Physical AI and the Intelligence of Things

Artificial intelligence is leaving the cloud and entering the world, not as abstract code, but as a property of physical systems themselves. This is the promise of Physical AI: intelligence that is compact, adaptive, and embodied, inspired by the dynamics of living systems. Such AI could make our technologies more efficient, trustworthy, and human-centered, but it also forces us to confront profound questions. What does it mean when intelligence no longer sits apart from the world, but is woven into its fabric? Will Physical AI become a foundation for resilience and care, or will it bind us to technologies we cannot escape or control?

Physical Intelligence is achieved when AI’s power to understand text, images, signals, and other information is used to make physical machines such as robots intelligent. However, a critical challenge remains: balancing AI’s capabilities with sustainable energy usage. To achieve effective physical intelligence, we need energy-efficient AI systems that can run reliably on robots, sensors, and other edge devices. In this talk I will discuss energy and memory-efficient AI models and how they enable physical intelligence.

Speaker: Daniela Rus, Massachussets Institute of Technology

Attend in person or online (see weblink)