ACE ROBOTICS today unveiled Kairos 3.1, its latest action-oriented world model, alongside Ambient Capture Engine 2.0 and three commercial solutions spanning instant retail, hospitality and outdoor service scenarios. The announcements were made at a forum ACE ROBOTICS organized during the 2026 World Artificial Intelligence Conference, convened around the theme of advancing physical AI from 'understanding' to 'execution.' The event brought together economists, technology executives and embodied AI researchers to examine how general-purpose world models can move from laboratory research to industrial deployment.
The forum also marked the launch of PHYSICAL IQ, a unified benchmark for embodied physical intelligence. It was jointly initiated by the Shanghai Artificial Intelligence Association, the Shenzhen Loop Area Institute and the East China branch of the China Academy of Information and Communications Technology, with participation from more than 20 universities and industry partners. Thomas J. Sargent, Nobel laureate in Economic Sciences, discussed the limitations of current intelligent systems in rare and previously unseen situations.
'In the digital world, a model error may result in a flawed image or paragraph. In the physical world, an incorrect action can have real consequences,' said Wang Xiaogang, Chairman of ACE ROBOTICS. 'Kairos 3.1 is built around a first-principles approach to embodied world models, helping robots act more reliably in complex and uncertain environments, and accelerating the arrival of physical AI's Kairos moment.'
Kairos 3.1 is designed as a natively unified model that integrates generative, physical and cognitive intelligence within a single architecture, rather than combining separately developed capabilities. Built on a hybrid Transformer architecture with a shared mixed-attention mechanism, it brings visual observations, language instructions, force and tactile signals, and policy trajectories into a unified latent space. This supports an 'understand, reason, execute and reflect' loop. The model can break down long-horizon tasks, simulate physical cause and effect across multiple scenarios, rank candidate actions, execute the selected strategy and evaluate the outcome for further adjustment.
At the core of its spatial understanding is ACE-BRAIN-0.5. ACE ROBOTICS said it has achieved state-of-the-art results across 12 public evaluations covering spatial understanding, navigation, manipulation and task-progress assessment, among publicly reported models as of July 2026. In a household laundry scenario, a robot can identify spatial relationships between objects, divide a task into more than a dozen steps and verify each stage in real time. If a failure occurs, it can identify the affected step and restart from that point rather than repeating the entire task.
For physical generation and reasoning, Kairos-HomeWorld supports whole-home scene generation and object interaction. It is built on 300,000 residential floor plans, 5,000 simulated home environments and 8,700 3D assets covering six categories of physical properties, designed to reflect common residential layouts in China. The model can simulate multiple action trajectories in parallel and rank them based on predicted success and execution cost before sending instructions to a physical robot. In internal testing, the Kairos 3.1 8B model achieved an inference latency of 125 milliseconds on the NVIDIA Jetson Thor platform at BF16 precision. Its in-house KairosRT computing engine supports real-time, on-device inference. Kairos 3.1 also incorporates self-reflective iteration: when an action fails, the robot can evaluate the result and adjust its strategy.
ACE ROBOTICS also introduced what it calls the 'Information-Density Law' for embodied models: the value of data is determined not only by its volume, but by whether it contains information capable of changing the outcome of an agent's actions. ACE ROBOTICS classifies embodied data across five information-density levels, from L1 to L5. At L5, data incorporates three-dimensional force and tactile signals, failure-recovery trajectories and variables from open environments. Built on this principle, Ambient Capture Engine 2.0 is a human-centric system for capturing, processing and reusing high-density physical-interaction data. Key components include ACE Ego Kit, a lightweight wireless wearable with the ACE Sense Glove offering 0.01 newton sensitivity; ACE Data Engine, an automated data-production platform; and ACE Ego Matrix, which standardizes embodied data across four dimensions. ACE ROBOTICS has open-sourced the framework, which it says placed first on the RoboCase and RoboTwin leaderboards. The company also announced the open release of ACE-Data-0, an L5 household-interaction dataset.
Building on its data infrastructure and Kairos world-model capabilities, ACE ROBOTICS introduced three standardized industry solutions. Xiaoman, its integrated fulfillment solution for instant retail, is paired with the new W1 fulfillment robot, featuring a robot-to-payload weight ratio of less than 2:1 and force-control precision within one newton. It has been deployed with customers including Sense MartGo, Kuaikeda and PetroChina convenience stores. ACE ROBOTICS plans to deploy the solution across 1,000 retail locations over the next year and expand to approximately 10,000 stores within two years. Xiaoxin addresses hotel-laundry operations, where ACE ROBOTICS estimates that approximately 80% of demand occurs at night. Xiaotu is designed for autonomous operation in complex outdoor environments using a 'one brain, many bodies' architecture, and has been deployed in cultural-tourism events such as the Begonia Flower Festival in Tianjin.
ACE ROBOTICS also announced a series of partnerships spanning infrastructure, computing and commercial deployment. The company entered into a strategic collaboration with the Caohejing Development Zone to develop an embodied AI innovation platform. In retail and fulfillment, ACE ROBOTICS announced collaborations with PetroChina, Kuaikeda and SenseTime Shanhui. To support computing requirements, ACE ROBOTICS launched the World Model Cloud Ecosystem initiative with Baidu AI Cloud, Alibaba Cloud, Huawei Cloud, Tencent Cloud and SenseCore AI Cloud. By connecting high-density data, unified world models, robot platforms, commercial applications and shared evaluation standards, ACE ROBOTICS aims to support the transition of embodied AI from individual technical demonstrations to sustained operations in real-world environments.
