AI and the World's Hard Problems · Physics · Nature Computational Science · 2026-10-09
Photonic circuits become trainable AI hardware
The authors demonstrate a physics-based in situ learning method that directly measures optical gradients in photonic integrated circuits. It allows diverse circuit topologies to be trained after fabrication, without requiring a full digital model of the circuit. The hardware is reported to achieve matrix design, multiwavelength computation and rapid meta-learning.