Physical Intelligence
The robotics and embodiment layer — humanoids, manipulators, and autonomous manufacturing systems that close the loop from decision to physical effect.
What this layer does
The physical-intelligence layer closes the loop from coordination decision to physical effect. Without embodiment, planetary coordination is a planning exercise. With it, decisions become motion in the world.
This layer depends on the agentic layer for direction, the AI layer for reasoning, and the cognitive layer for inference primitives. The economic-orchestration layer depends on it: every supply-chain instruction eventually runs through manipulators, humanoids, and autonomous logistics.
What it provides
General-purpose manipulation
Dexterous manipulation across the kinds of objects and tasks that human-scale environments require. We treat this as a foundation-model problem, not a per-task engineering problem.
Whole-body humanoid control
Locomotion and whole-body coordination at human speeds in human-scaled environments. Hardware-software co-design with safe-by-construction torque limits.
Autonomous manufacturing primitives
Modular cells that compose into larger production lines, with reconfiguration measured in days rather than months.
How it is composed
- 01Sensorimotor foundation models trained across multiple embodiments.
- 02Action-tokenization layer enabling cross-embodiment policy transfer.
- 03Real-time inference at the edge with cryostat-equivalent latency budgets in robotics.
- 04Aegis envelopes specifying physical safety invariants (torque limits, exclusion zones, contact constraints).
- 05Operator console with explicit physical-handoff and interrupt primitives.
What's hard
- 01
Contact-rich manipulation at scale
Most progress to date is on quasi-static manipulation. Dynamic, contact-rich tasks remain hard outside of narrow domains.
- 02
Real-time inference budgets
Closed-loop physical control requires inference within strict latency bounds. Foundation-model architectures and edge compute must co-evolve.
- 03
Safety in shared spaces
When humanoids work alongside humans, the safety case must be auditable and provable, not just empirical.
Where the work stands
- Shipped2025
Sensorimotor research stack
Internal pipeline for cross-embodiment policy training and evaluation.
- In progress2026
Bench-top humanoid prototype
Indoor manipulation and locomotion development platform.
- Planned2027+
External operational pilots
Bounded industrial pilots in well-characterized environments.