Hacker News Reader

Comment by 20k | Hacker News Reader

Git is part of the LLM's training set though, so simply asking it to recreate git in another language is pretty equivalent. Like, you can almost certainly get these LLMs to output gits full source code with some prompting, so there's not that much difference (as much as we like to pretend that AI generated code has no copyright implications)

View on HN

As mentioned in another comment, it's even more clear cut in this case. They actually put the original git sources in their project repo and instructed the agent to use it as the "source of truth".

Simple thought experiment. If you handed this same agents.md file (https://github.com/gitbutlerapp/grit/blob/main/AGENTS.md#sou...) to a human software developer and let them work on exactly the same goal, would their output be considered a derivative work?

That's something I have been wondering. If I as a human want to make a clean room reimplementation of some API or application, I must not have read the source code of the original implementation. I don't see why this shouldn't apply to LLMs as well. If an LLM might have been trained on the original source code, it should be considered "tainted".

Yes, and realistically any code that LLMs produce is a derivative work of its training data. There's going to be a huge disaster licensing wise

I have absolutely no idea how LLMs got through anyone's legal departments, I guess the hope is that if everyone breaks the law enough, it'll just be fine

Problem is there's a lot more than a single repo in training data, the corpus is massive... Should the author of a blog post on cats also be compensated for simply being in the same training data as the git repo?

Honestly? Yes. This is why its such a problem that most of the training data was not used with permission, and without the correct copyright status or license associated with it

There's a lot of arguments about humans doing the same thing, but the reality is that humans and robots don't enjoy the same legal protection. Its clearly a derivative work of all of its training data

> Honestly? Yes.

Then it works both ways. Say I manage to generate essentially a ripoff of your copyrighted song, release it and make a ton of money, you now have to split that royalty with keyboard cat. And Joe bloggs. You'd end up fractions of pennies

> if everyone breaks the law enough, it'll just be fine

That's pretty much what happened, isn't it? These concerns were all discussed in the beginning back in 2022, and I recall answers from many here on HN along the lines of "oh well, we can't stop it now or we'll risk falling behind China in AI development"

So yeah, the laws went out the window a long time ago the moment our government and the people decided to just look the other way willingly in the name of "progress."

> the hope is that if everyone breaks the law enough, it'll just be fine

Ever since the early 2010s when companies were started with the business idea "unlicensed hotels" and "unlicensed taxis" and made the owners really, really rich, this is said pretty much out loud. Look for words like "regulatory risks" and similar.

Maybe it started with the unlicensed gambling fad before that? That also made a lot of people filthy rich. Every time you have something under special license, or insuance requirements, then of course there is a margin for you if you can skimp on the license and hire gig workers instead.

The LLM situation with copyright and derived works in the 2020s is similar. Someone is likely to be rich, but there is a clear regulatory risk to it.

> If I as a human want to make a clean room reimplementation of some API or application, I must not have read the source code of the original implementation.

That is the difference between necessary and sufficient. Clean-room is sufficient to guarantee avoiding copyright, but it is not necessary. The line legally is south of there, but that position was chosen because they didn’t want to crossing and it was easier to argue for legally in court.

tl;dr: clean room is overkill for avoiding copyright infringement

> Like, you can almost certainly get these LLMs to output gits full source code with some prompting, so there's not that much difference (as much as we like to pretend that AI generated code has no copyright implications)

Are you sure? LLMs are in some way a compressed version of their input but it's a pretty lossy compression (arguably this makes them more like a compression algorithm than a compressed version of the data). I'm not sure you can prompt a full, accurate, copy of a nontrivial codebase out of them. Even with zero temperature their accuracy is just not that high.

> I'm not sure you can prompt a full, accurate, copy of a nontrivial codebase out of them. Even with zero temperature their accuracy is just not that high.

Granted, these are some of the most widely spread texts, and not codebases, but just fyi: https://arxiv.org/pdf/2601.02671

> For Claude 3.7 Sonnet, we were able to extract four whole books near-verbatim, including two books under copyright in the U.S.: Harry Potter and the Sorcerer’s Stone and 1984 (Section 4).

That paper is basically using the LLM as a compression algorithm: it's prompting with some section of the book and it's reprompting if it doesn't give the right output. Notably this only works if you already have a copy of the book in question!

Distributed a compressed copy of something is still copyright infringement

You misunderstand my point: the LLM is not a losslessly compressed version of the text: you need to supply additional information from the original in order to 'extract' it from the LLM (and from that point of view, the extra information would be the compressed form).

Reply on news.ycombinator.com