151–160 of 206 posts
But no, you always have to infiltrate and harass existing projects, because without the actual human developers your poor "AI" "contributions" are nothing.
I don't understand this anti-AI stance. Either the code works and is useful, and it should be accepted, or it doesn't work and it should be rejected. Does it really matter who wrote it?
That's why codebases die when they lose maintainers and forks often don't make it past the first few months.
LLM-generated code might work, but it's not backed by anyone's mental model. And the industry has had a long running term for code which is there but no-one understands it nor the reason behind it: legacy code.
Every time I encounter these kinds of policy, I can't help but wonder how these policies would be enforced: The people who are considerate enough to abide by these policies, are the ones who would have "cared" about the code qualities and stuff like that, so the policy is a moot point for these kinds of people. OTOH, the people who recklessly spam "contributions" generated from LLMs, by their very nature, would not r…
Several projects have rejected "AI" policies using your argument even though those projects themselves have contributor agreements or similar.
This inconsistency makes it likely that the cheating argument, when only used for "AI" contributions, is a pretext and these projects are forced to use or promote "AI" for a number of reasons.
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This seems like the kind of thing you'd want from a distro. Would you be happy if your doctor just started giving you new drugs because they're "new technology"? Or would you prefer it to go through rigorous rounds of testing and evaluation to figure out the potential problems?
I certainly hope my medical team is using AI tools, as they have been repeatedly demonstrated to be more accurate than doctors. Only downside is my last psychiatrist dropped me as a patient when he left his practice to start an AI company providing regulatory compliance for, essentially, Dr. ChatGPT.
AI is not a new tool - transformer-based LLMs are. Which is what this post is about.
The latter are very known to be a LOT LESS accurate, and still are very prone to hallucinate. This is just a fact. For your health I hope no one of your medical team is using the current generation for anything else than casual questions.
I'm not an opponent, and I don't think straight up banning LLM-generated code commits is the right thing, but I can understand their stance.
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Where did you disclose it?
Only after getting reviews so it is hidden by default: https://github.com/llvm/llvm-project/pull/146970#issuecommen...
Perhaps the most telling portion of their decision is: Quality concerns. Popular LLMs are really great at generating plausibly looking, but meaningless content. They are capable of providing good assistance if you are careful enough, but we can't really rely on that. At this point, they pose both the risk of lowering the quality of Gentoo projects, and of requiring an unfair human effort from developers and users to…
LLMs trained on open source make the common mistakes that humans make.
No, made. Which is a very important difference.
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Only after getting reviews so it is hidden by default: https://github.com/llvm/llvm-project/pull/146970#issuecommen...
Disclosing that you used AI three days after making the PR, after 4 people had already commented on your code, doesn't sit right with me. That's the kind of thing that should be disclosed in the original PR message. Especially so if you are not confident in the generated code
This might get me in trouble, but with all the negativity I’m seeing here I’ve got to ask. Why do you care? Their sandbox their rules, and if you care because you want to contribute you’re still free to do so. Unless you’re an LLM I guess, but the rest of us should have no problem. The negativity just seems overblown. More power to them, and if this was a bad call they’ll revisit it.
Exactly this. It's their decision to make; their consequences as well.
Then again I would have bet $1000 that gentoo disappeared 15 years ago. Probably around 2009? I legitimately havent even heard about them since at least that long.
So rejecting contributions from who might even still be around seems like a bad decision.
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Go look at the PR man, it's pretty clear that he hasn't just dumped out LLM garbage and has put serious effort and understanding into the problem he's trying to solve. It seems a little mean to tell him to stop coding forever when his intentions and efforts seem pretty positive for the health of the project.
One of resolved conversation contains a comment "you should warn about incorrect configuration in constructor, look how it is done in some-other-part-of-code." This means that he did not put serious effort into understanding what, when and why others do in a highly structured project like LLVM. He "wrote" the code and then dumped "written" code into community to catch mistakes.
There are pitfalls everywhere. It’s not so small that you can get everything in your head with only a reading. You need to actually engage with the code via contributions to understand it. 100+ comments is not an exceptional amount for early contributions.
Anyway, LLVM is so complex I doubt you can actually vibcode anything valuable so there are probably a lot of actual work in the contribution.
There is a reason the community didn’t send them packing. Onboarding new comer is hard but it pays off.
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Onboarding a new contributor implies you’re investing time into someone you’re confident will pay off over the long run as an asset to the project. Reviewing LLM slop doesn’t grant any of that, you’re just plugging thumbs into cracks in the glass until the slop-generating contributor gets bored and moves on to another project or feels like they got what they wanted, and then moves on to another project. I accept that…
>Onboarding a new contributor implies you’re investing time into someone you’re confident will pay off over the long run as an asset to the project. No you don't. And if you're that entitled to people's time you will simply get no new contributors.
Trying to understand a problem and taking some time to work out a solution proves that you’re actually trying to learn and be helpful, even if you’re green. Using a LLM to generate a nearly-thousand-line PR and yeeting it at the maintainers with a note that says “I don’t really know what this does” feels less hopeful.
I feel like a better use of an LLM would be to use it for guidance on where to look when trying to see how pieces fit together, or maybe get some understanding of what something is doing, and then by one’s own efforts actually construct the solution. Then, even if one only has a partial implementation, it would feel much more reasonable to open a WIP PR and say “is this on the right track?”