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Agentic AI struggles with Earth Observation because reprojection, resampling, and other geospatial operations silently corrupt data, demanding a new agent design paradigm.
Open-ended reinforcement learning with LLM-based rewards unlocks surprisingly strong performance in medical reasoning for multimodal models, even with limited training data.
