> I don't understand why what the ducklings are doing is considered desirable. So their cognition prioritizes following same-coloured shapes. So what? Why is that the right thing to do?

The important point is that a newly-born duckling can pick up the notion of "similar shapes" vs "different shapes" and show a measurable preference for one or the other, after seeing 1 example (of course, that must somehow be hard-coded in its brain, so it has probably been learned through evolution).

In contrast, a neural net is very hard to train to achieve a similar feat. Whether the feat itself is desirable or not is not relevant. It's just a measure of how different our current training methods are from the ones employed in animal brains - even relatively dumb ones like newly-born ducklings.

I don't think it matters specifically what the ducklings do, only that they are able to learn to do it. The question is then can we train an artificial model to do the same thing.

If we find that existing techniques can't easily do this, it implies a gap in our capabilities.

It's an example of few-shot learning and abstraction. Show ducklings similar objects, they will prefer similar objects. Show them different objects, they will follow different objects even a cross categories.

This type of learning based on inductive bias without a huge pretrained network could be huge for required training times and data.

I think what you are missing is that ducklings "attach" to the first thing they see after birth and follow it around. Under normal conditions this would be their parent, which is desirable as it keeps them out of trouble.

(As an amusing aside, a similar imprinting is used in some security mechanisms, where the device allows the first use without authentication, but then trusts the first user to be the privileged user).

The important bit is that this is not "training", but a single stimulus that they need to figure out who mom is. But it turns out that mom can be also abstract things, like "similarity".

Now if you compare this to a neural net, you can't get it to recognise anything after showing just 1 image, let alone the notion of similarity.

I bet you could pre-train a neural net to do exactly this, without too much trickery. Newborn animal brains aren't blank slates, they exhibit all manner of complex behaviour far too quickly to have learned it from scratch.

Is it ‘just’ one image? The sensory systems of a duck seem fantastically rich and high-bandwidth compared to a JPEG.

If you show a network 10000 very similar inputs it won't learn much, and likely overfit.