Based on the collective input of Dagstuhl Seminar (21342), this paper presents a comprehensive discussion on AI methods and capabilities in the context of edge computing, referred as Edge AI. In a nutshell, we envision Edge AI to provide adaptation for data-driven applications, enhance network and radio access, and allow the creation, optimization, and deployment of distributed AI/ML pipelines with given quality of experience, trust, security and privacy targets. The Edge AI community investigates novel ML methods for the edge computing environment, spanning multiple sub-fields of computer science, engineering and ICT. The goal is to share an envisioned roadmap that can bring together key actors and enablers to further advance the domain of Edge AI.
翻译:根据达格斯图尔研讨会(21342)的集体投入,本文件全面讨论了边际计算(称为边缘AI)的人工智能方法和能力。总而言之,我们设想边缘AI为数据驱动的应用提供适应,加强网络和无线电接入,并允许创建、优化和部署分布式AI/ML管道,并具有一定的经验质量、信任、安全和隐私目标。Edge AI社区调查边缘计算环境的新型ML方法,涵盖计算机科学、工程和信通技术的多个子领域。目标是共享一个设想的路线图,将关键行为者和使能者聚集在一起,进一步推进边缘AI的范畴。