FOSS4G NA 2024 - Applying Large Language Models to Geospatial Search and Analysis - Jason Gilman

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

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Project Geospatial is a non-profit media organization committed to growth, innovation and collaboration among academic, commercial and government partners in the geospatial industry. We believe a revolution is coming in geospatial technology – big data is democratizing, satellites are shrinking, and the science of where has never been more important to the health and future of our planet. We provide a leading voice in geospatial industry trends, insights and cross-industry applications to help inspire and conspire with the next generation of great geospatial ideas.