https://video.osgeo.org/videos/watch/eb0dc8bd-74c8-41c9-b233-f9b98f5f5158 Jason Gilman from Element 84 discusses the integration of large language models (LLMs) with geospatial data to enhance search and analysis capabilities in his talk at FOSS4G NA 2024. Highlights 🌍 LLMs can bridge the gap between geospatial data and user inquiries, enabling effective search. 🤖 LLMs function like CPUs, processing natural language but lacking real-world awareness. 🌐 A “broker” system is essential to manage LLM’s capabilities and ensure deterministic outputs. 📊 The use of JSON and vector databases facilitates efficient data extraction and manipulation. 🗺️ Natural language geocoding allows users to specify geospatial queries easily. 💻 LLMs can generate SQL queries from natural language, streamlining database interactions. ⚡ Performance optimization is crucial, balancing prompt brevity with output quality. For more content like this check out www.projectgeospatial.com #Geospatial #AI #LLM #DataAnalysis #FOSS4G #NaturalLanguageProcessing #TechInnovation Mon, 01 Jun 2026 13:55:59 GMT https://validator.w3.org/feed/docs/rss2.html PeerTube - https://video.osgeo.org https://video.osgeo.org/lazy-static/avatars/de841c88-3a57-45ac-9eff-a00237356bfc.png https://video.osgeo.org/videos/watch/eb0dc8bd-74c8-41c9-b233-f9b98f5f5158 All rights reserved, unless otherwise specified in the terms specified at https://video.osgeo.org/about and potential licenses granted by each content's rightholder.