This paper discusses the perspective of the H2020 TEACHING project on the next generation of autonomous applications running in a distributed and highly heterogeneous environment comprising both virtual and physical resources spanning the edge-cloud continuum. TEACHING puts forward a human-centred vision leveraging the physiological, emotional, and cognitive state of the users as a driver for the adaptation and optimization of the autonomous applications. It does so by building a distributed, embedded and federated learning system complemented by methods and tools to enforce its dependability, security and privacy preservation. The paper discusses the main concepts of the TEACHING approach and singles out the main AI-related research challenges associated with it. Further, we provide a discussion of the design choices for the TEACHING system to tackle the aforementioned challenges
翻译:本文讨论了H2020教学项目的观点,该项目涉及在分布式和高度多样化的环境中运行的下一代自主应用的下一代自主应用,包括跨越边缘波云连续体的虚拟和物质资源;教学提出了以人为本的愿景,利用用户的生理、情感和认知状态作为调整和优化自主应用的驱动力;通过建立一个分布式、嵌入式和结合式的学习系统,辅之以实施其可靠性、安全和隐私保护的方法和工具,开展这项工作。 论文讨论了教学方法的主要概念,并挑出了与此相关的与AI相关的主要研究挑战。 此外,我们讨论了教学系统应对上述挑战的设计选择。