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Pokémon Go Player Data Being Used to Train AI & Construct ‘Large Geospatial Model’

Company behind popular mobile game compiling user data to construct comprehensive AI world model.

Pokémon Go Player Data Being Used to Train AI & Construct ‘Large Geospatial Model’ Image Credit: Wachiwit / iStock Editorial / Getty Images Plus
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Millions of users’ location and imaging data is being compiled to construct a global virtual model of the real world, ostensibly to build new augmented reality experiences, the company behind the popular mobile game Pokémon Go has revealed.

In a blog update Tuesday, Niantic explained they’ve been enlisting Pokémon Go players to participate in efforts to construct a Large Geospatial Model (LGM), which the company says “could guide users through the world, answer questions, provide personalized recommendations, help with navigation, and enhance real-world interactions.”

The company says the LGM constructs a comprehensive AI world model by leveraging its Visual Positioning System (VPS), which was “built from user scans, taken from different perspectives and at various times of day, at many times during the years, and with positioning information attached, creating a highly detailed understanding of the world. This data is unique because it is taken from a pedestrian perspective and includes places inaccessible to cars.”

“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,” Niantic said. “As we move from phones to wearable technology linked to the real world, spatial intelligence will become the world’s future operating system.”

“Over the past five years, Niantic has focused on building our Visual Positioning System, which uses a single image from a phone to determine its position and orientation using a 3D map built from people scanning interesting locations in our games and Scaniverse,” the company wrote.

Today we have 10 million scanned locations around the world, and over 1 million of those are activated and available for use with our VPS service. We receive about 1 million fresh scans each week, each containing hundreds of discrete images.

The company explains the LGM will harness AI to map previously uncharted areas by utilizing data compiled by the VPS.

Imagine yourself standing behind a church. Let us assume the closest local model has seen only the front entrance of that church, and thus, it will not be able to tell you where you are. The model has never seen the back of that building. But on a global scale, we have seen a lot of churches, thousands of them, all captured by their respective local models at other places worldwide. No church is the same, but many share common characteristics. An LGM is a way to access that distributed knowledge.

An LGM distills common information in a global large-scale model that enables communication and data sharing across local models. An LGM would be able to internalize the concept of a church, and, furthermore, how these buildings are commonly structured. Even if, for a specific location, we have only mapped the entrance of a church, an LGM would be able to make an intelligent guess about what the back of the building looks like, based on thousands of churches it has seen before. Therefore, the LGM allows for unprecedented robustness in positioning, even from viewpoints and angles that the VPS has never seen.

The company said a new Pokémon Go feature enables users to contribute to the company’s virtual mapping.

“For example, we recently started rolling out an experimental feature in Pokémon GO, called Pokémon Playgrounds, where the user can place Pokémon at a specific location, and they will remain there for others to see and interact with.”

The company’s plan is raising concerns among privacy advocates, who fear the geo-mapping could be exploited by robots with anti-human directives.

“It’s so incredibly 2020s coded that Pokémon Go is being used to build an AI system which will almost inevitably end up being used by automated weapons systems to kill people,” Elise Thomas, Institute for Strategic Dialogue senior intelligence analyst, wrote on X.

In a comment to IGN on Friday, Niantic pointed out:

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.



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