With reported 3x speed gains and limited degradation in output quality, the method targets one of the biggest pain points in production AI systems: latency at scale.

Researchers from the University of Maryland, Lawrence Livermore, Columbia and TogetherAI have developed a training technique that triples LLM inference speed without auxiliary models or infrastructure ...

The company open-sourced an 8 billion parameter LLM, Steerling-8B, trained with a new architecture designed to make its ...

Exposed endpoints quietly expand attack surfaces across LLM infrastructure. Learn why endpoint privilege management is important to AI security.

Traditional SEO metrics miss recommendation-driven visibility. Learn how LCRS tracks brand presence across AI-powered search.

ThreatsDay Bulletin tracks active exploits, phishing waves, AI risks, major flaws, and cybercrime crackdowns shaping this ...