The Alternet Summer School will return from 19–29 August 2026 in the mountain village of Peyresq, France, bringing together PhD candidates, early career researchers, and professionals to examine one of the most pressing challenges of our time: the relationship between biodiversity and society. The programme combines lectures with interactive formats, including field trips, collaborative group projects, and participant-led discussions. A defining feature of the Summer School is the integration of participants’ own research topics into the learning process, creating a reflexive and co-creative academic setting.

A new study reviews how machine learning (ML) is being used to help communities recover critical infrastructure after natural hazards such as earthquakes, floods, and hurricanes. The research synthesizes global studies and shows that ML can support recovery by characterizing recovery trends, predicting recovery times, and optimizing recovery schedules. The authors also identify key challenges, such as limited data availability, and outline future directions for building more resilient infrastructure systems using ML.

A new study demonstrates how machine learning can accelerate the discovery of antimicrobial peptides (AMPs) for ulcerative colitis (UC). Researchers developed a computational pipeline that screened thousands of peptide sequences and identified a lead peptide, LR. In a mouse model of colitis, LR reduced inflammation, restored intestinal barrier integrity and reshaped gut microbiota, particularly enriching Akkermansia muciniphila. The findings highlight the promise of AI-guided peptide discovery for developing microbiota-friendly therapeutics for inflammatory bowel disease.

Egocentric vision, which captures the world from cameras worn on the human body, is rapidly emerging as a crucial frontier in artificial intelligence.