this post was submitted on 26 Jul 2024
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[–] [email protected] 7 points 1 month ago (1 children)

AI is just gonna show u the wrong tree then argue with you about how you're wrong lol

[–] [email protected] 11 points 1 month ago (2 children)

I actually think this is a great application for AI. "Hey AI, look at these 2 million trees and tell me which ones look similar to this one."

It identifies a bunch of trees and even though it identifies a bunch that aren't similar then you have a much smaller list to sort through. It doesn't have to be right all the time, it's just helping narrow it down.

This is way different from "Hey AI, what time does the show start tonight", where if you get it wrong 10% of the time then it's a useless tool.

[–] [email protected] 5 points 1 month ago (1 children)

So basically AI is good at categorizing data where perfect accuracy isn't needed, but manual categorization isn't feasible.

[–] [email protected] 3 points 1 month ago

Kinda,

AI is great where statistical accuracy is more valuable.

This would be a good test to run competitive models over, one model is optimized to find the target tree with a 80+% confidence, the second model is optimized to find all trees which are not the target with the same confidence. Where the two models agree, run the first model again but with a confidence requirement of 99+% (which will take much longer to run) over the smaller data set.

[–] [email protected] 3 points 1 month ago (2 children)

Unfortunately it doesn't quite work that way. The dataset they are training it on contains images of a single tree, so it's ability to generalise to a normal tree of that species will be incredibly limited.

Consider a facial recognition algorithm trained only on images of Nicolas Cage, then being tasked with identifying members of his family. It would do very well at identifying Nicolas Cage in a crowd, but probably not a good job of identifying anyone else.

[–] [email protected] 2 points 1 month ago (1 children)

Would it help if you photoshopped a bunch of trees with different superficial characteristics but kept the defining traits of the subspecies and trained it on those images?

[–] [email protected] 3 points 1 month ago (1 children)

Maybe, if you could reliably render known traits based on descriptions for which we likely don't have photographic evidence.

You risk tainting the model though. If some artefact of the photoshop gets detected well by the model, then it will quickly learn to identify photoshopped trees, not trees that actually look like the target species.

[–] [email protected] 2 points 1 month ago

Ah that makes sense. Kind of like the old AI problem where it thought fish had fingers because most of the training material had people holding up the fish.

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

Yes you make a good point. Perhaps they trained it on other trees of a similar family?

[–] [email protected] 3 points 1 month ago

"We lost the entwives. We cannot find them. I don't suppose you've seen Entwives in the Shire?"