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?

1 Like

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?

1 Like

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?

1 Like

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.

1 Like

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.


This topic was automatically closed 60 days after the last reply. New replies are no longer allowed.