Nature Machine Intelligence, Published online: 13 July 2026; doi:10.1038/s42256-026-01273-1

The brain’s architecture exhibits diversity across many temporal and spatial scales, yet our computing architectures remain largely homogeneous. Low-powered neuromorphic hardware offers a path towards energy-efficient AI, but could these approaches be improved with heterogeneous computing architectures?