this post was submitted on 21 Nov 2024
332 points (96.6% liked)

Technology

60102 readers
1918 users here now

This is a most excellent place for technology news and articles.


Our Rules


  1. Follow the lemmy.world rules.
  2. Only tech related content.
  3. Be excellent to each another!
  4. Mod approved content bots can post up to 10 articles per day.
  5. Threads asking for personal tech support may be deleted.
  6. Politics threads may be removed.
  7. No memes allowed as posts, OK to post as comments.
  8. Only approved bots from the list below, to ask if your bot can be added please contact us.
  9. Check for duplicates before posting, duplicates may be removed

Approved Bots


founded 2 years ago
MODERATORS
 

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.

you are viewing a single comment's thread
view the rest of the comments
[–] [email protected] 3 points 1 month ago (1 children)

I was thinking about the exact same thing! Open source, OSM mapping with a Pokemon-like travel and collection game. But I'm super busy in grad school at the moment, so I can't do it. Just put the idea out into the universe for now.

[–] [email protected] 8 points 1 month ago* (last edited 1 month ago) (1 children)

That already exists in Street Complete: https://streetcomplete.app/

I was thinking more about machine learning against images of places to populate data automatically.

[–] [email protected] 1 points 1 month ago

I participate in Street Complete already. But I was interested in something more game-like.