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 ...

Abstract: The narrow-bit-width data format is crucial for reducing the computation and storage costs of modern deep learning applications, particularly in large language models (LLMs) based ...

This library provides the capability to emulate MX-compatble formats and bfloat quantization in pytorch, enabling data science exploration for DNNs with different MX formats. The underlying ...

What if the future of artificial intelligence wasn’t about building bigger, more complex models, but instead about making them smaller, faster, and more accessible? The buzz around so-called “1-bit ...

I'm diving deep into the intersection of infrastructure and machine learning. I'm fascinated by exploring scalable architectures, MLOps, and the latest advancements in AI-driven systems ...

As deep learning models continue to grow, the quantization of machine learning models becomes essential, and the need for effective compression techniques has become increasingly relevant. Low-bit ...

Large language models (LLMs) are increasingly being deployed on edge devices—hardware that processes data locally near the data source, such as smartphones, laptops, and robots. Running LLMs on these ...

ABSTRACT: As documented by NASA space shuttle films and detailed in this report, self-illuminating, pulsating, plasma-like UAP/UFO (“plasmoids”) have multiple shapes and sizes, are attracted to ...