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.

Bringing AI agents and multi-modal analysis to SAST dramatically reduces the false positives that plague traditional SAST and rules-based SAST tools.

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 ...

Robin has worked as a credit cards, editor and spokesperson for over a decade. Prior to Forbes Advisor, she also covered credit cards and related content for other national web publications including ...