智能终端AI计算技术的路径与挑战OA

With the migration of artificial intelligence(AI)technologies toward the edge,intelligent terminals are evolving from cloud service access devices into computing nodes with local intelligence capabilities.This paper systematically sorts out the development path of intelligent terminal AI computing technologies,analyzing its evolutionary trajectory from cloud-based inference to edge-side inference,from lightweight models to the deployable large models,and from single-point optimization to system-level collaboration.It summarizes core optimization technologies including model compression,compilation optimization,hardware acceleration and system-level energy efficiency management,and discusses key challenges such as edge-friendly model paradigms,unified compilation and runtime systems,AI-native operating systems,and local intelligent agent construction,providing a useful reference for research and industrial practices in this field.