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 origin of many diseases begins at the cellular level and involves multiple molecular interactions. However, previous methods have struggled to accurately observe changes in individual cells.

Reasoning large language models (LLMs) are designed to solve complex problems by breaking them down into a series of smaller ...

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.