But in my hatred, I began to wonder, could AI really be that bad?
It's been proven scientifically: https://machinelearning.apple.com/research/illusion-of-thinking Until there's a counter-study specifically regarding this one, there's no point in assuming AI is suddenly smart. The new agentic stuff just seems to be a while loop around the previous state-of-the-art lack of any intelligence.
I don't believe for a second YouTube didn't try to intentionally push slop, hoping users would be satisfied so that they could cut out human creators. I bet the only reason they're now backtracking is that people hate it.
The point I was making was rather, there is no guaranteed safe length and you probably don't want to make that call as a maintainer. Unless you're a lawyer that happens to do FOSS, I guess.
The same seems to be the case for KDE. It seems like GNOME also somewhat is (since they didn't ban AI for GTK+ or mutter or gnome shell, as far as I'm aware). It's quite frustrating to see.
I'm not a lawyer but I'm really unsure if there's even some safe guess like two lines. E.g. if you look at lyrics, I think people have been sued less - not that I would know for sure, though, and no idea if that allows any conclusions for code...
It could also simply be seen as a bad look no matter any risks, potentially the taking of code snippets from other projects that may have a significant code length, without attributing them properly. I find it sad.
The main confusing (or confused?) actor in the FOSS space in relation to this probably really is the Linux kernel.
I've seen so many projects reference significant LLM patches as acceptable "because the kernel does it". It continues to blow my mind that the kernel would accept such a risk.
Sad to see that it's accepted outside of the test cases at all. But good to see they're severely limiting it, at least.
Why do I find even minor LLM changes sad?
Because it moves the goalpost about what is okay to copy. If you brought a one-line change to a FOSS project in the past that you took out of the leaked MS Windows source code, you would have been scolded for risking such an explosive origin for such low gain. Nowadays with LLMs people seem to be trying to make that the new normal. I don't think that's a good path to take for the ecosystem.
And because no project should have to think about what's "copyright significant". If you reach that state, I feel like you should perhaps just reject it and have somebody rewrite it cleanly.
Perhaps submit yourself anyway and just put that explanation into the pull request. I don't think the list is designed to be super bullet proof, I was merged without directly linking any code too (although I suppose it's not too hard to find). At the end of the day, a lot of the internet runs on the honor system still, for better and for worse.
Curiously enough I wasn't able to actually find any lemmy commit marked as created with the help of AI, other than some bug located by AI without indication that an AI fix was used. I wonder if that means either they don't adhere to their own rule, or whether they're not actually using AI but just felt like really being pro-AI anyway. Why though? I'm so curious.
So how would that work given LLMs apparently can't do much other than rearrange/plagiarize the training data?
I think that's where the article writer's definition comes from. A model probably won't seem very open to most people if the output licensing isn't really compatible with free use.
Is that meant to be some sort of humorous remark regarding the OpenAI name? I think most observers would agree that the name isn't particularly fitting, so that seems like a fair observation.
The "open" criteria listed in the article seem applied inconsistently by the writer:
In our recent AI and Ethics article, "The open-source advantage in large language models (LLMs)," my co-authors and I operationalize this even more concretely: a model qualifies as open-source only when its architecture, training code, model weights, and training data are all publicly available under licenses that permit unrestricted use, modification, and redistribution. By that standard, very few models qualify. The Allen Institute’s OLMo, EleutherAI’s GPT-NeoX, and LLM360’s K2 are among the handful that meet these four criteria.
I just checked the first one, OLMo. It just ingests random web pages, as far as I can tell. How would that possibly qualify for "training data [...] available under licenses that permit unrestricted use"? Why does the article writer think it would?
How would anything but pure CC0 training data fit that, given attribution requirements are so common and I assume they're a restriction on use (that most models ignore)?
The article apparently not wanting to admit this, and/or not having done the basic research to check, makes it seem as bad to me as the open-washing it is complaining about.
Yup. And looking at the fallout from the other comments, seems like it may have been a good idea to take a stand.
(I don't like people becoming upset, but clearly some people embrace AI a little much, and if you look at Forgejo for example then you'd know Codeberg was always on some level anti AI due to the ethics and all that. And as far as I can tell, Codeberg always wanted to be a somewhat opinionated pro ethics code host. Now I understand some people don't like where the line has been drawn, but it's not suprising Codeberg wants to draw a line somewhere.)
It really is a scourge (my personal opinion).
And still no response to this from the kernel maintainers or the Linux Foundation: https://lore.kernel.org/lkml/e12330b9-c29e-45ca-9375-9e3d13426d85@horse64.org/T/
It's been proven scientifically: https://machinelearning.apple.com/research/illusion-of-thinking Until there's a counter-study specifically regarding this one, there's no point in assuming AI is suddenly smart. The new agentic stuff just seems to be a while loop around the previous state-of-the-art lack of any intelligence.
I don't believe for a second YouTube didn't try to intentionally push slop, hoping users would be satisfied so that they could cut out human creators. I bet the only reason they're now backtracking is that people hate it.
For what it's worth, there's this: https://codeberg.org/brib/slopfree-software-index
I don't use voyager beyond it being my favorite star trek series! 😁
are you saying people here may have been banned by communities without even knowing? fascinating :o I wouldn't even know how to check that
It seems like they do though, because
it's explicitly allowed
and beyond that,
some numbers suggest it's highly likely that it's happening with no public concern or pushback from the kernel leadership.
I've also brought up these concerns on the mailing list, with apparently no response from the maintainers, even though Linus was CC'ed here by another kernel dev. Specifically, my suggestion to not allow AI code submissions resulted in no response.
I'm not saying I would be owed a response. But the implications of that seem pretty clear.
The point I was making was rather, there is no guaranteed safe length and you probably don't want to make that call as a maintainer. Unless you're a lawyer that happens to do FOSS, I guess.
Sadly, LxQt is pro slop too:
The same seems to be the case for KDE. It seems like GNOME also somewhat is (since they didn't ban AI for GTK+ or mutter or gnome shell, as far as I'm aware). It's quite frustrating to see.
I'm not a lawyer but I'm really unsure if there's even some safe guess like two lines. E.g. if you look at lyrics, I think people have been sued less - not that I would know for sure, though, and no idea if that allows any conclusions for code...
It could also simply be seen as a bad look no matter any risks, potentially the taking of code snippets from other projects that may have a significant code length, without attributing them properly. I find it sad.
Well, that's sad. Who knows what potential unattributed plagiarism landmines are part of it then...
The main confusing (or confused?) actor in the FOSS space in relation to this probably really is the Linux kernel.
I've seen so many projects reference significant LLM patches as acceptable "because the kernel does it". It continues to blow my mind that the kernel would accept such a risk.
Sad to see that it's accepted outside of the test cases at all. But good to see they're severely limiting it, at least.
Why do I find even minor LLM changes sad?
Because it moves the goalpost about what is okay to copy. If you brought a one-line change to a FOSS project in the past that you took out of the leaked MS Windows source code, you would have been scolded for risking such an explosive origin for such low gain. Nowadays with LLMs people seem to be trying to make that the new normal. I don't think that's a good path to take for the ecosystem.
And because no project should have to think about what's "copyright significant". If you reach that state, I feel like you should perhaps just reject it and have somebody rewrite it cleanly.
Perhaps submit yourself anyway and just put that explanation into the pull request. I don't think the list is designed to be super bullet proof, I was merged without directly linking any code too (although I suppose it's not too hard to find). At the end of the day, a lot of the internet runs on the honor system still, for better and for worse.
Kind of funny (or sad?) that lemmy itself probably wouldn't make it on the list, given they seem adamant on allowing LLM coding: https://github.com/LemmyNet/lemmy-docs/pull/414/changes
Curiously enough I wasn't able to actually find any lemmy commit marked as created with the help of AI, other than some bug located by AI without indication that an AI fix was used. I wonder if that means either they don't adhere to their own rule, or whether they're not actually using AI but just felt like really being pro-AI anyway. Why though? I'm so curious.Update: seems like they don't put it into the commit log, just the merge request info: https://github.com/LemmyNet/lemmy/pull/6304
So how would that work given LLMs apparently can't do much other than rearrange/plagiarize the training data?
I think that's where the article writer's definition comes from. A model probably won't seem very open to most people if the output licensing isn't really compatible with free use.
Is that meant to be some sort of humorous remark regarding the OpenAI name? I think most observers would agree that the name isn't particularly fitting, so that seems like a fair observation.
The "open" criteria listed in the article seem applied inconsistently by the writer:
I just checked the first one, OLMo. It just ingests random web pages, as far as I can tell. How would that possibly qualify for "training data [...] available under licenses that permit unrestricted use"? Why does the article writer think it would?
How would anything but pure CC0 training data fit that, given attribution requirements are so common and I assume they're a restriction on use (that most models ignore)?
The article apparently not wanting to admit this, and/or not having done the basic research to check, makes it seem as bad to me as the open-washing it is complaining about.
(However, perhaps I'm misunderstanding something here?)
Yup. And looking at the fallout from the other comments, seems like it may have been a good idea to take a stand.
(I don't like people becoming upset, but clearly some people embrace AI a little much, and if you look at Forgejo for example then you'd know Codeberg was always on some level anti AI due to the ethics and all that. And as far as I can tell, Codeberg always wanted to be a somewhat opinionated pro ethics code host. Now I understand some people don't like where the line has been drawn, but it's not suprising Codeberg wants to draw a line somewhere.)