The Manila Times

DEEPX and Ultralytics Forge Strategic Alliance to Define the Global Standard for Physical AI in the YOLO Community

Empowering the world's largest computer vision ecosystem with a unified, one-click NPU hardware standard for building the ...
How-To Geek on MSN

Don't pay for an AI coding assistant until you've tried running one locally

Your CPU can run a coding AI—here's why you shouldn't pay for one (as long as you have the patience for it).
MUO on MSN

I was wrong about local LLMs, and these 4 myths were why

Stop thinking you need a $5,000 rig to run local AI — I finally ran a local AI on my old PC, and everything I believed was ...
IEEE

Quantization via Distillation and Contrastive Learning

Abstract: Quantization is a critical technique employed across various research fields for compressing deep neural networks (DNNs) to facilitate deployment within resource-limited environments. This ...
GitHub

Python implementation of the TurboQuant and QJL vector quantization algorithms.

turboquant-py implements the TurboQuant and QJL vector quantization algorithms from Google Research (ICLR 2026 / AISTATS 2026). It compresses high-dimensional floating-point vectors to 1-4 bits per ...
IEEE

An Information-Theoretic Framework for Receiver Quantization in Communication

Abstract: We investigate information-theoretic limits and design of communication under receiver quantization. Unlike most existing studies that focus on low-resolution quantization, this work is more ...
Microsoft

Advances to low-bit quantization enable LLMs on edge devices

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 ...