At the robotics team in @huggingface, we take cyber security very seriously. So we have deployed a physical guard rail to all our robots to prevent further AI security threats from @OpenAI to affect our devices.

This weekend, our team won Paris Builds, a 36-hour selective hackathon by @Unaite, in partnership with @ycombinator. In just 36 hours, we built VIGIE, a robot safety watchdog & harness, an external runtime safety layer for learning-based robots. It watches the robot and its workspace through cameras from the environment, detects dangerous situations, and can pause, hold, and resume a real OpenARM / LeRobot run when the scene becomes unsafe — with a demo harness interfaced with the @LeRobotHF framework. The core idea behind VIGIE is that robot safety should not depend only on the robot policy itself. Today, most robots still operate with little to no external safety harness. The robot executes actions, but there is no independent runtime layer continuously asking: “Is the current scene still safe?” “Is a human hand entering the workspace?” “Is the robot about to continue an action that became dangerous?” We see this as a layered roadmap. Huge shoutout to Joseph @Batatasfri13181 , Maelic, Tristan @tristanlecourt and Raph, amazing sprint. A very special thank you to Alba @leader_arm for helping us set up the OpenARM. Huge thanks as well to @Unaite for organizing the event, and to the mentors, jury members, and partners who pushed us throughout the weekend — including @dessaigne, people from @gs_ai_ , @MistralAI , Qube Research & Technologies, and the broader ecosystem around the event. Big thanks to Stephenson Harwood Paris for hosting us in central Paris. And the cherry on top: winning the hackathon means we earned a YC interview for a chance to join a future batch, which is an incredible opportunity. Repo here:

I placed 🥈 2nd in the LeHome Challenge (at @ieee_ras_icra 2026) earlier this month, and before that I was 🥇 1st of 62 teams in the simulation round. Now I am sharing my solution — with a detailed logic walkthrough and open-source code. The task was to teach a cheap two-armed robot to fold different garments in simulation and on a real robot. I trained a VLA policy with an RL loop to make it work. Let's break it down 👇

The largest open-source humanoid teleop dataset EVER just dropped on @LeRobotHF @huggingface We re-encoded the full dataset into LeRobot format: ~10TB → ~2TB, no loss of fidelity. Same trajectories, a fraction of the footprint, far easier to stream and train on. Explore the dataset in LeRobot Visualizer: live 3D render of the robot, synced camera feeds, subtask annotations and language instructions, all in your browser. Most importantly: Unitree G1 is supported in LeRobot, meaning you can load HIW-500 and start training imitation / VLA policies on 20,000 real-home humanoid episodes on your G1. Huge thanks to @BitRobotNetwork for sharing the data. Go build. 🤖

Have you thought where all that physical AI data should live? 🤖 If you haven’t, 𝗶𝘁’𝘀 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗰𝗼𝘀𝘁𝗶𝗻𝗴 𝘆𝗼𝘂 𝗮 𝗹𝗼𝘁. Unoptimized storage, egress fees, and idle GPUs will drain your budget. Check out why & how to reduce your bill:

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

🤗 LeLab now keeps itself up to date! 🦾 We shipped an in-app popup that alerts you the moment a newer version is on GitHub - plus same upgrades based on users feedback: - Import any external/Hub model to run & rollout, no retraining - Per-camera codec & backend control when recording - Warning when your GPU is present but CUDA isn't being used - Real camera names on Windows & Linux - Smoother calibration & teleop (cameras stay off until you turn them on 🛠️ Update now with: uv tool install --force git+ GitHub: Docs:

ETH has semester-long courses. Stanford? Lecture halls. MIT 826-page textbooks. 📌 Hugging Face’s robotics? 10 minutes… >pip install lerobot That’s it. This command gets you started: Classical foundations. Imitation learning. Reinforcement learning. Foundation models. Real datasets. Real robots. The gap between academic and accessible is closing faster than most people realize. And that matters more than any single course. 📌[ ——- Weekly robotics and AI insights. Subscribe free:

One question follows us to every robotics panel: 𝘈𝘳𝘦𝘯’𝘵 𝘺𝘰𝘶 𝘸𝘰𝘳𝘳𝘪𝘦𝘥 𝘵𝘩𝘢𝘵 𝘰𝘱𝘦𝘯-𝘴𝘰𝘶𝘳𝘤𝘪𝘯𝘨 𝘳𝘰𝘣𝘰𝘵𝘪𝘤𝘴 𝘸𝘪𝘭𝘭 𝘫𝘶𝘴𝘵 𝘮𝘢𝘬𝘦 𝘪𝘵 𝘦𝘢𝘴𝘪𝘦𝘳 𝘧𝘰𝘳 𝘪𝘭𝘭-𝘪𝘯𝘵𝘦𝘯𝘵𝘪𝘰𝘯𝘦𝘥 𝘢𝘤𝘵𝘰𝘳𝘴 𝘵𝘰 𝘥𝘦𝘱𝘭𝘰𝘺 𝘥𝘢𝘯𝘨𝘦𝘳𝘰𝘶𝘴 𝘴𝘺𝘴𝘵𝘦𝘮𝘴? It's a fair question. We think the answer is the opposite of what most people expect: 𝗧𝗵𝗲 𝘀𝗮𝗳𝗲𝘀𝘁 𝗳𝘂𝘁𝘂𝗿𝗲 𝗳𝗼𝗿 𝗿𝗼𝗯𝗼𝘁𝗶𝗰𝘀 𝗶𝘀 𝗮𝗻 𝗼𝗽𝗲𝗻 𝗼𝗻𝗲. Here's why:

VLA-JEPA just dropped in LeRobot 🤖 What makes this model special is that it does not just learn what action to take from a given observation, it also leverages a JEPA world model to learn action-relevant dynamics. During training, the VLA leverages V-JEPA2 by conditioning its predictor. This clever trick adds a world modeling objective to the training, which also allows pretraining on human videos. At inference, the world model is dropped entirely, keeping only a standard VLA architecture: Qwen backbone and action head. The demo here was only fine-tuned on 13 examples, showing great pretraining capability and running in real time on @NVIDIARobotics DGX Spark! VLA-JEPA is the first world model to be ported to LeRobot, and I feel like it won't be the last 🚀 @Thom_Wolf @ClementDelangue

Check out this fantastic video created by @_jong_hyun_park for his channel and Korean audience! It offers a great behind-the-scenes look at what we do at the LeRobot team. We had a wonderful time doing the interview, and the video is packed with interesting insights.