Anthropic created a cybersecurity model so dangerous that it decided not to release it to the public. Instead, it gave it to companies like Apple, Google, Microsoft, AWS, and Cloudflare. And in just one month:
→ 10,000+ vulnerabilities found
→ bugs hidden for 27 years
AI
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Anthropic’s Powerful Cybersecurity AI Model Shared Selectively After Revealing 10,000+ Vulnerabilities
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AI Progression: AGI, ASI, and Convergence Stages
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C'est facile de répondre à cette question. Nous avons 3 étapes à venir après l'IA. Prochaine étape, AGI.
Puis à l'étape suivante, ASI.
Et pour finir, CBT. AGI = Artificial General Intelligence (human-level)
ASI = Artificial Superintelligence (human surpassed)
CBT = Convergence -
Montreal.AI launches public forum for AGI-first to ASI-first era
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MONTRÉAL.IA / http://
MONTREAL.AI is live on Eventbrite. Public Intelligence for the AGI-first → ASI-first Era. Briefings. Debates. Archives. Public record. http://
MONTREAL.AI convenes the public-intelligence forum for frontier AI, sovereign intelligence, -
Frontier Models and Scientific Progress Forecasting Study
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Can frontier models forecast scientific progress? Mostly no, but here is why. This work looks at 4,760 scientific events across disciplines. Frontier models can identify plausible research directions when given options. They cannot reliably predict whether an advance will land,
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Lightning Indexer DSA Top-k Inference Path Demo
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It’s just demoing the inference-time DSA top-k selection path at this point. The Lightning Indexer has trainable parameters, but this version does not train them (yet)
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Gemini AI Studio vs Consumer App Design Tradeoffs
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AI Studio is for developers and defaults to higher thinking levels (in general). The Gemini app is a consumer product with 900 million MAU where we are trying to balance latency, cost, intelligence, etc with an opinionated product experience. The constraints are totally
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Gemini 3.5 Flash Achieves Pareto Frontier on Vending Bench
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Gemini 3.5 Flash is on the Pareto frontier of cost per intelligence on Vending Bench (a measure of a models ability to run a simulated store)!
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Validating Data Integrity for AI Models
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How do you validate the integrity of data feeding your AI models?
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Data Poisoning Risk in Edge AI Systems
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Did you know? Data poisoning emerges as a new risk for edge AI systems. Traditional cybersecurity focuses on network perimeters but edge AI requires validating data quality at the source. Partner content with TDK SensEI. #TDK_iioT pic.twitter.com/YBmV9x1gtC
— Lucian Fogoros (@fogoros) 23 mai 2026Did you know? Data poisoning emerges as a new risk for edge AI systems. Traditional cybersecurity focuses on network perimeters but edge AI requires validating data quality at the source. Partner content with TDK SensEI. #TDK_iioT
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DeepSeek Sparse Attention Implementation in LLMs Repository
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Added a DeepSeek Sparse Attention (DSA) from-scratch implementation to my LLMs-from-scratch repo thanks to an awesome new reader contrib. With motivation, overview, and GPT-style model reference implementation as standalone example code: https://
github.com/rasbt/LLMs-fro
m-scratch/tree/main/ch04/09_dsa
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