Building the Foundation
of Physical AI Together
Robots operating in the real world need more than algorithms. Actuators that control force, sensors that perceive the environment, and AI that learns on top of it all — the entire foundation must be ready together.
ONE PhAI designs the structure for realizing Physical AI alongside mechanical engineers, electronics engineers, AI researchers, and industry experts.
By Research & Industry Pioneers
What is ONE PhAI
ONE PhAI addresses the structure that connects hardware, control, and data so that robots can operate amid the diverse physical variables and complexity of reality.
Approach
The Real World Doesn't Behave Like a Simulation
There is a gap between simulation and reality. Friction, gravity, and impact change every moment in the real world. These physical uncertainties are difficult to fully address with mathematical approximations alone. Without a well-defined environment, as data grows, the variables AI must handle may grow alongside it.
Backlash: Response delay caused by gear clearance inside the reducer
Noise: Irregular fluctuations in sensor signals
Elastic Deformation: Micro-bending of structures under load
ONE PhAI first resolves these errors at the actuator layer, creating a structure where AI can focus on high-level decisions without physical burden.
From Centralized to Distributed Intelligence
ONE PhAI adopts a distributed intelligence structure. When the actuator layer absorbs nonlinear errors and the sensor layer filters meaningful data, AI can focus on narrower, clearer problems. We believe that a structure where each layer focuses only on its own role increases stability in complex physical environments.
Lower layers (actuators & sensors) self-correct physical disturbances
Upper layer (AI) focuses on pattern learning and adaptation on refined data
Flexible response to environmental changes
Shared Autonomy — Data Built with Experts
Full automation is not the only goal. In the early stages, robots perform intended motions while human experts observe and intervene in the process. The data accumulated this way is not just sensor records — it is behavioral data containing field experience.
First secure basic robot motions, then generate training data through human intervention
Tacit knowledge of field experts is converted into explicit data
AI gradually expands its autonomy on top of this data
ONE PhAI is a platform that supports this co-evolution process itself.