AI & Environment Resource HubSania Jevtic; Colleen Drapek; Christophe Gaillochet; Andrew Brockman; James Cadman; Timo Flesch; Nicolas Kral · 2024-12-09
The CRE.AI.TIVE platform uses machine learning to enhance plant gene regulation, enabling scalable gene upregulation without prior knowledge of regulatory elements.
Sania Jevtic; Colleen Drapek; Christophe Gaillochet; Andrew Brockman; James Cadman; Timo Flesch; Nicolas Kral. 2024-12-09. A Scalable Method for Modulating Plant Gene Expression Using a Multispecies Genomic Model and Protoplast-Based Massively Parallel Reporter Assay. https://www.biorxiv.org/content/10.1101/2024.12.05.626999v1 (AI & Environment Resource Hub; record paper-036; collection snapshot 2026-09-15).
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Shared topics: Governance and society; Biodiversity and ecosystems; Agriculture and food
A 35-minute documentary by Animal Ethics featuring 16 leading experts on AI and animal advocacy from Princeton, NYU, the London School of Economics, and beyond. The film examines how AI will significantly impact the lives of animals — for better or worse — arguing that animal advocates must act proactively rather than reactively. Topics include AI's role in wildlife monitoring, factory farming, and animal sentience research.
Shared topics: Governance and society; Biodiversity and ecosystems; Agriculture and food
Introduces BoreaRL, a multi-objective reinforcement learning environment for climate-adaptive boreal forest management. Boreal forests store 30-40% of terrestrial carbon, much in climate-vulnerable permafrost soils. The authors show carbon sequestration goals are easier to optimize than permafrost preservation, and that effective policies must balance species composition and density to protect permafrost while maintaining carbon gains.
Shared topics: Governance and society; Biodiversity and ecosystems; Agriculture and food
Earth Map is an innovative, free and open-source tool developed by the Food and Agriculture Organization of the United Nations (FAO) in the framework of the FAO - Google partnership. It was created to support countries, research institutes, farmers and members of the general public with internet access to monitor their land in an easy, integrated and multi-temporal manner. It allows everyone to visualize, process and analyze satellite imagery and global datasets on climate, vegetation, fires, biodiversity, geo-social and other topics. Users need no prior knowledge of remote sensing or Geographical Information Systems (GIS).
Shared topics: Governance and society; Biodiversity and ecosystems; Agriculture and food
This study developed a high-resolution global map using satellite data and a neural network to classify the dominant drivers of forest loss from 2001 to 2022, revealing that permanent agriculture is the leading cause worldwide, and aims to support more effective policy, conservation, and supply chain monitoring at multiple scales.