Driven by the interplay among artificial intelligence, digital twin, and wireless networks, 6G is envisaged to go beyond data-centric services to provide intelligent and immersive experiences. To efficiently support intelligent tasks with customized service requirements, it becomes critical to develop novel information compression and transmission technologies, which typically involve coupled sensing, communication, and computation processes. To this end, task-oriented communication stands out as a disruptive technology for 6G system design by exploiting the task-specific information structures and folding the communication goals into the design of task-level transmission strategies. In this article, by developing task-oriented information extraction and network resource orchestration strategies, we demonstrate the effectiveness of task-oriented communication principles for typical intelligent tasks, including federated learning, edge inference, and semantic communication.

翻译：在人工智能、数字孪生和无线网络之间的相互作用驱动下，6G被设想超越数据中心服务，提供智能和沉浸式体验。为了有效地支持具有定制服务需求的智能任务，开发新型信息压缩和传输技术变得至关重要，这通常涉及到耦合的感知、通信和计算过程。为此，任务导向通信凭借利用任务特定的信息结构，并将通信目标折叠到任务级传输策略的设计中，成为6G系统设计的颠覆性技术。在本文中，通过开发任务导向的信息提取和网络资源协作策略，我们展示了任务导向通信原则在典型智能任务中的有效性，包括联邦学习、边缘推理和语义通信。