418
Linus Torvalds used AI to fix a Linux bug, and now LLM critics on Linux face an uncomfortable choice
(www.xda-developers.com)
this post was submitted on 01 Sep 2026
418 points (90.5% liked)
Technology
87773 readers
3290 users here now
This is a most excellent place for technology news and articles.
Our Rules
- Follow the lemmy.world rules.
- Only tech related news or articles.
- Be excellent to each other!
- Mod approved content bots can post up to 10 articles per day.
- Threads asking for personal tech support may be deleted.
- Politics threads may be removed.
- No memes allowed as posts, OK to post as comments.
- Only approved bots from the list below, this includes using AI responses and summaries. To ask if your bot can be added please contact a mod.
- Check for duplicates before posting, duplicates may be removed
- Accounts 7 days and younger will have their posts automatically removed.
Approved Bots
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
"oversight" is a myth. I'm pretty sure you can't oversight your way of plagiarism out of millions of training data sources that you don't even have on your local disk for comparison and reference.
(This isn't legal advice. I'm not a lawyer.)
you are confusing two issues here: oversight for the output of an ANN can very much achieve good results. as i explained in my post.
oversight over the output won't help you with copyright, water and energy consumption, slave labour and all the ethical issues further up the pipeline. but we don't need ANNs for big corpos to do all these evil things. we need oversight and real consequences for those corpos - no matter what they produce.
ANNs as a technology are old and have not fundamentally changed since Alan Turing. Sure, we have iterated and improved. But the fundamentals are the same. LLMs just made that old tech quite popular recently and introduced a "line go up" race. i do not believe that we will gain significant improvements from simply feeding more stolen works to the machine. A fraction of the MNIST dataset is enough to train an ANN on a 20 years old laptop to recognise the digits 0-9 reliably. The technology is sound, limited in its usability and detached from the big corpos.