Researchers at Lawrence Livermore National Laboratory (LLNL) have developed a novel, integrated modeling approach to identify ...

This partnership aims to provide more than 250,000 Siemens employees with personalised learning experiences and upskilling ...

Abstract: In this letter, we propose an energy-efficient split learning (SL) framework for fine-tuning large language models (LLMs) using geo-distributed personal data at the network edge, where LLMs ...

Abstract: Neuromorphic computing with bio-inspired spiking neural networks (SNNs) offers an energy-efficient paradigm for edge intelligence. But, achieving practically high on-chip SNN learning ...

Send your kids to these sites to help them learn, study, indulge their curiosity, and get a fresh perspective on academic subjects. I've been contributing to PCMag since 2011 in a variety of ways ...

That's a big reason why in 2015 Microsoft released Edge, their new and improved browser. Edge gradually replaced Internet Explorer and became increasingly popular over the years, until the latter ...

Materials and methods: Using traditional machine learning methods, including random-effects meta-analysis and forward-search optimization, we developed a robust signature validated across 14 publicly ...

Still, like any advance at the cutting-edge of electrical or electronic technology, solid-state cells are really, really hard to take from the lab to production EVs. For every 100 promising lab ...

Honda's new facility could drive breakthroughs in solid-state batteries for electric cars, ultimately leading to batteries with more than double the range of existing EVs. Honda plans to produce ...

I. Rahmati, H. Shahmansouri, and A. Movaghar, "QECO: A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning for Mobile Edge Computing". @article{rahmati2024qeco, ...

College of Chemistry and Chemical Engineering, Central South University, Changsha ,Hunan 410083, China ...