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If you played Pokémon Go you trained an AI without realizing

Niantic is training an AI to auto-complete real-world locations using limited data, powered by insights gathered from Pokémon Go players

byKerem Gülen
November 21, 2024
in News, Artificial Intelligence, Gaming
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Pokémon Go players are unwittingly training an advanced AI system designed by Niantic to complete real-world locations. This initiative centers around a “Large Geospatial Model” (LGM), which relies on user-generated data to enhance augmented reality and robotics applications.

Pokémon Go players trained advanced AI for real-world applications

Niantic’s official blog outlines that the LGM functions similarly to a “Large Language Model,” like ChatGPT, but pertains specifically to physical environments. The LGM is trained on extensive data points of real-world locations such as churches, parks, and homes. By utilizing this model, Niantic aims to predict the characteristics of locations it hasn’t directly encountered. The company highlighted that while unique to their locale, many structures share common traits that make this model effective for understanding urban geography.

To facilitate this, Niantic is developing a Visual Positioning System (VPS). This technology employs smartphone images to discern a user’s position and orientation with high accuracy, allowing for precise digital overlays on the physical landscape. Niantic explained this will enable augmented reality content to remain at specific locations, contributing to a more intricate user experience. For instance, its recently rolled out “Pokémon Playgrounds” feature allows players to place Pokémon at pinpointed real-world locations, which remain accessible for other users.

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Palworld vs Pokemon debate could end in court due to copyright claims


The sheer volume of data generated by Pokémon Go players has been foundational for this project. Niantic currently boasts about 10 million scanned locations, with 1 million being viable for its VPS service. The company collects approximately 1 million new scans each week, featuring hundreds of images each. This continuous influx of location data is essential for refining the geospatial AI functionality that Niantic is advancing.

“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 [Large Geospatial Model] is a way to access that distributed knowledge.”

-Niantic

Despite these optimistic applications, concerns over data privacy and the broader implications of AI training persist. As outlined by various commentators, including OSINT analyst Elise Thomas, the potential military applications of such technology raise ethical questions. The technology harnessed for gaming could evolve into tools with significant ramifications in various fields, beyond entertainment.

The applications may start innocuously—like creating digital Pokémon in specific real-world locales—but investigations into the broader implications of this technology are likely to continue. As Niantic pushes forward with the LGM project, the balance between harnessing valuable data and ensuring user privacy remains a pivotal subject for ongoing discourse.


Featured image credit: Pokémon Go

Tags: AIPokemon Go

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