this post was submitted on 16 Jul 2026
155 points (96.4% liked)
Linux
14365 readers
326 users here now
A community for everything relating to the GNU/Linux operating system (except the memes!)
Also, check out:
Original icon base courtesy of lewing@isc.tamu.edu and The GIMP
founded 3 years ago
MODERATORS
you are viewing a single comment's thread
view the rest of the comments
view the rest of the comments
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?
By copy pasting from Stack Overflow
Did you purposely respond like an AI?
Damn, I forgot the em dash.
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.