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 ...

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

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 ...

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

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

Abstract: As a typical application of the low-altitude economy, UAV collaborative monitoring contributes to urban management and data collection. The dense distribution of urban buildings leads to ...

Abstract: This paper presents Temporal-Context Planner with Transformer Reinforcement Learning (TCP-TRL), a novel robot intelligence capable of learning and performing complex bimanual lifecare tasks ...

Now available in technical preview on GitHub, the GitHub Copilot SDK lets developers embed the same engine that powers GitHub ...

Overview: Generative AI is rapidly becoming one of the most valuable skill domains across industries, reshaping how professionals build products, create content ...

Large-language models (LLMs) have taken the world by storm, but they’re only one type of underlying AI model. An under-the-radar company, Fundamental, is set to bring a new type of enterprise AI model ...

EEschematic is an AI agent designed for automatic schematic generation in analog integrated circuit design. Built upon a Multimodal Large Language Model (MLLM), EEschematic bridges the gap between ...