Human cognition is a full-body experience, not just a brain function. Current AIs are 'disembodied brains,' fundamentally limited by their lack of physical interaction with the world. Integrating AI into robotics is the necessary next step toward more holistic intelligence.

While language models understand the world through text, Demis Hassabis argues they lack an intuitive grasp of physics and spatial dynamics. He sees 'world models'—simulations that understand cause and effect in the physical world—as the critical technology needed to advance AI from digital tasks to effective robotics.

Unlike cloud-reliant AI, Figure's humanoids perform all computations onboard. This is a critical architectural choice to enable high-frequency (200Hz+) control loops for balance and manipulation, ensuring the robot remains fully functional and responsive without depending on Wi-Fi or 5G connectivity.

Google's robotics strategy isn't to build its own hardware, but to provide the dominant AI "brain." CEO Demis Hassabis envisions the Gemini Robotics model being used by many different robot makers, mirroring the Android OS strategy for smartphones.

The cutting edge of physical AI involves more than just programming a robot's response to a stimulus ("policy"). It also requires a "world capability"—a virtual twin that simulates and predicts outcomes, allowing the physical robot to choose intelligent actions based on those predictions.

Large Language Models are limited because they lack an understanding of the physical world. The next evolution is 'World Models'—AI trained on real-world sensory data to understand physics, space, and context. This is the foundational technology required to unlock physical AI like advanced robotics.

Robotic intelligence has two components. "Reasoning," which involves creating a plan, is quickly being solved by AI. The other, harder part is "movement"—the robot's physical dexterity to execute that plan reliably in a complex environment without tripping or failing.

Neurological studies show the human brain maps a tool's tip as if it were our hand. This implies that a powerful physical intelligence should not be tied to a specific body (e.g., a humanoid) but should be a general "brain" capable of controlling any embodiment, from a bulldozer to a multi-fingered hand.

While China's humanoid hardware demonstrates impressive locomotion in programmed tasks, the major obstacle to widespread deployment is the "robot brain." Current AI lacks the ability to autonomously navigate unpredictable, real-world environments, making massive data collection the current R&D focus.