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AI

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  • Machine LearningSoftware Engineering

    Jason Gilman

    Introducing Natural Language Geocoding v0.1.0: An LLM-Enabled Geocoding Database

    The landscape of geospatial AI is rapidly evolving. Many organizations are building LLM-powered solutions that tackle complex geospatial problems and answer sophisticated questions about our planet. These agentic approaches allow LLMs to autonomously select from toolsets that include geospatial tools, Earth Observation (EO) catalogs, and EO data processing capabilities. The result? Systems that can process…

  • Machine LearningSoftware Engineering

    Jason Gilman

    Introducing Natural Language Geocoding v0.1.0: An LLM-Enabled Geocoding Database

    The landscape of geospatial AI is rapidly evolving. Many organizations are building LLM-powered solutions that tackle complex geospatial problems and answer sophisticated questions about our planet. These agentic approaches allow LLMs to autonomously select from toolsets that include geospatial tools, Earth Observation (EO) catalogs, and EO data processing capabilities. The result? Systems that can process…

  • CompanyMachine Learning

    Lauren Frederick

    Prioritizing Responsible AI

    AI is moving fast. It’s moving faster than we can govern and regulate it, and even sometimes faster than our understanding of its full impact. As we push the boundaries of what AI can do, everyone is scrambling to keep up. Thus, the guidance and governance around AI usage are still evolving.  In this time…

  • Machine LearningDesign

    Jason Gilman

    Sean Malone

    Sara Mack

    Generating truly useful solutions to real problems with the help of user experience and AI

    We discuss how AI and user experience methodologies might serve to connect scientists and researchers back to important data and technology to solve the world’s biggest problems.

  • Machine LearningGeospatial

    Lauren Frederick

    The State of Geospatial AI Heading into 2025

    For the second year in a row, I spent the week after Thanksgiving in Las Vegas, immersed in AWS re:Invent. Last year’s conference left me energized and inspired— geospatial AI was just beginning to emerge as a transformative force. This year, as anticipated, AI took center stage, with a wealth of sessions dedicated to its…

  • CompanyMachine Learning

    Lauren Frederick

    Jason Gilman

    Sustainable AI: Reduce Your Carbon Footprint, Cut Costs, and Keep Your Users Happy

    Our team at Element 84 is excited about AI’s potential to help in building systems, understanding the impacts of climate change, and generally helping users access data. At the same time, we’re also concerned with the environmental impact of using this technology. Hugging Face sums up the issue well in their AI Environment Primer: Artificial…

  • Machine Learning

    Adeel Hassan

    Segmenting Sandstorms in Satellite Imagery

    In this blog, we walk through our approach to segmenting sandstorms in satellite imagery, evaluate the quality of our results, and compare them against existing solutions.

  • GeospatialMachine Learning

    Sara Mack

    Emerging trends in geospatial: May 2024

    In this post, we highlight a few of the trends in geospatial our team noticed at SatSummit, and we’re outlining how we plan to integrate these trends into our work.

  • Machine LearningGeospatial

    Jason Gilman

    Natural Language Geocoding

    We discuss how natural language geocoding is changing the landscape of data analysis, making it more accessible and efficient.

    Partial screenshot of the world map, the Natural Language Geocoding query selected is "Show me algal blooms within 2 miles of Cape Cod" and the portion of Massachusetts is appropriately outlined in a blue line. There is an image of the algal blooms tiled next to the map.
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