Every now and then, I go looking for new running routes to mix things up, which was why I was intrigued by this post by Simon Willison, who gave ChatGPT Work his address and asked it to find 5K and 10K routes, using OpenStreetMap data:

It worked for 27 minutes and produced exactly what I’d asked for, as both an embedded visualization and downloadable GPX file and GeoJSON files. Here’s that 5K route:

I decided to give the same thing a try and was impressed by the results. ChatGPT spent a similar amount of time, poring over OpenStreetMap data, but it didn’t stop there. The model consulted my town’s website to account for road construction and the availability of sidewalks. Then, it visited the county’s website to review maps of greenways that aren’t part of the local road system. The final results were within 100m of exact 5K and 10K routes with notes on where to be careful to verify safe pathways and road crossings.

What I love about this sort of experiment is that it’s not something I’d ever have thought to ask ChatGPT myself. In hindsight, it’s obvious that all the data is there, ready to assemble. However, it just goes to show the many ways that I, and I’m sure many others, are still just scratching the surface of what LLMs make possible.