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?

Nature Machine Intelligence, Published online: 13 July 2026; doi:10.1038/s42256-026-01272-2

Sartore et al. present ergoCub, a humanoid robot that prioritizes human safety at hardware and motion levels. Using a shared embodied intelligence framework, design and control are jointly optimized with human-related metrics such as back stress alongside locomotion objectives, reducing spinal load and improving walking robustness.

Nature Machine Intelligence, Published online: 13 July 2026; doi:10.1038/s42256-026-01260-6

Song et al. propose Sustainability Robotics as a new discipline to overcome fragmentation and enhance societal and environmental impact. They define three guiding principles, alongside two dimensions spanning sustainable design and robotics for sustainability.