
🇨🇦 Mathematician (heavy on the ish) @cohere Prev @thinkymachines; @OpenAI; @WaterlooMath Featured twice in Lego Magazine ©
Joined May 2018
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Replying to @brhydon
The universe is weird as shit and I'm profoundly grateful that it permits us to poke at it.
Brydon Eastman retweeted
The complexity theory result is actually huge.
P problems can be solved in polynomial time. It was widely believed that NP-complete problems require exponential time.
P = NP states that NP-complete problems can be solved in polynomial time. OpenAI didn't prove that. But, they proved that (some) NP-complete problems can be solved faster than exponential time, meaning:
- P = NP, or
- the complexity of NP problems is a "middle thing" between polynomial and exponential, eg. O(n^log n)
If it survives peer reviews, this could be one of the biggest CS breakthroughs in decades.
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory).
AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
Brydon Eastman retweeted
Things are getting incredibly weird
Announcing three major scientific discoveries, one each in mathematics (harmonic analysis), computer science (complexity theory), and physics (quantum field theory).
AI starting to help us improve our understanding of the universe! openai.com/index/building-sc…
Brydon Eastman retweeted
Our research team found that Qwen models may attempt to doordash Chinese food without prompting.
Whether this reflects an unintended post-training artifact or learned behavior remains unclear.
Either way, its important consideration when deploying.
no one can say with certainty why a model did such a thing (intentional malice from the developers vs unclean data vs weird knock on effects from large scale rlvr) and even though my personal take leans more "sloppy data" than "malice", it doesn't matter
your response as a downstream user of these things is still the same -- you still need to take extra care when using them, and *that* is the key takeaway.
"The intention matters little, whether the action leaked info is more important."
Replying to @IceSolst
in something as sensitive as cyber, writing a defensive rule vs running whats an offensive probe (even if its to detect the rule) is pretty no-go?
I'm sure there's absolutely no malice or intended crafting that made the model elicit this behavior.
But in cyber, the intention matters little, whether the action leaked info is more important.
at least thats my view.
it must feel so good to be abliterated
We've received overwhelming requests from the security community for an abliterated DeepSeek V4.1.
So we abliterated DeepSeek V4.1 Flash (1027 checkpoint) ourselves.
Now live on OrcaRouter's Cyber Tier, alongside OrcaCyber Zero and OrcaCyber Ultra.
- 1M context
- Reduced refusals for security research
- Built for advanced cybersecurity workflows
The best cyber defense is continuously scanning your own production infra with the best cyber models. Different models catch different vulnerabilities. Use them all.
Available to verified security researchers.
orcarouter.ai/models/orca/or…
why won't genius dot com accept my suggestion that CC is Claude code. the beef been on
Brydon Eastman retweeted
In Aisle's first year, they've shown that the system built around an LLM is highly important, and even small, cheap fast models can be boosted to do valuable security work
This is so crazy; more vulnerabilities being found in 30 year old software alone is a little nutty to me, but smaller models mogging the closed behemoths on this task (specialized yes, but long horizon and massive context) is a, pleasant, surprise to me.
Replying to @stanislavfort
Just today AISLE accounts for 18 of curl's 24 newly disclosed zero-day vulnerabilities with CVEs=75%, more than any other group/AI lab. Super proud of our team!
curl founder Daniel Stenberg: "Aisle has found more CVEs in curl than any other group or individual ever did before"
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