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Tasking Sprint #3 Recap
The Berlin tasking sprint was a significant step forward in the documentation and details of the specification, while we also developed the foundation of an ecosystem to prove out STAPI.
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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.
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Building a queryable Earth with vision-language foundation models
We take a close look at two such remarkable VLMs that have come out in the past few months and, using these models, we build a prototype “queryable Earth” functionality that allows retrieving images along with their geolocations using text queries over a large geographical area.
![An outline of the state of Massachusetts with several locations noted on the map depicting a single tree in an empty field.]()
Using GDAL with EMR-serverless for large-scale data processing
In this blog, we discuss the history of modern big data and outline how we use GDAL-EMR-serverless for large-scale data processing.
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Climate Unit Director Profile: Catherine Oldershaw
In this blog series, we’re profiling the new directors of our business units to provide a full picture of how we’re gearing up to make the biggest possible impact in 2024 beginning with this feature of Catherine Oldershaw, our Climate Unit Director.
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Using Kerchunk to make NOAA’s National Water Model Dataset more accessible
In this blog, we discuss our experience using Kerchunk to improve access times to short-range streamflow predictions generated by NOAA’s National Water Model Predictions Dataset, achieving a speedup of 4 times, using 16 times less memory.
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Announcing our 2023 Geospatial Tech Radar
Ahead of this year’s FOSS4G North America gathering, we’re rolling out a 2023 edition of our Geospatial Tech Radar idea, which we plan to update annually to track what’s up-and-coming in geospatial techniques, standards, data, and tools/platforms.
![Screenshot of the geospatial tech radar with dots in four different colors arranged around a circle in various rings mapping to categories: Adopt, Trial, Assess, and Watch]()
Running ROCm 5.4.2, ONNX, and PyTorch on a SteamDeck
In this blog post, we’ll guide you through setting up ROCm 5.4.2, ONNX, and PyTorch on a SteamDeck.
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Streamlining search-and-rescue operations using machine learning on the edge
In this blog, we discuss various improvements that we have made to the proposed workflow first discussed in our previous blog post focused on edge processing of drone imagery for search-and-rescue.
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