I disagree to an extent with your example, I’m not sure a child would recognise all cats from a single photograph of a cat, and I’m not sure it would be possible to test this (what child first encounters an image of a cat at the age of three?)
As a related example, 3 year old children often cannot reliably recognise basic shapes (letters from the alphabet), and certainly not after a single example. I daresay an ML model would outperform a child in OCR even with significantly less exposure to letter forms in its training.
When a child looks at a picture of a cat at the age of three, they have already learned to recognise animals, faces, fur, object, depths in photographs, the concept of a cat being a physical thing which can be found in three dimensional space, how physical things in three dimensional space appear when represented in 2D… the list goes on.
It’s simply not within our capabilities at the moment to train ML models in the same way.
As a related example, 3 year old children often cannot reliably recognise basic shapes (letters from the alphabet), and certainly not after a single example. I daresay an ML model would outperform a child in OCR even with significantly less exposure to letter forms in its training.
When a child looks at a picture of a cat at the age of three, they have already learned to recognise animals, faces, fur, object, depths in photographs, the concept of a cat being a physical thing which can be found in three dimensional space, how physical things in three dimensional space appear when represented in 2D… the list goes on.
It’s simply not within our capabilities at the moment to train ML models in the same way.