The issue is it's going to be trained only on places people go. My understanding is that most geolocating systems are more focused on the uncommon or less traveled locations. Maybe I'm wrong, but I guess they're probably tested it out before announcing it.
You'd be surprised how a pokemon go player will open the app in the middle of the wilderness, even with one questionable reception bar, just to see if there's a secret rare pokemon that lives there. Bonus if you get a postcard from a pokestop someone submitted, because that trail mile marker is "special." You can keep it for memories, or send it to a friend you've never spoken to, for bragging rights. It's also not unheard of, for people to crawl through backroads in their car, since the app won't let catch pokemon or count km's, if you go more than +-15 mph.
AI delivery bots maybe? It's basically an aggregate of "here's where it's possible/common to walk" so it's not useful for driving/flying AI. Also useful for marketing, knowing where foot traffic is.
The article says they're treating it as a Large Geospatial Model (like a Large Language Model), so it seems like you could use that as a predictive way to navigate between two points. With an LLM it spits out phrases based on context. The LGM would return paths based on context.