Abstract: Post-training quantization (PTQ) is an effective solution for deploying deep neural networks on edge devices with limited resources. PTQ is especially attractive because it does not require ...

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 ...

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 ...

1 CNRS, Univ. Lille, UMR 8163 - STL - Savoirs Textes Langage, Lille, France 2 Univ. Lille, UMR 9189 - CRIStAL - Centre de Recherche en Informatique Signal et Automatique de Lille, Lille, France In the ...

Official support for free-threaded Python, and free-threaded improvements Python’s free-threaded build promises true parallelism for threads in Python programs by removing the Global Interpreter Lock ...

Writing about AI, tech, and startups. with a focus on practical insights for builders, founders, and creators. Writing about AI, tech, and startups. with a focus on practical insights for builders, ...

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 ...

ABSTRACT: Breast cancer remains one of the most prevalent diseases that affect women worldwide. Making an early and accurate diagnosis is essential for effective treatment. Machine learning (ML) ...