Abstract
Generative AI (GAI) has emerged as a significant advancement in artificial intelligence, renowned for its language and image generation capabilities. This paper presents "AI-Generated Everything" (AIGX), a concept that extends GAI beyond mere content creation to real-time adaptation and control across diverse technological domains. In networking, AIGX collaborates closely with physical, data link, network, and application layers to enhance real-time network management that responds to various system and service settings as well as application and user requirements. Networks, in return, serve as crucial components in further AIGX capability optimization through the AIGX lifecycle, i.e., data collection, distributed pre-training, and rapid decision-making, thereby establishing a mutually enhancing interplay. Moreover, we offer an in-depth case study focused on power allocation to illustrate the inter-dependence between AIGX and networking systems. Through this exploration, the article analyzes the significant role of GAI for networking, clarifies the ways networks augment AIGX functionalities, and underscores the virtuous interactive cycle they form. This article paves the way for subsequent future research aimed at fully unlocking the potential of GAI and networks.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1 |
| Number of pages | 1 |
| Journal | IEEE Network |
| DOIs | |
| State | Accepted/In press - 2024 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- Software
- Information Systems
- Hardware and Architecture
- Computer Networks and Communications
Keywords
- Adaptation models
- AI-generated everything (AIGC)
- Communication system security
- Generative AI
- Generative AI (GAI)
- generative diffusion model
- Laboratories
- networks
- Optimization
- Resource management
- Semantics