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submitted 8 months ago by neme@lemm.ee to c/technology@lemmy.world
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[-] Imgonnatrythis@sh.itjust.works 5 points 8 months ago

What do we need this for? Not clear what it does

[-] Darkassassin07@lemmy.ca 6 points 8 months ago

Seems to be a tool for taking an image and Geo-locating it, even in cases where other sources of data like Googles street map cars are insufficient.

[-] jacksilver@lemmy.world 5 points 8 months ago

The issue is it's going to be trained only on places people go. My understanding is that most geolocating systems are more focused on the uncommon or less traveled locations. Maybe I'm wrong, but I guess they're probably tested it out before announcing it.

[-] SpacetimeMachine@lemmy.world 7 points 8 months ago

Maybe they will start/already have putting pokemon in locations that they need data for to make a more comprehensive map.

[-] Imgonnatrythis@sh.itjust.works 2 points 8 months ago

Seems questionably reliable as an independent system. Maybe could help refine more traditional systems? Not sure I understand a use case for this.

[-] jacksilver@lemmy.world 2 points 8 months ago

It definitely has applications in defense/Intel spaces. Knowing where a photo was taken can be really useful info.

[-] Zoomboingding@lemmy.world 1 points 8 months ago* (last edited 8 months ago)

AI delivery bots maybe? It's basically an aggregate of "here's where it's possible/common to walk" so it's not useful for driving/flying AI. Also useful for marketing, knowing where foot traffic is.

The article says they're treating it as a Large Geospatial Model (like a Large Language Model), so it seems like you could use that as a predictive way to navigate between two points. With an LLM it spits out phrases based on context. The LGM would return paths based on context.

this post was submitted on 19 Nov 2024
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