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.
In a blog post published last week, first spotted by Garbage Day, Niantic says it is building a “Large Geospatial Model.” This name, the company explains, is a direct reference to Large Language Models (LLMs) Like OpenAI’s GPT, which are trained on vast quantities of text scraped from the internet in order to process and produce natural language. Niantic explains that a Large Geospatial Model, or LGM, aims to do the same for the physical world, a technology it says “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. As we move from phones to wearable technology linked to the real world, spatial intelligence will become the world’s future operating system.”
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.
I think people will still “contribute” because they also don’t care that their use of certain platforms leaks data used to target ads at them.
In the same vein though, once AI essentially destroys a site like Stack Overflow, where will AI companies source new training data with updated information? Also, we are likely to see something like 50% of content being AI generated. Are AI models then going to train on the content they themselves created? What is the impact of that? What is the use?
It leads to model collapse. The second AI starts to focuses on certain patterns in the output of the first AI instead of the actual content and you get degraded output. They are pattern matching machines after all. Repeat the cycle a few times and all output becomes gibberish. Think of it as data incest.
So the AI companies are pretty desperate for more fresh user data. More data is the only way they have currently to push through the diminishing returns.