when you translate a post from hebew
המחבלים בכלא לביא ישבו ואגרו מהמעט מזון שיש להם. כף ריבה ועוד כף ריבה, פרוסת לחם ועוד פרוסת לחם, כך במשך כמה ימים, הכל כדי להכין עוגה מאולתרת ולחגוג ביום שלישי, במידה ולא אבחר.
אלא שנציב שב״ס המצוין ואנשיו איתרו את העוגה, והאסירים הועמדו לדין משמעתי, והועברו לצינוק.
הם כבר צלנו נגמרה החגיגה. ביום שלישי אסור לתת להם לחגוג, מצביעים ב׳ בקלפי!
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it didn't even cross onto the mind of my opus 5.5 max agent to run a job on github ci instead of on its cloud CC env, still missing logic.
I've been reviewing a lot of code written by Opus 5.5, and it still seems to make a lot of bad software engineering decisions. The kind that will accumulate/calcify into unmaintainable software over time. IMO even the agents will struggle to maintain vibecoded software.
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they distilled fable 6 already chat
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we all go through the phase of formal copium all bug hunters included in the future, we all collectively hope it doesn't work which im pretty confident it wont eliminate all, there are still novel vectors.
hear me out, mathematicians entering ai alignment maybe consider this challenge. i think its probably millennium level problem(?)
take any complex real world software, like a browser or a kernel. let's pick a kvm based sandbox, which i suspect is somewhat less complex than chromium(?), running an increasingly capable, potentially adversarial AI agent.
we want to formally prove one simple property, no matter what code the agent executes inside the VM, it cannot escape and compromise the host. for that we need to prove the entire relevant software stack, kvm, cpu virtualization, kernel, virutal devices that could affect the isolation. (to make things easiers, lets assume hardware wont have weird states)
can we mathematically establish whether formally verifying a system of this complexity is even computationally feasible?
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dumb post, tl;dr they just made claude write the spec, no progress made whatsoever
New on our Frontier Red Team blog: using Claude to formally verify software at large scale.
Formal verification can prove that code is free of certain bugs, but historically it has only been feasible for small codebases (or required a lot of expert time).
With AI models, however, this is beginning to change. In collaboration with @theoremlabs, we used Claude to prove security properties in over one hundred real-world open-source libraries over the span of a few weeks.
Read our research in full here: anthropic.com/research/forma…
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T3ch retweeted
My iPhone Duo video went viral, so I'm giving away 100 iPhones on X 😛
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In 4 weeks Anthropic are going to be talking about the engineering breakthroughs to serve inference for cheaper. (of course not made by mythos, see references below...) @teortaxesTex
🚀 Introducing DeepInfer, our in-house inference framework, now fully open source!
Powering DeepSeek-V4.1-Flash at scale with high throughput and low latency. We’re sharing our production stack to help the community lower compute costs, reduce energy use, and make AI more affordable.
🔗 github.com/deepseek-ai/De…
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goy of the year award
tried dsv4.1-flash-1017 abliterated just now & feel sick to my stomach.
for context, "abliterated" models have the weights responsible for making the base version refuse illegal requests removed. you can ask them to help with things like hacking or violence & they'll just comply.
they make it trivial to hack businesses running old software. e.g. getting guest data for a motel with some old asp site.
abliterated models have a catch-22 in that the only way to harden your systems against them is to use them to run penetration tests against yourself.
in theory, this sounds similar to buying a gun to defend against others who own guns, but it's different in practice since there's a 100% chance that you're going to use the abliterated model to protect yourself whereas there are low odds that you'll actually use the gun.
when you point the abliterated gun at your own infra, who knows what it's going to do? it could just as easily hack you & exfiltrate data as it could protect you. most users aren't going to meticulously watch traces to make sure it behaves safely.
given this, my new take is that gpu compute is going to become a federally regulated resource. abliterated models in the wrong hands are a national security risk.
used to believe all the people at the labs thinking about safety were wasting their time, but now i'm feeling grateful. they're doing very important work.
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all it takes is one novel vector and the entire system is demolished, people try to build fortresses on moving goalposts, will not work.
i am extremely pessimistic about what defenders can realistically achieve, not because secure systems are impossible to build or defenders are incompetent, but because the economics, incentives, and complexity are against them. security is not a necessary property for most things built in cyber.
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