Ten fingers surely wouldn't be tagged, but the thing about numbers is that they work as well for 10 apples as they do for 10 coins and 10 cups and 10 whatever. It never made the leap of abstraction to learn in the latent space the meaning of numbers 1-10 independent of the particular object. This lack of extrapolation lends it to a very rote learned style.
I already have a way around the specific numerical vocabulary/training problem. When I ask for "a picture in a frame", "a picture of a picture in a frame", "a picture of a picture of a picture in a frame" etc, I'm trying to use linguistic recursion to make numeracy emerge. But even that form of counting without predefined numbers fails. There's no reliable way to make a prompt the produces k of something. That's a deeper issue than it not deducing the specific meaning of characters 0-9 by example.
It can't learn that by example as there really isn't training data with more than 2 nested pictures of pictures, and by itself it will never realize it can just fill in the nested painting by prompting itself with the nested statement. It lacks thought loops.
I already have a way around the specific numerical vocabulary/training problem. When I ask for "a picture in a frame", "a picture of a picture in a frame", "a picture of a picture of a picture in a frame" etc, I'm trying to use linguistic recursion to make numeracy emerge. But even that form of counting without predefined numbers fails. There's no reliable way to make a prompt the produces k of something. That's a deeper issue than it not deducing the specific meaning of characters 0-9 by example.
It can't learn that by example as there really isn't training data with more than 2 nested pictures of pictures, and by itself it will never realize it can just fill in the nested painting by prompting itself with the nested statement. It lacks thought loops.