Does iNaturalist log what the AI guess is for each record?

Hello all,
Just wondering, does iNaturalist currently log what the computer-vision AI thinks the image is, at the moment of uploading, before the user / community weighs in with our human-vision IDs? If so, can we look at these data? I think there’s some cools stories here. If not, please let me know, and I’ll put this in a feature request thread.
Thank you! :)


i don’t think this already exists as its own feature request. however, there’s quite a bit of discussion about this as an alternative suggestion in a feature request thread that proposes something similar:


I was also wondering about the results, achievements, improvements of the differnt models as tere is a lot of rumour of using this ai models at
For the testrun they have a distribuiton set

But i think this is mainly for comparising models ?

But i do agree there are cool stories waiting but i think the best results and reports are by comparing models with using the same training data

I have no idea where this image is from

The actual image i wanted to post i can not find, probably it is from another source (Naturalis, not iNaturalist)

Thanks for the insight, both of you!
@pisum, given the existing discussion in that feature request thread you mentioned, do you think I should still make another feature request? Or would that be redundant?

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honestly? i wouldn’t bother because it’s unlikely to be done, i think.

but there’s no harm in writing up a feature request. worst case, the mods will say that the existing feature request covers things already.

Gotcha, thank you!! I will do just that.

I would like to know the difference/improvement in the different models for the different ordes (plants, fungi, birds). Somewhere there was a nice example for it but i can not find it. How do you know that a new model is better than the old one ?


Maybe in one of iNat’s blog posts?

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Here is a standard blog for a new CV release.

If -overall- a new computer vision model performs more bad then the old model, I should expect that the old model would not be replaced… So a new model in PRD should always be better?

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Well the actual graph i was probably from and showed the performance of each species against the number of available photos and the number of observations.
I showed there was a relation between the accuratenes/prediction of the model and the number of the photos.
I thought it was from a powerpoint for Belgium

I found this:

but I am not sure if this means that a new model in a new year means a better top-1 accuracy.

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I always try to add my input before the CV can make a guess.

What is SOTA? showed
“…Our main goal has been to keep accuracy about the same as the model gets bigger more complex with more species. This is a few models behind, but the trend has continued…”

nfortunately there’s no tag, but there is a link buried in each post linking back to the previous post. Here’s all of them going back to March 2020:


Probably a jargon acronym for “state of the art”. So, “…dynamic MLP consistently achieves SOTA results” is a way of saying “we didn’t win but we didn’t lose either”.


That is also what I think, but my interpretation of SOTA there is “we’re doing just as good as or better than other models are doing” even though the IDs aren’t perfect, but YMMV.