Time-sensitive AI System for Physical Agents

The integration of Artificial Intelligence (AI) into physical agents, such as drones, robots, and autonomous vehicles, demands not only intelligence but also timely perception and decision-making. This work presents a time-sensitive AI system architecture that addresses the critical timing challenges inherent in such intelligent physical agents. We propose system-level designs that enable deadline-aware Deep Neural Network (DNN) execution on edge/embedded platforms, along with time-sensitive Large Language Model (LLM) serving on edge servers, thereby providing end-to-end support for time-critical physical intelligence.