
As the tech industry grew around private companies like Sun Microsystems, IBM, Microsoft, and Apple in the late ’90s and early ’00s, new open-source projects sprang up, and established ones grew roots. Apache emerged as an open-source web server in 1995. Red Hat, a company offering enterprise companies support for open-source software like Linux, went public in 1999. GitHub, a platform originally created to support version control for open-source projects, launched in 2008, the same year that Google released Android, the first open-source phone operating system.
I don’t understand why Github is being included in this list of “open source projects”. Github isn’t free software! It’s as proprietary as it gets. Gitlab, Gitea, or Sourcehut make more sense as they are actually free software projects. It’s a strange fact of life that the largest free software code forge is proprietary. I also think it does Apple a disservice by not mentioning the fact that Apple completely rebuilt its operating system on a free software BSD foundation in the late '90s, and then released parts of it as free software, like the XNU kernel, as well as CUPS, which I use today! Even as far back as the '90s, large private corporations like Apple were releasing both proprietary software and free software. Sun Microsystems of course was a much bigger free software contributor at the time.
All in all, I’m kind of confused by this paragraph. Is it trying to juxtapose “private companies” and “open-source”? Well, private companies just so happen to be the biggest contributors to the largest free software project today; the Linux kernel. Is it trying to say that private companies suddenly started releasing free software because of ‘open-source’? Why list companies that have made big contributions to free software without listing those contributions, then?
This is made even more confusing when it talks about Amazon relying on the free software Java language developed by Sun, trying to make the point that private companies relied on a blend of proprietary and free software components. It confuses things a bit more by introducing patents when it starts off talking about copyright, which can also be registered for free software.
Others, including Kelsey Hightower, are more sanguine about corporate involvement. “If a company only ends up just sharing, and nothing more, I think that should be celebrated,” he says. “Then if for the next two years you allow your paid employees to work on it, maintaining the bugs and issues, but then down the road it’s no longer a priority and you choose to step back, I think we should thank [the company] for those years of contributions.”
I agree very much with this. Red Hat’s many contributions to the freedesktop project come to mind.
There’s no singular definition, either. The Open Source Initiative (OSI) was founded in 1998 to steward the meaning of the phrase, but not all modern open-source projects adhere to the 10 specific criteria OSI laid out, and other definitions appear across communities.
I find this very troubling. The OSI applied for a trademark on “Open Source” in 1999 and were not granted it. They wanted to trademark the term so no one could twist “Open Source” into something it wasn’t (there’s a quote earlier in the article referring to “openwashing”), meaning they foresaw this. The Open Source Definition is very specific and if we start applying the term “open source” to source-available projects (or whatever else, like Brave Search’s “open” API), it loses all its meaning, and Windows suddenly becomes an open source operating system.
GitHub helped lower the barrier to entry, drawing wider contribution and spreading best practices such as community codes of conduct. But its success has also given a single platform vast influence over communities dedicated to decentralized collaboration.
Yes. That’s pretty scary.
While this volunteer spirit aligns with the original vision of free software as a commerce-free exchange of ideas,
…No, it was never like that. Since this article judiciously references our shared history, let’s talk about how Richard Stallman funded the GNU Project. Richard Stallman originally made his living off selling GNU Emacs (free software) on tapes to programmers so he could employ developers to work on parts of the GNU Project. Free software isn’t about not making money. Linus Torvalds, in fact, is the guy that originally didn’t want to make money from software! He originally released Linux under a restrictive license that prevented anyone from making any money from Linux. The GNU Project celebrated the kernel when Linus released it under a free license that allowed commercial exploitation—specifically, the GNU General Public License (V2).
But allowing anyone to use, modify, and distribute AI models and technology could accelerate their misuse.
This isn’t new. The GNU Project has a page about why software must not restrict people from running it. The entire point of free software is that no one is at the mercy of the developers and their ethics. Personally, I don’t trust OpenAI to know what is good for me.
LLaMA 2, a new model released in July, is fully open to the public, but the company has not disclosed its training data as is typical in open-source projects—putting it somewhere in between open and closed by some definitions, but decidedly not open by OSI’s.
This demonstrates why the Open Source Definition is important and canonical.
Overall, I’d say this article actually rates better than most articles I’ve seen written about free software in terms of accuracy and history. It makes some good points about funding. The article also includes voices from very relevant people in the free software / open source space, which is good.
FYI on CUPS, Apple hired the dev and bought the code in 2007. He left Apple in 2019 and actually forked CUPS. My system it is running OpenPrinting CUPS and not the Apple one. It is still nice that they share its code it just got a little more complicated in the past few years.
Well, so much for me having the right side of history 🙂
Thanks for the correction! I had a proper look at the CUPS page on Wikipedia and it’s as you say:
Michael Sweet, who owned Easy Software Products, started developing CUPS in 1997 and the first public betas appeared in 1999.[5][6] The original design of CUPS used the Line Printer Daemon protocol (LPD), but due to limitations in LPD and vendor incompatibilities, the Internet Printing Protocol (IPP) was chosen instead. CUPS was initially called “The Common UNIX Printing System”. This name was shortened to just “CUPS” beginning with CUPS 1.4 due to legal concerns with the UNIX trademark.[7] CUPS was quickly adopted as the default printing system for most Linux distributions. In March 2002, Apple Inc. adopted CUPS as the printing system for Mac OS X 10.2.[8] In February 2007, Apple Inc. hired chief developer Michael Sweet and purchased the CUPS source code.[9] On December 20, 2019, Michael Sweet announced on his blog that he had left Apple.[10][11] In 2020, the OpenPrinting organization forked the project, with Michael Sweet continuing work on it.[12][13]
This is kind of counter to the point I was making, so thanks for bringing it up. Apple still released some of their software under a free license back then, but without CUPS, it’s nowhere near as significant. I guess it’s worth mentioning that Apple forked KHTML from KDE as Webkit and continues to develop and maintain that browser engine today. However, Safari is not free software. Webkit is free software because KHTML was released under the LGPL, which prevents derivative software from developing it under a proprietary license.
Although, Apple’s own contributions and “any further contributions” are available under the BSD 2-Clause license: webkit.org/licensing-webkit/
Which kind of contradicts what I’ve read on the Wikipedia page where it says certain parts of the browser are licensed under LGPL and others are licensed under the BSD license…
GitHub helped lower the barrier to entry, drawing wider contribution and spreading best practices such as community codes of conduct. But its success has also given a single platform vast influence over communities dedicated to decentralized collaboration.
Yes. That’s pretty scary.
Yeah it is scary. Since code is speech, where it’s stored should be censorship resistant, and github ain’t it.
I‘m sure it’s not as simple, but my first take on this was: Europe doesn’t invest in EVs, but China does. They start to loose the Chinese market and are about to loose their own market to China as well. Then politics steps in to “rescue” their own companies but all that does is shelter them from the pressure to adapt and evolve, and in the end they’re beyond hope and left in the dust while the advanced Chinese cars dominate everything.
Countering subsidies with import taxes is a different story ofc. But it certainly feels like the European car industry is in decline and it’s probably their own fault. If not in Europe most certainly in China.
I should add that I have no idea what I’m talking about here, so feel free to tell me where I’m wrong.
China has been doing this for centuries now. You couldnt even break into the chinese consumer space if the CCP decides that you might be a danger to their own industry.
So it’s kinda hypocritical to now claim the EU is doing something because its china.
Take a look at what VW did to the British car market with illegal subsidies from the German Government. Then look at VW being caught in the emissions scandle. Long story short, cheating is profitable.
British car manufacturers didn’t need Germany to dismantle themselves. The only reason you even have a car industry left is because German companies came in, bought up those husks of mismanagement out of (near) bankruptcy, and turned them around.
Long story short: Don’t let nobs run your companies. They were as good at deciding what customers want as Homer Simpson is at designing a car and caused strike after strike by being, well, arrogant nobs telling the peasants to eat cake.
Correct, that was the thinking what had happened at the time but when you realise VWs were being sold about 5k below market cost you realise there was no competing. Look deeper.
If you mean “German cars were cheaper” there’s an easy explanation: Unlike the UK ones German manufacturers managed to introduce automation by negotiating its introduction with the workers, who realised that it’s necessary to keep the industry but got concessions such as automation first being used for the most back-breaking stuff, not what would save the most money. Meanwhile, in the UK, well, strikes. Strikes, strikes, and strikes.
I’d like to see a source on the below market cost bit, and even if why didn’t the UK simply outlaw it. But yes German industry played it fast and loose back then, e.g. it didn’t became illegal under German law to bribe foreigners abroad until 2000, on the contrary you would get a tax write-off. Not like the UK operated a different regime, though, you simply weren’t as good at it when it came to cars. You’re more into the tax haven kind of business, shuffling money discretely to crown dependencies which unlike manufacturing is not dependent on riffraff workers.
No, Germany’s government colluded with the manufacturers to charge them less tax to purposefully give them an advantage. By about £5k. You’re not providing sources for your claims so I don’t feel obliged to.
Well that’d be direct state aid which EU rules forbid on the internal market so… I guess you should’ve joined earlier. Or had an actual trade policy. Something like that, instead of bemoaning the evil Teutons harassing the poor, poor British Empire with its utter lack of sovereignty. I know it’s a popular narrative but it hasn’t been true since WWII. Modulo football of course. We’d love to not bully you there, see you take second place instead of the Brazilians, but, alas, you know.
Also, I don’t believe that number for a second. Why? Because a VW Golf cost £2099 in 1976, in today’s pounds (which I assume that your £5k are) that’s as per Bank of England £13,448.89. That’s so off scale for a subsidy it’s not even funny, and it would also mean that all those other countries there subsidised their cars as VWs aren’t cheaper than the Fords and Citroens and whatnot. The Golf is in fact right in between two not entirely incomparable Vauxhalls. Extraordinary claims require extraordinary evidence, yours is one, mine aren’t.
I heavily suspect that you read an article wrong somewhere. “(some) UK car manufacturers needed to sell at a loss (and in some cases that might’ve been £5k) because they didn’t manage to introduce automation” sounds more like it.
And it was the Japanese who kicked that off, btw, the German car industry had to react to it to stay competitive just as the rest of the world.
What about “The EU forbids direct state aid” was waffley bollocks? Why didn’t the UK have Berlaymont nuke Germany’s practice from orbit?
Or are we at a cultural impasse, here, I know that at least Americans often don’t understand the practice of what we call, over here, when speaking English, taking the piss.
It is impossible for that to have been sarcasm, of course, as I am German and therefore do not partake in such frivolities. It all makes perfect sense now. Toodeloo.
It is not like European companies are not investing into EVs, but that EVs are different. The big advantage is battery technology, but most batteries are bought from third parties. Only Tesla and BYD have large battery production of their own. So everybody else buys them from other companies. So it is hard to be better on that technological front. The rest is a generally nice interior and software. Interior is something Europeans can do, but it has relativly little value add. What is more important is software and that is difficult for manufacturing based companies like traditional car companies.
This is not to say that European companies can not win this or lack innovation. They make good EVs, but so do the Chinese and that means a war on price. Europe is in a disadvantage on that. However there are solutions being planned like large battery plants by European manufacturers and better software development.
EVs are more the just batteries and both Volkswagen and BMW have set up production lines for EVs they developed themself. That is certainly investment. However they are using batteries from other companies. They are catching up with tesla and BYD by also setting up battery factories now. It is a bit late, but maybe not too late.
They should have done it 20 years ago, but Big Oil and Big Car are besties. I live in EU and I think it’s okay to let them die. They made fun of people demanding EVs. They spread misinformation. Hindered development. Let them pay the price. However, I don’t wanna rely on China either. Public transportation should be the answer.
Technology is not apolitical, because humans are not apolitical. Anyone who says they are or claims to be “neutral” or “centrist” simply means their ideals align with the status quo.
This is a problem with all sectors of tech, but especially in places where algorithms have to be trained. For example, facial recognition systems are notoriously biased against anyone who isn’t cis and white. Fitness trackers/smart watches/etc. have trouble with darker skin tones. Developers encode implicit biases because they are oblivious to the fact that their experiences aren’t universal. If your dev team and your company at large aren’t diverse, that lack of diversity is going to show through in your product, intentional or not. How you shape the algorithms, what data you feed it to train it, etc. are all affected by those things.
Anyone who refuses to accept this and insists on holding on to the idea that somehow “computer” means “neutral and objective” is generally not worth engaging in any discussion about LLM’s/AI/etc.  Their partisan blinders are impenetrable. 
Essentially, it looks at why conservatives vs. liberals approach the world differently. Democracy vs. capitalism is inherently a logical contradiction; in a true democracy, everyone is treated equally and all voices have equal weights. In capitalism, some people are more equal than others - it's a pyramid. Fascism is when these "some people are better" is because of something like genetics, or culture. (The video doesn't touch on this, but modern Communism falls into the same trap as well, where "some people are better" because they know the party leaders or they're technocrats. It's a mindset that humans have and not something exclusive to capitalism.)
Where you wind up on the American political spectrum is based on where you fall when the ideals of equality vs. hierarchy clash. There is no middle ground because the two are fundamentally incompatible - if everyone was truly treated equally, you couldn't have people with more power/status than others. If you accept that not everyone should wield power and that at the end of the day there must be some rich and some poor - some that have power and others that do not - then you are therefore arguing that people shouldn't be treated equally. From there, the pyramid structure is the natural order of things ("always a bigger fish").
Because the structure is fundamentally at odds with itself you can't have both at once. You have to compromise on one side more than the other. Hence there is no such thing as "apolitical", even with technology - it will hold a bias one way or the other.
And you really nailed it. This is why I can’t stand the rhetoric of “can’t we put politics aside and agree to disagree?” because the answer is “if your ideals are at odds with equality, and you deny the basic human nature, human rights, and civil rights of others, then no. We can’t.” There’s no middle ground between “we want everyone to be happy, healthy, and be able to live comfortably as their true selves” and “these entire groups of people need to be eradicated”/
And bring it back, the “can’t we put politics aside” is a symbol of privilege. The “neutrality” or “centrism” that aligns with one’s ideals allows them to not have to worry about whether or not you’re going to be beaten to death the next time you have to go to the store, or if the police are going to stop you for just walking down the street and murder you because some facial recognition system mis-identified you because no one trained it on Black faces. Or if you’ve already had a hard time getting a job you want because of who you are, and now capitalists in that field have decided that they’re going to just bulldoze the whole thing and give the job to an LLM.
This whole thing is basically a nonstory when you realize how much money is in tech. Meta changed their name and sank billions on an idea that everyone thought was stupid from the beginning, and they’re still fine.
Putting a billion into the flavor-of-the-month that has like 10% chance to be the next big thing is a no-brainer when you’re printing multiple billions in profit doing nothing, and have a lot more cash on hand.
The real story, is how wealth inequality and monopolies have essentially allowed the rich to waste tons of money chasing more wealth while having almost no incentive to provide value to society. Who gives a fuck about hallucination and prompt injection? It’s all trivial details that VCs are giving away billions to eventually solve.
This parallels the height of GM, when they put money in everything from satellites to ATMs. Sure, at the time there was plenty of money to dump on such ventures. But eventually, those bad bets caught up to them. It seemed like a "no big deal" when a hugely profitable company wasted billions of dollars on bad investments. But each one of those bad investments represented a lost opportunity for a good investment. Eventually, the cash cow at GM ended, and the company is left with nothing but huge debts and worthless investments. Any tech company that is just buying the equivalence of lottery tickets is probably destined for failure too, no matter how profitable it is right now.
I mean, I would also call genetic algorithms a form of brute forcing. And just like with genetic algorithms, this approach is going to be severely limited by the range of values that can be updated and the ability to test the outcome.
So they configured the experiment so that only certain lines of code were able to be iterared/updated. Maybe you could ask it to start from scratch, but I imagine that would increase the time for it to converge (if it ever does).
Regarding testing, not all mathematical proofs can be verified by example. Here they were trying to prove that there was an even lower bound for the problem, but not all proofs will work with that structure.
Isn't that how we learn too? We stop doing the things that don't work in favor of things that do while repeatedly "brute forcing" ourselves (training/practice).
It’s more like educated guessing, which is a lot faster than brute forcing. They can use code to check the answers so there is ground truth to verify against. A few days of compute time for an answer to a previously unsolved math problem sounds a lot better than brute forcing.
Generate enough data for good guesses and bad guesses and you can train the thing to make better guesses.
it is what we (the people) do as well. we look at the data and try to find a pattern. but the computer can process larger amount of data than people can.that’s it.
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