Photonic circuits become trainable AI hardware

Summary

Nature Computational Science, Published online: 09 October 2026; doi:10.1038/s43588-026-01071-0 A physics-based in situ learning method is demonstrated that directly measures optical gradients with photonic integrated circuits, allowing diverse circuit topologies to be trained after fabrication. This hardware achieves matrix design, multiwavelength computation and rapid meta-learning without requiring a full digital model of the circuit.