A geospatial career journey
In 1951, Paul Fitts edited a report on human engineering for air-navigation and traffic-control systems. One of its lasting artifacts was a deceptively simple allocation device that came to be known as the Fitts list: what humans are better at and what machines are better at (Fitts, 1951). In shorthand, it became HABA-MABA: Humans Are … Continue reading Interpretation and Ownership
Introduction The current data center boom appears to be an early-stage, brute-force response to the first wave of artificial intelligence demand. The market has encountered a rapid increase in demand for training, inference, and AI-enabled cloud services, and the immediate response has understandably been physical scale in the form of larger campuses, more megawatts, denser … Continue reading AI Data Centers and the Risk of Stranded Infrastructure
Every general-purpose technology reaches a point where it stops being the subject and becomes part of the foundation. The web passed through it, as did virtualization, the relational database, and cloud infrastructure. Few people now describe a product as running "in the cloud" as though that were the noteworthy fact about it. The capability has … Continue reading Life After AI
I recently finished implementing a network analysis through PostGIS and pgRouting, exposed through an MCP interface so it can be called by AI. I have done versions of this as a Lambda and as a Google Cloud Function. Before that, I did it in Node. Before that, in ASP.NET with a different routing library. Before … Continue reading Twenty Years, Part Three
This post summarizes themes that emerged across multiple sources curated by GeoFeeds during April and May 2026. Taken together, these themes suggest that geospatial AI (GeoAI) is moving through a familiar stage in the life of an emerging technology. The early question was whether it could do useful work. The current discussion revolves around what … Continue reading Geospatial AI State of Play, April–May 2026