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Only First party#Robot models and learning
Oct 14Wed
  1. 珞石机器人50

    CIIF Live: Rokae's humanoid force-controlled arm makes its first appearance after 10,000-unit delivery, showcasing industrial embodied intelligence deployment solutions

    Rokae Robotics made its first appearance at the 2026 China International Industry Fair, presenting the results achieved after the delivery of 10,000 humanoid force-controlled arms. The Zhuxing H series wheeled humanoid robot, equipped with the ROKAE-Brain multimodal model and the Xuanhe iNex control system, has already been deployed in real manufacturing scenarios such as the Schaeffler factory for tasks including bin picking; ROKAE-Brain achieves a task success rate of 95%-99% in vertical tasks such as precision assembly. The Taibai AR series force-controlled arm has seven degrees of freedom, a force-control bandwidth exceeding 30Hz, and a force-control resolution of <0.05N.

Oct 13Tue
  1. 云启资本66

    Stardust Intelligence completes new RMB 1 billion funding round at RMB 15 billion valuation

    Stardust Intelligence recently completed a new funding round of RMB 1 billion, reaching a valuation of RMB 15 billion. The round was led by Toushe Donghai (Shenzhen Investment Holdings), with participation from Hongtai Fund, Ninghai Xingtaaihe Fund, and Shanheng Capital, among others, and existing shareholder Xianmu increased its investment. This is its fourth funding round in the past six months; its Series B valuation first exceeded RMB 10 billion in June 2026 and rose to RMB 15 billion three months later.

    Why it matters: It reviews the pace of the company's four funding rounds in six months and details of its full-stack architecture, which can be used to understand the commercialization progress of the rope-driven approach.

  2. Physical Intelligence62

    Physical Intelligence opens Pi API beta, offering π model training and inference

    Physical Intelligence has opened the Pi API beta, allowing developers to upload data, fine-tune π models on the company-managed compute and infrastructure, and then run inference through a hosted gateway; the current interface already offers more data-efficient fine-tuning and improvement capabilities.

    Why it matters: Pi API brings data upload, fine-tuning, and hosted inference into one ready-made pipeline, helping readers weigh building their own machine learning infrastructure against calling the API directly.

Oct 12Mon
  1. 松灵机器人55

    What is Mobile ALOHA? How a dual-arm mobile robot learns tasks through teleoperation

    Mobile ALOHA is a low-cost, open-source dual-arm mobile manipulation system proposed by a Stanford research team. It adds a mobile base and a whole-body teleoperation interface to the ALOHA dual-arm teleoperation platform, synchronously collecting vision, robotic arm state, and base motion data through teleoperation, then training policies with imitation learning methods such as behavioral cloning. Among these, ACT predicts a segment of an action sequence at a time.

  2. Pollen Robotics · YouTube64

    Pollen Robotics launches Microduck Arena virtual competition arena

    Pollen Robotics has released Microduck Arena, a virtual arena where Microduck robots race, train, and compete without the need for physical robots. Users train policies with reinforcement learning and publish them to their own Hugging Face accounts to enter challenges; each submission is evaluated uniformly by the Arena, and results can be compared across players. Published policies can be downloaded as .onnx files to watch replays and learn from the best runs.

    Why it matters: It connects policy training, unified evaluation, and replay-based learning into a closed loop, letting readers learn how to train and compare reinforcement learning policies without physical robots.

Oct 3Sat
  1. Sanctuary AI78

    Sanctuary AI releases TIGER method to accelerate robot reinforcement learning with imitation policies as dense rewards

    Sanctuary AI proposes TIGER (Task-Space Imitation Guidance for Efficient Reinforcement Learning), which does not execute the imitation policy but instead maps its action chunks through the controller into end-effector reference trajectories, converting them into dense rewards for reinforcement learning.

    Why it matters: The original text provides the specific approach for converting imitation policies into dense rewards along with ablation data, allowing readers to judge whether it can be applied to their own sparse-reward manipulation training.

Oct 2Fri
  1. Rainbow Robotics61

    Samsung unveils robot commercialization roadmap and Metro-WM world model at Samsung AI Forum 2026

    At Samsung AI Forum 2026, held at its Seoul headquarters, Samsung Electronics unveiled a robot commercialization roadmap led by its newly established RX (Robot eXperience) Business Promotion Office, combining robot foundation model (RFM) and world model technology to first advance automation at its own more than 100 factories and more than 100 production lines, before entering the home assistant robot market.

    Why it matters: The article presents the per-unit cost breakdown of humanoid robots and the success-rate threshold for factory scenarios, which can be used to compare and understand differences in manufacturers' commercialization paths.

  2. Rainbow Robotics63

    Samsung unveils robot commercialization roadmap: factory automation first, then the home

    At the Samsung AI Forum 2026, Samsung announced its robot commercialization roadmap. Centered on its newly established RX (Robot eXperience) business promotion office, the plan is to first advance automation at its more than 100 factories and more than 100 production lines, then enter the home assistant robot market.

    Why it matters: The article lays out the cost math for a humanoid robot at about $100,000 per unit and a three-layer behavior stack, helping readers understand why Samsung puts factory automation ahead of home robots.

Oct 1Thu
  1. Boston Dynamics67

    Boston Dynamics unveils dexterous hand for next-gen Atlas robot: 13-DOF four-finger design

    Boston Dynamics has unveiled a dexterous hand for its next-generation Atlas humanoid robot, increasing from GR2's 7 degrees of freedom to 13, using a four-finger design with a 4-DOF opposable thumb, direct drive, and only a single actuator type. The design drops the pinky finger to reduce cost and complexity, is equipped with fingertip and palm pressure tactile sensors, supports pinch grasping, three-finger grasping, and pressing tool triggers, and was optimized for high-fidelity simulation for sim-to-real transfer and reinforcement learning, with preliminary sim-to-real results on dynamic tasks already available.

    Why it matters: The original article details the degrees of freedom, actuation, and simulation design tradeoffs of the next-generation Atlas dexterous hand, letting readers understand how the hand design serves reinforcement learning and real-world work.

Sep 30Wed
  1. Stial/斯帝尔科技29

    Case Study | Stial's AI Flexible Grinding Robot Targets Weld Seam Grinding Pain Points in Welded Boxes

    Stial has launched an AI flexible grinding solution for grinding weld seams on welded boxes, achieving uniform removal of weld seams, smooth transitions between welds and base material, and no damage to thin-walled base material. The solution uses the self-developed SeeV vision system to locate weld seams, and NextBrain™ AI Mushroom Cloud computing to calculate grinding allowance and generate grinding paths. After digital twin simulation verification, a six-axis robot works with the PolishX flexible force control system to execute the grinding, with force control accuracy of ±0.5%FS and output force as low as 4N, suitable for energy storage, electrical, new energy battery housings, and other multi-category box scenarios.

  2. 北京智在无界科技有限公司58

    Being-H0.7 from ZhiZaiWuJie accepted to NeurIPS 2026, Being-H series completes ICML, CoRL, and NeurIPS acceptances within one year

    Being-H0.7, the general-purpose dexterous manipulation large model independently developed by ZhiZaiWuJie, has been accepted to NeurIPS 2026, marking the Being-H series' completion of acceptances to the three top conferences ICML, CoRL, and NeurIPS within one year.

Sep 28Mon
  1. PsiBot/灵初智能66

    Lingchu Intelligence releases Psi-R2.5, using strong Pair Data to solve human-machine data alignment challenges

    Lingchu Intelligence has officially released its embodied model Psi-R2.5, which uses a two-tier architecture with a QwenVL3.5-4B high-level planner plus a Wan2.2-IT2V-5B low-level controller, and proposes the strong Pair Data standard. The model reverse-invokes the Psi-W0 world model to generate human demonstration videos backward from real-robot data, enabling mass production of paired data, and supports in-context learning (ICL) for zero-shot generalization to new tasks. It comes with a HIL+RL post-training framework and is claimed to raise task success rates to 99% after a few iterations taking only 1-2 working days, and has already been deployed at customer sites.

    Why it matters: The original article details the model architecture, the strong Pair Data data standard, and the reverse-generation method, letting readers understand how its data approach supports real-robot generalization.

  2. Tsinghua Embodied Intelligence and Robotics Institute28

    Excerpt from Professor Zhang Tao's Lecture at the Tsinghua Humanities Forum: Embodied Intelligence Empowers Everything

    Professor Zhang Tao, Dean of Tsinghua University's Institute for Embodied Intelligence and Robotics, delivered a lecture titled "Embodied Intelligence Empowers Everything" at the Tsinghua Humanities Forum. He described three major characteristics of embodied intelligence—generality, interactivity, and autonomy—and noted that key technologies still need to be breakthroughs, including multimodal embodied large models, environmental perception, dynamic planning and control, and dexterous bodies.

Sep 24Thu
  1. CMU Robotics Institute56

    CMU launches LAMP system to help multiple robots collaboratively move objects in crowded spaces

    A team at Carnegie Mellon University's Robotics Institute has developed the LAMP (Long-Horizon Adaptive Manipulation Planning) system, which helps multiple robots collaborate to move objects in severely cluttered spaces by jointly planning object and robot motion rather than handling them separately.

  2. Zerith Robotics/零次方31

    Zero Power Robotics appears at 2026 CIFTIS, deploying Zerith H1 in Malaysia to expand embodied AI overseas

    Zero Power Robotics appeared at the 2026 CIFTIS as a representative company expanding embodied AI overseas; its robot convenience store project demonstrated an unmanned retail loop in which, after a customer scans a code to place an order, the robot autonomously completes product recognition, grasping, and delivery. Recently, multiple Zerith H1 wheeled-arm humanoid robots have been deployed at a laboratory in Malaysia for local solution providers to conduct secondary development, data collection, and model training. The company is continuously iterating its Zerith V series embodied-native motion models and advancing the API-ization of embodied AI physical grasping.

Sep 23Wed
  1. Skild AI62

    Skild AI releases physical self-play post-training results; S1 model learns soccer in simulation and transfers to humanoid robots

    Skild AI announced that it post-trained its foundation model S1 through physical self-play, letting the policy play against a recent version of itself with scoring as its sole objective. In NVIDIA Isaac Sim, over 140 years of simulated time, it learned skills such as dribbling past opponents, shielding the ball, and tackling, and these skills were successfully transferred to humanoid robots for matches. The authors believe self-play can break through the capability ceiling of pretrained human data, and the next step will be to extend it to everyday tasks such as collaborative manipulation and city-scale navigation.

    Why it matters: The authors describe using physical self-play to let a foundation model acquire soccer skills in simulation and transfer them to real robots, which lets readers learn about a feasible path for self-play-style post-training.

  2. MagicLab/魔法原子70

    MagicLab analyzes Magic-Brain's in-context visual guidance design; magicVLA grasp success rate rises from 70% to 94.4%

    MagicLab introduces the visual guidance approach in the Magic-Brain framework: a VLM Agent outputs a bbox, and a segmentation model refines it into a three-color mask overlaid on the observation image, converting semantic guidance into visual guidance.

    Why it matters: MagicLab details the design motivation and implementation of Magic-Brain's visual guidance layer, letting readers understand the impact on grasp success rate of converting language instructions into pixel guidance.

Sep 22Tue
  1. 若愚科技25

    Ruoyu Technology Invited to Attend 2026 Energy Industry Science and Technology Innovation Integration Development Conference

    Ruoyu Technology was invited to attend the 2026 Energy Industry Science and Technology Innovation Integration Development Conference, where founder and CEO Sun Teng delivered a keynote speech introducing the self-developed Ruoyu Jiutian robot brain. This robot brain features multimodal perception, long-sequence task planning, autonomous decision-making and execution, and other capabilities, providing underlying intelligent support for robot bodies; based on the embodied intelligence brain system solution for high-risk energy scenarios built on it, the special explosion-proof robot Ruoyu Lanyue was launched. Following its debut at the Chain Expo, Ruoyu Lanyue recently entered a regular operating gas station, launching pilot operation of multiple new functions.

  2. Tsinghua Embodied Intelligence and Robotics Institute25

    2026 AI Computing Conference Embodied Intelligence and Intelligent Computing Development Forum Held: Unlocking the Future of Robotics and Intelligent Computing Innovation

    The Embodied Intelligence and Intelligent Computing Development Forum of the 2026 AI Computing Conference (2026AICC) was held in Beijing on September 21, hosted by Tsinghua University's Institute for Embodied Intelligence and Robotics, under the theme "Breaking Through the Critical Point of Human-Machine Symbiosis." Scholars including Zhang Tao and Zhao Mingguo of Tsinghua University, along with representatives from companies such as Lingyu Intelligence, Shouyi Technology, and Qianjue Technology, shared results on directions including clinical applications of embodied intelligence, brain-inspired approaches for humanoid robots, data infrastructure, and world models. The forum built an exchange platform for industry, academia, and research, promoting the engineering and deployment of embodied intelligence technologies.

Sep 21Mon
  1. AgiBot49

    AGIBOT demonstrates WITA-Omni real-time human-robot interaction at Greater Bay Area Film Concert

    At the Greater Bay Area Film Concert, AGIBOT used the WITA-Omni omni-modal embodied model to achieve real-machine human-robot interaction; the robot can identify its conversation partner, judge the right timing to respond, and coordinate speech, motion, and facial expressions in real time. The model uses a Thinker-Talker-Actor architecture, and WITA-Omni Preview ranked first on the DailyOmni benchmark with an average accuracy of 85.21%, leading in six of eight evaluation dimensions.

Sep 20Sun
  1. PsiBot/灵初智能73

    Psi Robotics Releases Psi-R2.5 Model: Scaling Human Data for Embodied Intelligence with Strong Pair Data

    Psi Robotics released the Psi-R25 robot manipulation model. Its core upgrades are improved data quality and data attribute compression: it reviewed and extracted high-quality data from 100,000 hours of data, and used strong pair data to align human data with robot data.

    Why it matters: The original article details how strong pair data is generated and the data quality standards, giving readers a referenceable path for aligning human data to robot data.

  2. Robotphoenix/翼菲科技18

    RoboCT Robot Wins 2026 China Embodied Intelligence "Yingxing Benchmark Enterprise Award"

    On September 18, at the EBC 2026 Embodied Intelligence and Humanoid Robot Brain Technology Conference in Shanghai, RoboCT Robot received the 2026 China Embodied Intelligence "Yingxing Benchmark Enterprise Award." At the conference, software algorithm engineer Liu Xiaopeng delivered a keynote speech titled "Engineering Practice of VLA Models in Complex Assembly for Humanoid Robots." Its second-generation Hongjun wheeled dual-arm robot has entered small-batch pilot procurement and completed deployments across multiple industries, and the YiBrain large model has been validated on real production lines.

Sep 17Thu
  1. Figure AI79

    Figure AI releases Helix 2.5, achieving zero-shot full-body autonomy in 30 unfamiliar homes

    Figure AI released Helix 2.5, which completed three long-horizon full-body behaviors—tidying a living room, folding towels, and making a bed—zero-shot in 30 Bay Area homes where no data had ever been collected, without collecting data or fine-tuning in the evaluation environments.

    Why it matters: The original article provides controlled comparison data on Index pretraining for zero-shot generalization and evaluation details, helping readers understand the actual level of humanoid robot pretraining transfer.

Sep 15Tue
  1. 小鹏机器人66

    XPeng XOS 6.3.0 OTA Deploys Second-Generation VLA Upgrade, Adds InfiniVLA and X-Foresight World Model

    XPeng XOS 6.3.0 deploys a second-generation VLA upgrade via OTA, restructuring the model architecture around the time dimension: InfiniVLA lets historical visual information continuously participate in current judgments, with the vehicle side selecting 30 seconds of historical context alongside streaming autoregressive inference.

    Why it matters: The article explains concretely the trade-offs in co-designing model architecture and deployment under onboard compute constraints, making it a useful engineering reference for deploying large models on limited hardware.

Sep 11Fri
  1. PKU EPIC Lab64

    PKU EPIC Lab proposes UniPart for zero-shot language-driven 3D part segmentation

    PKU EPIC Lab proposes UniPart, a feed-forward cross-modal 3D Transformer conditioned on CLIP text embeddings that uses free-text phrases to select functional parts on point clouds, achieving zero-shot language-driven 3D part segmentation.

    Why it matters: The paper presents a text-driven 3D part segmentation method and a self-built dataset, and validates transfer to real-world language-conditioned grasping.

Sep 10Thu
  1. 云启资本60

    Yunqi Podcast Roundtable: Three Embodied AI Founders Discuss World Models, Scaling, and Deployment Bottlenecks

    During the World Robot Conference, Yunqi Capital co-hosted a themed roundtable with SEE Fund, which was included in the podcast Attent!on. Three founders—Xu Huazhe of PokeBot, Li Qiang of Quantum Dynamics, and Liu Nianqiu of Feimo Yi Technology—shared their views on world models, scaling, and deployment.

    Why it matters: The three entrepreneurs approached the topic from models, hardware systems, and mobility respectively, specifically breaking down where the bottlenecks in embodied intelligence deployment lie and where they diverge on scaling efficiency.

  2. Skild AI79

    Skild AI annual recurring revenue tops $100 million, outlines deployment-first robotics strategy

    Skild AI announced that its annual recurring revenue (ARR) has surpassed $100 million, of which $50 million was confirmed within 10 months of starting deployments. It has more than 60 paying customers, covering material handling, delivery, inspection, security, food service, and warehouse, factory, and data center scenarios; about 90% of revenue comes from manipulation tasks, with mobility accounting for 10% (of which AMR solutions account for 4%).

    Why it matters: Beyond the company's self-reported revenue milestone, it also offers concrete lessons on how deployment in turn shapes model research, which is useful for understanding the relationship between real-world deployment and research.

Sep 8Tue
Sep 5Sat
  1. PKU EPIC Lab68

    GIF: An agentic generation framework for interactive and functional object compositions for robot learning

    PKU EPIC Lab proposes GIF, an agentic generation framework for robot learning that reframes the problem as disentangled reconstruction followed by relative pose recovery. CoGen combines 2D and 3D generative models to produce instance-disentangled meshes and coarse initial poses; GPRM refines the relative poses under joint geometric and physical guidance; and a VLM verifier selects the candidate that best matches the structured specification.

    Why it matters: The paper splits interactive and functional object composition generation into disentangled reconstruction and relative pose recovery, and provides a benchmark of eight contact-geometry classes along with collision-rate figures, which can help readers assess this route to simulation data generation.

Sep 4Fri
  1. 智动未来49

    Zhido Future Launches "Zhizi World" World Model, Enabling Xiaozhi S3 to Understand the Real World

    At the 2026 XAIR Expo Embodied Intelligence Industry Expo, Zhido Future unveiled a technical preview of its differentiable world model "Zhizi World" (PGD World Model) and demonstrated validation progress on its embodied intelligent robot Xiaozhi S3. "Zhizi World" reconstructs particle-based scenes from short multi-view videos and can edit parameters such as object pose, material, mass, and friction to predict the physical outcomes of actions. S3 Xiaozhi features bionic dual arms, lidar-vision fusion navigation, and multimodal voice interaction; on-site demonstrations included scooping popcorn, filling cups and delivering them, and self-service retail shopping.

Sep 3Thu
  1. ETH Zurich Robotic Systems Lab38

    euROBIN final event showcases 15 AI robots at the European Parliament in Brussels

    The euROBIN project's final event was held in Brussels, where 15 AI robots joined European researchers, industry, and policymakers to showcase Europe's robotics strength and discuss how to turn research leadership into global industrial competitiveness. The ETH Zurich Robotic Systems Lab team, as a project member, presented its robot Transformer.

Sep 2Wed
  1. PKU EPIC Lab79

    ZETA: A Controlled Study of Zero-Shot Cross-Embodiment VLA Transfer for Tabletop Manipulation

    PKU EPIC Lab published the ZETA study on arXiv (arXiv:2609.02546), proposing a unified definition of zero-shot cross-embodiment VLA transfer and a controlled benchmark covering 14 held-out target embodiments, distinguishing strict zero-shot transfer from pretrain-exposed transfer. Experiments show that local end-effector state-action representations, source embodiment diversity, and auxiliary co-training improve transfer by about 15, 18, and 7 percentage points, respectively, and that adding only 5% target-embodiment data during pretraining raises average target-embodiment progress by 13.4 percentage points.

    Why it matters: The paper provides a unified definition of zero-shot cross-embodiment transfer and a controlled benchmark, allowing readers to understand the actual benefits of different representation and data strategies.

  2. Stial/斯帝尔科技33

    Stial Uses AI Flexible Wet Grinding Solution to Repair Complex Defects in Titanium Alloy Plates

    Stial has released an AI flexible wet grinding solution for repairing scratches and pits in titanium alloy plates. The process includes the SeeV AI perception system to identify defects, the NextBrain™ AI brain to plan grinding paths and process parameters online, and PolishX flexible force control to stabilize contact force, with wet cooling simultaneously carrying away grinding heat. Under the specified range and test conditions, the system's contact force control accuracy can reach ±0.5% FS. The solution transforms experience-driven grinding into a controllable process driven by data and algorithms, and the related technology has been applied in multiple high-end manufacturing fields such as shipbuilding, automotive parts, and 3C electronics.

  3. 机器科学48

    RoboScience launches REX G1 wheeled humanoid general-purpose manipulation robot

    RoboScience has launched REX G1, a wheeled humanoid general-purpose manipulation robot equipped with its self-developed Visics general embodied large model built on the VLOA architecture, targeting scenarios including logistics, factories, retail, and homes. REX G1 has 22 degrees of freedom, can carry 10 kg with both arms, supports ±0.1 mm repeat positioning accuracy, is only 540 mm wide and can enter 0.75-meter narrow passages, and relies on 2070 TFLOPS of on-device compute to complete the perception, decision, and control loop.

Sep 1Tue
  1. 小鹏机器人63

    XPeng's second-generation VLA large model gets its first major upgrade, XOS 6.3.0 to debut globally on the G9L

    XPeng held a sharing and experience day themed "TIME," announcing the first major upgrade to its second-generation VLA large model. The new XOS 6.3.0 version will make its global debut on the XPeng G9L, with the core aim of moving AI from 3D spatial understanding to 4D spatiotemporal understanding.

    Why it matters: The original breaks the upgrade into three specific changes: contextual memory, reasoning approach, and world model. Readers can use these to understand how the shift from spatial understanding to spatiotemporal understanding is realized.

  2. Keenon Robotics/擎朗智能46

    KEENON Robotics showcases KOM 3.0 at the 2026 World Robot Conference, letting robots "think before they act"

    At the 2026 World Robot Conference, held August 19–23, KEENON Robotics showcased KOM 3.0, a VLA architecture for the service industry, which it says integrates a latent-space world model. On site, the XMAN-R1 autonomously completed the full process from picking up a cup to extracting coffee; two humanoid robots collaborated under unified scheduling to wash and fold clothes; and together with the T10 delivery robot and C40 cleaning robot, they demonstrated "general-purpose + specialized" collaborative service. In the demonstrations, the robots completed long-horizon tasks end-to-end autonomously, with no teleoperation.

Aug 27Thu
  1. Pollen Robotics · YouTube64

    Pollen Robotics opens pre-orders for Microduck, a 25 cm reinforcement learning robot

    Pollen Robotics has opened pre-orders for Microduck at $399 (excluding taxes and shipping), with first deliveries targeted before Christmas 2026. The 25 cm-tall robot is built for reinforcement learning, with 15 degrees of freedom, a front camera, an 8x8 LiDAR, two IMUs and a full sensor suite, and supports designing behaviors in simulation and transferring them to the real robot.

    Why it matters: It packs the full loop from simulation training to real-world deployment into a small, pre-orderable complete robot, letting readers gauge the barrier to building their own reinforcement learning workflow.

  2. Pollen Robotics · YouTube62

    Pollen Robotics launches Microduck, a $399 tiny robot that can be trained in simulation

    Pollen Robotics has launched Microduck, a 25 cm tall, 780 g, 15-degree-of-freedom tiny robot, priced at $399 for pre-order (excluding taxes and shipping), with first deliveries targeted before Christmas 2026. It comes in four colorways: Cream, Graphite, Lavender, and Sky.

    Why it matters: The original article provides hardware specs, pricing, and an open-source simulation training entry point, which together indicate the learning value of this small robot for developers.

  3. PsiBot/灵初智能69

    Lingchu Intelligence completes over $100 million new funding round, with industrial capital including Tuopu Group and Chery Ruicheng Fund participating

    Lingchu Intelligence announced the completion of a new funding round of over $100 million. Investors include Tuopu Group, Ruicheng Fund under Chery Holding, Lens Technology, 37 Interactive Entertainment, Wuhu Municipal Investment Holding Group, and Fosun Chuangfu, while existing shareholder Zhuhai Technology Industry Group made an excess additional investment. The proceeds will focus on embodied world model R&D and commercial deployment in logistics and advanced manufacturing scenarios. The company's self-developed dual-system architecture comprises the Psi-R2 manipulation policy model and the Psi-W0 action-conditioned world model, and it plans to expand the scale of human data collection and accelerate the layout of data collection facilities.

    Why it matters: Lingchu Intelligence officially announced the completion of the funding and stated that the funds will go toward world model R&D and commercialization in logistics and manufacturing scenarios, giving readers insight into its industry-finance resource layout.