1,561 karma · joined May 2, 2013
Also the whole "we're only releasing it to cyber defenders first" framing is weird, is any Gemini model an actual cyber risk?
If someone has good A/B evals of this being more effective I'll eat my hat, but the reason no one is publishing them is because well, evals are hard, and this is likely just magical thinking.
My current view is that an agent generally needs three things to work effectively: a way to discover information that isn’t obvious, such as a minimal `AGENTS.md` that points to more focused brief files; a clear way to verify that its work is correct; and some guidance on project-specific tastes. Everything else is noise.
I am quite convinced that the whole nerfing phenomenon is 90% AI psychosis. I have the word muted on X.
I don’t actually know if this is LLM-generated, but phrasing like this is weirdly triggering to me now
And the "hiring technicians" thing... great, humans on call for robots isn't the future I want.
I have a plug-in to do this. I don't know if it's effective but Claude said it was genuinely helpful (obviously would say that about anything)
I would not run an OpenClaw with full access to my bitwarden, but it certainly has some logins available to it, and can make purchases with link-cli which has human-in-the-loop.
I have had some $3,000 token days - even without Fable. I don't see how this is sustainable.
My personal 20x plans get so much usage for so cheap. The consumer subsidies are crazy, but alas I can't use them for work.
Labs do not train on benchmark data (allegedly). They can train on similar problems, but benchmarks have specific strings in them that labs are supposed to be aggressive in filtering out of their training corpora.