I guess this makes sense, intuitively. If I understand a cat as a “furry animal with four legs, a long tail and pointy ears”, that’s a pretty generalizable mode

I guess this makes sense, intuitively. If I understand a cat as a “furry animal with four legs, a long tail and pointy ears”, that’s a pretty generalizable model. If I see a new picture of a cat that has orange fur for the first time ever, I will still guess it’s a cat. I’ll also be able to quickly update my model parameters to include orange fur (I.e. on-line learning is fast). Whereas if my model of a cat is “brown stripy thing that’s usually on a window sill”, and I see a picture of an orange cat outdoors, not only will I probably guess it’s a pumpkin or something, it will also take many steps in parameter space to adjust my model to incorporate this new data (on-line learning will be slow).