121–130 of 427 posts
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Can't release someone else's proprietary source under a "do whatever the fuck you want" license and actually do whatever the fuck you want, without getting sued.
It’d be like trying to squeeze blood from a stone
This seems absolutely impossible to enforce. All my editors give me AI assisted code hints. Zed, cursor, VS code. All of them now show me autocomplete that comes from an LLM. There's absolutely no distinction between that code, and code that I've typed out myself. It's like complaining that I may have no legal right to submit my stick figure because I potentially copied it from the drawing of another stick figure. I'…
> I'm firmly convinced that these policies are only written to have plausible deniability when stuff with generated code gets inevitably submitted anyway. Of course it is. And nobody said otherwise, because that is explicitly stated on the commit message: [...] More broadly there is, as yet, no broad consensus on the licensing implications of code generators trained on inputs under a wide variety of licenses And in t…
Don’t be ridiculous. The majority of people are in fact honest, and won’t submit such code; the major effect of the policy is to prevent those contributions.
Then you get plausible deniability for code submitted by villains, sure, but I’d like to hope that’s rare.
This is signed off primarily by RedHat, and they tend to be pretty serious/corporate. I suspect their concern is not so much whether users have own the copyright to AI output but rather the risk that AI will spit out code from its training set that belongs to another project. Most hypervisors are closed source and some are developed by litigious companies.
> but rather the risk that AI will spit out code from its training set that belongs to another project. this is everything that it spits out
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The way I interpret it is that if you brainstorm using ChatGPT but write your own code using the ideas created in this step that would be fine, the reviewer wouldn't suspect the code of being AI generated because you've made sure it fits in with the project and actually works. The exact wording here is that they will reject changes they suspect of being AI generated, not that you can't have read anything AI generated…
What if the code is AI generated and the developer that drove it also understands the code and can explain it?
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It's happening slowly all around. It's not obvious because people producing high quality stuff have no incentive at all to mark their changes as AI-generated. But there are also local tools generated faster than you could adjust existing tools to do what you want. I'm running 3 things now just for myself that I generated from scratch instead of trying to send feature requests to existing apps I can buy. It's only goi…
Can you show these 3 things to us?
The others are just too specific for me to be useful for anyone else: an android app for automatic processing of some text messages and a work scheduling/prioritising thing. The time to make them generic enough to share would be much longer than creating my specific version in the first place.
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Had someone higher up ask about something in my area of expertise. I said I didn't think is was possible, he followed up with a chatGPT conversation he had where it "gave him some ideas that we could use as an approach", as if that was some useful insight. This is the same people that think that "learning to code" is a translation issue they don't have time for as opposed to experience they don't have.
A friend experienced a similar thing at work - he gave a well-informed assessment of why something is difficult to implement and it would take a couple of weeks, based on the knowledge of the system and experience with it - only for the manager to reply within 5 min with a screenshot of an (even surprisingly) idiotic ChatGPT reply, and a message along the lines of "here's how you can do it, I guess by the end of the…
A far too common trap people fall into is the fallacy of "your job is easy as all you have to do is , but my job is hard because ..."
Statistically generated text (token) responses constructed by LLM's to simplistic queries are an accelerant to the self-aggrandizing problem.
Oh hey, the thing I predicted in my blog titled "yes i will judge you for using AI" happened lol Basically I think open source has traditionally HEAVILY relied on hidden competency markers to judge the quality of incoming contributions. LLMs throw that entire concept on its head by presenting code that has competent markers but none of the backing experience. It is a very very jarring experience for experienced indiv…
I've started seeing this at work with coworkers using LLMs to generate code reviews. They submit comments which are way above their skill level which almost trick you in to thinking they are correct since only a very skilled developer would make these suggestions. And then ultimately you end up wasting tons of time proving how these suggestions are wrong. Spending far more time than the person pasting the suggestions…
So it goes back for changes. It returns the next day with complete rewrites of large chunks. More "lgtm" from others. More incredibly obvious flaws, race conditions, the works.
And then round three repeats mistakes that came up in round one, because LLMs don't learn.
This is not a future style of work that I look forward to participating in.
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This isn't 100% true meaning it isn't well settled. Have people already forgotten Google vs Oracle? Google ended up winning that after years and years but the judgements went back and forth and there are around 4 or 5 guidelines to determine whether something is or isn't fair use and generative AI would fail at a few of those.
Google vs. Oracle was about whether APIs are copyrightable, which is an important issue that speaks to antitrust. Oracle wanted the interface itself to be copyrighted so that even if someone reproduced the API from a description of it, it would infringe. The implication being that components which clone an API would be infringing, even though their implementation is original, discouraging competitors from making API-…
In addition to the Structure, Sequence and Organization claims, the original filing included a claim for copyright violation on 9 identical lines of code in rangeCheck(). This claim was dropped after the judge asked Oracle to reduce the number of claims, which forced Oracle to pare down to their strongest claims.
Open source and libre/free software are particularly vulnerable to a future where AI-generated code is ruled to be either infringing or public domain. In the former case, disentangling AI-edits from human edits could tie a project up in legal proceedings for years and projects don't have any funding to fight a copyright suit. Specifically, code that is AI-generated and subsequently modified or incorporated in the res…
> or public domain https://news.artnet.com/art-world/ai-art-us-copyright-office... https://en.wikipedia.org/wiki/Monkey_selfie_copyright_disput... Im pretty sure that this ship has sailed.
Oh hey, the thing I predicted in my blog titled "yes i will judge you for using AI" happened lol Basically I think open source has traditionally HEAVILY relied on hidden competency markers to judge the quality of incoming contributions. LLMs throw that entire concept on its head by presenting code that has competent markers but none of the backing experience. It is a very very jarring experience for experienced indiv…