Feasibility Study of Edge Computing Empowered by Artificial Intelligence—A Quantitative Analysis Based on Large Models-Reference-Cited by-同舟云学术

Feasibility Study of Edge Computing Empowered by Artificial Intelligence—A Quantitative Analysis Based on Large Models

Published:2024-08-19 Issue:8 Volume:8 Page:94
ISSN:2504-2289
Container-title:Big Data and Cognitive Computing
language:en
Short-container-title:BDCC

Author:

Chen Yan¹,Wu Chaonan¹,Sui Runqi²^ORCID,Zhang Jingjia³

Affiliation:

1. School of Economics and Management, Beijing University of Posts and Communications, Beijing 100876, China

2. School of Cyberspace Security, Beijing University of Posts and Communications, Beijing 100876, China

3. APEC Study Center of Nankai University, Nankai University, Tianjin 300071, China

Abstract

The advancement of artificial intelligence (AI) demands significant data and computational resources that have an adverse impact on the environment. To address this issue, a novel computing architecture that is both energy efficient and eco-friendly is urgently required. Edge computing has emerged as an increasingly popular solution to this problem. In this study, we explore the development history of edge computing and AI and analyze the potential of model quantization to link AI and edge computing. Our comparative analysis demonstrates that the quantization approach can effectively reduce the model’s size and accelerate model inference while maintaining its functionality, thereby enabling its deployment on edge devices. This research serves as a valuable guide and reference for future advancements in edge AI.

Funder

Chinese Academy of Engineering Strategic Research and Consulting Program

Major Project of the Key Research Institutions for Humanities and Social Sciences of the Ministry of Education of China

Publisher

MDPI AG

Link

https://www.mdpi.com/2504-2289/8/8/94/pdf

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