Niantic, the company behind the extremely popular augmented reality mobile games Pokémon Go and Ingress, announced that it is using data collected by its millions of players to create an AI model that can navigate the physical world. (View Highlight)
By training an AI model on millions of geolocated images from around the world, the model will be able to predict its immediate environment in the same way an LLM is able to produce coherent and convincing sentences by statistically determining what word is likely to follow another. (View Highlight)
“Large Geospatial Models will help computers perceive, comprehend, and navigate the physical world in a way that will seem equally advanced,” Niantic said. (View Highlight)
“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.” (View Highlight)
Niantic’s LGM builds upon its Lightship Visual Positioning System (VPS), which allows players to pin virtual items to physical locations in the world with “centimeter-level accuracy.” For example, Niantic recently introduced an experimental feature in Pokémon Go called Pokémon Playgrounds, where the user can place Pokémon at a specific location that will remain there for others to see and interact with. This feature, Niantic explains, is powered by massive amounts of data, and is unique because it is taken from a pedestrian perspective from locations inaccessible to cars. (View Highlight)
“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,” Niantic said. “We receive about 1 million fresh scans each week, each containing hundreds of discrete images.” This data, Niantic’s blog explains, is collected from its games and Scaniverse, Niantic’s app for 3D scanning objects and locations. (View Highlight)
The AI gold rush of the last few years prompted a frenzied hunt for large datasets that can train generative AI models. We’ve seen companies scrape text from the internet, YouTube subtitles, YouTube videos, books, and more, with little consideration for the humans who created this data. In this case also, players of the incredibly viral Pokémon Go had no way of knowing that when they downloaded the game in 2016 that it would one day fuel this type of AI product. (View Highlight)
It should come as no surprise that Niantic would now try to leverage its data in the AI space. As the company says, data from Google Street View and various self-driving companies means that there’s quite a bit of data from roads, but Niantic’s games have created a huge dataset of where only pedestrians can go. At the moment, the company says the data can be useful in a few ways, like other augmented reality products, but the way this data might help robots navigate the world is the most interesting since robots that navigate the real world do anything from deliver food to carry automatic rifles. (View Highlight)
