One way of thinking about these results — this is the widest diversity of complex tasks I’ve *ever* seen performed by *any* robot.
Finally, something actually exceeds the ~2010 PR1 videos :)
Also to clarify the video below is teleop, but they have autonomous results for a smaller set but still impressive mix of tasks.
Amazing work @zipengfu@tonyzzhao@chelseabfinn
RT-X: generalist AI models lead to 50% improvement over RT-1 and 3x improvement over RT-2, our previous best models. 🔥🥳🧵
Project website: https://t.co/GAlvFdqwx5
@haqhuy’s new project:
*Scaling up* robot data collection using LLM for ✅ task decomposition ✅ reward formulation
*Distill down* into visuomotor policies that ✅ operate from raw sensory input ✅ improve overtime.
Check out the engaging Q&A here 😉 https://t.co/fDkTSi7843
We just released our work on robot soccer. I've been working on this for quite some time with my amazing colleagues at DeepMind. It's exciting how deep RL can produce such beautiful behaviors with low-cost robots. Full paper is available at https://t.co/A65rPLL7UD Enjoy!
We built PaLM-E 🌴🤖 one of the largest multimodal language models to date, trained end-to-end on robot data. Images, text, state inputs, neural scene embeddings – you name it.
And it's fantastic on robots. Check out Danny's thread 👇