🤖 I’m happy to announce rho-alpha 🤖, @Microsoft's first physical AI model for bimanual robotic manipulation 🦾🦾 built on Microsoft’s own phi-series VLM: microsoft.com/en-us/research… Rho-alpha is unusual among VLAs in a few ways. You can think of it as a VLA+, as we are experimenting with including tactile and force feedback into the set of rho-alpha’s “native” input modalities – in part, using simulation data we generate in #NVIDIA #IsaacSim - while also enabling rho-alpha to continually learn from real-time human feedback. Perhaps most importantly, we envision Rho-alpha and its training pipelines as a foundation – a foundation to help @Microsoft's partners in the robotics space to create powerful physical AI models for their hardware using their data. Currently, the predominant paradigm for this is VLA finetuning. Rho-alpha’s tooling affords much richer approaches by injecting the partner’s data into virtually any rho-alpha training stage to produce custom Rho-alpha versions for the partner’s robots and use cases. For the next few months, we will be refining rho-alpha and will report the results in due time. Why are we announcing rho-alpha already now? Because we want to invite you 🫵- robot OEMs, integrators, and operators - to work with us on the refinement process, and encourage you to apply for the Rho-alpha Research Early Access Program here: tinyurl.com/38p6bn4u Giant thanks and congratulations to @MSFTResearch SPEAR team (@t_hellebrekers, Michael Murray, Galen Mullins, @dean4ta__, Simran Bagaria, Harshavardhan Gajarla), our internal (Reuben Tan) and external research collaborators (@patrickhyin, @abhishekunique7), and TPM Vivan Amin for making rho-alpha happen. 👏 We have a lot more motors to fry and tactile sensors to burn out – that’s how progress in physical AI is made. Stay tuned! 🚀 #Robotics #physicalai @NVIDIARobotics