This is our release that I am actually most excited about because it shows and proves what truly matters. Deployment is the ultimate prize and the only reliable eval for robotics. After having worked on so many research projects and models in my career, where I saw so many new capabilities I had never seen before, there was always a question in the back of my mind: do they matter and how? At a time in robotics where the signal-to-noise ratio is so low, where there’s so many demos, models, pilots, you see everyday, the conclusion I arrived at has always been shipping our models, robots, and entire systems to real customers and proving that they actually fulfill a need for real people. Showing a demo is easy, proving that the robots create sustainable value for customers over a long period of time is extremely hard. We know it's hard, but we also know it's necessary to get right. This mindset is also why I decided to start Dyna with @Lindon_Gao and @YorkYang5050 in the first place, because our heart has been focusing on the right problems from day 1. It’s great to see the whole team’s effort culminating in this first scaled deployment release of its kind for the industry. But we are just getting started, and I am more excited about the future of the physical economy than ever before.

I will be at #Actuate26# giving a talk on the model and infrastructure behind dyna-2. Excited to chat with everyone about scaling robot foundation models and deploying them in the real world! Please reach out if you'd like to chat!

Thanks Eric! High praising from you means a lot! Our goal with each release has always been shipping real impact to the whole field. Dyna-1: demonstrating the first reliable models; the way we demo'd has become industry standard by now Dyna-2: redefining frontier robotic scaling research; I certainly hope to see more progress on this front!

Super excited to share Dyna-2, the first robot foundation model trained on over 1 million hours of human data. At this scale, we saw the emergence of a cross-embodiment transfer scaling law: training on increasing amount of human data not only improves model prediction on held-out human data but also on robot data the model has never seen before 🤯 We validate that this transfer scaling law does translate to on-robot performance across 3 different robot platforms, and uncovers that both training objective and data matter greatly for this emergence. Crucially, our results position video as a new scaling axis for physical AI. Beyond these scaling-law oriented results, we also dissect Dyna-2 greatly, going in-depth on its many capabilities, including language following via world modeling, enhanced robustness and precision, zero-shot customer site deployment, and some cool video generation results! Read our technical blog post for more details! I do think this is a very important result that shows a very different path for robot foundation models from the ones we are marching on. Really excited for the road ahead. We have more releases coming, stay tuned!

Many people are excited about our grippers and the task (rightfully so, maybe we should release a blog on that too?), but our release is actually about “cracking” something much different, and much more fundamental.. Coming soon