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Most people don’t have an intuitive sense of just how technically difficult mapping from real geospatial coordinates to feature spaces is. This is a great examp

Most people don’t have an intuitive sense of just how technically difficult mapping from real geospatial coordinates to feature spaces is. This is a great example of a relatively simple case. You are essentially doing inference on a sparse data model with complex local non-linearities throughout. If you add in dynamic relationships, like things that move in space, it becomes another order of magnitude worse. We frequently don’t have enough data to make a reliable inference even in theory and you need a way of reliably determining that. This problem has been the subject of intense interest by the defense research community for decades. It has been conjectured to be an AI-complete type problem for at least ten years, i.e. solving it is equivalent to solving AGI. The current crop of LLM type AI persistently fails at this class of problems, which is one of the arguments for why LLM tech can’t lead to true AGI.

TimTheTinker 2y ago
Just putting this out there. This is one area where Esri's software really shines. They have so many software offerings and so much is said about different things you can do with ArcGIS (and competing systems), but the capability of their projection engine and geocoding systems - the code that lies at its heart - is unmatched, by far, at least as of 5 years ago when I left for a different company. I had long conversations with Esri's projection engine lead. Really remarkable guy - he's got graduate degrees in geography and math (including a PhD) and he's an excellent C/C++ developer. That kind of expertise trifecta is rare. I'd walk by his office and sometimes see him working out an integral of a massive equation on his whiteboard (not that he didn't also use a CAS). "Oh yeah, I'm adding support for a new projection this week."
- jandrewrogers 2y ago
  Many people don’t appreciate the extent that building robust geospatial systems requires seriously hardcore mathematics and physics skills. All of the mapping companies have really smart PhDs wrangling with these problems. I’ve always enjoyed talking with them about the subtleties of the challenges. There are so many nuances that never occurred to me until they mentioned them.
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TimTheTinker 2y ago

Just putting this out there. This is one area where Esri's software really shines. They have so many software offerings and so much is said about different things you can do with ArcGIS (and competing systems), but the capability of their projection engine and geocoding systems - the code that lies at its heart - is unmatched, by far, at least as of 5 years ago when I left for a different company. I had long conversations with Esri's projection engine lead. Really remarkable guy - he's got graduate degrees in geography and math (including a PhD) and he's an excellent C/C++ developer. That kind of expertise trifecta is rare. I'd walk by his office and sometimes see him working out an integral of a massive equation on his whiteboard (not that he didn't also use a CAS). "Oh yeah, I'm adding support for a new projection this week."

jandrewrogers 2y ago
Many people don’t appreciate the extent that building robust geospatial systems requires seriously hardcore mathematics and physics skills. All of the mapping companies have really smart PhDs wrangling with these problems. I’ve always enjoyed talking with them about the subtleties of the challenges. There are so many nuances that never occurred to me until they mentioned them.

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