#具身智能

Five new VLAs in LeRobot 0.7. The zoo keeps growing 🤖 - G0.5 from @GalaxeaDynamics: a 2B VLA that writes its subtask, then its actions, in one stream. Works with /subtask and /autosteer - LingBot-VLA 2.0 from @robbyant_brain: one model across embodiments (55-D action space, ~60,000 h of pretraining). Its sparse MoE runs an action chunk in 120 ms in LeRobot, down from 756 ms - DM0.5 from @Dexmal_AI: a Gemma3-4B VLM + a 680M flow-matching action expert, on standard LeRobot datasets - Wall-OSS 0.5 from @XSquareRobot: a 4B VLA that also writes text. It answers /vqa and plans its own subtasks - FineART-VLA: π0.5 with a language head, trained on FineART (more in our language post) Docs in the comments 👇

At Baidu World, Baidu put a Kunlun supernode on stage and said it goes on sale next year. Baidu has run such racks in its own cloud since 2025; the 256-card version went on sale in June. Next year is when a buyer outside Baidu has to take the bet.

Introducing GR00T 2: our most advanced, open System One model for robotics. It runs entirely on your robot’s onboard compute, fully untethered, and you own every weight of it. GR00T 2 features: 1. Long-horizon tasks: dexterous manipulation and whole-body control chained over 20+ steps and 5+ minutes, such as performing chemistry lab experiments or assembling model airplanes end to end. 2. X-Adapt: adapting from easy data sources (human wearables and simulation) and deploying zero-shot to diverse real robots. 3. Unified Cognition: native integrations with frontier agents for advanced physical reasoning, robust error recovery, and safety monitoring. It's an open-source buffet! We are releasing not only the model weights and X-Adapt recipes (coming December), but also our agentic framework, simulation engine, annotation engine, hardware design, and even training data (100K hours, that's ~11 yrs of experience), all available today! Everything that moves will be autonomous. Anyone can become a roboticist. Lock in, build with us! Deep dive in thread:

Introducing PAN 2: an open foundation world model for physical intelligence. A language model predicts the next word. PAN 2 predicts the next world: what happens after each action, grounded in time, physics and space. Towards AI that simulates “what if?” before it acts. More details: ifm.ai/pan/

The results for the 2nd BEHAVIOR Challenge at CoRL 2026 are out! 🚀 In just one year, here's how far we've come together: 🏠 2× benchmark scale: 50 → 100 tasks, 3 → 7 scenes 👥 3× participation: 96 → 265 participants, 18 → 57 submissions 📈 4× full-task success: 12% → 48% Congratulations to our winners! 🥇 The North Star, Huawei Noah EAI Team 🥈 IF1001, Intellifusion 🥉 Cyber, Xiaomi Robotics Thank you to every team, from academia, industry, and independent labs worldwide, for making this year's challenge exceptional! 🙌 📝 Challenge description: x.com/drfeifei/status/2076729… (1/N)

Fable 5.2 shows substantially improved skills in controlling physical robots, even on tasks it has never explicitly been trained to do. On RoboDojo, a benchmark with a simulated two-arm robot, it outperformed other models and most AI systems built to control robots.