Abstract: Cloud-based quantization is a key technique for deploying deep neural networks on resource-constrained devices. However, the growing number of heterogeneous devices has placed an increasing ...

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 ...

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) ...

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 ...