At Gasgoo's 4th AI-Defined Vehicle Forum on Sept. 18, Qian Xiangjun, vice president of technology at QCraft, presented on QCraft's Physical AI, outlining its deployment path, technical architecture, mass production progress, and future roadmap. Qian said autonomous driving is the first large-scale commercial application of physical AI and the cornerstone for general physical AI development, with world models and reinforcement learning the bridge between the digital AI world and the physical one. He introduced QCraft's "Cloud World Model + Vehicle World Behavior Model" dual-system framework; the cloud model offers highly controllable video generation, a zero-shot generation engine, and low-cost pre-simulation, while the vehicle model integrates VLA and reinforcement learning for full-chain modeling from perception to action, supported by an automotive data closed-loop system. On mass production, QCraft's assisted driving solutions are equipped in over 1 million vehicles, spanning more than 40 production models and 10 automaker brands. Its three-tier L, Pro, and Max solutions cover full-scenario needs; the Pro platform first delivered high-experience city NOA on the 128 TOPS Horizon Journey 600M chip, with multiple models entering mass production and delivery in the second half of this year, while the Chengfeng Max platform uses over 500 TOPS of on-board computing to deliver an experience exceeding 1,000 TOPS.