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FOSS4G NA 2024 - Applying Large Language Models to Geospatial Search and Analysis - Jason Gilman
Manage episode 462005245 series 3234430
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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
362 episodes
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Manage episode 462005245 series 3234430
Content provided by Project Geospatial. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by Project Geospatial or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://podcastplayer.com/legal.
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
362 episodes
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Similar to Project Geospatial
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