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Linux creator Linus Torvalds puts foot down on anti-AI comments
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this post was submitted on 16 Jul 2026
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All it takes is one person using an LLM tainted with proprietary code which then just gives them that code line for line to undo decades of courtroom defense.
Not only that, but AI output can't be licensed/copyrighted. The GPL license no longer covers the kernel in legal terms.
The uncopyrightability of AI-written code only applies to the actual strings of code generated by an AI, not to the entire project.
A person could ignore the GPL if they only copied the AI-written portions. But, how could they know for sure which lines were AI generated and which were not? A wrong choice would leave them civilly liable for copyright violation and all they stand to gain would be tiny portions of the Linux kernel code which are worthless by themselves.
There's no reason to steal the AI generated portions and risk a lawsuit, when you can just generate your own code.
There seems to be legal discussions about that. It’s not quite as simple as you say:
https://kpmg-law.de/en/ai-and-copyright-what-is-permitted-when-using-llms/
Yeah any decision would be on a case by case basis, which is normally something you'd want to avoid.
I've seen a couple of Linux devs talk about how they just give a prompt to claude and walk away leaving it alone to spit out the code, none of which can be licensed as GPL. But good luck working out what specific lines of what specific patches of theirs used an LLM vs. were re-written or such.
While I share Linus opinion on LLMs, I think doing this shit is extremely stupid and lazy.
And extremely abusive, since they don’t review the code fully, but a human must review the whole commit before accepting it. They save their time but consume that of others.
Ist that a common thing that LLMs using proprietary code for coding tasks?
Because I don’t think so.
They use everything for everything, that's the big issue. Also gpl code. Anything they can trawl through they use. And replicate, in part or in full.
They take code snippets and copy and paste them? Or do they create own code based on what they’ve learned by trawling?
LLMs don't "create". Under the hood, they're tokenizing the queries, looking for "clouds" of tokens that are similar to the query, then returning a sequence of tokens (with some random noise thrown in) that match what their training data says the answer should be.
In short: all LLM code is an amalgamation of their training data by definition. If there's nothing similar in there, it's literally not possible for it to be part of any response.
You’re exactly right. I should have used „generate“ instead of „create“.The point is I don’t think LLMs normally use copyrighted code in a way that would hurt open source projects.
Lol, so how do humans code in comparison?
Did you purposely respond like an AI?
By copy pasting from Stack Overflow
Human programmers at least can tell you where they got a snippet they copied, whether it was in the docs, stack overflow or elsewhere, and you can try to keep attribution if you care about compliance. Not only that, but most of our skills are related to designing stuff and recognizing which pattern to use, the specific implementation isn't necessary the same unless we go look for whatever we saw in the past, as our memories don't just record everything and repeat it word by word. And after picking up a new language or framework I only need to look around when using a third party library or some API I'm less familiar with, or when something breaks.
I don't know. I'm not a lawyer, and copyright for code was a hot mess even before LLMs got involved. With how many opportunistic copyright/patent trolls there are and how easily convinced judges have been in the past, it could go either way.
The good programmers normally code by breaking down the problem into constituent parts and logically working through the problem, step by step. What differentiates this from tokenization is that instead of just looking for code that is similar for a similar problem, programmers can usually understand the effects of each line of code, visualize what the state of each variable will be in that step (or dump out the variables to look directly if unsure), and then move on to the next step. This logical problem-solving approach is fundamentally different from a tokenization+noise looking for a similar-looking problem approach. For one thing, you can solve problems that haven't been solved before.