Author: Jason Gilman
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Introducing the new Agentic Queryable Earth: Conversational, Composable, and Traceable
We discuss the evolution of Queryable Earth into Agentic Queryable Earth, including a more conversational experience.
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Introducing the new Agentic Queryable Earth: Conversational, Composable, and Traceable
We discuss the evolution of Queryable Earth into Agentic Queryable Earth, including a more conversational experience.
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ChatGSFC: Building Composable AI Tools for NASA on Open Source Tooling
Sharing our findings from the past year helping NASA build and scale a chat-based AI tool called ChatGSFC.
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Queryable Earth Demo Update: Now with Change Detection!
We detail how we used our research surrounding queryable Earth and natural language geocoding to demonstrate data accessibility in an intuitive and interactive way – and how you might be able to harness some of the same ideas in your own work.
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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…
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Why We’re Talking About a Centralized Vector Embeddings Catalog Now
We discuss our detailed white paper in which we make the case for how Earth Observation (EO) data providers such as NASA can dramatically improve access to their data by creating a centralized vector embeddings catalog, in addition to the more standard data catalogs that they already maintain.
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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.
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Finding Changes on the Earth with Natural Language
We discuss our work with Natural Language Driven Geospatial Change Detection with Vector Embeddings. This technology builds on our ongoing development of generative AI and vision models that enables users to explore our world through natural language queries.
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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…
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Natural Language Geocoding
We discuss how natural language geocoding is changing the landscape of data analysis, making it more accessible and efficient.
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Using Generative AI in AWS for the Federal Government
In this blog, we detail how to get started with Generative AI in your existing Federal Government cloud accounts.
