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Phys.org — Physics · October 9, 2026 · On the brief until October 23, 2026

Physics model reveals fundamental trade-off between prediction and energy efficiency in intelligent systems

PhysicsComputer Science
THE AI ANGLE
Facing thermodynamic limits on prediction and energy efficiency

Physicists modeled active agents whose actions alter their environments and proved that maximizing energy extraction requires forgetting useful past data. This trade-off between accurate prediction and energy efficiency stems from the laws of thermodynamics rather than hardware limits. The result provides a baseline for designing future energy-efficient computing systems.

Summary written by AI Business Lens with an AI model from the article at phys.org. It is not the article, and the publisher has not reviewed it. For publishers.

THE TEACHING ANGLE
Students can examine why an agent must discard predictive information to maximize the energy it extracts from its environment.

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