Physical AI
AI systems that perceive the real world through sensors and execute tasks through physical action
What is Physical AI?
Physical AI refers to AI systems that do not stop at digital output, but act in the physical world. They observe environments through sensors such as cameras, LiDAR, and tactile inputs, then execute decisions using actuators like robot arms, wheels, and grippers.
How does it work?
Its core loop is Perception -> Reasoning -> Action -> Learning. The system interprets real-time sensor signals, plans actions, executes control commands, and feeds outcomes back into training or policy updates. Because this loop runs in real environments, model quality alone is not enough. Control stability, latency, and safety constraints are equally important.
Why does it matter?
Physical AI creates value in industries where digital intelligence must translate into measurable physical execution: manufacturing, logistics, healthcare, and agriculture. It also introduces higher operational risk than software-only AI, so validation protocols, safety governance, and rollout discipline are essential.