计算机科学
云计算
软件部署
GSM演进的增强数据速率
边缘计算
移动计算
移动设备
数据科学
万维网
人工智能
计算机网络
软件工程
操作系统
作者
Minrui Xu,Hongyang Du,Dusit Niyato,Jiawen Kang,Zehui Xiong,Shiwen Mao,Zhu Han,Abbas Jamalipour,Dong In Kim,Xuemin,Shen,Victor C. M. Leung,H. Vincent Poor
出处
期刊:Cornell University - arXiv
日期:2023-03-28
被引量:2
标识
DOI:10.48550/arxiv.2303.16129
摘要
Artificial Intelligence-Generated Content (AIGC) is an automated method for generating, manipulating, and modifying valuable and diverse data using AI algorithms creatively. This survey paper focuses on the deployment of AIGC applications, e.g., ChatGPT and Dall-E, at mobile edge networks, namely mobile AIGC networks, that provide personalized and customized AIGC services in real time while maintaining user privacy. We begin by introducing the background and fundamentals of generative models and the lifecycle of AIGC services at mobile AIGC networks, which includes data collection, training, finetuning, inference, and product management. We then discuss the collaborative cloud-edge-mobile infrastructure and technologies required to support AIGC services and enable users to access AIGC at mobile edge networks. Furthermore, we explore AIGCdriven creative applications and use cases for mobile AIGC networks. Additionally, we discuss the implementation, security, and privacy challenges of deploying mobile AIGC networks. Finally, we highlight some future research directions and open issues for the full realization of mobile AIGC networks.
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