Every story in this issue with a short summary, so you can decide what to read before leaving the site. Summaries are written by AI (Claude) only from each publisher's own description and checked by Jev for anything not in that description. They are not full translations. Follow "Read the original" for the full story.
Researchers at the University of Gondar report that a voting ensemble of tree-based machine learning models, combined with permutation-based feature selection, predicts rice yield.
Read the original →The Karnataka State Remote Sensing Applications Centre has called bids for a pilot using satellite imagery, drones and AI. The pilot would map crops, detect pests and diseases and estimate village-level yields.
Read the original →Researchers combined deep learning, grey wolf optimization, explainable heatmaps and a Gemini-powered chatbot to detect finger millet diseases. The system reached 98.36 percent accuracy.
Read the original →A new architecture-diverse TabNet ensemble classifies seven crop types from harmonized multi-source soil data. It reaches 90.5 percent accuracy, outperforming XGBoost and single optimized models.
Read the original →The article gives ten examples of how cannabis companies can use AI technology that organizational leaders should consider.
Read the original →Effective weed management is essential to any operation, as it prevents yield loss and helps produce a healthy crop. The article notes that input costs are rising.
Read the original →The Korea Local Information Research & Development Institute has issued guidelines to support local governments in their artificial intelligence transformation.
Read the original →CEO Kim Dong-ro returned to farming in Yesan, South Chungcheong Province in 2016 and began raising 46 head of Hanwoo cattle.
Read the original →ET's Tech Editor Surabhi Agarwal speaks to Google DeepMind's Chief AI Readiness Officer, Lila Ibrahim, about building responsibility into AI and bringing affected communities into the development process. Ibrahim discusses research on neglected crops and tools that help students learn rather than simply supply answers.
Read the original →Gyeongsangbuk-do is stepping up efforts to transform agricultural produce distribution using artificial intelligence.
Read the original →The federal AI committee flags sovereign capability, sharing benefits with Pacific neighbours, and security access to frontier models. Copyright remains unresolved.
Read the original →Among manufacturers in Aichi Prefecture, there are moves to work with other companies on developing physical AI, in which AI autonomously decides how to operate robots and machines. The report cites a major machine tool maker headquartered in Oguchi, Aichi.
Read the original →SACMOTs Inc., based in Fukuoka, has been selected for the PwC Foundation's spring 2026 grant program. The CEO is Shinya Murakami.
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