IEEE

Extreme Error-bounded Compression of Scientific Data via Temporal Graph Autoencoders

Abstract: The generation of voluminous scientific data poses significant challenges for efficient storage, transfer, and analysis. Recently, error-bounded lossy compression methods emerged due to ...
IEEE

Data-Driven Robust Resource Allocation for Vehicular Communications via Deep Support Vector Clustering

Abstract: In this paper, we investigate the power control and spectrum allocation challenge in vehicle-to-everything (V2X) networks with uncertain channels, where two types of services coexist, i.e., ...
Wall Street Journal

Locals Are Using AI to Fight Data Centers Being Built in Their Backyards

CINCINNATI—Late at night, or when her 18-month-old daughter is napping, Jessica Sharp logs onto Chat GPT and asks it to help her in her fight to stop a data center from being built just steps away ...
Reuters

Investors press Amazon, Microsoft and Google on water, power use in US data centers

LONDON, April 6 (Reuters) - Amazon, Microsoft and Alphabet's Google have each recently abandoned construction of multibillion-dollar data centers over community opposition and now the companies are ...
PC Magazine

Nvidia, Intel Texture Compression Techs Cut VRAM Use Dramatically

Intel and Nvidia showed off their respective AI-powered texture-compression technologies over the weekend, demonstrating impressive reductions in VRAM use while maintaining texture quality, or even ...
GitHub

llama-cpp-turboquant-guide

RTX 3090 24 GB Mistral-Small-3.2 24B 100,000 tokens −8.3% RTX 4070 Laptop 8 GB Llama-3.1 8B 64,000 tokens −3.2% TurboQuant scales with the GPU: the principle (+7-12× context, minimal speed loss) holds ...