Thunderhead Explorer

Continuing the GenAI-with-a-GeoSpatial-twist thread I started a while back. Back then, I had a language model reason about geospatial logic. This time, I wanted it to actually do the work—on my open project, inside my running ArcGIS Pro session, while I watch. The result is ProCowork , an experimental native ArcGIS Pro add-in that embeds the Claude Code engine in a dockable chat panel. I can ask it to list layers, add and calculate fields, select features, run a buffer, or write a more specialized ArcPy script. Claude generates the code, the add-in runs it against the live project, and the code and results come back into the same panel. For example, I can type: “List the layers in the current map.” “Add a DOUBLE field POP_DEN to Parcels and set it to POP / AREASQMI.” “Select parcels where POP_DEN > 5000 and zoom to them.” “Buffer Roads by 100 meters and add the result to the map.” The panel is useful, but the interesting part is ...

Artificial Intelligence / Machine Learning implementations have been part of Esri software in ArcGIS for a very long time. Geographic Weighted Regression (GWR) and Hot Spot Analysis are Machine Learning algorithms. ArcGIS users have been utilizing supervised and   unsupervised learning like clustering  to solve a myriad of problems and gain geospatial insight from their data.  We just did not call these learning algorithms AI/ML back then.  Not until the recent popularity of DeepLearning that finally blossomed from the AI Winter  and made AI a household name. And guess what? Esri software has now DeepLearning implementations ! It is important to understand the difference between AI, ML, and DL.  I came across this very insightful article that analogizes the relationship to Russian dolls . Typically, collected data is very "dirty", and a lot of cleaning has to performed on it before processing it through a Machine Learning algorithm.  The bigger ...