Robots Can Now Do Chores! A key takeaway from this year’s WAIC: Embodied AI is moving beyond just "looking human." The real competition has shifted to "can they actually do the work?" Everyone’s trying out different real-world uses, and it's much more practical this time around. #WAIC2026# #EmbodiedAI# #Robotics# #FutureTech# #AIInRealLife# Risk Disclaimer: Investment involves risk, including possible loss of principal. Any forecasts, projections, or opinions contained herein are for reference only and are not guaranteed to occur. The information in this material reflects prevailing market conditions and our judgment as of the release date, which are subject to change without further notice.

Humanoid Robots Debut at WAIC—The Resemblance Is Uncanny! WAIC 2026 wrapped up in Shanghai, with robots once again stealing the spotlight. Nothing gets the crowd going quite like a robot dancing or shaking hands. Over 200 companies gathered this year, showcasing the latest breakthroughs in humanoid robotics and embodied AIr, and honestly, it’s pretty wild to see in person. #WAIC2026# #Robotics# #HumanoidRobot# #EmbodiedAI# #Shanghai# #TechInsight# Data Source:Jiemian News, Robots: The No.1 Hard Worker at WAIC 2026, as of 2026.07.19 Risk Disclaimer: Investment involves risk, including possible loss of principal. Any forecasts, projections, or opinions contained herein are for reference only and are not guaranteed to occur. The information in this material reflects prevailing market conditions and our judgment as of the release date, which are subject to change without further notice.

⏳ 1 Day to Go! Flink Forward Asia 2026 — Main Forum Agenda Revealed! FFA2026 brings together world-class tech leaders to showcase the full picture of real-time data intelligence — from Alibaba Cloud's Agent-native to AI-native evolution, and from automotive to embodied AI industry scenarios. 📅 June 26–27 | InterContinental Shenzhen OCT, Shenzhen ⚡ Limited seats available — don't miss out! 📝 Note: All sessions will be conducted in Mandarin Chinese. #FlinkForwardAsia# #FFA2026# #ApacheFlink# #RealTimeData# #DataAI# #AIAgent# #AgenticAI# #StreamingData# #OpenSource# #AlibabaCloud# #EmbodiedAI# #DataEngineering#

A new approach to physical world models — reason about "how the world changes" in language before generating any pixels. Title: PhiZero: A World Model Built Around Physical Language ❓ What is "Physical Language"? 💡 A discrete token sequence that directly represents state-transition patterns in a video — separate from visual appearance. Because dynamics and appearance are disentangled, the state transitions encoded from one video can be transferred to a completely different visual style. PhiZero's "Reason-then-render" paradigm predicts this physical language first, then generates video from it. ❓ Why did previous physical world models produce physically inconsistent results? 💡 They relied on direct pixel-space prediction, burying dynamics implicitly inside the model. Reconciling visual realism with physical consistency was difficult — leading to failures like a tennis ball hitting a rubber duck that doesn't react. The reasoning process was also opaque by design. ❓ What performance numbers did it achieve? 💡 State-of-the-art results across all six benchmarks: ・Physics-IQ IQ-Score: 41.2 (beats previous SOTA of 39.5) ・WorldModelBench: highest in physical compliance, commonsense, and overall score ・YoCausal causal reasoning: aggregated rank 2.0 (best) ・Tokenizer: just 256 tokens achieve PSNR 28.9 — 1/175th of Wan2.2-5B VAE's token count ❓ What does this mean for robotics and autonomous driving? 💡 Physical Language is appearance-agnostic, so zero-shot sim-to-real and human-to-robot transfer become possible. The team demonstrated encoding LIBERO simulation dynamics and replaying them as realistic video, and directly transferring human motion patterns to robot embodiments — all without task-specific training. #WorldModel# #EmbodiedAI#

Embodied AI Enters Deployment Year One, and @AGIBOT_US put A3, X2, and G2 in front of the North American automation crowd 🤖 A3 and X2 showed the service side: performance, reception, guided tours, and real work already moving into restaurants and exhibition halls. G2 showed the industrial side: teleoperated wire-harness routing, connector mating, precise grasping, visual perception, dual-arm coordination, and Jenga stacking. That was more than a booth interaction. Teleoperation is one of the ways robots learn. The factory follow-up was the stronger signal: G2 completed a 6-day tablet-inspection livestream on LONGCHEER’s real production line. 99.99% task success rate. 2 mm precision fluctuation. 17,625 units produced. 64,828 robot operations completed. Cycle time stayed at 22 seconds per operation. The livestream ran for 64 hours from June 23 to June 28, 2026. By the end of it, the robots had already been running on that line for 105 days, from March 16 to June 28. This is the shift we actually want to see: humanoid robots moving from demos into real factory work. #AGIBOT# #Automate2026# #EmbodiedAI#

🕶️ Walk through a first-person world with your own body motion, and explicitly specify what exists at a given location with an image and pose, including how it evolves over time. Meet AnchorWorld, an embodied egocentric world model. Title: AnchorWorld: Embodied Egocentric World Simulation with View-based Evolution Customization URL: 📝 Overview AnchorWorld generates first-person video controlled by full-body human motion. With "anchor views," it lets you explicitly specify what exists at a given 3D location and how it changes over time. ❓ Challenges Solved Existing world models struggle to supervise full-body motion from egocentric video alone, and define environments only implicitly. They lacked both natural embodied control and localized world customization. 💡 Methodology & Proposed Approach ・Since most of the body is invisible in first person, it uses third-person video as auxiliary supervision to learn body-environment positioning ・An anchor has three parts: an RGB image, a 6-DoF viewpoint pose, and an evolution prompt that specify local appearance and temporal change ・3D RoPE spatially distinguishes multiple anchors, and masked cross-attention enables anchor-specific text control ・It trains in four stages (third-person, first-person, static anchors, dynamic evolution), built on Wan 2.2 TI2V 5B 🎯 Use Cases It applies to embodied VR apps, first-person game environment design, embodied-AI training scenarios, and interactive video generation with localized control. 📊 Experimental Results ・On egocentric static scenes it reaches CLIP-V 0.885 and camera accuracy ATE 0.112m, beating PlayerOne and others ・On egocentric dynamic scenes, text alignment (VideoAlign-TA) is 0.717, far above CaM-Ego's 0.385 ・It generalizes strongly to out-of-distribution UE and real-world scenes with little visual overlap between the initial view and anchors #WorldModel# #EmbodiedAI#

Post-2000s Data Collectors: Teaching Embodied AI Robots to Learn In Jiaxing, Zhejiang, young “data collectors” at Institute of Flexible Electronics Technology of Tsinghua train robots by demonstrating daily tasks like folding clothes and cleaning. Wearing VR goggles and using mechanical claws, they record movements for robots to mimic. Yang Huiqin, a post-2000s graduate, said the job required controlling natural habits to avoid damaging robot parts. She named her robots to give them “life”, and the improvement of robots’ accuracy brought her great fulfillment. With growing demand, the institute now employs nearly 300 collectors, mostly post-2000s, and partners with schools for internships.