Researchers baked 3x inference speedups directly into LLM weights — without speculative decoding

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 ...

Bringing quantum ideas to the messy world of disordered proteins

Imagine trying to design a key for a lock that is constantly changing its shape. That is the exact challenge we face in ...
Unite.AI

Easy Rewording Breaks AI Safety, Even for Gemini and Claude

AI safety tests found to rely on 'obvious' trigger words; with easy rephrasing, models labeled 'reasonably safe' suddenly fail, with attacks succeeding up to 98% of the time. New corporate research ...
The Hacker News

How Exposed Endpoints Increase Risk Across LLM Infrastructure

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

I run local LLMs in one of the world's priciest energy markets, and I can barely tell

They really don't cost as much as you think to run.
IEEE

Smart Agriculture Framework for Multi-Crop Disease Detection using IoT and Vision Transformer

Abstract: In recent years, smart agriculture has turn out to be the transformative step to improve crop productivity and sustainability through the integration of Internet of Things (IoT) and ...
IEEE

LLM-RD: Multi-Dimensional Lightweight Ransomware Detection Using LLMs Based on Kernel-Level Events

Abstract: With the emergence of the Ransomware-as-aService (RaaS), ransomware threats became more destructive by encrypting files and holding them for ransom, rendering ransomware detection crucially ...