Announcing the beta release of the Pi API. We’ve partnered with companies across diverse industries to adapt our models to their robots and applications, from harvesting strawberries to assembling servers. Now we’re opening access to more teams.

4. Physical Intelligence X Deft: factory-proven foundation models Deft Robotics and Physical Intelligence are bringing general-purpose robot intelligence into real automotive factories. The task is line feeding: repeatedly picking up parts and placing them onto the production line in the correct position and orientation. It sounds simple. But parts shift around in the material bin as they’re picked. Each pick presents a different position and orientation, making fixed, rules-based automation impractical to deploy at-scale. Physical Intelligence’s robot foundation models, paired with Deft’s hardware and deployment stack, let the robot adapt to this variation. The robot locates each part, adjusts its grasp, and rotates it into position for placement—feeding the line without requiring every part to start in a predefined location. Across both deployments: 500 hours of operation and more than 10,000 parts processed. Every intervention surfaces the failures that matter, so the next model learns from real production failures. It's this iterative loop of deploying, intervening, retraining, and redeploying that makes the robot better over time — not just the cleanest demo. Robot intelligence becomes useful when it survives the factory.

New work with @nvidia: evaluating robot policies entirely inside a world model. The policy acts, the model imagines the consequences, and the imagined evals predict real-world results. 🧵 real vs world-model rollout side by side📷

π, But Make It Fly ✈️ We fine-tuned π0, a VLA model pretrained entirely on manipulators, to fly a drone that picks up objects, navigates through gates, and composes both skills from language commands.

General-purpose AI models are behind some of the most exciting applications we now can't live without. We envision that an analogous “physical intelligence layer” built with models like π0.6 will similarly spur a new wave of applications for the physical world. We’ve recently begun working with a handful of companies that have deployed their robots to do real-world, useful things.