Cessation of public development of Kefir C compiler
kefir.protopopov.lv
kefir.protopopov.lv
I feel this pain, one of my small donation driven sites has been destroyed by crawlers who just ignore robots.txt and burn the site into the ground.
Sort of jokingly I proposed an update to the "spam fax" law:
You have a hole here. Your web server is sending the response and the bot is receiving.
Fix that and … profit? :-)
> The initiator of the communication pays, not the server operator.
If I could put everyone pushing all this AI crap into a meat grinder, I would.
Those people who do that are too few and far between to make a difference. The majority of open source devs aren't giving away the source without a license. That license is how they specify what they want in return.
100% of open source devs aren’t giving away the source without a license, since a licence—the grant of permissions for what is otherwise exclusive to author under the law—is what makes something open source.
> That license is how they specify what they want in return.
No, the license is how they legally give away permission to use material that is legally subjejct to their exclusive rights by virtue of creation. The license may be a contract license that, as you suggest, involves mutual exchange of value, but for many (especially permissive) open source licenses it is a gratuitous bounded grant of permission which has limits but does not involve giving something of value back to the creator.
Wrong. What they want in return is either credit or derivatives of the software. It's disingenuous to suggest that all these authors specifying, in a legal document, the exact mechanism by which to pay them back don't know what they are asking.
If you're not happy with that trade, then don't make it.
And the more they DDOS small websites — instead of respectfully scraping once — the more realistic my conspiracy theory looks.
And I push a lot of open source code including a ton for the SWGEmu project, but now I’m of mixed mind to stop pushing anything public. I can’t decide, am I talking out of both sides of my mouth, it’s a confusing time to navigate for sure.
I think SWGEmu (cool project, just learned of it from you!) do represent some optimism though. Maybe these sorts of passion projects will take over the space?
Me too; not that I've published a lot, but definitely more than most. That won't be happening anymore.
There seems to be an implicit premise here that any work generated by an LLM whose training data includes a particular bit of code itself constitutes a redistribution of that code. I've yet to encounter any strong arguments substantiating this premise as a general principle, and my own suspicion is that it is not valid as a general principle, given the nature of how LLMs operate.
It's certainly possible that specific instances of LLMs lazily copy-pasting code from public repos may exist, and the extent to which this is happening is something that can be substantiated by empirical examples, so if you have any to point to, I'd be interested in looking at them. However, where this is happening, it ought to be regarded as a failure modality of LLMs, and not something that implicates the underlying nature of LLMs, given that their intended purpose is to function as stochastic generators that do not merely copy-paste input data.
My initial feeling here is that using open-source code to train LLMs is not per se a violation of the generally accepted FOSS social contract, but rather that attempting to restrict specific use cases of FOSS-licensed code on the basis of normative opinions unrelated to the license terms is a violation, or at least a rejection, of that social contract. I'm not fully committed to this position, though, and would welcome well-reasoned arguments to the contrary.
Yes but my answer would be different. It can be either about what coding agents do (and you'll see that it breaks the social contract), or it can be about what the FOSS social contract is (and you'll argue that coding agents don't break it.) Lo and behold, it was the latter.
> There seems to be an implicit premise here that any work generated by an LLM whose training data includes a particular bit of code itself constitutes a redistribution of that code.
Not any work. But if a specific work was generated based on a specific open source work, then according to the social contract that binds non-AI code generators such as transpilers, the output is derivative and should follow the license of that open source work.
There's also the question of whether the model itself is a redistribution. For every other lossy compression algorithm in history, the answer is a resounding yes. Is a model meaningfully different from a hypercompressed corpus of its learning data?
The social contract of the open source (not to be confused with the legal contract of GPL, MIT etc.) is that developers give users software that they can use and modify in any way they want, and in exchange the users give the developer recognition and help with development and maintance, as well as give each other the assurance that the software will remain available to them and any future users.
AI gives the user all the benefits of using open source software with none of the obligations that come from using open source software. Developer gains nothing from going open source. It makes no sense for any developer to go open source. Social comtract breaks down, and it's all because AI users didn't hold up their half of the bargain.
I don't disagree with the premise that any LLM that is cloning code wholesale from a third-party repo is creating a derivative work, and the license terms apply to it.
But I also don't agree that non-AI code generators such as transpilers are in the same category as LLMs -- a deterministic process that is simply parsing input from a single source and outputting it in a new form is not the same thing as a stochastic process that interpolates patterns from multiple sources and then uses those patterns to generate novel outputs.
> There's also the question of whether the model itself is a redistribution. For every other lossy compression algorithm in history, the answer is a resounding yes. Is a model meaningfully different from a hypercompressed corpus of its learning data?
The model isn't a lossy compression archive that merely represents a collection of pre-existing works in parallel to each other. It's a probability matrix that relates together uniquely isolatable units of data to each other across the entire collection.
If I build a Markov chain based on a statistical analysis of word sequences in Hamlet, and then use it to produce a new sentence that isn't found in the text of that work, I have not created a derivative work of Hamlet under any applicable sense of that term.
> The social contract of the open source (not to be confused with the legal contract of GPL, MIT etc.) is that developers give users software that they can use and modify in any way they want, and in exchange the users give the developer recognition and help with development and maintance, as well as give each other the assurance that the software will remain available to them and any future users.
I don't think that is generally true. There's always been a hope and expectation that some subset of users would contribute back to the project in the ways you're describing, but never a sense of there being any obligation to do so. Only a fraction of FOSS users have ever contributed to back to the projects whose software they use.
There's always been both a social and legal obligation to properly attribute authors and abide by license terms when redistributing or forking FOSS code, but neither obligation has ever applied when learning programming techniques from FOSS code in order to write your own software. And the way LLMs are designed to work is more similar to the latter than to the former.
But in cases where LLMs actually are acting in ways similar to the former, I agree that they should be held accountable both socially and legally.
Uh, that is exactly what a derivative work is. You literally specify that Hamlet is an input to your work. I believe you're conflating derivative with transformative. You're certainly creating a transformative derivation of Hamlet, but you are by definition creating a derivative work by training a Markov chain on the text of Hamlet.
The obvious follow up here is whether an LLM is creating transformative derivations or not. A lot of folks argue that yes, an LLM spitting out statistically sampled code that matches existing code is not transformative and is (or might be) infringing the terms of the license it was released under. Others argue that there's not an exact copy of the original source in the LLM's weights so by definition it must be a transformative work. I think it's a pretty obvious "somewhere in the middle" that is gonna make a bunch of lawyers a whole lot of money.
Personally, I don't care one way or the other. I'm one of the folks that thinks software shouldn't be copyright-able in the first place.
No, it isn't. A derivative work isn't something based on extracting underlying ideas or patterns from another work, it's something that includes copyrighted portions of the other work.
An annotated edition of Hamlet is a derivative work. A Cliff's Notes summary of Hamlet is a derivative work.
Strange Brew and The Lion King are not derivative works of Hamlet simply because they include literary themes and plot points that originated in Hamlet. A list of word counts of popular works of literature that includes an entry for Hamlet is also not a derivative work. The Markov chain described above is not a derivative work.
> The obvious follow up here is whether an LLM is creating transformative derivations or not. A lot of folks argue that yes, an LLM spitting out statistically sampled code that matches existing code is not transformative and is (or might be) infringing the terms of the license it was released under.
And I would agree with them. An LLM that actually is outputting non-trivial code that matches a public project's code verbatim is engaging in copying, and not stochastic inference.
> I think it's a pretty obvious "somewhere in the middle" that is gonna make a bunch of lawyers a whole lot of money.
It's a shame that the same fundamental questions have to be relitigated over and over again just because the contextual formalities and modes of expression have changed. I wonder how many of the legal cases are going to be copies or derivative works of previous ones.
But try to write your own story of a lion cub chased away by his uncle and living in a jungle until his childhood friend finds him and convinces him to reclaim his kingdom, and you'll quickly hear from Disney's lawyers how non-derivative it really is.
OSS devs aren't worried about Hamlet reinterpretations. They're worried about legally-distinct-but-functionally-identical software clones. Unlike Disney, they don't have millions in their pockets to fight the legal battle. You know who does have millions? The people they'd be fighting against, who are going to use every single of your arguments to claim their AI-generated reimplementation of Kefir is not bound by GPL (or even by BSD 3-clause in case of runtime). No share-alike, no attribution, no nothing. If they are right, then the OSS social contract is dead. Even if they're not right, but behave as if they're right because they have lawyers and OSS devs don't - the social contract is just as dead.
I'd expect them to say "we don't like this, but since it's not actually a derivative work, we can't do anything about it". As long as you're not directly copying things like characters, dialogue, etc., it's not a derivative work.
That's why Armageddon is not a derivative work of Deep Impact, the Shark Attack series is not a derivative work of Jaws, the more famous Titanic is not a derivative work of 1979's S.O.S. Titanic, and the Harry Potter series is not a derivative work of Teen Witch.
Using the same story themes, plot points, and setting as another work does not implicate that other work's copyright. Only substantial copying of specifics does.
Define a character. Is another lion prince named Simba the same character? Is a lion prince named something else the same character? Is a human prince named Simba the same character? I'm no copyright expert, but from what I know about fanfics and fanart, the US courts ruled all of these violate copyright (you can win a book plagiarism lawsuit even if the other book has all names changed and every sentence went through thesaurus). The few cases where the obvious stand-in was ruled non-infringing were on the grounds of parody exception, not on the grounds of being non-derivative.
The many Titanic movies are not each other's derivatives because none of them are based on each other. They're all based on the historical events directly. Now, if the original Titanic was fictional like the famous Nautilus, then yes, the 1997 movie would be derivative, but not of the 1979 series.
Which part of Harry Potter is directly rips off Teen Witch the way Lion King directly rips off Hamlet? I'm not familiar with that movie.
If you write "To see or not to see, that is the question" about a person named Eyelet, who is going blind, how can you argue that it is NOT derivative of / borrowed from Hamlet? Yet that sentence is not in the work. Isn't that what LLMs essentially do? Tokenize, then substitute in new values for certain tokens, while retaining the general structure?
There are stochastic compression algorithms (e.g. https://github.com/kaydotdev/sqic) and it would be insane to claim they don't produce derivative works. And as a general rule, a work based on multiple other works is derivative of all af them.
> If I build a Markov chain based on a statistical analysis of word sequences in Hamlet, and then use it to produce a new sentence that isn't found in the text of that work, I have not created a derivative work of Hamlet under any applicable sense of that term.
No, but your generated text is also useless if you want to read Hamlet. The danger I'm speaking of is people generating Hamlets but paraphrased - that's a derivative, especially if you use an automated tool that got original Hamlet as its input. Except the Hamlet in question is the Linux kernel but not bound by GPL. Also, your Markov chain itself is a derivative work.
> I don't think that is generally true. There's always been a hope and expectation that some subset of users would contribute back to the project in the ways you're describing, but never a sense of there being any obligation to do so. Only a fraction of FOSS users have ever contributed to back to the projects whose software they use.
True, but that fraction of a huge number is still big enough to be meaningful help. Plus the recognition. Most users respect the attribution clause. AI legally-distinct clones drop the fraction of helpers and the number of attributions straight down to 0. That changes the equation, what previously made sense now straight up doesn't.
> But in cases where LLMs actually are acting in ways similar to the former, I agree that they should be held accountable both socially and legally.
And because OpenAI et al. hold all the money and all the lawyers, the only way to hold them accountable is to stop publishing open source altogether. That's the only leverage OSS community has.
"If you copy my work, you should share your work too."
or at minimum (MIT):
"If you copy my work, you should credit me."
I think it is no longer under dispute that the legal contract is satisfied by LLMs. The AI companies won and will continue to win.
But we are talking about a social contract, which is not quite the same thing. The social contract is what leads some devs who previously enjoyed publishing their work openly to no longer feel the same way. What did the authors mean by "copy"? Did they mean literally CTRL+C, CTRL+V or something broader?
This is a matter of opinion which only each individual creator can answer. For me, copying meant something like:
"To reproduce the function of my work, dependent on my having published it, without effort nor understanding of your own"
Ten years ago this basically required doing a CTRL+C, CTRL+V so there was no need to be more specific. Anybody who did enough work to, say, rewrite in another language (with that language's idioms), met the bar of clause 3. Now AI enables a form of "copying" that matches my definition, without the user even being aware of whose works they are copying. It perfectly launders the origins of its output. It can write an FFmpeg clone in Rust for you that would appear to be a novel work.
Of course, I cannot say that my own little bits and pieces of open source code would make a scratch in AI's capability, were it removed.
But I do strongly believe that if all the code that was published by authors with the same mindset was unavailable, Claude would be a far weaker developer.
Perhaps this illustrates a fissure that was always lurking under the surface, then. The social contract that I've personally always attributed to FOSS communities was that attempting to restrict how people downstream of you use code is illegitimate, and that licenses like the GPL were meant to use copyright law to achieve something that resembles the state of affairs that might exist if copyright didn't exist in the first place. That's what the whole concept of "copyleft" always seemed to imply.
Now we have a new class of technologies that is admittedly fraught with a wide range of risks and pitfalls, but also a lot of promise to enable people to actually put the "four freedoms" into practice in ways they couldn't before, and we're seeing people who have normative opinions about AI derived from other, unrelated principles trying to circle the wagons and exclude those use cases. That is what seems like a breach of the social contract as I've always understood it.
> Did they mean literally CTRL+C, CTRL+V or something broader?
Given that FOSS licenses were always constructed to function within applicable copyright law, I don't see how they could mean anything else. "Literal CTRL+C, CTRL+V" is the only thing copyright has ever applied to, and the whole point of "copyleft" was to lessen the restrictions on even that.
That's wrong. What on earth gave you that impression when the licenses specifically set constraints on what downstream can do (from "release derivatives as open" to "put me in the credits").
Which part of which open source licenses gave you the impression that there were no restrictions?
These are restrictions on redistribution, not use. And they're there to make sure that derivative works can't themselves impose restrictions on use.
Yes, I do think there has always been such a fissure. People publish OSS code for many reasons, often a blend of multiple reasons. There are selfish reasons such as the desire for one's work to be recognized, or even the hope of getting better employment through showing ones' skill or making something companies will pay for support on. There are social reasons like the desire to collaborate with others. There are altruistic benefit-of-all-mankind reasons like Richard Stallman said "...restrictions reduce the amount and the ways that the program can be used. This reduces the amount of wealth that humanity derives from the program."
It sounds like your view of things is limited mostly to that last version of FOSS, the copyleft style. But even adherents of that style, I think, are not too happy with AI consumption of their code. For one, it allows laundering of the copyleft license so their work goes into closed-source products that are never shared. And for two, if your idea of OSS is that we all put our contributions into the great shared river of human achievements to benefit the world, it is disappointing to see that river funneled into a giant waterwheel of profit for a half dozen trillion dollar companies charging rent for its bounty.
> Given that FOSS licenses were always constructed to function within applicable copyright law, I don't see how they could mean anything else.
I agree from a legal standpoint. I cannot enforce my personal definition of copying nor do I expect that to become possible. It was just conveniently aligned with the reality of how copying software worked in the past, and no longer is and never will be again. That doesn't mean I will be writing OSS software with a new made-up unenforceable license. It just means, like OP, I'll weigh differently whether I want to bother releasing stuff at all.
No, I'm well aware of the different motivations for and approaches to FOSS. I'm mostly focusing on the copyleft/GNU GPL side of the discussion here because that's the side of the house where most of ideas of a social contract and desire to see a specific ecosystem develop have been located. People on the MIT/BSD side of things, which has always had a much more direct "do whatever you want" ethos, are not the ones I'd expect to be making these arguments in the first place.
> For one, it allows laundering of the copyleft license so their work goes into closed-source products that are never shared.
I'd agree that someone using an LLM to create a deterministic transcription of someone else's work is indeed violating the license. But I think the argument goes beyond that, into using LLMs in any way at all.
> That doesn't mean I will be writing OSS software with a new made-up unenforceable license. It just means, like OP, I'll weigh differently whether I want to bother releasing stuff at all.
That's a reasonable position, and from the perspective of examining whether the current LLM climate is sapping motivation to participate in FOSS, I can understand where you're coming from.
But to that point, I'd argue that if your motivation was to gain recognition, participate in a community, etc. then you're going to lose those things by keeping your code private anyway, whereas you won't necessarily lose those things just because an LLM was trained on your code. If you contribute to a popular project, people were almost certainly already using your work to do things you don't approve of -- if that didn't take away your motivation, why would LLMs do much worse?
This is extremely false. Copyright additionally grants you exclusive control over the production and distribution of derivative works.
A "derivative work" is a work based upon one or more preexisting works, such as a translation, musical arrangement, dramatization, fictionalization, motion picture version, sound recording, art reproduction, abridgment, condensation, or any other form in which a work may be recast, transformed, or adapted. A work consisting of editorial revisions, annotations, elaborations, or other modifications which, as a whole, represent an original work of authorship, is a "derivative work".
A training set is just an anthology, and the training process is condensation. That makes the weights a derivative work of every work in the training set.
Now, there's a separate discussion to be had about whether that derivative work meets the criteria for fair use, but that's it's own tangent.
A derivative work is a work that itself includes copyrighted content from the original work.
That is to say that for something to be a derivative work, some measure of its content must be "CTRL-C, CTRL-V" from the originating work.
Something that's merely inspired by another work, or draws underlying themes or factual knowledge from it, is not a derivative work.
> A training set is just an anthology,
Which might make the training set itself a derivative work, but works created by using the model trained on that anthology are a different matter.
> and the training process is condensation.
No, it isn't. It's the creation of a new work that represents patterns extrapolated or interpolated from the data set, without the resulting model actually including any of the copyrighted elements of the work.
The underlying ideas and facts in the original work were never protected by copyright. Only the specific fixed form of expression is copyrightable.
Someone who looks at a dozen code examples in public repos to learn how to do e.g. a quick sort, then upon understanding the logic flow of the quick sort algorithm, writes his own quick sort implementation is not creating a derivative work of the code in the repos he exampled. And the way LLMs work is much more similar to that process than to the "compressed anthology" concept you're describing.
If you put a GPL C program through Emscripten to run in a browser the output doesn't include the original C code but it's surely a derivative work.
> Someone who looks at a dozen code examples in public repos to learn how to do e.g. a quick sort, then upon understanding the logic flow of the quick sort algorithm, writes his own quick sort implementation is not creating a derivative work of the code in the repos he exampled. And the way LLMs work is much more similar to that process than to the "compressed anthology" concept you're describing.
This is undoubtedly the core of the disagreement. Humans can learn from what they have seen, appreciate it, understand it, and draw on that experience in what they create. They do this without being considered ripoff artists, so why not machines that simulate the "same" thing automatically?
To me the answer is simply that humans are special. Human thought and human effort makes it creativity when a human does it, copying when a machine does it. It's a double standard I am perfectly willing to accept. I am unabashedly biased in this regard.
That may seem remarkably unfair to the machines, or like a cop-out. I just carved out a hardcoded special case for humans, and my whole philosophical reasoning is "because I said so". But how fair do we want to be? After all, if you want to treat a machine exactly like a human who learns from prior art to create new art, then the ownership of the new art would also belong to the machine. Not to the person who prompts it.
Because it does include content from the original work -- this is just a translation, and isn't comparable to how LLMs work.
> To me the answer is simply that humans are special.
I don't disagree, but I also view LLMs as tools that extend human capacities and not autonomous entities unto themselves. LLMs are still just software, and can't really be regarded as anything other than instruments that humans use to broaden their capacity to see, appreciate, understand, and draw on that experience in what they create.
> That may seem remarkably unfair to the machines, or like a cop-out.
No, it's unfair to the humans. The machines are just tools that they use. The "double standard" is really a set of inconsistent standards applied to the same underlying moral agents.
> After all, if you want to treat a machine exactly like a human who learns from prior art to create new art, then the ownership of the new art would also belong to the machine. Not to the person who prompts it.
No, it always belongs to the person who prompts it. The machine is not a conscious entity, bears no intentions, and has no capacity to act on its own initiative. The machine is always just a tool that extends human capacity, as all machines always have.
For a good comparison here, we've never not credited a photographer as the author of a photograph. But the photographer is in a sense merely prompting the camera by framing the shot, selecting the exposure, adjusting the lighting, etc. -- the hard work in actually creating the photograph is being done by the camera itself, with the photographer playing no role in directly constructing the final image, and with the many of the qualities of the final image being determined by pre-existing features of the camera's functional design and components that the photographer also played no role in defining, apart from choosing which camera to use.
LLMs are like cameras in this way. And the fact that they rely on external data for model training no more disclaims the user as the author of the resulting work than looking things up in a dictionary or encyclopedia does the same for the author of an essay.
I agree with the framing of the AI as a tool not an autonomous entity. The thing is, to me, it is exactly that framing that makes it so the use of that tool means "copying" more than it means "learning and taking inspiration and creating new art", because who is doing the learning and being inspired? The person who types "make me a 3d arena FPS" certainly didn't do any learning from the Quake source code. The AI itself, being just a program, can't take credit.
I think of a trained AI like a lossy, highly compressed copy of its training data set. AI companies charge access to decompress targeted pieces of that copy and the lossiness makes that decompression interesting and "new". But normally I can't charge for access to other people's stuff even if the access is highly lossy, like a camcorder bootleg.
I've never had an LLM that had any of that baked into it either. LLMs just have token correlations trained on those works. Trying to get an LLM to output the data it was trained on verbatim is something I'd expect to be heading into monkeys-on-typewriters territory. "Write something in the style of Shakespeare" and "give me the original text of Hamlet" are two very different things.
> I agree with the framing of the AI as a tool not an autonomous entity. The thing is, to me, it is exactly that framing that makes it so the use of that tool means "copying" more than it means "learning and taking inspiration and creating new art", because who is doing the learning and being inspired?
It's not learning or taking inspiration, though. It's just making statistical inferences based on token correlations. Whether or not that's analogous to how humans learn is something I think is a metaphysical question that is of little practical relevance. The fact remains that LLMs are not human, have no intentions of their own, do not exercise any kind of agency despite how often people employing the misnomer "agentic", and are ultimately glorified statistical models.
The LLM is a tool that extends human capacities in the same way as any other mathematical framework or technological device.
> I think of a trained AI like a lossy, highly compressed copy of its training data set.
I've seen a few people in this thread make that argument, but I just can't agree with it. It's not compression, lossy or lossless, which aims to deterministically encode a representation of the specific input data. The training data is analogous to the sample set used in a regression analysis to generate a polynomial function -- it's not valid to treat the output from any application of that polynomial as a copy of the original sample data.
Not exactly. The GPL way is that you should share my work under the same terms if you want to share it, even if modifying it.
You are not required to share anything if you don't actually share anything, and just run it yourself. That's where all the criticism towards cloud providers who freely use FLOSS is directed.
> But we are talking about a social contract, which is not quite the same thing. The social contract is what leads some devs who previously enjoyed publishing their work openly to no longer feel the same way.
There is clearly a misalignment in expectations from some FLOSS enthusiasts. The main FLOSS licenses focus exclusively on distribution, but their expectations somehow extend well beyond distribution. We hear those FLOSS enthusiasts criticize and attack companies for using software exactly according to their terms, and somehow that is framed as abuse if said users happen to be bigger than some arbitrary boundary.
Attribution is often required even on MIT or BSD licenses where code is being redistributed, either in original or modified versions, but that would relate to this discussion only to the extent that one regards using LLMs whose training data included a certain bit of code as itself constituting redistribution of that specific code -- but that in turn is a very debatable premise which really ought to be argued for, and not merely argued upon as though it is already generally recognized as true.
Are you now layering the old and tired "copyright infringement = stealing" argument on top of the still unsubstantiated premise that all LLM training is copyright infringement?
Copyright maximalists like to borrow unearned moral weight for their position by conflating copyright infringement with "stealing", but this is not actually true in any legal sense. It's not clear that training an AI on publicly available data should even constitute copyright infringement, much less "stealing".
We based all of this on gentlemen's agreements and handshakes. That let quite a few people get only very wealthy, instead of hyper-wealthy. Thus those agreements have to be shredded.
AP mentions this in the link:
> Section 227(g)(4). Enforcement. Statutory damages of not less than $500 per server request made in violation of this section, consistent with the per-violation damages established under the original Act for unsolicited facsimile transmissions.
While this is at least something, it's not going to dissuade a startup from doing this sort of thing. They'll find ways to hide the origin of traffic, or just soak up the costs with more VC money.
You need to start throwing people in prison for long periods of time (10+ years) for this sort of thing to stick.
I can go on and on about how much safety measurements we take online since ages ago and how little trust we have for anything that comes through an Ethernet port. I have never needed such levels of vigilance in real life even though I live somewhere with higher crime rates compared to the national average.
This project in particular has been unconcerned with new coding practices so far, primarily, because I derive pleasure from hand-written implementations of my ideas, and believe that overcoming challenges the hard way is the main value I get from it.
Multiple times I got partially broken "citations" of GPL licensed code out of the models as answers to basic research questions (aka prompts) w/o any mentioning of the original license applied to the code. Just adding some random bugs every 10th line doesn't make it not a direct derivate. Image generators happily generated Sonics or Bart Simpsons (w/o directly prompting for that either). No mentions that those are copyrighted characters either.
I mostly make things because I felt they should be made. I am fine with what I produce being used by others provided they don't take it away from anyone else.
I was never very happy with the selfishness of the GPL, which is why I tended to prefer MIT, but the stances taken by people in recent years made me realise that nobody owns ideas, and even attribution is commoditised.
I am ok with voluntary attribution so that it may be used as a means to confirm additional information. I don't like the idea that if I think of something, someone else is not allowed to think about it without my permission.
Citation farming is a problem that happened because the value of the idea was placed on the names attached to it. That generated motivation to attach names to ideas as a way to gain power or prestige. To take credit for someone else's idea can only occur is because people have put the credit value onto the person and not the idea. Many of those names are of no use when it comes to verifying if the idea is sound, it's creating a denial of service attack on the ability to validate.
I understand the realities of commerce and academia that put these things in place, and how those who work within those frameworks have to do so in a way that is compatible with them.
I don't like it though, I think it makes the world less informed and less free. I don't have to create under those frameworks myself, so I made the decision to make any idea I have to not be bound to my will or identity.
- Seeing code (or a blogpost or whatever) was a result from effort where thought had gone into it. The writer paid effort so the reader didn't have to.
- There'd be some level of attachment to what you've put effort into.
With LLMs, that's undermined: it's easy to produce thoughtless imitations. Code or comments where thought didn't go into it. So, seeing some result isn't an indication of skill, but also not even an indication thought went into it.
I guess there's still something lost if someone isn't going to share code they've put thought into. -- But on the other hand, if it's just for me & I don't have to share it with a wider audience, getting LLMs to write out code isn't so expensive.. so code itself isn't necessarily something to value so much.
There was a relatively big shift in riding style right around the same time of the first mass production of vehicles.
I think the key part is how much thought goes into something.
Optimistically, LLMs are good at taking unstructured input, and (probably) producing the intended output from that. -- This allows for an interesting new way of coding: a set of instructions don't need to be as rigorous as a shell script, but can be natural language.
That part surely extends creativity. An LLM will be familiar with domain ideas I'm not, even if an LLM is completely disinterested in doing things.
Pessimistically, I think it's still not clear what the right way of interacting online with all of this is (other than clear expectations of "no AI")... in some sense LLM output is worthless to share, in the sense that I'm just as capable of asking the LLM to output something as anyone else is.
Recently the tune has changed somewhat, say with LLM's approaches to Erdos problems (and in particular the unit distance problem. The LLM solution here spurred progress on another large problem, namely https://arxiv.org/abs/2605.28781 ). There have been no claims that the LLMs work on the unit distance problem was derivative, and I've seen mathematicians claim it would have been accepted to a top journal (say Annals).
In spite of this, the capabilities of LLMs within mathematics are still limited. LLMs seem decent at
1. "constructions", e.g. where you claim \exists object with certain properties. It can help if the verification that the object has these properties is efficiently computable, but I don't believe this sort of verification was used for the unit distance problem.
There are other areas of math that LLMs so far are less adapted to, for example
2. impossibility results, or showing \lnot \exists object with certain properties, or
3. "abstraction building". Often in math results become much easier to obtain if you have "the right definition". Grothendiek was famous for this, as is e.g. Scholze currently.
These claims are based off of current public results via LLMs. It's possible capabilities will develop further. But also, in hindsight, it is natural that LLMs would be better at the thing they ended up being good at.
I'm unsure if there is a way of extracting from this insights to programming/writing. Plausibly, you could see LLM's developments of PoC exploits as similar to (1) but for computer science. It is a concrete "construction" that is efficiently verifiable. (2) would suggest trivial observations that it would be hard for ah LLM to show that a program does not have vulnerabilities. I'm not sure if there are less trivial observations. Finally, (3) might be what you're bemoaning. In simple language, it would currently be surprising if LLMs could create useful, novel, design patterns/abstractions.
First, I think it's the best time to write software since so much boring stuff can be automated. I can put my thoughts into what I'm trying to achieve instead of how. To put it otherwise, I think about big picture much more than about mundane details like dealing with particularities of a programming language.
Second, most people were using SO to solve just about any issue they had. The number of developers producing truly original code was minimal even 10 years ago.
Works as current readership is very small, about 20 or 30 people.
If a one-person show, closing it up would effectively kill it? Or (re?)turn it into a hobby project developed at snail pace.
If some community exists: fork coming up?
see https://variety.com/2025/tv/news/andor-creator-refuses-publi...
I suppose you could argue it also indirectly led to the empowerment of non-developers to create their own vibe coded solutions. But we're not quite there yet.
And the AI IP that makes that possible is still enclosed rather than open.
Judging from the number of projects I've seen from people who aren't software developers, we're there enough.
Could you perhaps explain that irony a bit more explicitly?
Can you provide any examples of "commercialized enclosure of software IP" somehow backwashing into the FOSS ecosystem and closing things up that are already open?
Nobody is empowered to do that because the models to do that aren't free.
I see a lot of risks involved in people surrendering their own decision-making to LLMs, but that's a question of how they're used, not how they're trained. The idea that using FOSS software to train LLMs is somehow a violation of FOSS norms just doesn't seem valid.
Not true. Most FOSS licenses require attribution and many require derivatives to be released under the same license.
Or are you saying that you think anything generated by an LLM qualifies as a derivative work of anything included in its training data?
It's a tool, if using data is necessary to make the tool work, then its output derives from the data.
If the LLM generation is not derivative of its training data, then why would it need the training data in the first place?
That's simply not correct within the applicable meaning of "derives" as understood in copyright law. In fact, data per se is not even within the scope of copyright protection in the first place: specific published works are copyrighted, but the underlying ideas and facts that they convey are not.
Even creating works that merely draw on a single source of data, but express the ideas drawn from that in a new or transformative way, are not considered derivative works (see the ruling in Google v. Oracle, for example), let alone works based on patterns extrapolated by relating together ideas sourced from many distinct works, which is what LLMs are principally doing.
If you applied the principle you're proposing here to human developers, you'd conclude that any code written by someone who learned to program by studying techniques used in FOSS software would in turn be a derivative work of that software. No one has ever regarded this to be the case.
Would be rather hard to write a definition that handles it properly back when LLMs didn't exist; not that laws particularly have anything to do with intent/desires behind FOSS anyway - intent is clearly there: you get code, under the condition that if you use it for anything, I get credited; else, you get nothing.
> In fact, data per se is not even within the scope of copyright protection in the first place: specific published works are copyrighted, but the underlying ideas and facts that they convey are not.
Luckily, FOSS is specific published works, and unless LLMs actually reasonably-provably do such decomposing into ideas/facts (good luck reasoning about that), that part is also irrelevant.
> If you applied the principle you're proposing here to human developers, you'd conclude that any code written by someone who learned to program by studying techniques used in FOSS software would in turn be a derivative work of that software. No one has ever regarded this to be the case.
Depending on intent, that very much can happen, it's called plagiarism. Good luck proving an LLMs intent. (not to mention the obvious differentiating factor of LLMs having arbitrarily-good memory unlike humans)
But this has never been a condition in the FOSS world, as far as I'm aware. I've only ever seen attribution requirements attach to redistribution of source, not usage of the software.
I understand that the crux of the debate here is whether training an LLM is redistribution of the underlying code, but to me, it seems to be fairly clear that it is not.
> Luckily, FOSS is specific published works, and unless LLMs actually reasonably-provably do such decomposing into ideas/facts (good luck reasoning about that), that part is also irrelevant.
That's literally all LLMs do. That's what tokenization is. And it's trivially provable, since if you compare LLM models with the copyrighted works you're claiming they replicate, all you'll see on the LLM side is probability matrices representing correlations between decomposed units of knowledge aggregated across the entire dataset as an integrated whole.
> Depending on intent, that very much can happen, it's called plagiarism. Good luck proving an LLMs intent.
The only intent ever in play is that of the user. LLMs are just software.
AGPL requires that even users using the software even across a network must be provided with a way to get the license (i.e. attribution) and source. Never mind that LLMs consume the source code instead of "using" the software anyway. (and of course things go more downhill for LLMs for licenses more restrictive than AGPL)
Otherwise, I'd say that, for many, the ideal condition for (copyleft) FOSS would be that anything that utilizes source code in any form also provides said source code and license/attribution. Sometimes that can even extend to outputs of software (and e.g. gcc takes time to explicitly state that its compiled code output does not count as being derived from gcc's code).
> whether training an LLM is redistribution of the underlying code
There's a funky side-note of whether LLM training can even be done on material with improperly-followed licensing; if you don't even have the permission to modify the material (as properly following MIT/GPL/etc would give you), it might be illegal to even tokenize it, never mind use it for training.
> That's literally all LLMs do. That's what tokenization is.
It's clearly not that simple, otherwise "split source into 10-char chunks, reverse that list, reverse it back, join this fun list we've gotten" would be enough to circumvent copyright.
> all you'll see on the LLM side is probability matrices representing correlations between decomposed units of knowledge aggregated across the entire dataset as an integrated whole.
Yeah, you need at least that, tokenization is irrelevant. But jury's out on this one - of course a good chunk is some form of "abstract knowledge", but other parts could be just encoding material in some compressed form (and surely gzipping a source code file doesn't circumvent copyright) that at the very least can apply to weights.
> The only intent ever in play is that of the user. LLMs are just software.
So my split-into-words-and-join-back is valid circumvention of copyright, if the user of some software doing that isn't informed that it's just effectively directly copying material. (I'll grant that perhaps, in such, the accidental-infringer might get a smaller penalty and/or get to defer punishment to whoever mismarketed the software to them,...but that wouldn't apply to anyone who knows that LLMs are very much just directly trained on copyrighted material. Don't know about legally derived, but surely mathematically derived)
Never mind that, for some things, learning some specific copyrighted code is the desired thing (humans do do this after all!), at which point at the very least the weights of the model are as copyright-infused as a gzipped source code file is.
If intent determination is on the user, and the user is aware that LLMs are very much technically capable of producing copyrighted works to some extent (which they better be), it would be on the user to ensure that any specific code they end up using is not, which is...a rather non-trivial task (a human that writes code can also reasonably-reason about whether they're infringing on whatever they learned from, but splitting into LLM writing + human checking fundamentally makes that basically infeasible).
That is wrong. How can you write that with a straight face? There are projects that are put into the public domain (one major one comes to mind), but the clear majority of FOSS projects have strings attached which make the intention of the authors absolutely clear.
IOW, if you're not happy with what the cost of the product is, then just don't use it.
I don't know how you can imply with a straight face that it did anything else.
I don't know how you can possibly argue that non-redistributive usage of software could ever violate the GPL -- and the other common FOSS licenses don't even have the copyleft provision, and literally are saying "do whatever you want, but I'm not responsible".
If copyright didn't exist then the share-alike and anti-tivoization clauses wouldn't work, FOSS in general wouldn't even protect attribution. Copyleft ecosystems depend on some amount of copyright law to uphold themselves.
And if copyright didn't exist in the first place we wouldn't be having this conversation, because the models created by all the token providers will be open to all for whatever use that anyone wanted.
But it does exist, and within this framework, the creator gets to say how you may redistribute their IP, and "We compressed it very much" isn't an out.
Right. And the way the creator gets to exercise that say is by releasing their work under a license. If you release your work under a FOSS license, you're saying "you are free to copy this work and use it for your own purposes".
Complaining that people are using it for purposes you don't like after you've already given permission to them to use it for whatever purposes they please seems a bit disingenuous.
> and "We compressed it very much" isn't an out.
It's not, but I don't think we're discussing that. We're talking about LLMs, not people redistributing zip files containing someone else's work. If you're trying to imply that LLMs are merely a form of compression, that's a position you've got to argue for, because I'm definitely not seeing any similarity between the two.
Before AI and in the early days of FOSS, people assumed that the primary recipient of code sharing were other FOSS enthusiasts, in the form of developers and users.
Then there was a wave of permissive licensing, which obviously brought with it corporate interests, however, this was easily foreseeable and many people who favored permissive licensing intentionally did so to appeal to corporate users, so the risk of them quitting due to perceived abuse was slim.
Now that LLMs are a thing, the primary recipient of a lone developer working on his project isn't really another human being. This human connection is now lost. Instead, your project is now laundered through the model and the model vendor can get away with ignoring your terms and conditions and let others write proprietary software.
In this transition period there were developers who thought that there was always going to be a human connection (even if part of a corporation), but then things changed and they realized their world view was wrong. Given the arrival of this new information, they obviously change their behavior in accordance to how the world actually is.
Other people using your code to enrich their lives or businesses doesn't exploit you in any way, as it doesn't cost you a thing. This is irrational.
As long as they are universally available, that is. That's the part people should be concerned about.
You may be fine with that, but the GPL is not a public domain license, and LLM training treats all things as if they were public domain.
This confuses two completely separate things. GPL governs distribution of derivative works. An LLM trained on GPL code does not distribute that code. The model weights are not a copy, a derivative, or a distribution of the training data in any legally recognizable sense; "influenced by" is not "derived from". The enforcement argument is a non sequitur; the GPL has never had a technical enforcement mechanism; it's always been legally enforced after the fact by copyright holders who discover violations. So if the LLM would indeed produce output sufficiently similar to my code and someone would publish it in violation of GPL, I have the same legal means to enforce my rights as if the code was copied by a human.
You can't simply make that assertion. You'll have to prove that LLMs do not actually contain encoded copies of copyrighted code and that they are incapable of reproducing such code verbatim.
There is no evidence for such a claim, and so your entire argument is completely baseless.
In law, the presumption is that an act is lawful unless proven otherwise. The burden lies on whoever claims a violation occurred. I already went into the case of sufficiently similar reproduction in my previous response.
https://www.reddit.com/r/programming/comments/oc9qj1/copilot...
You can disagree all you want, but there's ample evidence of this.
I feel this is a misrepresentation. GPL rather seems designed to maximize source availability for users.
But mandatory public source availability does make selling software products more difficult ("why would anyone pay if they can just use the source"), which is why most commercial software products still sell and ship binaries when they can.
Right. It depends on what you mean by "use"; GPL maximizes use in the sense that it prevents anyone from taking the code proprietary and thereby restricting future users' access. But it doesn't touch my actual point, which is that GPL explicitly permits commercial use, broad distribution, and also LLM training (none of which are restricted by the license). The source availability requirement is the condition, not a restriction on who can use the code.
> why would anyone pay if they can just use the source
Red Hat, Qt, and countless others have built commercial businesses on GPL code. So apparently there is a business and people willing to pay even if the source code is available. But that was not my point anyway.
But I can still understand the Kefir author; if you previously defaulted to GPL (over MIT/BSD) mainly because you wanted to foster an open-source software development culture, then the emergence of LLMs might well be a turning point were publishing your project makes no more sense to you; thanks to LLMs, publishing your open-source project might do more for commercial closed source actors (via better trained LLMs used by the developers they employ) than for open-source developers (or open source culture overall).
Instead of potentially creating a valuable GPL project that pushes other users towards GPL/open source, you might end up making your project a sort of "commodity" easily available to all closed-source developers for a moderate cost in tokens...
He explicitly states that the AI training concerns are not about legal GPL violations but about going against his licensing intentions (and those seem very much in line with the "copyleft spirit" from what I can tell).
My take is that the LLM emergence "threatens" the whole copyleft framework in a way similar to cloud services in the past (which led to the AGPL): closed source development can extract a lot of value from copyleft projects without contributing back in any way (to neither upstream nor their own users).
And companies are ultimately owned by people, including ordinary savers whose pension funds depend on them, and they employ people, so they contribute to society.