Nature Machine Intelligence, Published online: 03 July 2026; doi:10.1038/s42256-026-01267-z

Berner et al. show how to adapt popular neural networks into discretization-agnostic neural operators that learn from continuous scientific data, enabling scientific simulations that generalize more reliably across resolutions.

Nature Machine Intelligence, Published online: 02 July 2026; doi:10.1038/s42256-026-01266-0

Wang et al. develop DeepEvidence, a biomedical deep research agent for exploring and synthesizing evidence across various knowledge sources to support drug discovery, clinical trials and evidence-based medicine.

Nature Machine Intelligence, Published online: 02 July 2026; doi:10.1038/s42256-026-01264-2

Liu and colleagues introduce HelixFold-S1, a guided sampling strategy for biomolecular complex structure prediction that targets high-probability interaction regions. The method achieves higher accuracy than traditional unguided methods while reducing computational costs.

Nature Machine Intelligence, Published online: 01 July 2026; doi:10.1038/s42256-026-01261-5

Chen et al. demonstrate an AI X-ray scientist that autonomously aligns single crystals at a real synchrotron beamline, showing how large language models can enable adaptive closed-loop experimentation at large-scale scientific facilities.

Nature Machine Intelligence, Published online: 25 June 2026; doi:10.1038/s42256-026-01258-0

Rising pathogen drug resistance makes next-generation antimicrobial peptides a global priority. Generative AI accelerates discovery by rapidly proposing new peptides with high therapeutic potential. The key question is no longer whether broad data-driven exploration is possible, but whether it can refine biologically complex activity scaffolds.

Nature Machine Intelligence, Published online: 23 June 2026; doi:10.1038/s42256-026-01269-x

Recent breakthroughs in mathematical research show that AI is transforming the field at a remarkable pace. In an open letter published this month, an international group of mathematicians argue that the field needs to remain a human endeavour.

Nature Machine Intelligence, Published online: 23 June 2026; doi:10.1038/s42256-026-01263-3

Nassour, Berberich and colleagues present a soft robotic hand exoskeleton that restores grasping ability in individuals with severe hand paralysis, enabling meaningful tasks such as feeding. A lightweight textile glove with wrist dorsiflexion and an active opposable thumb increases hand articulations to enable more dexterous grasping.

Nature Machine Intelligence, Published online: 22 June 2026; doi:10.1038/s42256-026-01252-6

An, Luo, Zhang and colleagues present Turbo, a transformer-based reinforcement learning framework that enables simulation-to-real transfer for autonomous navigation and obstacle avoidance in physical microrobotic swarms operating in unknown environments.

Nature Machine Intelligence, Published online: 16 June 2026; doi:10.1038/s42256-026-01255-3

Pengfei Sun et al. develop a spiking neural network with a dual memory pathway, co-designed with a custom neuromorphic chip. The approach delivers over 4× throughput and 5x energy efficiency gains while using 40–60% fewer parameters than state-of-the-art implementations.