Researchers have developed a new way to compress the memory used by AI models to increase their accuracy in complex tasks or help save significant amounts of energy.

Memory swizzling is the quiet tax that every hierarchical-memory accelerator pays. It is fundamental to how GPUs, TPUs, NPUs, ...

D-Wave Quantum Inc. (NYSE: QBTS) has launched a new U.S. government business unit to accelerate federal adoption of its quantum systems, software, and services. The company appointed veteran ...

Meta released details about its Generative Ads Model (GEM), a foundation model designed to improve ads recommendation across ...

Scientists at Duke-NUS Medical School have developed two powerful computational tools that could transform how researchers ...

Jennifer Simonson is a business journalist with a decade of experience covering entrepreneurship and small business. Drawing on her background as a founder of multiple startups, she writes for Forbes ...

Leeron is a New York-based writer who specializes in covering technology for small and mid-sized businesses. Her work has been featured in publications including Bankrate, Quartz, the Village Voice, ...

This is because the different variants are all around 60GB to 65GB, and we subtract approximately 18GB to 24GB (depending on context and cache settings) from that as it goes to the GPU VRAM, assuming ...