I enjoy music production and systems programming in C
And I want to add: even though LLMs can identify cybersecurity risks, it doesn’t mean they are good at cybersecurity. They’re probably just as bad as in any other area. Also questionable if the actual positives outweigh the labor required to flag all the false-positives.
Just because they‘re used everywhere doesn’t mean that we just have to accept them. Also doesn’t mean that LLMs are a good thing.
I think LLMs can be used as an (additional!) cyber security analysis tool, that’s honestly the only area in which it seems to be actually useful (right now). And most projects don’t reach the size in which spotting security risks spanning across many different modules is a relevant skill to have. So it should be used sparingly, on things like the linux kernel. Then the cost of it might even be worth it (but I also don’t want to know about the amount of hallucinated bugs it finds).
Yeah, apart from the fact that I imagine that people who need alt text don’t appreciate LLM output. It‘s very boring. It’s either extremely technical and ice-cold or so cringe that you have to stop reading. Just what I think.
At least for me, if I realize that I’m reading an AI blog article or AI generated text in some other form, I don’t read it.
In my opinion, no. It has to be heavily curated. You’re not saving yourself a lot of work if you have to read it word by word (and probably correct stuff) anyway.
I think just one very short sentence describing what’s on there (it doesn’t have to be detailed) is a lot better than whatever an LLM will give you.
But then you’re primarily extracting text, which you don’t need LLMs for. OCR tools will do the job much cheaper and more effective.