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Oct 29Thu
  1. New Strategy Robotics74

    AgiBot releases embodied Agent framework Genie Master, validated in real convenience-store scenarios with Physical RSI

    During AI WAVE, AgiBot released the embodied Agent framework Genie Master, which lets robots autonomously locate the causes of failures after deployment, adjust strategies, and accumulate experience. The framework proposes the Embodied Execution Protocol (EEP), unifying four types of interfaces: capability, guidance, feedback, and continuity. Through two routes, Harness RSI and Policy RSI, it retains experience in prompts and memory and solidifies it into action-policy parameters, respectively.

  2. 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.

  4. Reddit r/robotics65

    RynnUnify: 16B unified embodied model combines physical understanding with long-horizon visual planning

    The authors propose RynnUnify, a 16B unified embodied model that combines embodied understanding with long-horizon visual planning through video-language interleaved reasoning. The model covers spatial reasoning, physical prediction, and grounding capabilities, linking physical world understanding with visual anticipation across subtasks. The post also provides links to the code and paper.

Oct 28Wed
  1. APPSO · 微信公众号71

    Google DeepMind releases world model Genie 4, extending single simulation to 120 seconds

    Google DeepMind has released Genie 4, a new-generation world model that extends single interactive simulation duration from about one minute to two minutes and supports native audio generation for the first time. Genie 4 introduces Gemini to plan actions while it generates the environment in real time; in a demo, Gemini 4 Argon breaks a task into consecutive steps, and Genie 4 simulates the Apptronik Apollo humanoid robot playing checkers.

  2. 机器人全球资讯 · 微信公众号70

    AgiBot releases embodied Agent framework Genie Master; Genie G2 works and evolves in a convenience store

    AgiBot has released its embodied Agent framework Genie Master. Equipped with this framework, Genie G2 has taken a job in a real convenience store, where it does not rely on manual demonstrations or debugging; it autonomously identifies the causes of failures, adjusts its strategies, and accumulates experience, continuously improving on tasks such as packaged hot-food preparation, picking, and restocking, achieving self-evolution without a human in the loop.

  3. AI前线 · 微信公众号78

    Google DeepMind Releases World Model Genie 4, Supporting 24 FPS Real-Time Interaction and Native Audio

    Google DeepMind launched its next-generation world model Genie 4 on October 27 local time, calling it its most realistic and interactive world model to date, with a single generated interactive experience lasting up to 2 minutes, compared with 1 minute for the previous generation, Genie 3.

    Why it matters: Google is connecting language models' planning capabilities to real-time world generation, which lets readers understand a new approach to synthetic training grounds for embodied intelligence.

  4. 36氪 · 微信公众号84

    Google DeepMind releases world model Genie 4, supporting real-time interaction and native audio

    Google DeepMind released its next-generation general world model Genie 4 on the evening of the 28th. It can generate and modify interactive scenes in real time based on prompts, sustaining a single coherent world for about 2 minutes at roughly 24 frames per second.

    Why it matters: Genie 4 combines real-time world simulation, native audio, and multi-step reasoning, which lets readers judge that robot training environments are shifting from manual modeling to generative simulation.

  5. 36氪 · 微信公众号11

    AGIBOT GO-3 Nano Preview Tops RoboDojo Benchmark Leaderboard

    AGIBOT's GO-3 Nano Preview has topped the latest RoboDojo embodied intelligence benchmark leaderboard with an average score of 61.90 and an average success rate of 56.42%, surpassing GPT-6 Astra. The model ranked first in all three sub-dimensions: fine manipulation (78.65), long-horizon execution (68.21), and open-ended semantic understanding (61.71).

  6. 硅星人Pro · 微信公众号78

    Google DeepMind releases world model Genie 4, integrated with Gemini for real-time generation and task reasoning

    Google DeepMind has released Genie 4, a new-generation world model that supports real-time generation of explorable virtual worlds and simultaneously generates physics effects, character movements, and native audio. Genie 4 is integrated with Gemini 3.8 Flash as a real-time guiding Agent, responsible for understanding goals, observing the environment, and planning next steps; in the demo, it simulated robotic arm operation in a virtual laboratory.

    Why it matters: Google released the Genie 4 world model, demonstrating its collaboration with Gemini to plan and simulate robot task execution in virtual environments, offering a look at a new way world models can be used for robot training.

  7. 机器之心 · 微信公众号58

    Chaoyan Intelligence releases 35B model Apex-35B-V1.0, leading Recursive Flint on 18 of 21 benchmarks

    Chaoyan Intelligence, founded by Chen Yongchao, an assistant professor at Tsinghua University's School of Artificial Intelligence, has released its first 35B model, Apex-35B-V1.0. It was trained and post-trained on Qwen3.6-35B-A3B, balancing general capabilities such as coding and agents with AI research, computational science, and robot simulation tasks.

  8. 机器之心 · 微信公众号73

    Google DeepMind releases world model Genie 4, supporting real-time control and native audio

    Google DeepMind has released Genie 4, its fourth-generation world model, which can generate dynamic environments in real time; users can control characters or the camera with the keyboard and use natural language to change the weather and add objects and characters. Genie 4 is Google's first world model to natively generate real-time audio, and it also improves physics simulation such as aerodynamics and collisions as well as the naturalness of character movements.

  9. 雷科技56

    Google releases Genie 4 world model: supports real-time interaction, can generate robot training scenarios

    Google has released a research preview of its world model Genie 4, which natively supports multimodality, can change the environment and introduce new objects and characters through instructions during generation, and lets existing characters react. The model is integrated with Gemini, with Gemini Omni anchoring the simulated visual behavior logic to the real world. It is currently open only to invited testers and will later open first to Ultra subscribers.

  10. 新智元 · 微信公众号80

    Google releases world model Genie 4, with three Gemini models jointly driving robot actions

    Google DeepMind has released Genie 4, a new-generation general-purpose world model that natively generates sound and improvised dialogue for the first time, sustaining a single coherent world for about 2 minutes at roughly 24 frames per second of real-machine footage. The model uses a hybrid world-model architecture: Gemini 3.8 Flash handles real-time control, while Gemini 4 Argon breaks tasks into 22-step action instructions, driving an Apollo robot to play checkers and, in simulation, controlling a UR5 robotic arm to perform pipetting operations.

    Why it matters: Google has released the Genie 4 world model, with three Gemini models jointly driving robot action decomposition; readers can learn how world models are used for robot training.

  11. CVer · 微信公众号78

    Google releases world model Genie 4, supporting real-time generation and collaborative reasoning with Gemini

    Google DeepMind has released Genie 4, a new-generation world model that supports real-time generation of explorable virtual worlds, simulates physics and character movements, and natively generates ambient sound effects and dialogue. Genie 4 connects to Gemini 3.8 Flash as a real-time guidance agent, with Gemini planning tasks, observing feedback, and adjusting strategies. In the demo, it simulated robotic arm experimental operations and the Apptronik humanoid robot Apollo playing checkers in the generated environment.

    Why it matters: Google released the Genie 4 world model, demonstrating its ability to collaborate with Gemini to plan and simulate robots executing tasks in virtual environments.

  12. 36Kr Embodied Intelligence58

    AgiBot GO-3 Nano Preview Tops RoboTwin Leaderboard with 85.01% Average Success Rate

    The latest RoboTwin leaderboard shows AgiBot GO-3 Nano Preview in first place with an average success rate of 85.01%. The leaderboard mainly evaluates dual-arm coordinated manipulation and environmental generalization in complex scenarios, with assessment dimensions including target recognition, motion coordination, and adaptation to environmental changes.

  13. 极客公园63

    From Stanford Research to Red Sea Corals: How LingBot Models Are Entering the Foundation of Global Embodied AI

    Geek Park reviewed how the LingBot model series from Ant Group's embodied AI unit Robbyant has been adopted in academia, open-source communities, and industrial toolchains. Stanford's OpenWAM uses the LingBot-VA architecture as a reference implementation, and a KAIST team used LingBot-VLA as a teacher model to raise its student model's single-step inference success rate from 35.3% to 51.2%.

  14. 简智机器人 · X67

    GenRobot.AI's two open-source datasets enter Hugging Face robotics dataset trending top five

    GenRobot.AI announced that both of its open-source datasets, Gen-HumanWholeBody and Gen-HumanEgo, have entered the top five of the Hugging Face robotics dataset trending list. Gen-HumanWholeBody is a first-person whole-body manipulation dataset containing 600 hours of whole-body manipulation data, 16,976 real-world scenes, and 1,281 human skills, with whole-body MPJPE of about 3 cm; the authors say it targets whole-body motion learning, human-to-robot transfer, and embodied foundation model research.

    Why it matters: Two open-source datasets entering the top five of the Hugging Face robotics dataset trending list can serve as a reference for observing the level of attention to whole-body manipulation data.

  15. 智东西62

    iFlytek Releases SparkAudio 1.0 Speech Foundation Model

    During its 2026 Global 1024 Developer Festival, iFlytek released SparkAudio 1.0, a speech foundation model trained entirely on domestic compute. It supports text and speech dual-modal input with text output, and can perform speech transcription, multilingual translation, multi-dialect recognition, environmental sound recognition, speaker separation, sentiment analysis, and complex audio question answering.

  16. 芯东西73

    Google releases world model Genie 4, capable of simulating aerodynamics and collisions with native audio generation

    Google released its next-generation world model Genie 4 on October 28, capable of simulating physical processes such as aerodynamics and collisions, and natively generating music, ambient sound, and interactive dialogue. The model combines capabilities from the Gemini series, with Gemini 3.8 Flash breaking down multi-step tasks in a loop, and Google also demonstrated it combined with Gemini Robotics to simulate an Apptronik Apollo humanoid robot playing checkers.

  19. The Humanoid Hub75

    Google DeepMind releases Genie 4 world model, capable of generating robot training environments

    Google DeepMind has released Genie 4, a real-time photorealistic world model that can be controlled with natural language, adding native audio and improved physics such as collisions and aerodynamics. The model can generate infinitely variable, controllable training environments for robots and agents, and has been paired with Gemini 4 Argon and Gemini Robotics to have Apptronik's Apollo humanoid robot complete a checkers task step by step in simulation.

  21. 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.

Oct 27Tue
  1. 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.

  2. 雷科技70

    AgiBot releases embodied Agent framework Genie Master, validating Physical RSI in a real convenience store scenario

    AgiBot released the embodied Agent framework Genie Master on October 27, enabling robots to autonomously identify the causes of failures after deployment, adjust strategies, and accumulate experience. The framework uses the Embodied Execution Protocol (EEP) to unify four types of interfaces: capability, guidance, feedback, and continuity, and through the two routes of Harness RSI and Policy RSI, it retains experience in prompts and memory, and in action policy parameters, respectively.

  3. 36Kr Embodied Intelligence60

    AGIBOT GO-3 Nano Preview Tops RoboDojo Leaderboard with 61.90 Points

    The latest leaderboard from embodied intelligence benchmark RoboDojo shows AGIBOT's GO-3 Nano Preview taking first place with an average score of 61.90 points and an average success rate of 56.42%, surpassing GPT-6 Astra. In the three sub-dimensions of fine manipulation, long-horizon execution, and open semantic understanding, GO-3 Nano Preview scored 78.65, 68.21, and 61.71 points respectively, ranking first in all three.

  4. arXiv cs.RO77

    AgiBot Team Releases GE-Act 2.0 World-Action Model Technical Report

    The AgiBot Research Team released a technical report on GE-Act 2.0, a world-action model whose generative and action components are all trained from scratch on manipulation data. It consists of a control-oriented autoencoder (CoAE), a single-step visual planner (SVP), and an inverse dynamics model (IDM), and is jointly trained with KASO.

    Why it matters: The original text presents the component design and data-scaling curves for pretraining a world-action model from scratch, allowing observation of changes in zero-shot cross-embodiment transfer.

  5. arXiv cs.RO63

    RoboJev-27B: An Open-Source Vision-Language Model for Judging Robot Task Success

    RoboJev-27B is an open-source vision-language model that takes a task instruction and 10 frames of a manipulation attempt as input and predicts whether the robot completed the task. It achieves 95.2% balanced accuracy and 0.993 AUROC on 268 held-out episodes of the same robot model (SO-101), and an AUROC of 0.890 on 459 episodes from unseen labs or robots. Median inference time is 0.26 seconds per episode on a single H100, and the model, inference code, and evaluation results for 20,628 predictions are released together.

Oct 26Mon
  1. 机器之心 · 微信公众号75

    COCO Matrix releases robot model CO01, using experience prompts to let robots learn while doing

    COCO Matrix released the robot model CO01, which treats demonstrations, failed attempts, and real-time guidance as experience prompts in context, allowing adaptation to new tasks without updating weights. Under the same pretrained model, a roughly 1-minute demonstration achieved an average success rate of 52% on unseen tasks; fine-tuning to a similar level required about 180 demonstrations and about 9 hours. In real-robot evaluations with at most five attempts per task, cumulative success rate rose from 33% on the first attempt to 84% when retaining its own history, versus 56% without retaining history.

  2. arXiv cs.RO72

    RynnUnify Releases 16B Unified Embodied Model Combining Visual Planning and Robot Control

    RynnUnify is a 16B unified embodied model that combines embodied understanding with long-horizon visual planning through interleaved video-language reasoning, covering spatial reasoning, physical prediction, and grounding. The authors also developed an agentic extension based on reinforcement learning to selectively use video prediction to reason about unobserved states and interaction outcomes, and a world-action extension that translates understanding and prediction capabilities into robot control.

Oct 24Sat
  1. 机器之心 · 微信公众号72

    Limpid Intelligence releases PrismWAM and RoboDoctor, topping RoboTwin 2.0 and RoboDojo leaderboards respectively

    Limpid Intelligence founder Li Yiming's team at Tsinghua University released the world action model PrismWAM and the execution diagnosis framework RoboDoctor. PrismWAM decouples semantic context from physical state and, without additional action-data pretraining, achieved an average success rate of 83.67% on RoboTwin 2.0 and 75.5% in the Clean-to-Random setting, ranking first on the official leaderboard.

  3. HuggingFace Daily Papers71

    RoboJev-27B: An Open-Source Vision-Language Model for Robot Manipulation Success Detection

    RoboJev-27B is an open-weight vision-language model that takes a task instruction and 10 frames of a manipulation attempt to judge whether the robot completed the task. It achieves 95.2% balanced accuracy and 0.993 AUROC on 268 held-out episodes of the same robot model (SO-101), and an AUROC of 0.890 on 459 episodes from unseen labs and robots. Median inference time is 0.26 seconds per episode on a single H100, and the model, inference code, and evaluation results for 29 model/protocol entries are released together.

  4. 简智机器人 · X60

    Gen-HumanEgo tops 550,000 HuggingFace downloads one month after release, ranking second among robotics datasets

    One month after release, GenRobot's open-source Gen-HumanEgo dataset has surpassed 550,000 downloads on HuggingFace, ranking second among robotics datasets. The dataset converts synchronized egocentric video via a Data Foundation Model into a unified token representation aligned across video, motion, hand tracking, depth, and semantic annotations, for robot learning and training. GenRobot says more open datasets will be released later.

Oct 23Fri
  1. 新智元 · 微信公众号58

    ZhiZhi Innovation Research Institute publishes IQuest-Q1 technical report: training details of a 320B open-source base model on one million tasks

    ZhiZhi Innovation Research Institute has published a complete technical report on IQuest-Q1, which has 320B total parameters and 15B activated parameters, disclosing results on 30 benchmarks and training details. The team built more than 1 million executable, containerized task instances from code repositories and existing agent trajectories, and set up a three-layer mechanism of environment preparation, runtime checks, and trajectory auditing to prevent reward hacking.

  2. HuggingFace Daily Papers62

    Ψ-0.6: Adaptive Streams of Thought in a Unified Vision-Language World Model

    The research team proposes Ψ-0.6, a unified vision-language world model that adaptively combines perception, language, geometry, and simulation within a shared reasoning process called streams of thought. These streams alternately generate and interpret images, text, and explicit representations of geometry and motion through a shared token interface. The model surpasses leading open-weight models zero-shot on multi-view spatial reasoning, with further gains from reasoning through geometric intermediate representations.

  3. HuggingFace Daily Papers75

    RynnUnify releases 16B unified embodied model combining visual planning and robot control

    RynnUnify is a 16B unified embodied model that combines embodied understanding with long-horizon visual planning through interleaved video-language reasoning, covering spatial reasoning, physical prediction, and grounding. The authors also built an agentic extension using reinforcement learning and introduced a world-action extension that translates understanding and prediction capabilities into robot control.

  4. 36Kr Embodied Intelligence55

    iFlytek releases device-cloud integrated Spark X2.6 and speech foundation model SparkAudio 1.0

    On October 22, at the main forum of the 2026 iFlytek Global 1024 Developer Festival, the device-cloud integrated iFlytek Spark X2.6 was released, with capabilities on both the cloud and device sides (Spark X2.6-4B) improved in sync, balancing task performance, security, and cost through precise division of labor and on-demand collaboration.