we've been stuck on mythos level intelligence for a year now
Are we hitting the sigmoid of despair? ai winter?
Dario Amodei says Anthropic held back broad access to Mythos-class models for four months to strengthen cyber safeguards. Mythos was originally scheduled for release in February this year.
He also says distillation poses no major commercial threat, but raises security concerns, and Anthropic has blocked suspected attempts to use its models for bioweapons.
Mohamed retweeted
Vibe coding has created a security epidemic.
(And I’m partially to blame)
When we launched GitHub Copilot in 2021, it combined GPT’s code generation with GitHub’s data. It could auto-complete a function from just its docstring.
5 years on, AI coding agents are orders of magnitude more powerful. Now a single prompt can send Astra or Fable off to write 1000s of lines of code without human intervention.
These models are trained on public source code, which doesn’t follow secure coding best practices. They generate more vulnerabilities than seasoned professionals would. Almost half of AI-written code fails basic security tests.
If you're shipping AI-written code, here's what I'd do:
1. Embed secure coding in your agents.
Don't leave it to each developer to remember. Write your secure coding requirements into the prompts every coding agent in your org runs with. Then review AI-written code with the same rigor as human-written code.
2. Closely scrutinize access controls.
AI is getting better at avoiding textbook bugs. Where it still struggles is your business logic: who should see what, and who can do what.
We recently tested an app where users upload documents for AI analysis. Nobody told the AI the documents should be private, so every user could see everyone else's…
3. Runtime testing at the speed you ship.
If agents write code around the clock, an annual pentest is not enough. Security testing has to be continuous and automated.
4. Assume attackers are already deploying autonomous attacks.
They won't tell you what they find. You need to find it first.
i don't understand these crowds honestly they wanna get scammed so bad
the current state of AI
NS proof isn't actually NS it found a loophole in the question and lean formalization is flawed
700 papers 3down after 24hours because of sign error
llms still can't see straight
NGL bro, the idea that billionaires want neo-feudalism using AI is going from a psycho conspiracy theory to reality every day.
now they want you to believe unverified results saying maybe the human mind doesn't understand
Mohamed retweeted
ok bro...
the artcraft dude got into my discord server and copied photon. but honestly - I like your approach and I wish you the best. no need to hide tho. we all copy.
Mohamed retweeted
I don't think an unmanned demo of a hunk of metal with wheels flying in the air is all that impressive.
Jamie and Adam from Mythbusters did similar stunts like 20 years ago. Except theirs was built by a team of 10 people, in just few days, on a shoe string budget.
the 2.8k likes prove that the ai hype crowd are bots
Mohamed retweeted
BREAKING: OpenAI’s solution to Navier–Stokes does not match its Lean verification.
The most important article to read today is not one of OpenAI’s 700 AI-generated math papers.
It is this other paper, making a deep and worrying point:
A Lean-verified proof does not automatically validate the proof written in natural language, nor does it mean that the formal statement captures the intended theorem.
During translation, an AI can change an assumption, weaken a statement, or replace the argument entirely.
It can hallucinate another theorem.
Lean correctly verifies the result.
But the proved result may no longer be what the paper claims.
This is a general problem. Things get spicy when the authors examine OpenAI’s proposed Navier–Stokes solution.
They identify at least two mismatches between the written intermediate results and their Lean counterparts:
One estimate claims that four additional input derivatives suffice. The Lean version requires five: a weaker result.
A pressure-flux estimate is obtained through a different bound, and proved through a different argument.
It is not clear whether these mismatches invalidate the entire proof.
But they raise an important issue.
OpenAI is flooding us with claimed revolutionary breakthroughs. Yet nobody knows whether the proofs are correct or whether they prove what they claim to be proving.
Epistemia at scale.
*
Paper in the first reply
Mohamed retweeted
The benchmark I actually care about:
Can our parents live longer?
Can we cure Alzheimer's?
Can we kill common cancers?
Can we prevent kids dying from rare diseases?
Why so much effort to solve low impact math problems? If these unreleased models are so good, solve real problems
We’re releasing a broad range of new mathematical results produced by an internal frontier model.
We’ve been consulting with the independent Advisory Group on Mathematics and Artificial Intelligence at the Institute for Advanced Study, and we have drawn on their advice and public recommendations to inform how we release these results.
github.com/openai/math
WHPX on ARM64 is virtualization cosplay: no 16K pages, no interrupt controller, QMP can't even read guest RAM,
instead of doing this you could have improved the platform
Today during the @AMD's #IFA2026 keynote, @pavandavuluri introduced Project Zenith - A ready-to-code Windows experience on developer-class devices.
Debuting on AMD's Ryzen AI Halo, with more devices to come. blogs.windows.com/windowsdev…
Mohamed retweeted
Imagine you’re a conman. You’ve said for years you have MAGIC BEANS. You’ve shown lots of REALLY BIG normal beans that you made in your lab.
“Almost there!” you say—over and over.
Now, you have *almost* convinced the villagers to give you TWO TRILLION DOLLARS.
But while the beans keep getting bigger. No magic yet…
What do you do? That money is SO CLOSE.
“I know!” you think, “instead of MAGIC beans, lets’s make them KILLER BEANS.”
So you pump up your beans up SUPER BIG and you say: “I’m sorry, but these BEANS ARE GETTING BIGGER ON THEIR OWN!” You threaten people that if they don’t give you the money, the beans may get into the WRONG HANDS. They might get BIGGER THAN THE EARTH!
The villagers, aghast, run to and fro arguing whether the beans are going to kill everyone or make them all rich.
“Well, either way,” the idiots in the village conclude, “We’d better give him the money.”
Mohamed retweeted
Two Scenarios
1. AI is superintelligent & sociopathic billionaires are genuinely worried for us.
2. Capital is gone & AI advancements have slowed. Now, billionaires need to use government constraints as cover for shareholders, framing the slowing as a regulatory issue outside of their control.
