1、2026 EDGE AI TECHNOLOGY REPORTThe Guide to Understanding the Technologies Defining the Next Phase of Edge AIAbout the AuthorsForewordIntroduction:The Era of Distributed AgencyChapter 1:Edge Foundation Models1.1.The Engineering of Efficiency:The Rise of SLMsLowering the Barrier to Edge AI with Arduin
2、o1.2.Distillation and Quantization:Mathematical Compression for the Edge1.3.Hardware Acceleration:The NPU Era1.4.The Continuum of Artificial IntelligenceChapter 2:Multimodal Edge Models2.1.The Architecture of Fusion:Early,Late,and HybridContext-Aware Multimodal Intelligence at the Edge2.2.Vision-Lan
3、guage Models(VLMs)and MobileCLIP22.3.The Event-Based Revolution:Neuromorphic Vision2.4.Multimodal AI for Industrial Reliability2.5.Robotics and Autonomous Systems:Multimodal Fusion Under Safety Constraints2.6.Multimodal Systems at the EdgeChapter 3:Ultra-Low-Power Architectures for Edge Intelligence
4、3.1.Neuromorphic Hardware and Spiking Neural NetworksPower-Efficient Intelligence for the Next Wave of Embedded Devices3.2.TinyML,State-Space Models,and MLPerf Tiny3.3.In-Sensor and Event-Based Vision3.4.Transparency,Ethics,and Sustainability3.5.OutlookChapter 4:Agentic AI at the Edge4.1.Architectur
5、e and Main Components of Edge AgentsUnlocking Extreme Efficiency in Edge AI with RISC-V4.2.Hardware Architecture and Compute Infrastructure of Agentic AI at the Edge4.3.Software Frameworks and Development Platforms for Edge Agents4.4.Digital Twin Simulation and Virtual Testing for Edge Behaviours4.5
6、.Safety,Liability,and Autonomous OperationChapter 5:Physical AI&Embodied AI5.1.Vision and Spatial UnderstandingEngineering Reliability at the Edge of Care5.2.Control and Learning:From PID to Policy5.3.Compute for Embodied Intelligence5.4.Simulation,Transfer,and Lifelong Learning5.5.Safety,Trust,and
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