@bekkaboo@girlcock.club Linux itself is heavily using AI models. Therefore, every Linux distribution moving to recent kernel versions is heavily built on top of using AI models. Creating a Linux distribution not heavily using it would require a hard fork of the Linux kernel and many other projects.
It's unclear what would be accomplished by banning AI for a tiny portion of the code while continuing to use Linux, AOSP, Chromium and hundreds of other projects heavily using it. We'd still be benefiting from it.
GrapheneOS is currently defending its use of AI coding tools on Mastodon against complaints by various accounts claiming to be users.
We do not understand where you’re coming from or why you’re so incredibly angry with us. It’s not justified and does not make sense.
I’ve been a programmer for two thirds of my life up to this point. I don’t see how the machine that generates code that must be assumed to be broken, and statements about said code that must be assumed to be wrong, until both have been manually verified, because the “hallucination” issue is inherent to the design of LLMs and cannot be solved, is supposed to make my life easier. Especially since a well known problem in computer science is that writing code is more fun than reading it.
If you’re using AI for code generation, I hope you like reading code.
If you’re using AI to learn a repo, I hope you’re prepared to fact check everything it tells you.
If you’re using AI for code review before merging a PR, fucking yikes. What made you think the sycophant machine that once told users a soggy cereal bar was a great business opportunity and cannot even transcribe McDonald’s orders correctly was suitable for that purpose?
If you’re telling yourself it’s okay because there’s a human in the loop, please read some studies about decision fatigue and consider that increasing the number of critical decisions a person must make per day, while giving them a suggested answer that’s right 90% of the time and catastrophically wrong the remaining 10%, and the only way to tell the difference is to read in depth, might not have the desired effect. Especially if the human in question is then put under time pressure.
It’s funny because anyone seeing this as black and white clearly hasn’t ever opened an IDE.
I’ve been a programmer for two thirds of my life up to this point. I don’t see how the machine that generates code that must be assumed to be broken, and statements about said code that must be assumed to be wrong, until both have been manually verified, because the “hallucination” issue is inherent to the design of LLMs and cannot be solved, is supposed to make my life easier. Especially since a well known problem in computer science is that writing code is more fun than reading it.
If you’re using AI for code generation, I hope you like reading code.
If you’re using AI to learn a repo, I hope you’re prepared to fact check everything it tells you.
If you’re using AI for code review before merging a PR, fucking yikes. What made you think the sycophant machine that once told users a soggy cereal bar was a great business opportunity and cannot even transcribe McDonald’s orders correctly was suitable for that purpose?
If you’re telling yourself it’s okay because there’s a human in the loop, please read some studies about decision fatigue and consider that increasing the number of critical decisions a person must make per day, while giving them a suggested answer that’s right 90% of the time and catastrophically wrong the remaining 10%, and the only way to tell the difference is to read in depth, might not have the desired effect. Especially if the human in question is then put under time pressure.
This in spades.
To add; now there’s an issue in the generated code that’s been pushed. What to do? Read the code? Have new code generated? Abandon the project?