AI 中文总结
针对移动环境下AI应用的约束，提出感知移动性的Mobile AI Stack架构框架，整合五大层级，为移动智能基础设施提供系统视角与概念蓝图。
AI 中文摘要
人工智能（AI）正从集中式计算能力迅速发展为与物理世界直接交互的普适性基础设施。近期研究虽强调能源、芯片、基础设施、模型及应用在支撑大规模AI系统中的作用，但这些框架主要基于静态、以云为中心的计算范式。然而，自动驾驶汽车、无人机、机器人、可穿戴系统等新兴智能应用，要求AI在高度动态的移动环境中运行，这一转变使移动性成为整个AI生态系统的基本约束，影响能源供应、计算及智能部署。本文提出移动AI栈（Mobile AI Stack）概念，这是一种感知移动性的架构框架，整合了五个紧密耦合的层级：移动能源网络、高能效AI芯片、云-边-端基础设施、分布式AI模型以及具身AI应用。该框架为理解能源供给、计算架构、通信网络与AI算法如何协同演进以支撑大规模移动智能提供了系统视角，还探讨了构建可扩展、可靠且高能效移动AI系统的关键研究挑战与未来方向，Mobile AI Stack为深度融合计算、能源与通信网络的下一代移动智能基础设施提供了概念蓝图。
英文摘要
Artificial intelligence (AI) is rapidly evolving from a centralized computing capability into a pervasive infrastructure that interacts directly with the physical world. While recent perspectives highlight the roles of energy, chips, infrastructure, models, and applications in enabling large-scale AI systems, these frameworks primarily assume a static, cloud-centric computing paradigm. However, emerging intelligent applications, including autonomous vehicles, drones, robots, and wearable systems, require AI to operate in highly dynamic and mobile environments. This shift introduces mobility as a fundamental constraint across the entire AI ecosystem, affecting energy supply, computation, and intelligence deployment. In this article, we introduce the concept of the Mobile AI Stack, a mobility-aware architectural framework that integrates five tightly coupled layers: mobile energy networks, energy-efficient AI chips, cloud-edge-mobile infrastructure, distributed AI models, and embodied AI applications. The proposed framework provides a systematic perspective for understanding how energy delivery, computing architectures, communication networks, and AI algorithms must co-evolve to support large-scale mobile intelligence. We further discuss key research challenges and future directions toward building scalable, reliable, and energy-efficient mobile AI systems. Mobile AI Stack offers a conceptual blueprint of the next-generation infrastructure which deeply integrates the networks of computation, energy, and communications for mobile intelligence.
