Comment by anilgulecha
2 months ago
> translation.
It's not technically a translation, it's a re-implementation, with test suites acting as the destination. If it was a file by file translation your argument would have been valid.
2 months ago
> translation.
It's not technically a translation, it's a re-implementation, with test suites acting as the destination. If it was a file by file translation your argument would have been valid.
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)
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
5 replies →
> 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).
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Wouldn't a re-implementation be akin to 'heres how it works, write the code' rather than 'heres the code, redo it in rust'?