Skip to main content

PoV on Physical AI

· 6 min read
Daniel Cho
Daniel Cho
Mellerikat Leader

Beyond Robot AI...​

The concept of Physical AI is often equated with robotic technology. Many envision a future where robots freely navigate spaces and perform tasks on behalf of humans. However, the reality is that it will take considerable time until technology reaches that level. Despite this, much of the current discussion around Physical AI remains robot-centric — which is limiting.

Physical AI does not need to exist solely in the form of a robot. There are already a wide variety of interfaces in our physical world that can interact with AI.



The Physical World Already Has Many “Interfaces”​

The world around us is full of objects and systems that humans constantly interact with. When a fire breaks out, we press a Fire Alarm Button to trigger evacuation. In industrial environments, if a hazard is detected, the Emergency Stop Button is pressed to halt the machinery.

All of these actions serve as links between cognition and physical action.

Based on this, Physical AI can be defined as follows:

Intelligent systems that understand the physical world through visual and sensory information (Perception & Understanding) and perform actions that directly or indirectly influence the physical world based on that understanding.

It is important to note that this process of “visual understanding → action” can be applied across various physical environments. Cameras are already watching the world. AI can now understand these visual scenes, and existing physical systems can receive signals to trigger actions. With this, we already have the foundational form of Physical AI.



Billions of CCTV Cameras Could Be the Beginning​

There are billions of CCTV cameras deployed around the world — effectively acting as the world's “eyes.” When combined with AI models that can analyze them in real time, AI can detect changes in the physical environment faster and more reliably than humans. These detections can lead to a wide range of physical actions, such as:

  • Triggering alarms when dangerous actions are detected on the factory floor.
  • Sending immediate alerts or temporarily reinforcing access control in stores or homes when unusual behavior is detected at night.
  • Sensing vibrations, leaks, or smoke — early warning signs that may escape human attention.

The crucial point is that AI serves as the brain that understands the physical world. And when it can trigger actual changes in that world, the full potential of Physical AI emerges.



The “Camera + Brain + Interface” Structure of Physical AI​

The essence of Physical AI lies not in a specific hardware form, but in a three-component architecture:

(1) Perception: Collecting and interpreting signals from cameras, microphones, radars, vibration sensors, and more.

(2) Reasoning (AI Brain): Understanding what is happening in the observed world through multimodal perception, VLM (Vision-Language Models), and behavior prediction.

  • “A worker seems to have entered a dangerous zone.”
  • “The operational pattern of the equipment appears abnormal.”

(3) Action: Influencing the physical world using actuators like alarm systems, emergency stop buttons, door locks, production line controllers, and IoT devices.

Once these three components come together, the AI becomes a “physical world-interactive entity” — without needing a robotic body. Thus, Physical AI must be redefined not as robot-centered, but as AI architectures designed to see, understand, and act in the physical world.



Tesla Autonomous Driving as an Example of Physical AI​

Tesla’s self-driving system is one of the clearest demonstrations of Physical AI today. Tesla vehicles are not complex humanoid robots, but they play a vital role in the physical world.

  • “Eyes” (Perception): Cameras and sensors collect real-time visual data on roads, vehicles, pedestrians, and more.
  • “Brain” (Understanding & Cognition): AI processes the data, determining the safest and most efficient driving actions (steering, braking, acceleration).
  • “Action”: The vehicle physically moves based on AI decisions.

This is Physical AI in practice — understanding and controlling the physical world through cameras and AI.



Physical AI Is Already Here​

Physical AI is already making a significant impact.

For example, CCTV cameras in manufacturing environments act as “eyes” that detect workers entering dangerous zones or displaying unsafe behavior. AI can instantly trigger alarms to raise awareness or even halt machinery if a hazardous incident seems imminent.

In retail spaces or homes, if intrusion is detected at night, AI can send push notifications and initiate defensive actions such as turning on internal lights or activating alarms.

These are powerful examples of Physical AI directly influencing the physical world through signals and control commands. Physical AI is not limited to robotic arms. It can naturally integrate with existing infrastructure like CCTV, sensors, and networked devices to deliver a wide range of interactions with the physical environment.



Why Physical AI Will Inevitably Spread​

Physical AI is expanding beyond robotics due to several compelling reasons:

  • Lower Infrastructure Cost: Physical AI reuses existing assets — cameras, sensors, and IoT devices — thus avoiding costly robotics hardware investment.
  • Economic Value of Real-Time Decisions: Preventing accidents, reducing production line downtime, and responding to crime all translate into direct financial and social value.
  • Seamless Integration with CPS (Cyber-Physical Systems): Factories, buildings, and cities are evolving into digitally controlled CPS environments, making it easier for AI to interface with physical control systems.


Physical AI Begins When the Physical World Connects to AI Eyes and Brain​

Physical AI is not a far-off dream. It is a reality built on the infrastructure we already have.

Rather than limiting our thinking to physical robots, we can dramatically enhance safety, efficiency, and security by connecting existing cameras and IoT systems with AI intelligence.

The future of technology hinges on how precisely we can build AI systems that understand the world, and how effectively we can connect those systems to physical action interfaces. The evolution of Physical AI will not begin when robots start walking — it will begin when the world becomes observable and reactive through AI.