Huge shoutout to the entire team and everyone involved behind the scenes! 🙌 KAI0 is going fully open-source this week. 🚀 📄 Paper: arxiv.org/abs/2602.09021 💻 Code: github.com/OpenDriveLab...

🧥 Live-stream robotic teamwork that folds clothes. 6 clothes in 3 minutes straight. χ₀ = 20hrs data + 8 A100s + 3 key insights: - Mode Consistency: align your distributions - Model Arithmetic: merge, don't retrain - Stage Advantage: pivot wisely 🔗 mmlab.hk/research/kai0 checkout 3mins demo

🚀 HERE WE GO! Join us at CVPR 2025 for a full-day tutorial: “Robotics 101: An Odyssey from a Vision Perspective” 🗓️ June 12 • 📍 Room 202B, Nashville Meet our incredible lineup of speakers covering topics from agile robotics to safe physical AI at: opendrivelab.com/cvpr2025/tut... #cvpr2025

Thanks for sharing! I will host the workshop for the whole day and welcome anyone who is struggling with current embodied AI trend to visit and chat and exchange ideas! We want to hear the opposite opinions from vision and robotics people on the topic of autonomy.

When at @cvprconference.bsky.social a major challenge is how to split yourself for super amazing workshops. I'm afraid to announce that w/ our workshop on "Embodied Intelligence for Autonomous Systems on the Horizon" we will make this choice even harder: opendrivelab.com/cvpr2025/wor... #cvpr2025

Wonderful end-to-end driving benchmark! We are getting **closer and closer** to **close-loop** evaluation in real world!

DriveLM got 1k stars on GitHub, my first project reaching such milestone. Great thanks to all my collaborators who contribute much to this project, many thanks to the community who participate and contribute better insight upon this dataset, and wish this is not my end!

Thanks for sharing! We long to know if we could improve e2e planner with limited but online data and compute, as performance with more training data seems plateau. However, online failure cases are unexplored as they couldn’t directly contribute to the model performance via previous training scheme.

Random thoughts today: in humanoid research the methodology is basically decided by the final tasks/demo you would like to show off.

🌟 Previewing the UniAD 2.0 🚀 A milestone upgrade on the codebase of the #CVPR2023 best paper UniAD. 👉 Check out this branch github.com/OpenDriveLab..., and we will get you more details soon

🚀 This year, we’re bringing you three thrilling tracks in Embodied AI and Autonomous Driving, with a total prize pool of $100,000! Now get ready and join the competition! Visit the challenge website: opendrivelab.com/challenge2025 And more on #CVPR2025: opendrivelab.com/cvpr2025

Thanks for all the staff who work hard to make it happen! Love to hear your feedback.

Random thoughts (again) on: 1. Benchmark & Evaluation & Metrics 2. Data collection (especially tele-op) 3. Policy network architecture & training receipt.

Random thoughts today: situation in humanoids today is similar to autonomous driving back into 2020-ish. Different hardware setups, people more favor of RL-based planning and sim2real deployment, etc. Will humanoids get into a similar development curve like driving?

We implemented undo in @rerun.io by storing the viewer state in the same type of in-memory database we use for the recorded data. Have a look (sound on!)