Physical Intelligence

Physical Intelligence has released π0.7, a new foundation model demonstrating "emergent" abilities to combine skills and adapt to new robot hardware without task-specific training.

Just four months after its last major raise, the AI robotics startup is reportedly seeking new capital to double its valuation as it accelerates the development of its "universal brain" for robots.

Physical Intelligence has introduced RL Tokens (RLT), a method that allows robots to master delicate tasks like screwdriving and zip-tying in as little as 15 minutes, eventually outperforming human speed.

Physical Intelligence (Pi) has unveiled Multi-Scale Embodied Memory (MEM), a hybrid architecture that combines short-term video encoding with long-term textual summarization to help robots master long-horizon tasks like kitchen cleaning and in-context error recovery.

Physical Intelligence (Pi) is positioning its foundation models as a universal 'intelligence layer' for the industry, releasing new data that shows significant reliability gains for laundry-folding and industrial-packaging robots.