It's not a good analogy cause no one sues each other for little hammer injuries. It's more like the guy who gets wacked saying 'hey what the heck man that's my distinct hammer design but you made a machine that makes almost precisely my exact hammer and I hold a patent for this'...(or something like that)
Why would ChatGPT be sued exactly? They didn’t publish the picture, they did what the user asked. The user is responsible because they directed the creation and publishing. The user is the entity who should be sued. Or dmca’d. Or whatever.
Think if the user commissioned the art from an outsourced creative shop nobody has heard of. Then they published it. They wouldn’t go after the creative shop, they would go after the publisher.
(I am just addressing publishing here, training on the artist’s works is a different, well discussed issue)
It is certainly not trademark infringement, I can say that for sure -- no reasonable person would prompt ChatGPT to create a "new yorker style cartoon" and then think the result is produced by the actual cartoonist in mere seconds for their viewing pleasure. So there's no confusion in the marketplace.
The user could cause confusion in the marketplace of course, but that would be her doing, not the app's. Surely we can all agree that suing adobe illustrator for facilitating trademark infringement of logomarks and such would be silly?
It could be copyright infringement, which should drive home how absurd copyright is as a concept. Everyone's all up in arms about Anthropic reporting a user to the police today -- imagine if the thing they were reporting was that she had written a sacred symbol in her personal notebook...
The original story is, the Disney movie’s version isn’t.
Edit: This sort of thing is common in Hollywood. For example James Bond (first book) hits public domain in ten years, but not all of the elements we associate with the movies are from there. Q and his gadgets are inventions of the movies and don’t enter public domain. There’s a reason patent/tm/copyright firms make money.
It’s their hardware and their web response. Especially more heinous if it’s being served as part of a subscription. I don’t think it’s functionally the same as me opening Microsoft Paint and recreating pixel-for-pixel a New Yorker artist’s signature.
I don't see that as a reasonable argument unless you're claiming the user was lying:
> In the comments section of her post, she wrote she had simply asked ChatGPT to make “a New Yorker-style cartoon.”
If you commissioned me to record music onto a CD for you, and then I put in the credits that Jimi Hendrix recorded the guitar parts without you asking, it seems pretty reasonable that I should get in trouble for that rather than you.
>she wrote she had simply asked ChatGPT to make “a New Yorker-style cartoon.”
A "style" can't be copyrighted, at least in US law. They might have a stronger case of trademark/likeness infringement, but the fact that the person knew it was AI generated would make that difficult. Of course they knew it wasn't made by Brendan Loper. Of course, if they then published it, the other people viewing it might not know this, but who published it?
If you asked a studio musician to play a solo in the style of Jimi Hendrix, and then the producer tried to credit the guitar solo to Jimi Hendrix, I feel like we would all recognize that this is absolutely bananas and should not be allowed.
What does the case law say on what counts as "misattribution"? If a paste the "BLOPER" signature onto a jpeg, did I commit a crime right then and there? What if I put a notice next to it saying "btw it's not actually Brendan Loper"? What if I took that image (with the notice), uploaded it for the whole world to see, then some guy cropped out the "btw it's not actually Brendan Loper"?
This reminds me of the Helen Green David Bowie Gif image (https://dollychops.tumblr.com/post/107517113745/happy-birthd... ) that got changed, tweaked, cropped, distorted and distributed by humans without attribution in all sorts of places [0] over ten years ago. I recall Mediachain (which was later acqui-hired by Spotify to help address attribution and licensing) would talk about this problem and proposing blockchain ledger approaches to help validate a media files similarity to existing content and notification to the original artist of its use. Didn’t follow them closely, but Spotify saw some value in their attribution ideas.
There's a difference between reproducing a signature in an encyclopedia or in some way that makes it clear that you are recording the thing as it is.
Putting a signature on a work is forgery and in most jurisdictions charged as fraud.
If you produce an artwork in the style of someone and then clone the signature of someone who produces art in that style, there is a reasonable case for fraud.
Yeah, the references to copyright/trademark in this thread are confusing to me. I feel like there are much more straightforward legal arguments against falsely claiming artwork is by a famous artist.
For starters people pay for ChatGPT accounts used to generate these things. Secondly people use ChatGPT to generate stuff they put up on social media slop accounts to earn money. You'd probably build a case by finding a collection of these to justify discovery for more and build your fraud case based on that kind of thing where people are generating and publishing work with your signature on it for money. That's both a criminal and civil case.
There are three things that have become very clear to me after the rise of generative AI:
1. The sheer amount of material on the internet that is "free to view but not free to use for any purpose" is the greatest resource of our time, and despite it being easy for individuals to take advantage of it (no one will take you to court for printing a newspaper comic and pinning it to your corkboard,) it's historically been difficult for corporations to exploit it (their best idea pre-AI is to encourage people to post it on social media walled-gardens where they can surround it with ads.)
2. The reason behind the impressive results of generative AI is because it exploits the above "free" resource, which is the greatest resource of our time. The reason behind the industry-wide push for AI and the insane amount of investment in it, is that they know it's their first real chance to exploit the greatest resource of our time. This is the gold rush.
3. Anthropomorphism is the wool that AI labs are pulling over legislators eyes so they can pull off this heist. If you see training and inference as a black box, a process that consumes a copyrighted work (among others) and produces something very similar to the original work that also competes directly with it, is clearly something that's against the spirit of copyright. But if you (afraid of being judged a luddite) see AI as a little man inside the computer who is "learning" and "creating," how could you deny him? Especially if it would deny your jurisdiction access to the above gold rush. A lot of scientific-sounding AI communication is propaganda for this way of thinking, like the Anthropic J-space stuff, which stops just short of claiming AI is conscious, despite leading the reader to that conclusion.
If you think Aaron Schwartz would not have fought for exactly the freedom of information that would enable AI training, you misunderstand Schwartz and the nature of information freedom.
I continue to find that people strongly advocate for justice on exactly opposing sides, depending on who they have been told to think the “bad guy” is.
> what's different is that someone lost their political career (the horror!) and you don't get charged if you have enough money
I don’t believe for a second Schwartz wouldn’t have been charged if his parents were rich. He would have been better equipped to fight it. But that’s it.
Yes, our political economy is more corrupt today. But it’s silly to project the Schwartz example onto AI companies given the former is seen as a mistake and the latter are orders of magnitude more potentially valuable. And yes, if you can swing a state’s tax coffers meaningfully that’s going to influence voters and thus prosecutors.
Voters might feel differently once they wake up and realize that it's 5% of GDP because of the anticipation that so many voters will be thrown out of work.
> once they wake up and realize that it's 5% of GDP because of the anticipation that so many voters will be thrown out of work
But it's not. The only layer anyone has a handle on is consumers and companies paying AI ridiculous sums for AI. Some of those users are probably justifying it with labour replacement. But a lot may not be. So far, we haven't seen the employment effect outside recent college graduates at enterprise companies.
> as implemented in the United States it's a malignant tumor, a theft of labor by capital, and it must be (minimally) adddressed with confiscatory taxes applied to all those involved with it's creation and operation
It's also a godsend of economic growth. Growth other countries who are trying to balance their books would kill for. Without AI, we'd be in a failure state. Maybe we are, if this is all a bubble. But as it stands, there is paper wealth that can and has–limitedly–been taxed. That gives everyone options.
> If a single AI billionaire exists in the year 2030, then the US is a failed state
This is silly and projecting a narrow view of the world onto a larger voting population. Voters don't care so much that there are billionaires as that living standards haven't kept up with the rate at which they're being minted. Double tax brackets, add more on top, raise the minimum wage, raise Social Security taxes and benefits, expand Medicare, beef up antitrust, establish a progressive property tax on wealth that starts at 1,000x the median American's wage (about $65mm) and billionaires are fine.
> consumers and companies paying AI ridiculous sums for AI.
VCs are paying ridiculous sums for AI. Consumers are not - we get tokens subsidised by VCs.
> if this is all a bubble
Interesting to see that revenue growth for both Anthropic and OpenAI has levelled off recently. Once this fact percolates through to the VCs, it's going to cause problems. All those valuations are based on projections of vastly greater revenue than they're getting now (and, ofc, achieving AGI and "winning" everything immediately that happens). This is looking less and less likely - the current batch of AIs are very, very, useful tools, but as we learn how to use them commercially they're not generating those limitless revenues that were anticipated.
This tech, like all the rest, will go through the Gartner Hype Cycle, and that includes the Trough of Despair where it all looks shit and the bubble pops. I think we're approaching that rapidly.
Many people are saying that's why there's this sudden, coordinated media push that AI is going to cause human extinction and needs regulation: because the regulation it will get, in classic regulatory capture, will serve the needs of the frontier companies and lock out any competition to them, so they can stay in business.
> It's also a godsend of economic growth. Growth other countries who are trying to balance their books would kill for. Without AI, we'd be in a failure state.
Sorry, what? You're claiming that which countries exactly are failed states because of a lack of AI? And that the US would have failed, what, in the past four years if ChatGPT hadn't released or something? That's an absolutely insane thing to claim, but I have no clue how to else to interpret what you're saying.
AI is creating a huge portion of it's value through labor replacement.
Right now it's replacing "recent college graduates", which makes sense, because they're the least differentiated white collar workers. However it's advancing quickly, and it will (quite obviously) eat more and more white collar jobs.
> It's also a godsend of economic growth.
Fuck no. There is unprecedented Capex that is propping up the economy, as companies are rushing to create capacity that they intend to use to destroy jobs. So yes, those datacenter buildouts and chip purchases and power infrastructure buildouts are creating economic activity... all with the hope that someday companies will be able to fire a huge percentage of workers.
You wrote it as though the gains were from productivity, which they really aren't... but even if they were (and that is likely to happen at some point), it would only be beneficial to actual people if that also results in greater distributions to labor. But a technology like this disfavors labor, so we can anticipate aggregation toward capital, and a slower velocity of money overall.
> Voters don't care so much that there are billionaires as that living standards haven't kept up with the rate at which they're being minted.
I suspect that voters will, at some point, care quite deeply that a lot of awful people got INSANELY rich by destroying tens of millions of lives, and making the K shaped economy have a much smaller segment of winners
The policies you suggest could help... but we have an administration (all three branches) that oppose anything of the sort. They're much more likely to simply try to deploy AI to further oppress the people whose careers they destroyed, than to try to create soft-landings or fair outcomes.
The party most supportive of mass AI deployment is a party that despises the poor, and would happily simply lock them up. This... is not a good mix.
I hope that your optimism turns out to be warranted, but I think you're a fucking idiot, defending reckless bullshit that is executed as part of the biggest heist in modern history.
> So far, we haven't seen the employment effect outside recent college graduates at enterprise companies.
Ignoring the obvious “citation needed” and taking this as accurate, wiping out entry level jobs at massive employers is a serious problem with longterm effects we likely only understand a part of at best.
We gleefully moved manufacturing overseas for decades and finally realized the extent of the cons after it was too late. We clearly needed a more balanced approach. Something tells me we’re setting ourselves up for the same mistake.
Perhaps, that still frames harassing and antagonizing "Aaron Schwartz" as a bad thing (he was a "good guy"), and then implying that said bad thing should happen to AI because it is bad, when the modern AI frontier lab is operating on the fundamental philosophy that Aaron shared which is that information is free.
> All of these people need to go to jail after what happened to Aaron Swartz
Their wealth has exceeded an escape velocity beyond which they won't be put in prison (or if they are they would quickly be pay-for-play pardoned) unless they are seen as a threat to even wealthier people.
See, for example: Devon Archer, Jason Galanis, Benjamin Delo, Arthur Hayes, Samuel Reed, Trevor Milton, Carlos Watson, Paul Walczak, Todd and Julie Chrisley, Lawrence Duran, Marian Morgan, Imaad Zuberi, Changpeng Zhao (CZ), Joseph Schwartz, et al.
Some of these people are broke bitches compared to the group of people you're talking about now, and yet still hit the threshold of being above the law as long as they play the corruption game.
Nobody seems to care about AI automating coders out of a job.
If anyone can just prompt all their basic “information needs” however how sloppy, then what remains of the economy? Health care, child care, handyman?
Most people won’t even pay for ad free YouTube. I don’t think any software business can survive AI as a substitute good even if it’s inferior (and it might not be).
same here, been automating my work for 40 years starting with a data entry job I had in 1994 as an office temp, wrote a C program to do the whole thing for me, hung out on IRC all day where I made connections to get my first dot-com job
Meanwhile housing, health care,
food, energy, and things like college all get more expensive while wages are stagnant (and falling when inflation adjusted). Now on top of that we toss a new jobs disrupting technology into the mix.
You’re making a lot of things objectively better, but none of them are the essentials that people need.
I’m not saying it’s bad to make AI bots or video games or network apps. I’m saying that the blanket statement “we make things better” is oblivious to a lot of realities.
Yes, this is why no one really feels sorry about the LLM code situation other than other coders. Believe it or not, before the current iteration of LLMs(around 2015-2020), coders were still gloating about how they were going to replace other professional jobs (law, medicine, dentists, finance, etc.) in due time, and they and researchers were going to be the only people with white-collar jobs. There is a delicious irony of how it all ended up shaking out.
Nope, because there's always been an executive to shaft said engineers out of success. But they went to business school, so I guess what's yours is theirs. I think that's biz 101.
> If anyone can just prompt all their basic “information needs” however how sloppy, then what remains of the economy? Health care, child care, handyman?
That kinda describes a lot of “not the USA” developed countries since quite some time.
IMO this doesn't really capture fully what AI is or does. It is possible to use AI to create artwork that has never been seen before and that is not derivative of an artist that already exists. I've used it myself for my own photos and drawings. It understands the basics of art like composition, lighting, the physics of things to some extent and all of this it uses in the art it creates.
The problem is that copyrighted material is intermingled with non-copyrighted material in a way where it's not obvious how to solve it. But I think in this case, AI is so powerful that we should (gasp) cut it some slack. This would be the perfect example of throwing the baby out with the bathwater if OpenAI were to be sued into oblivion.
This is one of the reasons I'm extremely unimpressed by complaints from openai and anthropic that other labs are "distilling" their models based on them... Basically: "You're training your model by running it again our own model which is itself a gargantuan copyright and content violation of a scale never seen before by humankind, HOW DARE YOU"
You may not like AI but their business model is a silly twitter-worthy dunk. This is obviously not their business model. I didn't know I could've plagiarized all this code myself the entire time!
The narrative is constantly about "when AGI arrives." We're gonna have UBI, it's gonna solve human labor, it's gonna produce better and more music, cinema, art, and literature than all of human history before it. The AI bros from Altman all the way down to the YouTube commenter say anything to keep the conversation off of the present. It's always the pie in the sky that is perennially almost here. The progress is happening "so fast." Next model update we're all gonna get luxury space communism.
AI is here. We've had a good long look at what it does and what it's used for, and it's not going to be something else. This is what it's for. It's for copyright washing other people's work (shitily). It's for astroturfing social media with product placement comments. It's for presidents to make videos of themselves dropping poop on protestors from airplanes. It's for souless "creators" to earn updoots from other bots for their "street photography" generated images of neon lights on puddles in Tokyo. It's rube goldberg automations that almost always accomplish nothing. It's fanatics claiming that it has multiplied their productivity by some incredible factor, but never showing the receipts, or when they do it's always something trivial like a calorie counter app.
This is it. This is the AI we've heard so much about. I'd say I can't wait for the hype to end, but after living through several cycles, I'm almost certain that whatever hype cycle emerges from the IT sector next will be even worse.
> If it is a hype, then one that produces lots of working code. Way faster than I can type it. And I am fast.
I covered that:
> It's fanatics claiming that it has multiplied their productivity by some incredible factor, but never showing the receipts, or when they do it's always something trivial like a calorie counter app.
There is no shortage of "working code" out there. GitHub is reportedly falling over from all the working code. Where's your business? Who's using it? Why aren't products better yet? It's a mirage. Your "working code" is the same thing as gen-AI "street photography" images. No one wants to see them, yet it's pumped out in vast enough amounts that it's choking the spaces that are ostensible for photography. The low quality, low investment nature of it excites the lazy wanna-bes who leave a trail of half-baked, soon-forgotten detritus behind them.
You’re making solid points but I do think that, at least, programming is changing to be around AI generation. Even if not much has changed in terms of visible output. AI may add some marginal GDP growth, nothing explosive. Switching from file cabinets to computers didn’t result in face melting productivity gains despite totally retooling how information flows through a business.
Steal one mp3 and you might get fined thousands, steal a book from your local shoppe and the police would come visit you. Forge a signature and you would also be in trouble. Hack a government website and you will have to answer some questions.
Steal all the books in the world, forge millions and this story begins to tell and nothing happens.
The part of the AI generating the mashup doesn’t really understand what the signature means, or how it may be interpreted, it’s just a visual part of a New Yorker cartoon. Elsewhere in ChatGPT there is plenty of information about signatures and what they mean, and what plagiarism is.
It’s not organized like a human brain, it shouldn’t be surprising that unusual results occur. They are approximating human intelligence from a different angle. It’s interesting to see the improvements in areas like this that require introspection that isn’t fully wired up yet.
[edit] I should add that a human making a New Yorker cartoon is extremely iterative and introspective. Current generative AI is meant to push it out, and you can do the iteration and introspection yourself.
> It’s not organized like a human brain, it shouldn’t be surprising that unusual results occur. They are approximating human intelligence from a different angle. It’s interesting to see the improvements in areas like this that require introspection that isn’t fully wired up yet.
AI boosters take note: this sort of thing is exactly what skeptics have in mind when they insist that you are nowhere near "AGI" and have not meaningfully passed Turing tests and your claims of goalpost-shifting are fake. You have been aiming at straw goalposts.
I have used a simple feedback loop to generate AI art: 1) the initial prompt 2) ask for criticism of the generated image 3) apply those changes and generate another image 4) repeat the criticism / fix cycle again
Literally, no. Introspection is an internal self-driven process. And typically both the creating and criticisms draw from the general distribution of information, there’s still “nothing” to do the introspecting.
Sure, my point is not that you can’t wire up introspection, just that it’s not currently an extensive part of image generation. I expect that to change over time as better quality is demanded.
This has been a perennial problem with my own generated comics with both Nano Banana Pro and ChatGPT (all generations). I often have to put in an extra edit to erase the false signature. It is annoying and I'm unsurprised most users don't bother.
Despite what all the clickwrap warnings and "AI can make mistakes" subtitles might lead you to believe, the service offering of AI is explicitly designed to be as "one and done" as possible. The inherent nature of these tools is to service laziness, and disincentivize too much scrutiny.
> I often have to put in an extra edit to erase the false signature.
Given that they can reliably do this, I'd think it should be trivial for the harness to automatically insert a "review the image for anything that looks like an artist's signature or other blatant indicator of plagiarism, and fix it" pass.
Yes, but that could double the cost by default! Which is probably why they don't. On reflection, coding bots do implement something like this with the verification tic they seem to have.
And then people wonder why the default mood of AI is so pessimistic. It's just revealing all of society's broken windows and adding a few more in the process.
>Even if you posted on Twitter or something, nobody is coming after you.
Are you sure about that one? Are you saying if you posted say, a racist cartoon on twitter, and you forge my signature onto the thing, I can't come after you?
I don't know about the US but here in Germany the category for this is personality rights. The entire point of a signature is to establish authenticity, using someone's likeness or identity without consent will get you into deep trouble even without money being exchanged.
>I'm certain if I drew a cartoon and used the signature that looks just like a real cartoonists', I would get sued and liable for the damage.
Would you? Always? Suppose I hate Obama drone striking people, so I made a satirical cartoon of him signing an executive order to "bomb brown people" or whatever, affixing his signature[1] to that image. Would that get me in trouble, even if the image was clearly satirical? What if someone takes that, then passes it as non-satire, either intentionally or unintentionally?
That's the whole point of hypotheticals? If we're just discussing the common case, the conclusion is so obvious that no serious analysis happens and everything becomes vibes based. "Is torrenting fine?" would have been met with something along the lines of "yes, copyright is just an artificial monopoly created by the government and harms innovation", "information should be free", etc. Now people have done a 180 because it's evil corporations doing it so the vibes have totally reversed. They may have a point about the vibes of evil corporations training AI models then selling back the models for $$$, but vibes is no way to run a legal system.
There's nothing illegal unless someone seriously thinks Obama signed it. The easiest example would be his signature on his wikipedia page. Clearly he didn't sign that page, nor (probably) did he authorize it.
I don't understand your argument. Wikipedia and a satirical cartoon are both things clearly not made by Obama, nobody in their right mind would be "fooled" by the presence of his signature.
These cartoons are intentionally drawn in the style of a cartoonist and feature their signature. The goal is forgery. The whole point of these AI-generated images is to look like the real thing.
>These cartoons are intentionally drawn in the style of a cartoonist and feature their signature. The goal is forgery. The whole point of these AI-generated images is to look like the real thing.
You can't seriously claim that the very person who prompted the AI image generator thinks the image it spit out was created by Brendan Loper?
Who knows what happened, kids sometimes become suicidal... and 1% of the population that are psychopaths are on occasion documented killing people over $5 because they uniquely don't value most living things except themselves.
What is weird was how fast things were buried, and the family's concerns were never properly addressed. =3
> The New York Times article cites Stanford University law professor Mark Lemley, who disagreed that generative AI services violate copyright law, and intellectual property attorney Bradley Hulbert, who said a new law might be necessary to settle the question of legality.
> Months after Balaji's death, which attracted significant public attention, Hulbert told Fortune magazine that Balaji's essay "[reads like] the argument of a really smart non-lawyer who read up on the subject but does not have a thorough understanding".
If there's some kind of industrial-scale intimidation campaign that's stopping IP lawyers from litigating the case of their lifetime, that's an even bigger story than OpenAI taking out a hit on somebody. It seems like they're agreeing that the copyright abuse was never hidden, and it's sufficiently transformative enough that nobody could argue it's illegal.
That seems to suggest that Disney's lawyers agree. You can use AI to violate copyright laws no different from a text editor or Bittorrent, but training it on copyright material isn't inherently illegal.
> training it on copyright material isn't inherently illegal
Unless folks spider sites that clearly state the terms of use prohibit such actions, violate GPL licenses, and scrape private conversations or markup input.
Also, fair-use loopholes that protect academics don't always apply in a commercial context. The encoding of the data in a proximity vector search space is irrelevant. =3
Fair-use doesn't specifically protect "academics" at all. It does apply consistently in a commercial context, even to the GPL, which is the clear intent of it in-law.
That's why companies hire lawyers. The lawyers seemingly agree on the legality in American law, which is why we aren't seeing any vindication of Suchir's protest.
Engineering manager at my company put a comic at the end of our sprint demo that was signed bloper. Except it wasn’t funny at all, and kind of weird. I asked him, sure enough it was ChatGPT and he didn’t notice the signature.
Nice. This demolishes the "LLMs can reason" (but not enough to avoid this sort of basic error) and "humans make mistakes too" (not like this) talking points from the LLM promoters.
A human wouldn't mindlessly reproduce the signature due to "not reasoning" and being intellectually lazy while doing the drawing. For the human, including the signature is more effort than omitting it; for the generative system, it appears the opposite is true. The point is to highlight that difference.
This is completely silly. If you don’t think LLMs can reason, you’ve either never used them to do tasks that require reasoning, or you don’t understand enough to recognize what’s involved in the responses you get.
In this case it’s clearly the latter, because you’re confusing image generation models with LLMs. There are very big differences between the two. No-one is claiming that image generation models are capable of reasoning.
What's the argument here? An airplane, a bee and a bird all fly despite doing it totally differently. LLMs also reason despite being made out of matmuls instead of meat.
The most common argument for this is some core unexamined axiom that only humans can reason by definition, and then working backwards to a justification for that.
Not only unexamined, but ineffable. I've yet to see anyone give a good definition of what they think "reasoning" is that applies to humans solving complex logical problems but not to machines.
(I suppose a religious or otherwise superstitious person might introduce the soul into this, but I haven't come across anyone actually willing to defend that hill.)
This is just a trick of language. There's no rule that says a priori whether an English word created before the invention of machines mimicking the behaviour, should describe the mimicry. There's no contradiction between "an airplane can 'fly'" and "a computer cannot 'reason'" because there is no reason why the two claims should relate whatsoever.
Well, but we do we have these words, and they are useful. An airplane and a bird both travel through the air. A human and an LLM both make logical deductions.
You can just look at the definitions and see whether they apply.
The relevant MW definition for "reasoning" is: "the use of reason, especially: the drawing of inferences or conclusions through the use of reason."
And "reason" is: "the power of comprehending, inferring, or thinking especially in orderly rational ways."
Functionally speaking, i.e. in terms of observable behavior, LLMs exhibit comprehension, inferring, and reasoning. If someone wants to object to that, they'd need to explain what relevant property prevents a conclusion drawn by an LLM from being counted as involving reasoning.
What do you think they are doing, and do you think machines can reason (in general, not necessarily current systems)? If they can't, how do you explain humans being able to reason given that we are physical machines too?
I've spent a long long time thinking about the problem of reasoning and consciousness, and it's not nearly as simple as your confidence and feeling of intellectual superiority would indicate you think it is.
First, you'd obviously have to define what you even mean by reasoning, precisely. Let's hear it.
Then demonstrate that LLMs do not corresponds to that description. You are making absolute statements ("They are not reasoning", "It does nothing of the sort.", "FFS lmao"), and basing your insults on this premise ("Ai Psychosis", "Know the difference."), so surely you have an extraordinarily solid ground to support that - rather than just speculation, innuendo, and a lot of confidence.
P.S. I don't see why you're equaling "reasoning" with "behaving like a human".
P.P.S. We don't even know if LLMs are conscious (in any way, shape or form, however foreign). We simply do not know. They might. Minds far smarter than you and me tried to answer this question, and they couldn't prove nor disprove it. So feel free to speculate, but anytime anybody makes absolute statements regarding this, they are either overconfident, underinformed, or both.
The thing about a generative language model that’s trained from a massive but unknown corpus is, it’s practically (if not theoretically) impossible to evaluate the extent to which data leakage contributes to any particular output.
But I would argue that, as things currently stand, “sophisticated engine for approximately querying a pastiche of the results of human reasoning that comprise its training corpus” remains a more parsimonious explanation than “it’s doing actual reasoning” for how this neural network architecture produces the phenomena we’ve been observing.
>sophisticated engine for approximately querying a pastiche of the results of human reasoning that comprise its training corpus
Well if the thing can find and fix bugs in something that is using non-mainstream stuff that is surely not in it's training dataset, that's better than a rubber duck already. Whether it has soul is a different question of course.
Don’t even bother. These people almost always have some goofy ass, non standard, fluid definition of “thinking” or “reasoning” that cannot ever be met.
My opinion of their reasoning capability is based in part on (proprietary, non-published, only internally peer reviewed) experiments on GPT-series models’ ability to perform a suite of formal and informal inference and deduction tasks.
Perhaps you could argue that “appropriately applies syllogism to arrive at correct conclusions” is too high a bar to set, but I don’t think it would be fair to call it a “goofy-ass”, “non-standard” or “fluid” element of a reasoning capacity assessment.
But you're not just saying they are insufficiently good at reasoning, you're saying they're (probably) not "doing actual reasoning". So we need to know how you are defining "actual reasoning".
I don't think the bar for an actual reasoner can possibly be 'always appropriately applies syllogism to arrive at correct conclusions', because in that case nobody in the world is an actual reasoner. And if your bar were 'sometimes appropriately applies syllogism to arrive at correct conclusions', it's hard to understand why the current generation of AIs doesn't meet it; they are clearly capable of doing so, at least to all outward appearances. (Maybe you think their apparently successful demonstrations of reasoning are illusions, but again, you would need to define what counts as "actual reasoning" vs. a superficially convincing simulation of it.)
It’s hard to say. But supposedly the counter example wasn’t found by an agent running in full auto; it came out of a bunch of back and forth with a human operator. Without, in addition to the aforementioned access to currently non-public information about these models, a detailed transcript of the chat sessions leading up to the discovery, it’s hard to ascribe the reasoning steps involved to any source in particular.
Part of my concern here is that simply pointing out that LLMs appear to be performing tasks that can be done through reasoning, and using that in and of itself as evidence of reasoning, is affirming the consequent.
this is trivial to reproduce ever since early stable diffusion models, it's not really an oai exclusive issue.
for example if you ask any of these models (just about any image-gen) to produce Japanese ukiyo-e art they will almost always produce it with a hanko[0] that has been seen a lot in historical art pieces, usually having nothing to do with the era or style of the replica but seen so often in 'Japanese artwork' that it's just permanently tokenized into it as a defining characteristic.
Of course it does this. The training data is full of examples that associate e.g. "New Yorker-style cartoon" with Loper's signature in the corner, because Loper's signature is in the corner of a lot of them. There's nothing to make it treat the signature as anything special by default; that would have to be trained in explicitly.
One would hope that the person prompting ChatGPT would notice this sort of thing and do something about it before sharing it publicly, out of a genuine desire not to cause confusion etc. But I guess that's way more personal responsibility than we can expect average people to take on nowadays.
I'm not trying to assign blame. I'm only saying that the result is completely expected.
In practical terms, the legal system probably isn't built to withstand blaming the user. I'd like to advocate that everyone who can do something should try to do their part, though.
> A technology being flawed does not absolve its users of responsibility.
It may not absolve the users of responsibility that they actually have, but that doesn't change that the entity making and selling the technology is to blame for its flaws, not the user.
This reminds me my early attempts to use GitHub Copilot when it just straight added some guy's name in a javadoc copyright note in the code it generated.
New Yorker cartoonists could have grounds for a “right of publicity” case, a body of state-based law that protects individuals from the unauthorized use of their name or identity. For that, there would need to be proof that the AI-generated cartoons were used for a commercial purpose, not just as a joke or gag.
I would have thought the fact OpenAI is commercially selling these forgeries (in exchange for subscription payments) would make that fairly straightforward to prove.
> “It’s like somebody attributed a quote to me that I didn’t say.”
> Katzenstein considers the reproduction of his signature by ChatGPT to be more than just a violation of intellectual property; to him, it’s closer to false impersonation. “[ChatGPT] is attaching my name to work that I do not endorse or like. It’s slop, and unlike the other slop that I’ve encountered, this is slop that’s pretending to be me.”
> “I’ve had people hack my credit card,” said Joe Dator, a New Yorker contributor for the past 20 years. “That feels like less of a violation than this. When they hacked my credit card, they didn’t dress up like me.”
So this has morphed from plagiarism and copyright infringement (bad) to impersonation (also bad, arguably worse, and maybe more provable in court). It’s chilling to think of the implications of having one’s signature attached to a document or to words that are not one’s own.
And I think maybe it's time for that. People need to learn that there's real, expensive legal liability for doing stuff like this. And AI companies the same.
I am very much not an advocate of "sue everybody for everything". This is major enough that it clears my threshold.
It seems like all the criticisms of Gen AI and LLM seems to concentrate on OpenAI and their products over products from anthropic and others.
I am pretty sure that this faking of signature can be done by Gemini, claude as easily as chatgpt.
Whatever the original intention, this is clearly a bug and should be fixed. But should ChatGPT sign its cartoons with its own name or leave them unsigned?
I think what you're seeing is the probability of a particular signature or style of signature appearing on a particular style of cartoon, not an intent to sign.
This. It's also while you'll sometimes get a mangled Getty Images watermark on some image generations, or a logo in the bottom left corner. If it's a prominent feature in the training dataset it'll show up, exactly how these models are supposed to work.
The 'bug' here is whatever post-processing step or system prompt is in place to steer the model away from doing this.
No one should be allowed to claim they drew something when they didn’t draw any part of it and LLM’s are not people/can’t work without a person. We don’t credit pens and paintbrushes after all.
One could argue nobody should be allowed to claim it. It just exists.
Even if the person can't claim the copyright of the image produced they ARE responsible for the use of their tools and what they do with the output.
In this case, they released an image with someone else's signature on it. That is wrong, the person should take the blame for that.
The person releasing the image may take it up with the AI service that their tooling led them into making such a mistake. But good luck with that in court...
i’m not saying it’s airtight, this is a pretty unbaked idea. But I think it pretty clearly has some legs to stand on. Can’t be any worse of an argument than somebody prompting an AI for a (facsimile of a) photograph and going “I made a photo.” And mind you I’ve heard people argue that that absolutely constitutes taking a photograph (which I wholly disagree with) here on HN.
Somebody “made something.” But just because you do something doesn’t mean you get to claim whole ownership of it and get to sign it with your name. Plenty of examples in life.
Why is it a bug? If other parts of the generated illustration are similarly taken from an artist, why not the signature as well? Why is a signature crossing the line but the rest of the image isn't?
For the same reason I'm allowed to draw, paint, or write things very similar to what others have drawn, painted, or written but I have to sign my own name not theirs.
You are a person, LLMs are not. You know this, which is why you know that if you signed someone else's name it would be forgery, but when you see the machine do it you call it a bug.
If the machine is like you, the machine is a forger. The machine is not like you, it is simply blending the work of others to order. Adding someone else's signature is simply part of that statistical process.
I don't even believe too much in Intellectual Property but the signature amounts to a false representation, rather than a resemblance. The pixels are not special in the image file, but they're special when we look at them. This behavior should be trained out of the model.
I've seen photorealistic generations add (distorted but still somewhat recognisable) watermarks too, because that's what the training data had.
Everything is a derivative work, and always has been. AI is just making that salient fact so much more visible, and now everyone who believes in the delusion of Imaginary Property is scared at that truth revealing itself.
Incidentally, this is also what young humans learning to draw will do. They start by copying what they've seen.
AI companies have created the best pirating tool known to man. And the president is complicit with senate / house lawmakers in his party refusing to take action to reign them in.
I follow anti-LLM discourse quite a lot, and across the main bulletpoints: energy/carbon emissions, content worker harm, job displacement, deskilling, mental health effects, and copyright/plagiarism, the plagiarism one seems to have the most attention, and it's also the most solvable, if there were only more serious effort on ethically sourced models that can actually do the real science / math / code work that is what LLMs are best at. The whole world of LLMs to create videos/books/art/literature is where most of the offense is (the video/imagery side of it is where most of the energy/carbon emissions problems are too. and content worker harm).
I really wish there'd be a split among these disciplines (science/math/code vs. videos/art/literature) - one is vastly more problematic than the other.
Yep. I’d probably be a lot less chastised in some circles for using Claude Code at work if it wasn’t misconstrued as being in support of, I don’t know, encroaching on the hypothetical commissions of a chronically online instagram furry artist or something.
It is very tiring to say “I don’t necessarily disagree with you about AI ‘art’, but in my field—which you do not understand, and in which the underlying build process is often not the creative output—AI presents very real productivity gains” for the umpteenth time.
I am skeptical of there being sufficient data to build “ethical” training datasets, and I’m confident that much of the same contingent will (somewhat rightfully) argue that ‘second-generation’ copyrighted AI material has already irreversibly made its way into every modern dataset.
A reasonable next move, if the US was interested in acting like a democracy, would be legislation forcing this decision:
- prove that you had the rights for all of your training data
- open source the model
Give the labs a 3 month grace period in which to comply, so competition can persist even with dubiously sourced data, but the people can't be locked away from derivatives of their contributions for any significant amount of time.
> It is very tiring to say “I don’t necessarily disagree with you about AI ‘art’, but in my field—which you do not understand, and in which the underlying build process is often not the creative output—AI presents very real productivity gains” for the umpteenth time.
That’s not a justification. If a company were poisoning the water to your home as a byproduct, would you be satisfied if they told you “we don’t necessarily disagree with you about polluting the water, but in our field—which you do not understand, and in which the underlying build process is often not the water pollution—what we’re doing presents very real productivity gains”?
> I am skeptical of there being sufficient data to build “ethical” training datasets
Then you don’t build any. What fucked up world we live in where people think it’s OK to be unethical because they want something and can’t think of any other way to do it. What monumentally selfish rotten babies.
> has already irreversibly made its way into every modern dataset
The "gray goo" scenario finally happens... for AI. That's actually the good ending for humanity. I love it! Poetic and believable. Data doesn't "heal" like nature. :D
I think you can train on math /science using synthetic generation to a significant extent. Training for coding requires more of the "scraping github / stackoverflow" angle but IMO that's a shallower hill to climb than scraping copyrighted art and literature.
There are actual models trained on ethical datasets but they are obviously not very high powered. If companies with the resources of an anthropic or openai were doing it (ha) it would be more feasible
>“I don’t necessarily disagree with you about AI ‘art’, but in my field—which you do not understand, and in which the underlying build process is often not the creative output—AI presents very real productivity gains”
Being able to prove such gains in better products would be a start. And an emphasis on how it assists existing engineers/mathmaticians/researchers, not that any accomplishment made with AI assistance is "AI solves problem".
I don't know whatever happened to "words are cheap". I guess it literally made money to say words, so that adage is false for the time being.
>I am skeptical of there being sufficient data to build “ethical” training datasets
Well if all those scam job ads paying 100/hr to create AI training content was not a scam and instead the approach from the start, there may have been a chance to bridge that gap ethically. The industry chose to break things and is trying to act mad that people are mad at all the broken stuff.
These results are entirely a consequences of the actions chosen. And I don't believe there was ever an honest consideration of there being ethical training datasets. They just thought they could brute force society with fearmongering and bribes. The BOTD was already low in the beginning but completely gone now.
2. Acquire rights/licenses to any datasets that do not fit #1. e.g. the Google deal with Reddit for 60m/yr.
3. Offer programs to have creatives willingly submit their data, with some sort of residual output based on the number of times their assets are sampled.
4. If all that is still not enough, hire creatives to create assets for you. This is something Spotify did recently with "ghost artists"[0]. The intentions here are suspect, but a non-consumer facing artist providing work for an LLM wouldn't have the same ethical dilemmas
5. Lastly, if all that still isn't enough: governmental programs to either provide grants, subsidies, or more outreach to get the ball rolling.
Would this cost tens, hundreds of billions of dollars? Yes. But clearly, that was not a barrier to entry for the industry anyway. So we can chalk this down to the personality of leadership or the wider culture of modern big tech
I agree with most of your post, but I don't think I agree that method 2 (Reddit deal) is necessarily ethical. I know it's too high of a bar for our nation to ever clear, but I think explicit author opt-in is the only ethical source of AI training data.
Like, legally, I'm sure Reddit had the right to sell it, but probably over half their content was written before ChatGPT was ever announced. The TOS allowing reddit to make "derivative works" was largely understood to mean things like cropping photos, using your viral post in an ad, or maybe auto-translating your comment.
I don't really see the difference, code is protected by copyright (or copyleft) as much as art is, and yet the LLM scrapers use it without scruples. Same goes for math and science publications.
Artists take pride in the intentionality of every brushstroke, and for them any given work is much more likely to reach a point where it's considered "finished".
While coders may care about the craft (and I do), it's not as if the value of my code is in the exact variable names I chose.
In my experience, the science/math/code crowd don't care about copyright/plagiarism as much as the video/art/literature crowd, so the first crowd turns a blind eye to most of the latter crowd talks about.
Code can be art, and copyright/plagiarism is real. It sort of boils down to how much it bothers us.
I don't think it is likely that they could get enough data without stealing. It would be incredibly costly to have to pay artists to church out art just to train an AI.
> I really wish there'd be a split among these disciplines (science/math/code vs. videos/art/literature) - one is vastly more problematic than the other.
I disagree that they can be separated. Practically, I think they can't. Because the mere invention of new tools inspires even more AI advancement and that in turn will cause the other side (artistic side) to degenerate even more.
I'm anti-LLM all the way, 100%, no exceptions. Zero tolerance.
So you recognize that discovery cannot be cut off from other discovery, that it's never just one or the other, and your solution is to say shut down all discovery?
you can distinguish between the LLMs you have zero tolerance for and a system like Google Translate? You have a sharp line you can draw for when something becomes "an LLM"?
i think math is close to art (just to be a contrarian, but kind of really)
its somewhat funny that math people are in a conundrum as to support or not support but this might partially be because some wish to believe that math itself is and can be useful and therefore accelerating is good
but the art people have no such delusions so they’re just strictly against
imo proof writing is more akin to art than coding/tech but…
While that is true, theoretically a regulation could be enacted that output tokens must focus on STEM research and other practical tasks and the LLM must refuse tasks outside of those areas, just as Claude disallowed cybersecurity tasks. Obviously this would never happen, but the theft of the training data wouldn’t matter as much if the usecases were less sinister.
openai and anthropic trained on actually stolen data since it was pirated datasets.
google OTOH already had a lot of this dataset in their possession (e.g. Google Books etc), still questionably licensed for how they used it, but not quite as bad. They did apparently break through NYT paywalls and stuff like that though, still theft.
Man, forget the debate about AI being dangerous. The real reason all these companies need to be shut down is copy right infringement. None of this is "fair use." Does fair use imply doing things that actively harm the creators of works? Because training models to be able to replicate works only makes their skills less valuable...
Honestly, you all kind of mind fuck me that you're not more pissed off about AI basically replicating a large portion of your skills. This effects so many professions now and it's only going to get worse. I would expect a far greater outcry from software engineers trying to organise to ban this shit. But its like none of you even care?
This is a pretty solid argument against people who argue that LLMs are more than just (very massive) next token predictors.
If there was any thought or underlying thought going on here not putting a signature (at least a real one) would be the right move, despite it being less likely. It would realize, while generating the pixels that eventually became a signature, that it shouldn't do that.
> This is a pretty solid argument against people who argue that LLMs are more than just (very massive) next token predictors.
This quote is a pretty solid argument that you need to understand the technology you’re trying to criticize better. This issue has nothing to do with LLMs. LLMs are not image generation models.
A LLM, at least, prompted and served this image. LLMs can ingest images. They actually can generate them as well but that probably wasn't done here.
In the course of the conversation a with chatgpt, this image was generated and served by an LLM. It clearly shouldn't have been by any sort of reasoning.
If you do not want to be called a duck, it would help if you stopped quacking like one. Maybe you aren't a duck, but you aren't helping your case with stories like this about how AI generates images.
It would help if you stated what your own (clearly incorrect) beliefs are in this area, so we can help correct them.
The point is that working with natural language tokens is very different than tokens that represent an image.
A simple relevant example is that if you ask an LLM to write a psychological thriller about a poor former student who commits murder and deals with intense moral guilt, in classic Golden Age Russian literature style, it is unlikely to sign it with "Fyodor Dostoyevsky."
It does that when generating images because, at a high level, image generation doesn't benefit from the kind of reasoning that language generation is able to.
>It would help if you stated what your own (clearly incorrect) beliefs are in this area, so we can help correct them.
Sure, let's re-examine what this chain is doing
1. "This is a pretty solid argument against people who argue that LLMs are more than just (very massive) next token predictors."
2. (you) "This issue has nothing to do with LLMs."
3. (me) "yes, it does"
4. (you) "an LLM does not generate images"
5. (me) "this is an LLM generating images"
6. (you) "an LLM does not understand what a 'signature' is"
So we are getting lost in minutae to asset that..."LLMs aren't much more than just (very massive) next token predictors.", agreeing with what the original comment is claiming.
There's a bit of meta-commentary seemingly missing from your context here. so I'll mention it. Some people are trying to claim that LLM's are "reasoning" with data, and that the way they "learn" isn't actually too different from human learning. Aspects of an LLM like this, being unable to reason about with the image it generated, are disproving such notions as of 2026. That is all the top comment in this chain is saying.
LLMs do not generate images. LLMs prompt distinct, separately trained image models to generate images. The LLM has no ability to introspect the image model and cannot provide feedback during the image generation process. If the image model misinterprets the LLM's prompt (which can happen!) or inserts unexpected content, the LLM may become "aware" of that during subsequent chat steps as it ingests the generated image, but it cannot avert their generation.
I have a screenshot from 2024 when I asked ChatGPT to write me a draft of a story about a young boy who lost his parents and got send to a wizardry school. I specifically asked for the story to be original and not based on anything that has been already published.
As you probably suspect, chat gave me a full synopsis of Harry Potter.
I kept asking if that's an original idea, and it kept swearing on it's mothers grave, that the story has never been published before.
I appreciate your personal answer, nonetheless! It's clear which side of that dichotomy you land on, for better or worse.
This is not a binary, you are boxing in a person you had no detailed conversation with
Think if the user commissioned the art from an outsourced creative shop nobody has heard of. Then they published it. They wouldn’t go after the creative shop, they would go after the publisher.
(I am just addressing publishing here, training on the artist’s works is a different, well discussed issue)
OpenAI give lip service to the idea of not producing others' intellectual property - go ask it to explicitly make a picture of the genie from Aladdin.
The user could cause confusion in the marketplace of course, but that would be her doing, not the app's. Surely we can all agree that suing adobe illustrator for facilitating trademark infringement of logomarks and such would be silly?
It could be copyright infringement, which should drive home how absurd copyright is as a concept. Everyone's all up in arms about Anthropic reporting a user to the police today -- imagine if the thing they were reporting was that she had written a sacred symbol in her personal notebook...
Edit: This sort of thing is common in Hollywood. For example James Bond (first book) hits public domain in ten years, but not all of the elements we associate with the movies are from there. Q and his gadgets are inventions of the movies and don’t enter public domain. There’s a reason patent/tm/copyright firms make money.
> In the comments section of her post, she wrote she had simply asked ChatGPT to make “a New Yorker-style cartoon.”
If you commissioned me to record music onto a CD for you, and then I put in the credits that Jimi Hendrix recorded the guitar parts without you asking, it seems pretty reasonable that I should get in trouble for that rather than you.
Article said
>she wrote she had simply asked ChatGPT to make “a New Yorker-style cartoon.”
A "style" can't be copyrighted, at least in US law. They might have a stronger case of trademark/likeness infringement, but the fact that the person knew it was AI generated would make that difficult. Of course they knew it wasn't made by Brendan Loper. Of course, if they then published it, the other people viewing it might not know this, but who published it?
https://commons.wikimedia.org/wiki/Commons:When_to_use_the_P...
What does the case law say on what counts as "misattribution"? If a paste the "BLOPER" signature onto a jpeg, did I commit a crime right then and there? What if I put a notice next to it saying "btw it's not actually Brendan Loper"? What if I took that image (with the notice), uploaded it for the whole world to see, then some guy cropped out the "btw it's not actually Brendan Loper"?
[0]. https://www.newsweek.com/2016/09/16/digital-images-photos-gi...
> it may be reproduced, as long as the reproduction cannot be mistaken for an authentic signature.
Which seems applicable in this case, because the image is clearly generated by AI (at least to the guy who prompted it).
Putting a signature on a work is forgery and in most jurisdictions charged as fraud.
If you produce an artwork in the style of someone and then clone the signature of someone who produces art in that style, there is a reasonable case for fraud.
We can all try really hard to pretend that's not the business model, but that's totally the business model.
1. The sheer amount of material on the internet that is "free to view but not free to use for any purpose" is the greatest resource of our time, and despite it being easy for individuals to take advantage of it (no one will take you to court for printing a newspaper comic and pinning it to your corkboard,) it's historically been difficult for corporations to exploit it (their best idea pre-AI is to encourage people to post it on social media walled-gardens where they can surround it with ads.)
2. The reason behind the impressive results of generative AI is because it exploits the above "free" resource, which is the greatest resource of our time. The reason behind the industry-wide push for AI and the insane amount of investment in it, is that they know it's their first real chance to exploit the greatest resource of our time. This is the gold rush.
3. Anthropomorphism is the wool that AI labs are pulling over legislators eyes so they can pull off this heist. If you see training and inference as a black box, a process that consumes a copyrighted work (among others) and produces something very similar to the original work that also competes directly with it, is clearly something that's against the spirit of copyright. But if you (afraid of being judged a luddite) see AI as a little man inside the computer who is "learning" and "creating," how could you deny him? Especially if it would deny your jurisdiction access to the above gold rush. A lot of scientific-sounding AI communication is propaganda for this way of thinking, like the Anthropic J-space stuff, which stops just short of claiming AI is conscious, despite leading the reader to that conclusion.
1. https://storage.courtlistener.com/recap/gov.uscourts.nysd.64...
I continue to find that people strongly advocate for justice on exactly opposing sides, depending on who they have been told to think the “bad guy” is.
The same orgs that harassed and antagonized Aaron Schwartz are not going after AI for the same thing at a much much larger scale.
What's different? The size of their bank accounts.
One, time went on. The prosecution of Schwartz was seen as an overreach, as demonstrated by Ortiz’s failed political career thereafter.
Two, Schwartz’s charges were only ever charged. No jury or judge signed off on them.
Three, context changed. Schwartz wasn’t 5% of GDP. For better or for worse, that matters to voters.
I don’t believe for a second Schwartz wouldn’t have been charged if his parents were rich. He would have been better equipped to fight it. But that’s it.
Yes, our political economy is more corrupt today. But it’s silly to project the Schwartz example onto AI companies given the former is seen as a mistake and the latter are orders of magnitude more potentially valuable. And yes, if you can swing a state’s tax coffers meaningfully that’s going to influence voters and thus prosecutors.
But it's not. The only layer anyone has a handle on is consumers and companies paying AI ridiculous sums for AI. Some of those users are probably justifying it with labour replacement. But a lot may not be. So far, we haven't seen the employment effect outside recent college graduates at enterprise companies.
> as implemented in the United States it's a malignant tumor, a theft of labor by capital, and it must be (minimally) adddressed with confiscatory taxes applied to all those involved with it's creation and operation
It's also a godsend of economic growth. Growth other countries who are trying to balance their books would kill for. Without AI, we'd be in a failure state. Maybe we are, if this is all a bubble. But as it stands, there is paper wealth that can and has–limitedly–been taxed. That gives everyone options.
> If a single AI billionaire exists in the year 2030, then the US is a failed state
This is silly and projecting a narrow view of the world onto a larger voting population. Voters don't care so much that there are billionaires as that living standards haven't kept up with the rate at which they're being minted. Double tax brackets, add more on top, raise the minimum wage, raise Social Security taxes and benefits, expand Medicare, beef up antitrust, establish a progressive property tax on wealth that starts at 1,000x the median American's wage (about $65mm) and billionaires are fine.
VCs are paying ridiculous sums for AI. Consumers are not - we get tokens subsidised by VCs.
> if this is all a bubble
Interesting to see that revenue growth for both Anthropic and OpenAI has levelled off recently. Once this fact percolates through to the VCs, it's going to cause problems. All those valuations are based on projections of vastly greater revenue than they're getting now (and, ofc, achieving AGI and "winning" everything immediately that happens). This is looking less and less likely - the current batch of AIs are very, very, useful tools, but as we learn how to use them commercially they're not generating those limitless revenues that were anticipated.
This tech, like all the rest, will go through the Gartner Hype Cycle, and that includes the Trough of Despair where it all looks shit and the bubble pops. I think we're approaching that rapidly.
Sorry, what? You're claiming that which countries exactly are failed states because of a lack of AI? And that the US would have failed, what, in the past four years if ChatGPT hadn't released or something? That's an absolutely insane thing to claim, but I have no clue how to else to interpret what you're saying.
Right now it's replacing "recent college graduates", which makes sense, because they're the least differentiated white collar workers. However it's advancing quickly, and it will (quite obviously) eat more and more white collar jobs.
> It's also a godsend of economic growth.
Fuck no. There is unprecedented Capex that is propping up the economy, as companies are rushing to create capacity that they intend to use to destroy jobs. So yes, those datacenter buildouts and chip purchases and power infrastructure buildouts are creating economic activity... all with the hope that someday companies will be able to fire a huge percentage of workers.
You wrote it as though the gains were from productivity, which they really aren't... but even if they were (and that is likely to happen at some point), it would only be beneficial to actual people if that also results in greater distributions to labor. But a technology like this disfavors labor, so we can anticipate aggregation toward capital, and a slower velocity of money overall.
> Voters don't care so much that there are billionaires as that living standards haven't kept up with the rate at which they're being minted.
I suspect that voters will, at some point, care quite deeply that a lot of awful people got INSANELY rich by destroying tens of millions of lives, and making the K shaped economy have a much smaller segment of winners
The policies you suggest could help... but we have an administration (all three branches) that oppose anything of the sort. They're much more likely to simply try to deploy AI to further oppress the people whose careers they destroyed, than to try to create soft-landings or fair outcomes.
The party most supportive of mass AI deployment is a party that despises the poor, and would happily simply lock them up. This... is not a good mix.
I hope that your optimism turns out to be warranted, but I think you're a fucking idiot, defending reckless bullshit that is executed as part of the biggest heist in modern history.
Ignoring the obvious “citation needed” and taking this as accurate, wiping out entry level jobs at massive employers is a serious problem with longterm effects we likely only understand a part of at best.
We gleefully moved manufacturing overseas for decades and finally realized the extent of the cons after it was too late. We clearly needed a more balanced approach. Something tells me we’re setting ourselves up for the same mistake.
Compute, however, clearly is not.
Their wealth has exceeded an escape velocity beyond which they won't be put in prison (or if they are they would quickly be pay-for-play pardoned) unless they are seen as a threat to even wealthier people.
See, for example: Devon Archer, Jason Galanis, Benjamin Delo, Arthur Hayes, Samuel Reed, Trevor Milton, Carlos Watson, Paul Walczak, Todd and Julie Chrisley, Lawrence Duran, Marian Morgan, Imaad Zuberi, Changpeng Zhao (CZ), Joseph Schwartz, et al.
Some of these people are broke bitches compared to the group of people you're talking about now, and yet still hit the threshold of being above the law as long as they play the corruption game.
If anyone can just prompt all their basic “information needs” however how sloppy, then what remains of the economy? Health care, child care, handyman?
Most people won’t even pay for ad free YouTube. I don’t think any software business can survive AI as a substitute good even if it’s inferior (and it might not be).
somehow I still keep having work to do!
Have people ever really broadly cared about the IT professionals behind their devices?
You’re making a lot of things objectively better, but none of them are the essentials that people need.
I’m not saying it’s bad to make AI bots or video games or network apps. I’m saying that the blanket statement “we make things better” is oblivious to a lot of realities.
That kinda describes a lot of “not the USA” developed countries since quite some time.
The problem is that copyrighted material is intermingled with non-copyrighted material in a way where it's not obvious how to solve it. But I think in this case, AI is so powerful that we should (gasp) cut it some slack. This would be the perfect example of throwing the baby out with the bathwater if OpenAI were to be sued into oblivion.
It's also forgery as a service.
AI is here. We've had a good long look at what it does and what it's used for, and it's not going to be something else. This is what it's for. It's for copyright washing other people's work (shitily). It's for astroturfing social media with product placement comments. It's for presidents to make videos of themselves dropping poop on protestors from airplanes. It's for souless "creators" to earn updoots from other bots for their "street photography" generated images of neon lights on puddles in Tokyo. It's rube goldberg automations that almost always accomplish nothing. It's fanatics claiming that it has multiplied their productivity by some incredible factor, but never showing the receipts, or when they do it's always something trivial like a calorie counter app.
This is it. This is the AI we've heard so much about. I'd say I can't wait for the hype to end, but after living through several cycles, I'm almost certain that whatever hype cycle emerges from the IT sector next will be even worse.
I am curious, your type seems to become a rare species - I suppose you have never worked with a modern coding agent recently?
Otherwise you have noticed also here many, if not the majority expressing they rarely if ever write code anymore?
If it is a hype, then one that produces lots of working code. Way faster than I can type it. And I am fast.
I covered that:
> It's fanatics claiming that it has multiplied their productivity by some incredible factor, but never showing the receipts, or when they do it's always something trivial like a calorie counter app.
There is no shortage of "working code" out there. GitHub is reportedly falling over from all the working code. Where's your business? Who's using it? Why aren't products better yet? It's a mirage. Your "working code" is the same thing as gen-AI "street photography" images. No one wants to see them, yet it's pumped out in vast enough amounts that it's choking the spaces that are ostensible for photography. The low quality, low investment nature of it excites the lazy wanna-bes who leave a trail of half-baked, soon-forgotten detritus behind them.
Show us the receipts.
And I mean no wonder github is drowning in garbage, now that anyone can "code"
"The low quality, low investment nature of it excites the lazy wanna-bes who leave a trail of half-baked, soon-forgotten detritus behind them."
But would you also call Linus Torvalds a lazy wannabe?
Steal one mp3 and you might get fined thousands, steal a book from your local shoppe and the police would come visit you. Forge a signature and you would also be in trouble. Hack a government website and you will have to answer some questions.
Steal all the books in the world, forge millions and this story begins to tell and nothing happens.
It’s not organized like a human brain, it shouldn’t be surprising that unusual results occur. They are approximating human intelligence from a different angle. It’s interesting to see the improvements in areas like this that require introspection that isn’t fully wired up yet.
[edit] I should add that a human making a New Yorker cartoon is extremely iterative and introspective. Current generative AI is meant to push it out, and you can do the iteration and introspection yourself.
AI boosters take note: this sort of thing is exactly what skeptics have in mind when they insist that you are nowhere near "AGI" and have not meaningfully passed Turing tests and your claims of goalpost-shifting are fake. You have been aiming at straw goalposts.
Isn't that somewhat introspective?
I don't think introspection is necessarily self-driven. If a psychologist tells me to examine my thoughts, and so I do, am I not introspecting?
For certain values of "my own".
https://lemmy.ca/post/63438408
Given that they can reliably do this, I'd think it should be trivial for the harness to automatically insert a "review the image for anything that looks like an artist's signature or other blatant indicator of plagiarism, and fix it" pass.
And then people wonder why the default mood of AI is so pessimistic. It's just revealing all of society's broken windows and adding a few more in the process.
The same should apply to LLM vendors.
If you just draw a cartoon with a fake signature, nobody is coming after you. Even if you posted on Twitter or something, nobody is coming after you.
You'd have to be fraudulently selling it in a book of cartoons or on coffee mugs or something.
Are you sure about that one? Are you saying if you posted say, a racist cartoon on twitter, and you forge my signature onto the thing, I can't come after you?
I don't know about the US but here in Germany the category for this is personality rights. The entire point of a signature is to establish authenticity, using someone's likeness or identity without consent will get you into deep trouble even without money being exchanged.
Would you? Always? Suppose I hate Obama drone striking people, so I made a satirical cartoon of him signing an executive order to "bomb brown people" or whatever, affixing his signature[1] to that image. Would that get me in trouble, even if the image was clearly satirical? What if someone takes that, then passes it as non-satire, either intentionally or unintentionally?
[1] https://en.wikipedia.org/wiki/File:Barack_Obama_signature.sv...
There's nothing illegal unless someone seriously thinks Obama signed it. The easiest example would be his signature on his wikipedia page. Clearly he didn't sign that page, nor (probably) did he authorize it.
These cartoons are intentionally drawn in the style of a cartoonist and feature their signature. The goal is forgery. The whole point of these AI-generated images is to look like the real thing.
You can't seriously claim that the very person who prompted the AI image generator thinks the image it spit out was created by Brendan Loper?
What is weird was how fast things were buried, and the family's concerns were never properly addressed. =3
> The New York Times article cites Stanford University law professor Mark Lemley, who disagreed that generative AI services violate copyright law, and intellectual property attorney Bradley Hulbert, who said a new law might be necessary to settle the question of legality.
> Months after Balaji's death, which attracted significant public attention, Hulbert told Fortune magazine that Balaji's essay "[reads like] the argument of a really smart non-lawyer who read up on the subject but does not have a thorough understanding".
If there's some kind of industrial-scale intimidation campaign that's stopping IP lawyers from litigating the case of their lifetime, that's an even bigger story than OpenAI taking out a hit on somebody. It seems like they're agreeing that the copyright abuse was never hidden, and it's sufficiently transformative enough that nobody could argue it's illegal.
Many already settled out of court with Disney due to trademark violations, then killed a popular project mostly used for Star-wars satire at the time.
Best of luck =3
Unless folks spider sites that clearly state the terms of use prohibit such actions, violate GPL licenses, and scrape private conversations or markup input.
Also, fair-use loopholes that protect academics don't always apply in a commercial context. The encoding of the data in a proximity vector search space is irrelevant. =3
https://www.youtube.com/watch?v=YhgYMH6n004
I would also recommend this book if people tire of the marketing hype. =3
"Gilded Rage" (Jacob Silverman, 2025)
https://www.amazon.com/Gilded-Rage-Radicalization-Silicon-Va...
Could also be regulatory capture, and Sealioning. =3
https://en.wikipedia.org/wiki/Sealioning
- LLM's can reason
- everything an LLM does is the result of reasoning
This demolishes only the latter point, which as far as I know has no supporters.
It's like accusing somebody of being a lousy chef because they have such terrible taste in takeout. There's just no connection between these things.
I think these talking points are there to hype up the technology or otherwise excuse the mis-allignment (i.e. consumer hostility).
This is completely silly. If you don’t think LLMs can reason, you’ve either never used them to do tasks that require reasoning, or you don’t understand enough to recognize what’s involved in the responses you get.
In this case it’s clearly the latter, because you’re confusing image generation models with LLMs. There are very big differences between the two. No-one is claiming that image generation models are capable of reasoning.
The most common argument for this is some core unexamined axiom that only humans can reason by definition, and then working backwards to a justification for that.
(I suppose a religious or otherwise superstitious person might introduce the soul into this, but I haven't come across anyone actually willing to defend that hill.)
The relevant MW definition for "reasoning" is: "the use of reason, especially: the drawing of inferences or conclusions through the use of reason."
And "reason" is: "the power of comprehending, inferring, or thinking especially in orderly rational ways."
Functionally speaking, i.e. in terms of observable behavior, LLMs exhibit comprehension, inferring, and reasoning. If someone wants to object to that, they'd need to explain what relevant property prevents a conclusion drawn by an LLM from being counted as involving reasoning.
I've spent a long long time thinking about the problem of reasoning and consciousness, and it's not nearly as simple as your confidence and feeling of intellectual superiority would indicate you think it is.
First, you'd obviously have to define what you even mean by reasoning, precisely. Let's hear it.
Then demonstrate that LLMs do not corresponds to that description. You are making absolute statements ("They are not reasoning", "It does nothing of the sort.", "FFS lmao"), and basing your insults on this premise ("Ai Psychosis", "Know the difference."), so surely you have an extraordinarily solid ground to support that - rather than just speculation, innuendo, and a lot of confidence.
P.S. I don't see why you're equaling "reasoning" with "behaving like a human".
P.P.S. We don't even know if LLMs are conscious (in any way, shape or form, however foreign). We simply do not know. They might. Minds far smarter than you and me tried to answer this question, and they couldn't prove nor disprove it. So feel free to speculate, but anytime anybody makes absolute statements regarding this, they are either overconfident, underinformed, or both.
The thing about a generative language model that’s trained from a massive but unknown corpus is, it’s practically (if not theoretically) impossible to evaluate the extent to which data leakage contributes to any particular output.
But I would argue that, as things currently stand, “sophisticated engine for approximately querying a pastiche of the results of human reasoning that comprise its training corpus” remains a more parsimonious explanation than “it’s doing actual reasoning” for how this neural network architecture produces the phenomena we’ve been observing.
Well if the thing can find and fix bugs in something that is using non-mainstream stuff that is surely not in it's training dataset, that's better than a rubber duck already. Whether it has soul is a different question of course.
As popular as I know the rhetorical tactic is on both sides of these discussions about LLMs, I’d still thank you not to strawman me.
Perhaps you could argue that “appropriately applies syllogism to arrive at correct conclusions” is too high a bar to set, but I don’t think it would be fair to call it a “goofy-ass”, “non-standard” or “fluid” element of a reasoning capacity assessment.
I don't think the bar for an actual reasoner can possibly be 'always appropriately applies syllogism to arrive at correct conclusions', because in that case nobody in the world is an actual reasoner. And if your bar were 'sometimes appropriately applies syllogism to arrive at correct conclusions', it's hard to understand why the current generation of AIs doesn't meet it; they are clearly capable of doing so, at least to all outward appearances. (Maybe you think their apparently successful demonstrations of reasoning are illusions, but again, you would need to define what counts as "actual reasoning" vs. a superficially convincing simulation of it.)
Part of my concern here is that simply pointing out that LLMs appear to be performing tasks that can be done through reasoning, and using that in and of itself as evidence of reasoning, is affirming the consequent.
for example if you ask any of these models (just about any image-gen) to produce Japanese ukiyo-e art they will almost always produce it with a hanko[0] that has been seen a lot in historical art pieces, usually having nothing to do with the era or style of the replica but seen so often in 'Japanese artwork' that it's just permanently tokenized into it as a defining characteristic.
[0]: https://theartofzen.org/the-hanko-in-japanese-art-and-ukiyo-...
One would hope that the person prompting ChatGPT would notice this sort of thing and do something about it before sharing it publicly, out of a genuine desire not to cause confusion etc. But I guess that's way more personal responsibility than we can expect average people to take on nowadays.
In practical terms, the legal system probably isn't built to withstand blaming the user. I'd like to advocate that everyone who can do something should try to do their part, though.
When the user shares it, that is when reputational harm becomes an issue.
A technology being flawed does not absolve its users of responsibility. To the contrary, it amplifies it.
> A technology being flawed does not absolve its users of responsibility.
It may not absolve the users of responsibility that they actually have, but that doesn't change that the entity making and selling the technology is to blame for its flaws, not the user.
I would have thought the fact OpenAI is commercially selling these forgeries (in exchange for subscription payments) would make that fairly straightforward to prove.
> Katzenstein considers the reproduction of his signature by ChatGPT to be more than just a violation of intellectual property; to him, it’s closer to false impersonation. “[ChatGPT] is attaching my name to work that I do not endorse or like. It’s slop, and unlike the other slop that I’ve encountered, this is slop that’s pretending to be me.”
> “I’ve had people hack my credit card,” said Joe Dator, a New Yorker contributor for the past 20 years. “That feels like less of a violation than this. When they hacked my credit card, they didn’t dress up like me.”
So this has morphed from plagiarism and copyright infringement (bad) to impersonation (also bad, arguably worse, and maybe more provable in court). It’s chilling to think of the implications of having one’s signature attached to a document or to words that are not one’s own.
And I think maybe it's time for that. People need to learn that there's real, expensive legal liability for doing stuff like this. And AI companies the same.
I am very much not an advocate of "sue everybody for everything". This is major enough that it clears my threshold.
Wait, isn't it already illegal to forge someone's signature?
The 'bug' here is whatever post-processing step or system prompt is in place to steer the model away from doing this.
One could argue nobody should be allowed to claim it. It just exists.
Even if the person can't claim the copyright of the image produced they ARE responsible for the use of their tools and what they do with the output.
In this case, they released an image with someone else's signature on it. That is wrong, the person should take the blame for that.
The person releasing the image may take it up with the AI service that their tooling led them into making such a mistake. But good luck with that in court...
Somebody “made something.” But just because you do something doesn’t mean you get to claim whole ownership of it and get to sign it with your name. Plenty of examples in life.
If the machine is like you, the machine is a forger. The machine is not like you, it is simply blending the work of others to order. Adding someone else's signature is simply part of that statistical process.
Everything is a derivative work, and always has been. AI is just making that salient fact so much more visible, and now everyone who believes in the delusion of Imaginary Property is scared at that truth revealing itself.
Incidentally, this is also what young humans learning to draw will do. They start by copying what they've seen.
I really wish there'd be a split among these disciplines (science/math/code vs. videos/art/literature) - one is vastly more problematic than the other.
It is very tiring to say “I don’t necessarily disagree with you about AI ‘art’, but in my field—which you do not understand, and in which the underlying build process is often not the creative output—AI presents very real productivity gains” for the umpteenth time.
I am skeptical of there being sufficient data to build “ethical” training datasets, and I’m confident that much of the same contingent will (somewhat rightfully) argue that ‘second-generation’ copyrighted AI material has already irreversibly made its way into every modern dataset.
- prove that you had the rights for all of your training data
- open source the model
Give the labs a 3 month grace period in which to comply, so competition can persist even with dubiously sourced data, but the people can't be locked away from derivatives of their contributions for any significant amount of time.
That’s not a justification. If a company were poisoning the water to your home as a byproduct, would you be satisfied if they told you “we don’t necessarily disagree with you about polluting the water, but in our field—which you do not understand, and in which the underlying build process is often not the water pollution—what we’re doing presents very real productivity gains”?
> I am skeptical of there being sufficient data to build “ethical” training datasets
Then you don’t build any. What fucked up world we live in where people think it’s OK to be unethical because they want something and can’t think of any other way to do it. What monumentally selfish rotten babies.
The "gray goo" scenario finally happens... for AI. That's actually the good ending for humanity. I love it! Poetic and believable. Data doesn't "heal" like nature. :D
There are actual models trained on ethical datasets but they are obviously not very high powered. If companies with the resources of an anthropic or openai were doing it (ha) it would be more feasible
Being able to prove such gains in better products would be a start. And an emphasis on how it assists existing engineers/mathmaticians/researchers, not that any accomplishment made with AI assistance is "AI solves problem".
I don't know whatever happened to "words are cheap". I guess it literally made money to say words, so that adage is false for the time being.
>I am skeptical of there being sufficient data to build “ethical” training datasets
Well if all those scam job ads paying 100/hr to create AI training content was not a scam and instead the approach from the start, there may have been a chance to bridge that gap ethically. The industry chose to break things and is trying to act mad that people are mad at all the broken stuff.
These results are entirely a consequences of the actions chosen. And I don't believe there was ever an honest consideration of there being ethical training datasets. They just thought they could brute force society with fearmongering and bribes. The BOTD was already low in the beginning but completely gone now.
But sure, there's um, an ethical way of doing that?
1. Only use open source/CC compliant assets.
2. Acquire rights/licenses to any datasets that do not fit #1. e.g. the Google deal with Reddit for 60m/yr.
3. Offer programs to have creatives willingly submit their data, with some sort of residual output based on the number of times their assets are sampled.
4. If all that is still not enough, hire creatives to create assets for you. This is something Spotify did recently with "ghost artists"[0]. The intentions here are suspect, but a non-consumer facing artist providing work for an LLM wouldn't have the same ethical dilemmas
5. Lastly, if all that still isn't enough: governmental programs to either provide grants, subsidies, or more outreach to get the ball rolling.
Would this cost tens, hundreds of billions of dollars? Yes. But clearly, that was not a barrier to entry for the industry anyway. So we can chalk this down to the personality of leadership or the wider culture of modern big tech
[0]: https://harpers.org/archive/2025/01/the-ghosts-in-the-machin...
Like, legally, I'm sure Reddit had the right to sell it, but probably over half their content was written before ChatGPT was ever announced. The TOS allowing reddit to make "derivative works" was largely understood to mean things like cropping photos, using your viral post in an ad, or maybe auto-translating your comment.
While coders may care about the craft (and I do), it's not as if the value of my code is in the exact variable names I chose.
Code can be art, and copyright/plagiarism is real. It sort of boils down to how much it bothers us.
I disagree that they can be separated. Practically, I think they can't. Because the mere invention of new tools inspires even more AI advancement and that in turn will cause the other side (artistic side) to degenerate even more.
I'm anti-LLM all the way, 100%, no exceptions. Zero tolerance.
its somewhat funny that math people are in a conundrum as to support or not support but this might partially be because some wish to believe that math itself is and can be useful and therefore accelerating is good
but the art people have no such delusions so they’re just strictly against
imo proof writing is more akin to art than coding/tech but…
The current models intelligence depends on massive training dataset of essentially stolen data
google OTOH already had a lot of this dataset in their possession (e.g. Google Books etc), still questionably licensed for how they used it, but not quite as bad. They did apparently break through NYT paywalls and stuff like that though, still theft.
Honestly, you all kind of mind fuck me that you're not more pissed off about AI basically replicating a large portion of your skills. This effects so many professions now and it's only going to get worse. I would expect a far greater outcry from software engineers trying to organise to ban this shit. But its like none of you even care?
If there was any thought or underlying thought going on here not putting a signature (at least a real one) would be the right move, despite it being less likely. It would realize, while generating the pixels that eventually became a signature, that it shouldn't do that.
This quote is a pretty solid argument that you need to understand the technology you’re trying to criticize better. This issue has nothing to do with LLMs. LLMs are not image generation models.
In the course of the conversation a with chatgpt, this image was generated and served by an LLM. It clearly shouldn't have been by any sort of reasoning.
If you do not want to be called a duck, it would help if you stopped quacking like one. Maybe you aren't a duck, but you aren't helping your case with stories like this about how AI generates images.
Hint: it isn't "image".
The point is that working with natural language tokens is very different than tokens that represent an image.
A simple relevant example is that if you ask an LLM to write a psychological thriller about a poor former student who commits murder and deals with intense moral guilt, in classic Golden Age Russian literature style, it is unlikely to sign it with "Fyodor Dostoyevsky."
It does that when generating images because, at a high level, image generation doesn't benefit from the kind of reasoning that language generation is able to.
Sure, let's re-examine what this chain is doing
1. "This is a pretty solid argument against people who argue that LLMs are more than just (very massive) next token predictors."
2. (you) "This issue has nothing to do with LLMs."
3. (me) "yes, it does"
4. (you) "an LLM does not generate images"
5. (me) "this is an LLM generating images"
6. (you) "an LLM does not understand what a 'signature' is"
So we are getting lost in minutae to asset that..."LLMs aren't much more than just (very massive) next token predictors.", agreeing with what the original comment is claiming.
There's a bit of meta-commentary seemingly missing from your context here. so I'll mention it. Some people are trying to claim that LLM's are "reasoning" with data, and that the way they "learn" isn't actually too different from human learning. Aspects of an LLM like this, being unable to reason about with the image it generated, are disproving such notions as of 2026. That is all the top comment in this chain is saying.
I hope that helps.
LLMs do not generate images. LLMs prompt distinct, separately trained image models to generate images. The LLM has no ability to introspect the image model and cannot provide feedback during the image generation process. If the image model misinterprets the LLM's prompt (which can happen!) or inserts unexpected content, the LLM may become "aware" of that during subsequent chat steps as it ingests the generated image, but it cannot avert their generation.
As you probably suspect, chat gave me a full synopsis of Harry Potter.
I kept asking if that's an original idea, and it kept swearing on it's mothers grave, that the story has never been published before.