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Cake day: June 30th, 2023

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  • Well idc about the semantics, the fact is it is useful and there is a good reason to use it. Personally I think the “they can’t see or reply to you anymore” style of “block” is super toxic and Reddit switching to that model was a major factor in its decline. It is very easily weaponized and basically amounts to giving powerusers moderation powers. If someone who makes a lot of popular posts or top level comments blocks you under that model, that instantly limits your ability to participate, and no one ever gets to know this is happening or to what extent. The most obvious way this gets abused is by commercial spammers trying to monopolize relevant subs by blocking everyone who may call them out or post competing content, but it also shuts down disagreement and debate; if you have something controversial to say and don’t want it to look like any good objections exist, you can just silence your best critics. It also gets commonly used by people right after they write an inflammatory reply to ensure they get the last word.




  • If that is the case, is chardet 7.0.0 a derivative work of chardet, or is it a public domain LLM work? The whole LLM project is fraught with questions like these

    I think the reimplementation stuff is a separate question because the argument for it working looks a lot stronger, and because it doesn’t have anything to do with the source material having LLM output in it. Also if this method holds as legally valid, it’s going to be easier to just do that than justify copying code directly (which would probably have to only be copies of the explicitly generated parts of the code, requiring figuring out how to replace the rest), which means it won’t matter whether some portion of it was generated. I don’t see much reason to think that a purist approach to accepting LLM code will offer any meaningful protection.

    I’m mostly just playing along with your thought experiment. As I said, we know that projects are already accepting LLM code into projects that are nominally copyleft.

    So what though? If they aren’t entirely generated, you can’t make a full fork, and why would a partial fork be useful? If it isn’t disclosed what parts are AI, you can’t even do that without risking breaking the law.


  • but if they instead say that they copied the work into their LLM and produced a copy without protections (as chardet has done), the courts might be less willing to afford the project copyright protections if the project itself was making use of the same copyright stripping technology to strip others’ work to claim protections over copied work.

    ianal but does it even work like that? Is there any specific reason to think it does? I don’t believe you really get credit for purity and fairness vibes in the legal system. Same goes for the idea that code where it is ambiguous whether it is AI output could be considered public domain, seems kind of implausible, is there actually any reason to think the law works that way? If it did, then any copyrighted work not accompanied by proof of human authorship would be at risk, uncharacteristic for a system focused on giving big copyright holders what they want without trouble.

    the only code that may ultimately be protected is closed source code - you can’t copy it if you don’t have the source.

    There is no way, leaks happen, big tech companies have massive influence, a situation where their code falls into the public domain as soon as the public gets their hands on it just isn’t realistic. I feel suspicious that many of these concerns are coming from a place of not wanting LLM code in open source projects for other reasons, rather than the existence of a strong legal case that it represents a real and serious threat to copyleft licensing.


  • AI code damages copyleft projects no matter what - we know that some projects are already accepting AI generated code, and they don’t ask you to hide it - it is all in the open.

    I don’t see how that follows or contradicts what I’m saying though. They could hide it, easily. Even if they don’t hide it, how useful would it really ever be to only use the portions of the codebase that have been labelled as having been AI generated? Can one even rely on those labels? Making use of the non-copyrightability of AI output to copy code in otherwise unauthorized ways does not seem like a straightforward or legally safe thing to do. That’s especially the case because high profile proprietary software projects also make heavy use of AI, it doesn’t seem likely the courts will support a legal precedent that strips those projects of copyright and allow anyone to use them for whatever. So basically I’m not at all convinced about the idea that AI code damages copyleft projects, it seems unlikely to be a problem in practice.


  • The only portions of the work that can be copyrighted are the actual creative work the person has put into the work.

    Ok, but it’s not like everyone is documenting exactly which parts are generated, curated, or human written.

    Maintainers cannot prevent the LLM code from being incorporated into closed source projects without reciprocity

    Say someone incorporates GPL code without attribution, and gets sued for doing so. They try to make the argument in court that the source material they used is not copyrighted, because of AI. Won’t they have to prove that the parts they used were actually AI output for this defense to work? It isn’t like people are going around ignoring the copyright on things in general if they look like they were probably generated with AI, that isn’t enough to be safe from prosecution, because you usually can’t know the exact breakdown. It seems like preventing this loophole from being used would be as simple as keeping it ambiguous and not allowing submissions that positively affirm being entirely AI generated.





  • chicken@lemmy.dbzer0.comtoScience Memes@mander.xyz"Trippy" Reality
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    4 days ago

    IMO the term “hallucinogenic” undersells what psychedelics do in some ways. There is an interpretative layer of abstraction that naturally builds up between you and what you are perceiving. This is useful because it lets you make assumptions about and mostly ignore objects that you know are not necessary to pay attention to, and not be overwhelmed by the experience of being actively aware of all their details, but it also prevents us from considering and experiencing what is behind that layer of preconception.

    Obviously there’s also a lot of other things our brains do that is interpretive or corrective, but it’s really remarkable to be able to see the world without that one in particular, which is one of the more striking effects of those drugs, and it happens on doses lower than the ones that produce especially vivid hallucinations.







  • It doesn’t read like AI slop. This is a well structured essay that has a moderately complex point and efficiently explains and gives specific evidence for that point with citations. It even has a (highlighted for emphasis, near the beginning) note explaining to what extent AI was used:

    This article is written by me and spell checked with AI. Many of the images are generated by AI and are mostly to break up the wall of text.

    The images mostly actually do add to it by illustrating the concepts and being relevant. I’d only really criticize the first (fiber internet infrastructure vs water supply infrastructure) one for being a little lazy in having a duplicate text bubble, and the choice to format with text bubbles with arrows when the arrows don’t actually point to anything and it would have been better as bullet points or something.