Incredible generalist robots show us a future free of chores
Emerging startup Physical Intelligence has no interest in building robots. Instead, the team has something better in mind: powering the hardware with the continuously learning generalist 'brains' of AI software, so existing machines will be able to autonomously carry out a growing amount of tasks that require precise movements and dexterity – including housework.
Over the past year we've seen robot dogs dancing, even some equipped to shoot flames, as well as increasingly advanced humanoids and machines built for specialist roles on assembly lines. But we're still waiting for our Rosey the Robot from The Jetsons.
But we may be there soon. San Francisco's Physical Intelligence (Pi) has revealed its generalist AI model for robotics, which can empower existing machines to perform various tasks – in this case, getting the washing out of the dryer and folding clothes, delicately packing eggs into their container, grinding coffee beans and 'bussing' tables. It's not a stretch to imagine that this system could see these mobile metal helpers rolling through the house, vacuuming, packing and unpacking the dishwasher, making the bed, looking in the refrigerator and pantry to catalog their contents and coming up with a plan for dinner – and, hey, why not, also cooking that dinner.
"We believe this is a first step toward our long-term goal of developing artificial physical intelligence, so that users can simply ask robots to perform any task they want, just like they can ask large language models (LLMs) and chatbot assistants," the company explains. "Like LLMs, our model is trained on broad and diverse data and can follow various text instructions. Unlike LLMs, it spans images, text, and actions and acquires physical intelligence by training on embodied experience from robots, learning to directly output low-level motor commands via a novel architecture. It can control a variety of different robots, and can either be prompted to carry out the desired task, or fine-tuned to specialize it to challenging application scenarios."
In their research, pi-zero demonstrates how a variety of jobs requiring different levels of dexterity and movements can be performed by hardware trained by the AI. In total, the foundational model carried out 20 tasks, all requiring different skills and manipulations.
"Our goal in selecting these tasks is not to solve any particular application, but to start to provide our model with a general understanding of physical interactions – an initial foundation for physical intelligence," the team notes.