We now note that that we do not waive our attribution requirements for Spritely Goblins, which are present in Apache v2 (and for that matter, CC BY, CC BY-SA, and most FOSS licenses) https://codeberg.org/spritely/goblins/pulls/998/files
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@bkuhn @copiesofcopies While I appreciate being forthcoming, you are correct, I don't agree with feeding the torment nexus to defeat the torment nexus. I think using Claude is just helping them build more torment nexus, while normalize a situation that puts us in a legally dubious situation where we were previously relatively legally strong, and eroding community trust and shared understanding in the process.
@bkuhn @copiesofcopies I think the situation is more acceptable when using fully "local models", it doesn't erase all the concerns, but it at least improves user agency and autonomy. But overall, "local models" are mostly for "localwashing"; people like to bring them up as an alternative that nobody uses. Likewise, using LLMs to *find problems*, I don't have a problem with; search-space usage is one thing, but generative is another, in terms of social impact.
I also think that there are ways to improve the reliability of these systems, make them cheaper, and understandability of what they are doing, with neurosymbolic approaches, but that work hasn't advanced yet, and the current situation is pretty dismal. I really don't believe that we can vibe our way out of this mess, and I'm afraid we're going to see important projects, including Linux, head down the vibe bobsled https://dustycloud.org/blog/faulty-towers-vibe-sickness-and-the-vibe-bobsled/
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@bkuhn @copiesofcopies I think the situation is more acceptable when using fully "local models", it doesn't erase all the concerns, but it at least improves user agency and autonomy. But overall, "local models" are mostly for "localwashing"; people like to bring them up as an alternative that nobody uses. Likewise, using LLMs to *find problems*, I don't have a problem with; search-space usage is one thing, but generative is another, in terms of social impact.
I also think that there are ways to improve the reliability of these systems, make them cheaper, and understandability of what they are doing, with neurosymbolic approaches, but that work hasn't advanced yet, and the current situation is pretty dismal. I really don't believe that we can vibe our way out of this mess, and I'm afraid we're going to see important projects, including Linux, head down the vibe bobsled https://dustycloud.org/blog/faulty-towers-vibe-sickness-and-the-vibe-bobsled/
@bkuhn @copiesofcopies
I think we should be pushing back on these things. I'm worried and dissappointed that FOSS leadership isn't. I'm really worried we might never recover from the damage that's already been done. -
@bkuhn @yo8rzz @cwebber @trashheap
“Transformative” in the context of fair use doesn’t necessarily follow the word’s colloquial meaning. A work is transformative with respect to another if it adds “new expression, meaning, or message” to the original work. Compilation is more like translation, which is not considered transformative—a translation is a derivative work that must be licensed.
Ultimately though, this situation was arrived at not through careful reasoning about definitions but through court cases presenting specific facts before specific judges. So object code is basically deemed the same work as source code as a matter of law, and how we arrived there has nothing to do with the definition of “transformative.” It’s just the way the cookie crumbled.
@copiesofcopies @bkuhn @cwebber @trashheap The derivative aspect of LLM output seems pretty clear cut to me, after all, without being derivative how else can it reproduce facsimili of the original? There is no other mechanism to explain it sufficiently other than derivation and statistical amalgamation with numerous other sources by means of intermediate storage in an appropriate format for such computation, namely floating point.
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@copiesofcopies @bkuhn @cwebber @trashheap The derivative aspect of LLM output seems pretty clear cut to me, after all, without being derivative how else can it reproduce facsimili of the original? There is no other mechanism to explain it sufficiently other than derivation and statistical amalgamation with numerous other sources by means of intermediate storage in an appropriate format for such computation, namely floating point.
@yo8rzz @bkuhn @cwebber @trashheap
Again, it’s a mistake to apply the colloquial meaning of “derivative” to its use as a term of art in copyright law. Transformative works are necessarily “derivative” in the colloquial sense, and often even in the legal sense, but may nonetheless be deemed a fair use (depending on how the court applies the various factors of the fair use analysis).
And where models reproduce substantial portions of their reasoning data verbatim, courts are less likely to find fair use. But plaintiffs have had a harm time showing that in many cases, including the CoPilot case, because when you train on enough data, the likelihood of reproducing a single reasoning source verbatim is low.
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@bkuhn @copiesofcopies I think the situation is more acceptable when using fully "local models", it doesn't erase all the concerns, but it at least improves user agency and autonomy. But overall, "local models" are mostly for "localwashing"; people like to bring them up as an alternative that nobody uses. Likewise, using LLMs to *find problems*, I don't have a problem with; search-space usage is one thing, but generative is another, in terms of social impact.
I also think that there are ways to improve the reliability of these systems, make them cheaper, and understandability of what they are doing, with neurosymbolic approaches, but that work hasn't advanced yet, and the current situation is pretty dismal. I really don't believe that we can vibe our way out of this mess, and I'm afraid we're going to see important projects, including Linux, head down the vibe bobsled https://dustycloud.org/blog/faulty-towers-vibe-sickness-and-the-vibe-bobsled/
Indeed, we should all be looking at more at local models. @ossguy suggested to me just yesterday that perhaps big systems that rely on these soon-to-go-away gratis “token credits” should be run in parallel on local models and output compared to verify that the local models can serve as a drop-in replacement for the proprietary network LLM-gen-AI services. It's an excellent idea that should be pursued with rigor.
Cc: @copiesofcopies
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@bkuhn @copiesofcopies While I appreciate being forthcoming, you are correct, I don't agree with feeding the torment nexus to defeat the torment nexus. I think using Claude is just helping them build more torment nexus, while normalize a situation that puts us in a legally dubious situation where we were previously relatively legally strong, and eroding community trust and shared understanding in the process.
@cwebber @bkuhn @copiesofcopies the masters tools will never dismantle the master’s house
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@bkuhn @copiesofcopies I think the situation is more acceptable when using fully "local models", it doesn't erase all the concerns, but it at least improves user agency and autonomy. But overall, "local models" are mostly for "localwashing"; people like to bring them up as an alternative that nobody uses. Likewise, using LLMs to *find problems*, I don't have a problem with; search-space usage is one thing, but generative is another, in terms of social impact.
I also think that there are ways to improve the reliability of these systems, make them cheaper, and understandability of what they are doing, with neurosymbolic approaches, but that work hasn't advanced yet, and the current situation is pretty dismal. I really don't believe that we can vibe our way out of this mess, and I'm afraid we're going to see important projects, including Linux, head down the vibe bobsled https://dustycloud.org/blog/faulty-towers-vibe-sickness-and-the-vibe-bobsled/
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@cwebber @bkuhn @copiesofcopies the masters tools will never dismantle the master’s house
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@yo8rzz @bkuhn @cwebber @trashheap
Again, it’s a mistake to apply the colloquial meaning of “derivative” to its use as a term of art in copyright law. Transformative works are necessarily “derivative” in the colloquial sense, and often even in the legal sense, but may nonetheless be deemed a fair use (depending on how the court applies the various factors of the fair use analysis).
And where models reproduce substantial portions of their reasoning data verbatim, courts are less likely to find fair use. But plaintiffs have had a harm time showing that in many cases, including the CoPilot case, because when you train on enough data, the likelihood of reproducing a single reasoning source verbatim is low.
The CoPilot case¹ was ill-constructed from get. 'Twas brought by folks whose enthusiasm (for a payday from FOSS in a hastily & ill-conceived class action) exceeded their desire to build the correct & ethically sound case for adjudicating the problems with LLM-gen-AI with respect to FOSS.
As a matter of fact, one *must* make a copy (and, typically, receive distribution) to train LLM-gen-AI, and one needs a license for that.¹ https://sfconservancy.org/news/2022/nov/04/class-action-lawsuit-filing-copilot/
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@cwebber @bkuhn @copiesofcopies the masters tools will never dismantle the master’s house
But FOSS' success up until this point has shown the exact opposite.
FOSS was bootstrapped by using proprietary software every single day for more than a decade, at least.
Most FOSS developers regularly used proprietary technologies daily for their work for the entirety of FOSS' history.
Plus, what @copiesofcopies said:
https://fedi.copyleft.org/@copiesofcopies@social.coop/117457049015278425Cc: @cwebber
#LLMGenAI #LLM #AI #FOSS #SoftwareFreedom #OpenSource #FreeSoftware
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The CoPilot case¹ was ill-constructed from get. 'Twas brought by folks whose enthusiasm (for a payday from FOSS in a hastily & ill-conceived class action) exceeded their desire to build the correct & ethically sound case for adjudicating the problems with LLM-gen-AI with respect to FOSS.
As a matter of fact, one *must* make a copy (and, typically, receive distribution) to train LLM-gen-AI, and one needs a license for that.¹ https://sfconservancy.org/news/2022/nov/04/class-action-lawsuit-filing-copilot/
@bkuhn @yo8rzz @cwebber @trashheap
I agree about the CoPilot case. One of several purely conceived case hurriedly filed in a gold rush.
Copying is an essential step to training, but there’s strong support for that copying being fair use if the ultimate use is. That’s what the judge found re: book ripping in Anthropic v. Bartz, on the basis of decisions in multiple cases against Google in the early 2010, where plaintiffs alleged that intermediate copying to enable caching, image search, etc. was infringing.
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We are more in agreement than you realize:
I guess now is a good as time as any to “come out”: I'm using #Anthropic's #Claude on a regular basis to help me figure out what types of policies we should set for reasonable & ethical use of #LLMGenAI in #FOSS, & also to actually improve FOSS codebases.
I believe it is reasonable to use proprietary technologies as long as our eyes remain on the prize of defeating those technologies.
@cwebber, I suspect, doesn't agree.
@bkuhn @copiesofcopies @cwebber
imo, it is not beneath anthropic (or other AI companies) to steer their models - either generally or on a targeted basis - toward outputs that represent their own best interests rather than that of FOSS or of the wider public, even if only in subtle ways.do you think working out policy with humans exclusively, instead, has particular downsides that can't be overcome?
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I expect the world looks very different from where you’re sitting than from where I am. Every time I look at my (FOSS-heavy) fedi feed, I’m struck by the contrast between the AI pessimism & skepticism here versus everywhere else I look.
LLMs have become part of everyday life for vast swaths of ordinary people. Skilled software developers routinely use them to produce code that’s far from slop. And probably most importantly, the AI industry is widely viewed as the most significant driver of U.S. economic growth and competitive advantage going right now.
All of those things surely sound negative to you, but they’re descriptively true. And against that backdrop, I see very little possibility that US courts will cut OpenAI et al off at the knees, even though we’ll surely see adverse rulings in cases of obvious misappropriation (Anthropic’s trove of pirated books, Sora reproducing entire songs from its training data).
With genuine respect to @copiesofcopies (and also to @bkuhn
please consider the statement "vape pens have become part of everyday life for vast swaths of ordinary people."The Overton Window is an observation of an aggregate social phenomenon. IT WAS NOT PROSCRIBED AS A SOCIAL VALUE. (Moreover it is trivially weaponized by authoritarians, not-coincidentally aligned with the technologies you defend here.)
I genuinely believe that Jeffrey Dahmer deserved a vigorous criminal defense. But I hope you see that arguments like the ones you just proposed make non-lawyers think of lawyers as amoral.
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@bkuhn @copiesofcopies
I think we should be pushing back on these things. I'm worried and dissappointed that FOSS leadership isn't. I'm really worried we might never recover from the damage that's already been done.@cwebber amen
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With genuine respect to @copiesofcopies (and also to @bkuhn
please consider the statement "vape pens have become part of everyday life for vast swaths of ordinary people."The Overton Window is an observation of an aggregate social phenomenon. IT WAS NOT PROSCRIBED AS A SOCIAL VALUE. (Moreover it is trivially weaponized by authoritarians, not-coincidentally aligned with the technologies you defend here.)
I genuinely believe that Jeffrey Dahmer deserved a vigorous criminal defense. But I hope you see that arguments like the ones you just proposed make non-lawyers think of lawyers as amoral.
Think what you like about lawyers. My point was simply that courts tend to avoid interpreting the law in a way that destroys industries or massively unsettles the development of useful technology, when they have another option. They’ll probably do that here, not least because the caselaw (IMO) generally supports fair use.
As for whether LLMs are a net social harm, judges will generally take the view that that’s for congress to decide and legislate upon, rather than a matter for courts to decide.
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@bkuhn @copiesofcopies
I think we should be pushing back on these things. I'm worried and dissappointed that FOSS leadership isn't. I'm really worried we might never recover from the damage that's already been done.@cwebber @bkuhn @copiesofcopies I agree but believe that using #LLM tech for X is not acceptable almost whatever X is (certainly for finding problems is not excusable as a category).
Using them at the very least means normalising their use, first for yourself, then others and makes it much harder to say what is and isn't ok.
Anything that helps this tech is helping those behind it, techno fascism (ultimately genocide) climate Armageddon (also genocide) and numerous other widespread harms.
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We are more in agreement than you realize:
I guess now is a good as time as any to “come out”: I'm using #Anthropic's #Claude on a regular basis to help me figure out what types of policies we should set for reasonable & ethical use of #LLMGenAI in #FOSS, & also to actually improve FOSS codebases.
I believe it is reasonable to use proprietary technologies as long as our eyes remain on the prize of defeating those technologies.
@cwebber, I suspect, doesn't agree.
@bkuhn @copiesofcopies @cwebber it's ok, we can get by without you
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Think what you like about lawyers. My point was simply that courts tend to avoid interpreting the law in a way that destroys industries or massively unsettles the development of useful technology, when they have another option. They’ll probably do that here, not least because the caselaw (IMO) generally supports fair use.
As for whether LLMs are a net social harm, judges will generally take the view that that’s for congress to decide and legislate upon, rather than a matter for courts to decide.
@copiesofcopies You have amplified your assertion that courts defend the profitable status quo without regard to social cost.
Which was the critique I made, which I consider morally damning to the entire system.
(Also, since we are lawyering, read what I wrote closely. I was not pouring scorn on lawyers, I was pouring scorn on your argument.)
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@bkuhn @copiesofcopies
I think we should be pushing back on these things. I'm worried and dissappointed that FOSS leadership isn't. I'm really worried we might never recover from the damage that's already been done.@cwebber Is this whole free software endeavor about producing more and faster, or is it about empowering people and fostering collectives?
This is the question those LLMs companies have forced us to answer, thereby breaking the alignment that existed so far between industry & “open source” on one hand, and people focusing and user freedom and autonomy.
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But FOSS' success up until this point has shown the exact opposite.
FOSS was bootstrapped by using proprietary software every single day for more than a decade, at least.
Most FOSS developers regularly used proprietary technologies daily for their work for the entirety of FOSS' history.
Plus, what @copiesofcopies said:
https://fedi.copyleft.org/@copiesofcopies@social.coop/117457049015278425Cc: @cwebber
#LLMGenAI #LLM #AI #FOSS #SoftwareFreedom #OpenSource #FreeSoftware
And we shed them as soon as it became practical to do so.
You will never find it practical to shed Claude, because:
1. you will never be able to afford the necessary hardware to do so (Moore's law is dead),
2. you will never obtain an adequate corpus of training data (because you, lacking billions of dollars, are actually subject to copyright), and
3. you will be prohibited by law to do so (because compliance with AI regulations costs billions).
