New bio-inspired AI architecture designed for resource-constrained robots and wearables addresses physical AI's latency and energy challenges

Artificial Tripartite Intelligence (ATI) proposes a three-level hierarchical system mimicking the brain: Brainstem for safety reflexes, Cerebellum for sensor calibration, and Cerebral Inference Subsystem for reasoning

Sensor-first approach prioritizes controllable, adaptive sensing in dynamic environments rather than scaling model size, addressing limitations of deploying large models on edge devices

Architecture enables closed-loop integration of sensor control, edge-cloud execution, and foundation model reasoning while meeting strict latency, energy, privacy, and reliability constraints for physical AI applications