The vision of the upcoming 6G technologies, characterized by ultra-dense network, low latency, and fast data rate is to support Pervasive AI (PAI) using zero-touch solutions enabling self-X (e.g., self-configuration, self-monitoring, and self-healing) services. However, the research on 6G is still in its infancy, and only the first steps have been taken to conceptualize its design, investigate its implementation, and plan for use cases. Toward this end, academia and industry communities have gradually shifted from theoretical studies of AI distribution to real-world deployment and standardization. Still, designing an end-to-end framework that systematizes the AI distribution by allowing easier access to the service using a third-party application assisted by a zero-touch service provisioning has not been well explored. In this context, we introduce a novel platform architecture to deploy a zero-touch PAI-as-a-Service (PAIaaS) in 6G networks supported by a blockchain-based smart system. This platform aims to standardize the pervasive AI at all levels of the architecture and unify the interfaces in order to facilitate the service deployment across application and infrastructure domains, relieve the users worries about cost, security, and resource allocation, and at the same time, respect the 6G stringent performance requirements. As a proof of concept, we present a Federated Learning-as-a-service use case where we evaluate the ability of our proposed system to self-optimize and self-adapt to the dynamics of 6G networks in addition to minimizing the users' perceived costs.

翻译：未来6G技术以超密集网络、低时延和高数据速率为特征，其愿景是通过零接触解决方案支持泛在人工智能（PAI），实现自配置、自监控和自愈等自服务（self-X）。然而，6G研究仍处于起步阶段，仅在概念设计、实现方法探索和用例规划方面迈出初步步伐。为此，学术界与工业界已逐步从人工智能分布的理论研究转向实际部署与标准化。然而，设计一个端到端框架，通过零接触服务供给的第三方应用简化人工智能分布的系统化访问，尚未得到充分探索。在此背景下，我们提出了一种新型平台架构，用于在基于区块链智能系统的6G网络中部署零接触泛在人工智能即服务（PAIaaS）。该平台旨在将泛在人工智能标准化至架构各层级，统一接口以促进跨应用域与基础设施域的服务部署，缓解用户对成本、安全及资源分配的担忧，同时满足6G严苛的性能要求。作为概念验证，我们呈现了联邦学习即服务用例，评估了所提系统在动态6G网络中自优化、自适应的能力，同时最小化用户感知成本。