Embeddings in Context: Tools for Geospatial Problem Solving
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摘要
Chris and Krishna discuss their experiences working with geospatial embeddings, search and remote sensing in general, and how they think through problems.Timestamps sustainably sourced and hand crafted.(0:00) Intro(2:30) Background, earth observation and existing algorithms and the embedding fallacy.(9:49) Validation, how to solve problems, seductive embeddings, the museum of cool demos.(19:22) What are embeddings?(21:00) Search vs embeddings, the development of Earth Index. (25:00) Expert embeddings: the dumbest embeddings that work.(30:25) Computer vision embeddings/ImageNet. Experiments in pre-training, how to spend $40,000 in cloud credits.(37:22) Should we pre-train on satellite imagery? DINO v3 (44:30) What properties should embeddings have for search? Recall vs Precision/Landcover+(50:00) Real world consequences of mapping(54:00) Future outlook, Krishna is jaded
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