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Just tested and while it seems interesting, there doesn't seem to (yet) be any intelligence about the imagery itself from what I can tell. For example, it can g
by jasongill 1y ago
Just tested and while it seems interesting, there doesn't seem to (yet) be any intelligence about the imagery itself from what I can tell. For example, it can give me insights about vegetation data overlayed on a map (or try to), but it can't "find the most fertile grassland in this radius".
When there is a way to actually "search" satellite images with an LLM, it will be a game changer for businesses (and likely not to the ultimate benefit of consumers, unfortunately)
- Demiurge 1y agoHow would you even define “most fertile grassland”? What does “fertile” mean - soil nutrients, water availability, or productivity for a specific crop? And what counts as “grassland”? Are you talking about a 1 acre parcel, something for sale, or land next to a road? There’s already data for all of this: SSURGO soil maps, vegetation indices, climatology datasets, and more — that could help you find the “most something” in a given radius. But there are too many variables for a single AI to guess your intent. That’s not how people who actually farm, conserve, or monitor land tend to search; they start from a goal and combine the relevant data layers accordingly. In fact, crop-specific fertility maps have existed for decades, based on soil and climate averages, and they’re still good enough for most practical uses today.
- jasongill 1y agoIt was just an example, but you are correct. A more "imagery required" example would be "Find all the houses with roofs that have been damaged in the last 6 months" or something like that which could be used by salespeople or insurers
- Demiurge 1y agoThat's a good example, yes. I think this one can actually be interpreted by multiple AI agents to do search on the algorithms, or could even train a model, and then run the model. How amazing would it be, if this could actually all happen based on a few prompts :)