Hosted on MSN

Maximizing self-hosted LLM performance with limited VRAM

Large language models (LLMs) are increasingly everywhere. Copilot, ChatGPT, and others are now so ubiquitous that you almost can’t use a website without being exposed to some form of "artificial ...
Forbes

How Mixed-Precision Quantization Could Break AI’s Power Addiction

It turns out the rapid growth of AI has a massive downside: namely, spiraling power consumption, strained infrastructure and runaway environmental damage. It’s clear the status quo won’t cut it ...
VentureBeat

Here are 3 critical LLM compression strategies to supercharge AI performance

Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More In today’s fast-paced digital landscape, businesses relying on AI face ...
GIGAZINE

Huawei announces 'SINQ,' an open-source quantization method that reduces memory usage of AI models by 60-70% and enables them to run on inexpensive, low-performance hardware

Huawei, a major Chinese technology company, has announced Sinkhorn-Normalized Quantization (SINQ), a quantization technique that enables large-scale language models (LLMs) to run on consumer-grade ...
Morningstar

Fujitsu develops generative AI reconstruction technology for optimized and energy-efficient AI models based on Takane LLM

TOKYO, Sept. 7, 2025 /PRNewswire/ -- Fujitsu announced the development of a new reconstruction technology for generative AI. The new technology, positioned as a core component of the Fujitsu Kozuchi ...