Many people think that data mining and manipulation started with AI.
It didn't, it’s been happening for decades.
The surveillance era didn’t just begin.
We’re just finally waking up to it.
The moment we started referring to companies who’ve raised at a billion dollar valuation as “billion dollar companies” we helped to shift the focus of startup founders from their customers to their investors. I prefer to call companies with a billion dollars in revenue “billion…
Are LLMs truly capable of “PhD level” reasoning?
FormulaOne: Measuring the Depth of Algorithmic Reasoning Beyond Competitive Programming
Evaluated through PhD-level Dynamic Programming problems, and spoiler alert, AI code-solvers are only able to get under 1% right (for now…?)
🔴 Most SIEM alerts are junk. 74% of breaches had warnings — but analysts ignored them, buried under 5,000+ daily false positives.
The price? Burnout, wasted millions, and missed threats.
Why the SOC’s beating heart is now its weakest link → thehackernews.com/expert-insight…
Operational Technology (OT) cyber incidents can have severe consequences for OT systems, especially those in NSS, the DOD, & the DIB. Increase your asset & vulnerability awareness by checking out the recently released joint CTR with @CISAgov and others.
media.defense.gov/2025/Aug/13/20…
Iterative reflections for LLMs can outperform heavy RL?
This paper shows that having the LLM reflects on its own trajectories, rewrite its own prompts, and evolve a diverse pool of candidates beats RL w/ GRPO so far on four reasoning tasks .
10% improv with 35x fewer rollouts!
LLMs can now self-optimize.
A new method allows an AI to rewrite its own prompts to achieve up to 35x greater efficiency, outperforming both Reinforcement Learning and Fine-Tuning for complex reasoning.
UC Berkeley, Stanford, and Databricks introduce a new method called GEPA…
To me, the real danger of current artificial intelligence is that the whole society increasingly relies on "knowledges" generated by machines that in fact do not understand them. It is not the action of current AI systems that would doom us but our own misjudgment and behaviors…
One Token to Fool LLM-as-a-Judge
Watch out for this one, devs!
Semantically empty tokens, like “Thought process:”, “Solution”, or even just a colon “:”, can consistently trick models into giving false positive rewards.
Here are my notes:
The future of AI governance may hinge on our ability to develop trusted and effective ways to make credible claims about AI systems. This new report expands our understanding of the verification challenge and maps out compelling areas for further work. ⬇️
The future of AI governance may hinge on our ability to develop trusted and effective ways to make credible claims about AI systems. This new report expands our understanding of the verification challenge and maps out compelling areas for further work. ⬇️
I often rant about how 99% of attention is about to be LLM attention instead of human attention. What does a research paper look like for an LLM instead of a human? It’s definitely not a pdf. There is huge space for an extremely valuable “research app” that figures this out.
I often rant about how 99% of attention is about to be LLM attention instead of human attention. What does a research paper look like for an LLM instead of a human? It’s definitely not a pdf. There is huge space for an extremely valuable “research app” that figures this out.
I'm constantly irritated that I don't have time to read the torrent of cool papers coming faster and faster from amazing people in relevant fields. Other scientists have the same issue and have no time to read most of my lengthy conceptual papers either. So whom are we writing…
New Anthropic research: Why do some language models fake alignment while others don't?
Last year, we found a situation where Claude 3 Opus fakes alignment.
Now, we’ve done the same analysis for 25 frontier LLMs—and the story looks more complex.
Today we published a targeted transparency framework for frontier AI development.
Our framework focuses on major frontier model developers while exempting startups and smaller developers to avoid burdening the broader ecosystem.
⚡ Google just got hit with a $314M verdict — for secretly using your mobile data while idle.
Phones sat still. It sent 900+ background transfers a day — and you paid for it.
Details here → thehackernews.com/2025/07/google…
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