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> Our tests gave models the vulnerable function directly, often with contextual hints (e.g., "consider wraparound behavior"). "Often with contextual hints" is
by tao_oat 6mo ago
> Our tests gave models the vulnerable function directly, often with contextual hints (e.g., "consider wraparound behavior").
"Often with contextual hints" is doing some heavy lifting here, IMO. I agree with the article's premise -- you don't need Mythos to use AI to find novel, complex vulnerabilities -- but these results as presented are somewhat misleading.
- akavel 6mo agoAFAIU, their claim is that Mythos is in reality used in a framework that builds such contextual hints, and that their (Aisle's) own framework does the same: "(...) a well-designed scaffold naturally produces this kind of scoped context through its targeting and iterative prompting stages, which is exactly what both AISLE's and Anthropic's systems do."
- cyanydeez 6mo agoAll evidence is point to LLMs not being sufficient for the taks everyone want them to do. That harness and agentic capabilities that shove them through JSON-shaped holes are utterly necessary and along with all the security, that there's no great singularity happening here. The current tech is a sigmoid and even using the abilities of the AI, novelty, improvements don't appear to be happening at any exponetial pace.
- tao_oat 6mo ago> The current tech is a sigmoid What makes you say that? I'm only asking because the data I've seen looks pretty cleanly exponential still, e.g. https://metr.org https://metr.org.