Physical AI refers to the integration of advanced machine learning with fundamental laws of physics to enable autonomous systems to interact intelligently with the material world.
Unlike generative AI, which processes digital data, Physical AI utilizes real-world sensory input to understand structural integrity, thermodynamics, and material degradation.
This capability allows for precise predictive modelling of physical assets, optimizing their performance and longevity. It is the essential intelligence layer that transforms raw sensor data into actionable insights for autonomous maintenance.
Physical AI serves as the "body," sensing and interpreting physical laws, while LLMs act as the "brain," offering high-level reasoning. Together, they connect human language with material action, enabling complex autonomous decision-making in industrial environments.