Kimi K3 (2.8T MoE) + NVIDIA LeRobot GR00T 1.7. Massive open models for long-context reasoning meet physical AI platforms for humanoid robots. More frontier inference + real-world deployment = exploding GPU/edge compute demand. The race isn't just training anymore. It's agents that think, see, and act. #ComputeRace# #AIAgents#

Your robot arm is probably already supported by LeRobot. You just don't know it yet. The community has shipped 30+ hardware integrations: xArm, UR5e, Franka, Trossen, AgileX Piper, I2RT YAM, ARX5, ugo Pro, Quest and PICO 4 teleop, GELLO, Haply Inverse3 haptics, ROS 2 bridges. Most of them are drop-in plugins. pip install pass --robot.type=... and you're recording datasets. No fork, no patching our repo.

100,000 hours of human hands doing real work. LeRobot format, fully annotated and open. EgoSuite-Open100K from @LightwheelAI X @huggingface: 15,000+ tasks across 15,000+ real scenes, hand + body pose and wrist cams. Recorded across 7 environment categories and 128 scene types, from kitchens and bedrooms to warehouse floors and assembly lines. It's open for academic research and commercial training, and streams straight from the Hub. Always great to see a dataset at this scale released openly on the Hub. More info:

What do you do with 16TB of pure robotic manipulation data? 🤖 You open source it on @huggingface Simple World Lab just dropped HiFi-UMI-2K - an absolutely massive dataset pushing the limits of high-fidelity manipulation. The entire 16TB is already available in the LeRobot format, meaning you can plug this massive scale straight into your pipelines with zero friction. Dataset: Paper:

Most robot datasets store one sentence per episode: the task. Real problems need more: a plan, a memory, room to answer questions and change course. We just shipped full language support in the LeRobot dataset format. Now lerobot-annotate points a vision-language model at each episode and writes the subtasks, plans, memory, and grounded Q&A itself - roughly $1.20 for 100 episodes. From there, recipes turn the annotated rows into policy-agnostic training messages, so the same dataset can teach planning, memory, tool calls, or low-level control, no dataset redesign required. Read how it all works on the blog:

Is it really worth it joining a robotics hackathon? One year ago, thousands of people around the world spent a single weekend building AI robots using the open-source LeRobot stack. Many had never built a robot before. We sat down with the winners to ask what they made and where they are now. For many of them, that weekend changed everything, turning the intimidating field of AI robotics into an accessible hobby or even a full-time career. Here are a few key takeaways from their year-long journey: - You don't need a PhD to start. For many participants, this was their very first robot - One weekend can launch a career. Winning secured internships and full-time jobs - Community lowers the barrier to entry - Learning by doing is exponentially faster. Robotics still requires getting your hands dirty to truly progress Watch the full video to see their projects and hear their advice for taking the first step. @ClementDelangue, @Thom_Wolf

RMB 9,800 (about $1,460) to get started. BLUE WORM just unveiled Mantis Standard. Detach an arm for your desk, build a dual-arm workstation, or add the mobile base and lift for a wheeled humanoid. The arms, base, lift and head use mechanical and electrical quick-connects. Change the configuration, keep the same robot brain: BW-Brain. The full 1.4 m build has 22 degrees of freedom, a rated 7 kg payload per arm and 550 mm of vertical lift. It supports ROS 2, Isaac Sim and LeRobot, with compatibility for π0.5, ACT and SmolVLA. You can simulate a task, collect VR demonstrations, fine-tune a policy and deploy it on the hardware. For a small lab, reusing those components and development tools could mean fewer separate rigs to buy and less integration work.