Striding AI launches Physical AI solution for 24/7 retail. H1 Humanoid · C1 Carrying Robot · M1 Management Platform 🧠 World models + RL + embodied agents — enabling robots to perceive, plan, & execute on the floor, supporting 24/7 operations. 🏪 📹 youtu.be/M3lAuI1YxYk

Introducing C1, Striding AI's physical AI solution designed for real-world retail environments. Built for narrow aisles and dynamic store environments, C1 features: • Omnidirectional movement with a compact footprint • No modification required to existing shelves or store layouts • 100mm–1750mm+ operating height • Transport, restocking and handling capabilities • Depth vision and 360° visual perception From navigating narrow spaces to handling everyday retail tasks, C1 is designed to bring Physical AI into real commercial environments. #C1 #RetailRobot #PhysicalAI #Robotics #EmbodiedAI #StridingAI

Meet H1, Striding AI’s first fully self-developed humanoid robot. Built for real-world environments, H1 combines physical intelligence with natural human-robot interaction: • 20+ languages • 45 facial expressions • 36 gestures • Open API for further development Designed to work alongside people across retail, service, and other real-world settings. A step toward bringing Physical AI into the real world. #H1 #HumanoidRobot #PhysicalAI #Robotics

#AI has learned to generate answers in the digital world. The next step is to take action in the physical world. At #APRCE2026, Song Yao, Founder and CEO of Striding AI, shared how AI innovations can reshape 24/7 #retail & bring ease to the world with #physicalAI.

What will 24/7 retail look like in the age of #PhysicalAI? Our Founder & CEO Song Yao will take the stage at #APRCE2026 with a talk on Physical AI and the Future of 24/7 Retail. 📅 October 8 | 11:00 📍 Tokyo International Forum Stay tuned. #StridingAI #Robotics #Retail

How can robots clear a cluttered tabletop? 🤖 Our Physical AI system enables the robot to recognize each object, decides where it belongs, and completes a long-horizon sequence of actions—including coordinated dual-arm handovers. Thread 👇

Clearing a cluttered table is more than a pick-and-place task. The task demonstrates three core capabilities: 1️⃣Semantic understanding of everyday objects 2️⃣Long-horizon planning and execution 3️⃣Coordinated dual-arm manipulation and handovers

Higher task success and faster execution. 🚀 Our Physical AI system completes a multi-stage unboxing task with tool use & high-precision bimanual manipulation. Powered by #STEAM , it learns frame-level task progress from mixed-quality real-world experience.

Real-world gains 🚀 On four real-robot tasks, paired with CFGRL, STEAM lifts success rate by +59%, +54.3%, +23%, and +16.2% — towel folding, chip checkout, cola restocking, and pick-and-place. 🌐 Project: rlinf.github.io/steam/

From learning trajectories → learning progress. @ChaoYuTHU proposed STEAM, a label-free advantage model that reads progress, stalls, failures, and recoveries frame‑by‑frame — learned from nothing but the temporal order of expert demos.