update: the patch set from Linus Torvalds, Boy Genius, went into review and the reviewers immediately found a race condition: https://woof.tech/@techokami/117446164348546588
wow! it's really easy to write fast kernel code when it's wrong
and now he's apparently just dumping it on someone else because he's "going on vacation", a move that post-LLM commercial developers on most teams will be extremely familiar with
By the way, his argument about "you wouldn't mention tools" is just plain wrong.
A few years back, at work, I found a security bug introduced by a commit that said something like "fix Coverity warnings". I ended up reviewing every commit that mentioned Coverity, because that legacy codebase had a lot of rather bad tricks that triggered Coverity to have a false positive.
And when a large number of false positives were getting resolved by editing code, sometimes that resulted in a false negative. E.g. Coverity complains about a memory leak, you end up with double free. Or vice versa, it complains about double free, and you end up with a leak. (The exact example was even more on the nose; Coverity complained about use-after-free, and the fix for it introduced a real use-after-free).
Bottom line is, they do not want to have those labels because that would enable someone to actually measure how good or bad LLMs are at code.
This is another thing that is extremely familiar to most commercial developers: there's an LLM-powered code review bot, but unlike any tool ever before, nobody's even trying to capture statistics whether it works or not. Why? Because whoever rolls out AI tooling isn't sure that the tooling actually works for its stated purpose, and wants to for sure get their recognition and promotion for rolling out AI tooling, without jeopardizing it with the risk of adverse KPIs.
Oh another thing, purely anekdotally, coding LLMs still suck at multithreading.
I feel that's one part where they could legitimately make actual "AI" for, basically a tool that either proves that nothing depends on exact timing, finds a counter example, or tells you it can't do either (in which case your code is probably just very bad). But big overfunded AI labs probably feel that such tooling is beneath them.
At what point does this become best considered as purposeful or accidental, targeted sabotage?
TechTakes
Big brain tech dude got yet another clueless take over at HackerNews etc? Here's the place to vent. Orange site, VC foolishness, all welcome.
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