【Slides】Embodied Intelligence & Physical AI Lecture 2 (Chinese)
Speaker Michael Huo's lecture slides (Chinese version), detailing the evolution from VLA to World Models.
Jointly released by Silicon Valley Quantum AI Lab, NACUAA AI Club, and ZJUAANC
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Speaker Michael Huo's lecture slides (Chinese version), detailing the evolution from VLA to World Models.
Speaker Michael Huo's lecture slides (English version), providing a complete English technical breakdown.
Speaker Michael Huo Lecture 3 slides: Hands-on guide to embodied AI using StackChan desktop AI robot.
In-depth architecture whitepaper detailing the evolution from Prompt to Loop and Graph Engineering.
Comprehensive Physical AI blueprint covering physical perception, closed-loop brain control, and edge agency.
Architectural roadmap detailing how software AI agents cross the digital divide into physical embodiment.
Best engineering practices for deploying embodied AI from algorithmic models to physical robot hardware.
Local edge-run AI Agent engine architecture and multi-task scheduling mechanisms.
System architecture design for lightweight local LLM/VLM edge deployment and ultra-low latency execution.
OpenClaw autonomous agent framework design, tool orchestration, and zero-cost deployment playbook.
Detailed breakdown of OpenClaw agent action selection, environment perception, and feedback loops.
Fundamentals of StackChan desktop robot control, sensor alignment, and servo motor drivers.
Kinematic modeling, force control, and high-precision motion planning for Physical AI robotics.
Analyzing the global industry landscape and strategic blueprints for Physical AI and humanoid robotics in 2026.
Delving into physical AI architecture design, including end-to-end closed-loop control and multimodal perception.
Case studies on physical AI deployments on factory floors and large-scale industrial pipeline integration in 2026.
Explaining deployment workflows for physical agents on edge devices and humanoid robot hardware.
A systematic overview of the paradigm transition from Vision-Language-Action models to physical World Models.
Long-term tech evolution roadmap for Physical AI, covering multimodal world foundation models and physics simulation.
Note: All strategic and technical readings are in PDF format (with CN/EN versions or academic papers) for academic exchange and industry research.