A lot of people are misunderstanding the article in this thread.
I work with GIS data from multiple sources. Neither Google's APIs nor OSM nor Bing nor anything else is enough for applications with high specs. You need to mix machine learning and available sources.
Doing this is a PITA. Sources rarely match one another (e.g. an object will be referenced on both Bing and OSM, but 20 meters apart, with no way of accurately matching them in the middle of a dense city).
The article very clearly says that the goals include making the existing services interoperable, which would be a big advance for API customers. (This isn't about making a new Google Maps competitor, it's about a Google Maps _API_ competitor, though it will surely help build the former too.)
Just being able to download the same area from Bing and OSM and seeing "this house has ID 234 here and 234 here, that's the same building" would be great, because that lets you gather all the available information about it instead of having to choose one or use matching algorithms that can make mistakes. It can also remove false positives, which also happen.
I work with GIS data from multiple sources. Neither Google's APIs nor OSM nor Bing nor anything else is enough for applications with high specs. You need to mix machine learning and available sources.
Doing this is a PITA. Sources rarely match one another (e.g. an object will be referenced on both Bing and OSM, but 20 meters apart, with no way of accurately matching them in the middle of a dense city).
The article very clearly says that the goals include making the existing services interoperable, which would be a big advance for API customers. (This isn't about making a new Google Maps competitor, it's about a Google Maps _API_ competitor, though it will surely help build the former too.)
Just being able to download the same area from Bing and OSM and seeing "this house has ID 234 here and 234 here, that's the same building" would be great, because that lets you gather all the available information about it instead of having to choose one or use matching algorithms that can make mistakes. It can also remove false positives, which also happen.