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Only First party#Robot models and learning
  1. Shanghai AI Laboratory - Embodied Intelligence70

    Shanghai AI Lab launches Sage·LabOS laboratory operating system

    Shanghai AI Lab has launched its laboratory operating system Sage·LabOS, which uses Sage SCP-Lab as a unified interface and the Sage physical world model W0 to drive robots in completing experimental operations, connecting heterogeneous devices for autonomous execution and data return. The system has four core capabilities: capability discovery, task orchestration, execution scheduling, and data feedback. In a lipid nanoparticle (LNP) formulation optimization task at Lingang Laboratory, it completed five rounds of dry-wet closed-loop iterations, automatically synthesizing and validating 335 formulations, with encapsulation efficiency rising from 67% to 98%.

    Why it matters: The source provides the four core capabilities of the autonomous laboratory operating system and measured dry-wet closed-loop data from LNP formulation optimization, showing how robots can be integrated into scientific research workflows.

  2. Beijing Humanoid Robot Innovation Center70

    Beijing Humanoid releases Hi-WBC general whole-body control model on "Huisikaiwu" platform

    Beijing Humanoid released the Hi-WBC general whole-body control model on the "Huisikaiwu" platform on November 2. The model combines human motion references with real physical constraints, enabling robots to adjust how they execute tasks as payload, external forces, and terrain change. It uses a continual skill expansion framework based on MoE and policy distillation, Contact-aware Learning that incorporates contact force prediction, and Perceptive Control that introduces terrain awareness.

    Why it matters: The original text discloses Hi-WBC's technical approach to handling payload, external force, and terrain constraints beyond motion tracking, offering insight into how whole-body control is moving from demonstrations toward real work.

  1. AgiBot72

    Six AGIBOT G2 robots complete 24-hour trial at Shanghai convenience store, performing 1,730 tasks

    Six AGIBOT G2 wheeled humanoid robots completed a 24-hour trial at an operating convenience store in Xuhui District, Shanghai, performing a total of 1,730 tasks, with four of them passing the final assessment.

    Why it matters: AGIBOT disclosed the task distribution and assessment results of six G2 robots over 24 hours in a real convenience store, offering a view of how embodied intelligence performs in continuous operation.

  1. PsiBot/灵初智能71

    Lingchu Intelligence and collaborators propose FAFM, a continuous action generation method for heterogeneous-frequency data, accepted to NeurIPS 2026

    Lingchu Intelligence, together with Beihang University, Peking University, and The Chinese University of Hong Kong, proposed a frequency-aware flow matching method called FAFM; the paper was accepted to the NeurIPS 2026 main conference. The method uses the discrete cosine transform (DCT-II) to represent actions as frequency-domain coefficients corresponding to real time, performs flow matching in coefficient space and constrains the first-order time derivative, requires no additional learnable parameters, and can be used independently or integrated into VLA models such as π₀ and π₀.₅.

    Why it matters: The paper presents a frequency-domain action representation that adds no learnable parameters and can be integrated into existing VLA models, offering a transferable approach for joint training on heterogeneous-frequency data.

  2. PsiBot/灵初智能71

    PKU-Spirit AI Joint Lab's RoboFFT Accepted to CoRL2026, Uses Reinforcement Learning Post-Training to Generate Robotic Policies

    RoboFFT, proposed by the PKU-Spirit AI Joint Lab, has been accepted to CoRL2026. It is a reinforcement learning post-training method for generative robotic policies that reuses the forward noising process from diffusion model and flow model pretraining to construct an approximate probability ratio for PPO-style clipped updates.

    Why it matters: The method reuses the forward noising loss of diffusion and flow models to construct policy update signals, offering a reusable approach for post-training generative policies.

  1. 戴盟机器人72

    Daimon Robotics completes hundreds of millions in strategic financing, led by Ant Group

    Daimon Robotics announced the completion of a strategic funding round of hundreds of millions, led by Ant Group with existing shareholders oversubscribing, just two months after its hundred-million-yuan Series A. The company also launched its tactile-anchored world model Daimon-TWM, with parameter scale at the 10B level, capable of real-time inference on the NVIDIA RTX 5090 platform, and claims that its average success rate on contact-intensive manipulation tasks is twice that of π0.5. Daimon has also built the tactile full-modality dataset Daimon-Infinity; after the first 10,000 hours of data were open-sourced, it received nearly 5 million downloads on the ModelScope community.

    Why it matters: Beyond the funding news, the original article also details the architecture and data-collection layout of the tactile world model Daimon-TWM, which helps in understanding the technical proposition of the tactile approach.

  2. AgiBot75

    AGIBOT Unveils Worken Metrics Framework, AHA3 Hardware Platform, and G2 Max Industrial Robot at 2026 Innovation Day

    At its 2026 Innovation Day, AGIBOT proposed the Worken (effective intelligent working hours) framework, which measures robots' effective output in real environments using three metrics: number of active robots, autonomous working hours, and output efficiency ratio.

    Why it matters: AGIBOT announced its hardware platform, foundation model, operating system, and mass-production model all at once, giving readers a basis to judge its shift from manufacturing scale to measurable output.

  3. AgiBot72

    AgiBot releases embodied foundation model GO-3 Preview, ranks first on three embodied intelligence benchmarks

    AgiBot has released the embodied foundation model GO-3 Preview, built on its self-developed WRAM (World Reasoning Action Model) architecture that unifies task understanding, future state prediction, and action generation, and it ranks first on three embodied intelligence benchmarks: RoboDojo, RoboTwin, and RoboColiseum. It is planned to be fully open-sourced by the end of 2026.

    Why it matters: The original article fully discloses GO-3 Preview's three-stage design of pretraining, post-training, and post-deployment learning, which can be used to understand the engineering path for scaling embodied models across their full lifecycle.

  1. 云启资本60

    PHYMI Tech releases first robot Sagi, featuring four-wheeled-legged humanoid configuration and PHYMI BRAIN 1.0

    PHYMI officially released its first robot, Sagi, on October 28. It adopts a "four-wheeled-legged humanoid configuration" combining four wheeled legs with a humanoid upper body, dual arms, and a rear box, targeting scenarios such as office delivery, community errands, and outdoor camping transport.

    Why it matters: The first four-wheeled-legged humanoid robot presents a complete design approach covering configuration trade-offs, a three-layer model, and a data system, allowing comparison with existing bipedal routes to understand the choice of form.

  2. Yaskawa70

    Yaskawa Electric and GAZOO Racing to Bring AI Autonomous Welding Robot Technology to GR KART Manufacturing Site

    Yaskawa Electric and Toyota GAZOO Racing have jointly developed AI-driven autonomous robot production technology, with deployment beginning in September 2026 at the Gamagori GR KART workshop. The technology builds on the SFA method (Sequence Freezing Arc Welding) jointly developed by the two parties in 2024, and uses MOTOMAN NEXT robots equipped with GPUs and AI to autonomously recognize the state of pipe frames, complete welding, confirm and correct quality, and analyze appearance images, welding sounds, and various data in an integrated manner.

    Why it matters: Yaskawa and GAZOO Racing are extending their SFA welding experience into an AI autonomous welding line, and it has already gone into actual production at the GR KART workshop, offering a view of how welding automation moves from validation to the mass-production floor.

  3. Shanghai AI Laboratory - Embodied Intelligence60

    Shanghai AI Laboratory and partners jointly launch materials multimodal large model "Caihua·MatVerse"

    Suzhou National Laboratory, Shanghai AI Laboratory, Shanghai Jiao Tong University and others jointly launched the "Caihua·MatVerse" materials multimodal large model and agent application system, which uses an "independent encoders plus unified decoder" architecture to align XRD spectra, electron microscope images and molecular structures into the same semantic space.

    Why it matters: The materials present a multimodal unified representation architecture and 19-category disciplinary evaluation benchmarks, offering insight into how materials large models can move from retrieval to mechanistic reasoning.

  1. 云启资本60

    Synrise completes Pre-A round exclusively invested by Yunqi, first smart knee S5 in mass production

    Synrise announced the completion of a Pre-A funding round exclusively invested by Yunqi Capital, with proceeds going toward the SynchroMind algorithm foundation, R&D for next-generation products, and global market expansion. Within one year of founding, the company's first product, the Synrise S5 bionic intelligent hydraulic knee, has entered mass production, completed validation deployments in Europe, and received orders exceeding ten million yuan from domestic and overseas markets. A next-generation AI active-power knee is now in R&D, aiming to move from compliant motion to active power output.

    Why it matters: An approach to human augmentation starting from intelligent prosthetics, showing how an algorithm foundation can be reused across products and accumulate real gait data.

  2. Kinetix AI · YouTube67

    Kinetix AI releases KAI World Model, supporting locomotion and manipulation tasks

    Kinetix AI has released the KAI World Model, which is based on parallel video generation and 4D spatial modeling and can simultaneously generate virtual worlds and reconstruct spatial scenes. The model was pre-trained on millions of videos and supports pure locomotion, pure manipulation, and coordinated locomotion-manipulation tasks; it claims generalization across tasks and across robot embodiments. Live demonstrations include a robotic arm autonomously opening a beverage can and a humanoid robot playing real-time table tennis rallies.

    Why it matters: The original shows live demonstrations of the world model on two types of tasks—a robotic arm opening a can and a humanoid playing table tennis—which can be used to understand its approach to generalization across tasks and embodiments.

  3. AgiBot73

    AgiBot releases Genie Studio 2.0 embodied intelligence development and deployment platform

    AgiBot has released Genie Studio 2.0, an embodied intelligence application platform covering development, deployment, and operations. It consists of three modules—Flywheel, Agent, and Monitor—that connect data collection, model training, evaluation, inference, task orchestration, and robot fleet management.

    Why it matters: The original text provides the platform's three major modules and validation data from multiple production lines, which can be used to assess the engineering chain of embodied applications from development to operations.

  1. NEURA Robotics74

    NEURA Robotics unveils 4NE1 Gen 4 humanoid robot and opens TUM RoboGym with Technical University of Munich

    NEURA Robotics and the Technical University of Munich (TUM) have opened TUM RoboGym at LabCampus near Munich Airport, covering more than 2,300 square meters. TUM MIRMI is a co-builder, the initial collaboration runs for three years, and the two parties are jointly investing about 17 million euros, of which NEURA is contributing about 11 million euros.

    Why it matters: The original text covers both the new robot's hardware changes and the three sources of training data, letting readers understand NEURA's approach of tying data infrastructure to the hardware launch.

  1. NVIDIA80

    NVIDIA Expands Isaac Platform with New Humanoid Reference Platform, Isaac OS, and Isaac Lab 3.0

    At GTC Berlin, NVIDIA announced an expansion of the Isaac open-source robotics development platform, adding the Isaac OS runtime, the officially released Isaac Lab 3.0 learning framework, and an open-source reference workflow based on DGX Station.

    Why it matters: The original text lists the runtime, learning framework, and open-source workflow newly added to the Isaac platform, allowing readers to judge the specific changes in the data-to-deployment pipeline.

  1. Dexmate72

    Dexmate and CMU Release MeMoREval Benchmark: Robot Storing Camera Frames Beats Text Descriptions

    Dexmate and CMU introduced the MeMoREval benchmark, which uses a two-stage protocol of experiencing first and asking questions later to evaluate what embodied agents should store as memory. It includes 53 tasks and 4 simulated indoor environments, and runs on the Vega 1 Pro dual-arm mobile manipulator. Results show that storing raw camera frames scored 70% and had lower write cost, surpassing text descriptions at 56 to 60%; adding scene graphs achieved the highest overall success rate among all tested models. The protocol also completed two memory retrieval demonstrations on a real Vega 1 Pro using a SLAM map and head camera.

    Why it matters: The benchmark was proposed jointly by the platform developer and CMU; its frame-versus-scene-graph comparison can help with memory design choices, and the real-robot transfer offers a feasibility reference.

  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.

  1. 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.