Deepak Pathak

What if AI learned physics the way Newton did – by experiencing it? We built Sim2Reason: train LLMs inside virtual worlds governed by real physics laws, zero human annotation. Result: +5–10% improvement on International Physics Olympiad, zero-shot. 🧵

Excited to share Sim2Reason -- training LLMs in simulation to learn Olympiad-level physics (mechanics)! Today, LLMs learn science by reading what humans have already written, absorbing distilled knowledge from textbooks and the internet. But human-annotated physics data is fundamentally scarce, and that bottleneck isn't going away. Analogy to robotics: Sim2Real transformed robotics, where we train in simulation and deploy zero-shot in the real world. We do not try to teach robots by describing physics to them, but they have to experience it. Approach: Our Sim2Reason makes the same bet we made in robotics -- skip the descriptions, go straight to the source. Let models learn directly from simulated worlds, observing how objects move, collide, and interact, much like scientists build intuition through experiment. Result: Models trained purely on simulated experience develop transferable physical reasoning skills, improving even on problems that were never simulated. Zero-shot gains on IPhO, IIT JEE Advanced, OlympiadBench — problems the model never saw during training.

Excited to share Sim2Reason -- training LLMs in simulation to learn Olympiad-level physics (mechanics)! Today, LLMs learn science by reading what humans have already written, absorbing distilled knowledge from textbooks and the internet. But human-annotated physics data is fundamentally scarce, and that bottleneck isn't going away. Analogy to robotics: Sim2Real transformed robotics, where we train in simulation and deploy zero-shot in the real world. We do not try to teach robots by describing physics to them, but they have to experience it. Approach: Our Sim2Reason makes the same bet we made in robotics -- skip the descriptions, go straight to the source. Let models learn directly from simulated worlds, observing how objects move, collide, and interact, much like scientists build intuition through experiment. Result: Models trained purely on simulated experience develop transferable physical reasoning skills, improving even on problems that were never simulated. Zero-shot gains on IPhO, IIT JEE Advanced, OlympiadBench — problems the model never saw during training.

Modern AI is confined to the digital world. At Skild AI, we are building towards AGI for the real world, unconstrained by robot type or task — a single, omni-bodied brain. Today, we are sharing our journey, starting with early milestones, with more to come in the weeks ahead. Our Mission: Artificial General Intelligence grounded in the physical world. We believe AGI that can truly understand and reason in the real world can only be built through grounding in the physical world. Our Vision: Any robot, Any task, One brain. We tackle robotics in its full generality – building a continually improving, omni-bodied brain that can control any hardware for any task. Who are we? A passionate group of scientists & engineers driven by our shared vision. We have been researching AI and robotics for more than a decade. Our team includes pioneers of self-supervised learning, curiosity-driven exploration, end-to-end sim2real for visual locomotion, dexterous manipulation, learning from human videos, robot parkour, and many more. Many of these works have won awards at top-tier AI and Robotics conferences. Our team has also built production-ready systems at Anduril, Tesla, Nvidia, Meta, Kitty Hawk, Google, Everyday Robotics, and Amazon. Join us in our mission to build the robot brains of tomorrow.

A knee is "killed," but Figure 03 walks away on its own to the repair station. Self-awareness will be a critical safety feature in humanoid controls. A sudden malfunction or part failure shouldn't result in dangerous falls or uncontrolled flailing.

What if AI learned physics the way Newton did – by experiencing it? We built Sim2Reason: train LLMs inside virtual worlds governed by real physics laws, zero human annotation. Result: +5–10% improvement on International Physics Olympiad, zero-shot. 🧵

We have acquired Zebra Technologies’ robotics arm (formerly Fetch Robotics). This is what happens when orchestration meets intelligence -- a major step toward fully autonomous warehouses. More robots. More environments. One unified brain.

RUN PARAM! RUN!