AI 中文总结
本文提出混合数字-模拟计算是实现更节能AI系统的可行路径，指出应通过已部署系统指标而非孤立TOPS/W评估进展，研究了该转变的架构原则等内容。
AI 中文摘要
数字革命已逐步用数字电路取代模拟方法，随着AI扩展到云基础设施、移动网络、可穿戴设备及无人机、机器人等物理系统，该革命进入新阶段。数字计算仍是这一扩展的通用基础，其通过可编程控制、成熟软件及数十年积累的工程基础设施，支持异构、设备端及去中心化AI。然而，随着能耗与数据移动约束愈发显著，该基础正被其可承载、配置与验证的特定模拟及物理原理扩展，而非取代。光子、内存内及神经形态架构为减少数据移动、加速矩阵密集型与事件驱动型处理提供路径，它们并非数字基础设施的替代，而是在其中运行的专用引擎。本文提出，混合数字-模拟计算是实现更节能AI系统的可行路径：在数字编排下，物理基底仅在可提供可测量系统级优势的场景中发挥日益扩大的作用，该编排管理集成、不确定性及弃权（不执行）机制。本文研究了该转变相关的架构原则、工作负载适用性、能耗核算、软件需求、局限性及开放挑战，并提出未来进展应通过已部署系统的指标评估，而非孤立的每瓦峰值万亿次操作（TOPS/W）声明。
英文摘要
The digital revolution, which progressively replaced analogue methods with digital circuits, has entered a new phase as AI expands across cloud infrastructure, mobile networks, wearables and physical systems, including drones and robots. Digital computing remains the general-purpose foundation of this expansion: it supports heterogeneous, on-device and decentralised AI through programmable control, mature software and decades of accumulated engineering infrastructure. Yet as energy and data-movement constraints become more significant, that same foundation is increasingly being extended rather than replaced by selected analogue and physical principles that it can host, configure and verify. Photonic, in-memory and neuromorphic architectures offer routes to reducing data movement and accelerating matrix-intensive and event-driven processing, not as alternatives to digital infrastructure but as specialised engines operating within it. This paper argues that hybrid digital--analogue computing represents a credible pathway towards more energy-efficient AI systems: one in which physical substrates earn an expanding role only where they deliver a measurable system-level advantage, under digital orchestration that manages integration, uncertainty and fallback. It examines the architectural principles, workload suitability, energy accounting, software requirements, limitations and open challenges associated with this transition, and argues that future progress should be evaluated through deployed-system metrics rather than isolated peak tera operations per second per watt (TOPS/W) claims.
