1/ muse spark 1.2 is a very strong multimodal model—it can do visual coding, robotics planning, and audio-visual understanding that all come together through agentic tools.

Our G1 robot found its way to the pantry, picked up a Pringles can, and handed it over. No pre-built map. No training for this task. Behind it is a coding agent, writing, running, and fixing the robot's programs as it goes. And it self-evolves: what works is saved as code for the next task, no retraining needed. This is ASENA. Joint work with @Isabella__Liu, @edmund_bu, Johan Bjorck, @yin_hongxu, @zhengyiluo, @jankautz, @DrJimFan, @yukez, and @Sifei30488L. 🧵👇

Can we scale robot learning without scaling human labor? 📈 Demonstrations, resets, failure recovery, constant supervision—collecting robot data still takes substantial human effort. 🔑 Three keys let agents take on more of the work: 1. Real2Sim2Real: Agents explore and learn in digital twins, where trial and error is safer and cheaper. 2. Autonomous Recovery: Robots learn to recover from unexpected failures instead of waiting for human resets. 3. Human-on-Demand Learning: Multiple robots run in parallel, and humans step in only when autonomous recovery falls short. 🥑 Recova brings these together to get more robot learning out of every hour of human effort. research.nvidia.com/labs/gea… Joint work with @anjjei, Johan Bjorck, @ZhidingYu, @yin_hongxu, @jankautz, @DrJimFan, @yukez, and @Sifei30488L. 👇 Here's how it works 🧵

Today we give Atlas dexterous hands, with the strength to take on real work, and the simplicity for mass manufacturing. Like the body, the hands are designed with high fidelity simulation in mind, to enable sim-to-real RL. If you give dexterous hands to a robot, make them do dexterous things. More thoughts here Blog: bostondynamics.com/blog/robo… Video: youtube.com/watch?v=4whgw2gL…

Meet FINGR: a dexterous hand that solves a 2×2 Rubik’s Cube with continuous finger tricks. Here’s how we got the fingers to work together. 🧵

some belated life updates: earlier this year, i left academia and joined meta to work on personal superintelligence. these days i’ve mostly been trying to make our models really good at browser use. back in 2020, i wrote in my phd sop that i hoped one day my mom could use a product i helped build. i guess that day is here :)