As the web sets ablaze with the disclosure, fans are worried that their data has been cooled by Pokemon Go. Niantic, the creator of Pokemon Go, is believed to have scraped user data to train a massive AI model.
Unbeknownst to them, players of the 2016 augmented reality (AR) smartphone application “Pokémon Go” have been training an AI model to create a street-level map of the world. Or, so claims a post on LiveScience.
The developer of the hit game, Niantic, has announced that it will build a “large geospatial model” (LGM) using data extracted from its augmented reality apps. This will let robots and other gadgets traverse the real world more accurately, even with limited data.
According to a blog post on Niantic’s website on November 12, users have scanned more than 10 million sites worldwide, adding an additional 1 million scans each week.
We use player-contributed scans of public real-world locations to help build our Large Geospatial Model. This scanning feature is completely optional – people have to visit a specific publicly-accessible location and click to scan. This allows Niantic to deliver new types of AR experiences for people to enjoy. Merely walking around playing our games does not train an AI model.
Pokémon Go Unveils AI Model It Built by Secretly Collecting User Data
In a shocking revelation by the blog post, some 50 million local neural networks are already being trained and are set to serve in some 1 million locations worldwide.
“In our vision for a Large Geospatial Model (LGM), each of these local networks would contribute to a global large model, implementing a shared understanding of geographic locations, and comprehending places yet to be fully scanned,” Niantic staff scientist Eric Brachmann and chief scientist Victor Adrian Prisacariu wrote in the post.
“The LGM will enable computers not only to perceive and understand physical spaces, but also to interact with them in new ways, forming a critical component of AR glasses and fields beyond, including robotics, content creation and autonomous systems.”
