Interactive AI with Retrieval-Augmented Generation for Next Generation Networking

Interactive AI with Retrieval-Augmented Generation for Next Generation Networking

21 Jan 2024 | Ruichen Zhang*, Hongyang Du*, Yinquiu Liu*, Dusit Niyato, Fellow, IEEE, Jiawen Kang, Sumei Sun, Fellow, IEEE, Xuemin (Sherman) Shen, Fellow, IEEE, and H. Vincent Poor, Life Fellow, IEEE
This article explores the integration and enhancement of Interactive AI (IAI) in networking, aiming to address the challenges and opportunities presented by the advancement of artificial intelligence (AI). The authors review recent developments in AI, introduce the key technologies and components of IAI, and discuss its potential applications in next-generation networks. They propose an IAI-enabled network management and optimization framework, which includes environment, perception, action, and brain units. The framework is designed to enhance network functionality, improve user experience, and promote efficient network management through implicit and explicit interactions. The effectiveness of the framework is demonstrated through case studies, and potential research directions for IAI-based networks are discussed. The article highlights the benefits of IAI in networking, such as customizability, flexibility, and reduced bias, and outlines future research areas including integration with emerging technologies, security aspects, and evaluation methods.This article explores the integration and enhancement of Interactive AI (IAI) in networking, aiming to address the challenges and opportunities presented by the advancement of artificial intelligence (AI). The authors review recent developments in AI, introduce the key technologies and components of IAI, and discuss its potential applications in next-generation networks. They propose an IAI-enabled network management and optimization framework, which includes environment, perception, action, and brain units. The framework is designed to enhance network functionality, improve user experience, and promote efficient network management through implicit and explicit interactions. The effectiveness of the framework is demonstrated through case studies, and potential research directions for IAI-based networks are discussed. The article highlights the benefits of IAI in networking, such as customizability, flexibility, and reduced bias, and outlines future research areas including integration with emerging technologies, security aspects, and evaluation methods.
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