- cross-posted to:
- programming@beehaw.org
- programming@lemmy.ml
- cross-posted to:
- programming@beehaw.org
- programming@lemmy.ml
Seems like he’s been pushed into using LLMs as a way to cope with the deluge of LLM-generated security reports.
Seems like he’s been pushed into using LLMs as a way to cope with the deluge of LLM-generated security reports.
I hate when AI people say “things are so different in just the past few weeks, what you know from last year is meaningless” without specifying what’s so groundbreaking that us regular folks wouldn’t be able to comprehend. It just seems like a way to shut people up and feel superior.
The point is that AI is developing at an insane rate. They don’t specify, because you would always have to be naming new things every other week, by the very nature of the statement. Things AI was not able to do a month ago, it may be able to do incredibly well now.
If you want an example, AI in security vulnerabilities has made quite a breakthrough recently. Not just Mythos, but multiple AI’s are finding 15+ year old vulnerabilities in open source packages basically the entire world relies on. It couldn’t do that a few months ago.
But what they’re also implying is is that most people just can’t keep up. But they can, apparently.
About the security stuff, I don’t think it is a question of whether AI could do it or couldn’t do it, it just wasn’t extensively used for it. For a long time there have been LLM bots trying to automatically identify security vulnerabilities in hopes of making “free money”, but it wasn’t effective. Now there’s people actually trying to find real issues. And I would argue that AI is not good at it. You can just let it ponder for as long as you can feed it with money, and you will definitely find vulnerabilities. The false-positive rate is very likely high. If I try to roll a dice 12 times, and 3 out of those were 6, then that doesn’t make me a good dice roller.
I think it’s just more the act of discovering what we can do with AI. It’s like openclaw, that could’ve been around last year, it’s not like AI wasn’t capable enough at that point, it’s just that no-one thought of using it like that (or at least no-one built it to the extent of openclaw and got it that popular).
What would you call developement/improvement if not exactly this? Some of histories biggest advancements are finding better ways to utilize things we already have
Or alternatively “You’re just prompting it wrong”
Yeah, but have you tried Slaupe Octopus 6.9? It’s vastly superior to anything else on the market.
My reply would be the equivalent of sloperator for prompsitutes.
i think he’s talking about agentic harnesses getting better, and the new models being finetuned to use them. I don’t think the new models are much “smarter,” but it allows them to write shitloads of bad code and tests, then iterate over them until they’re “fixed.”