I've tried that once. Asked ChatGPT why L0, L1.. Ln norms, so seemingly different, were all named in a similar way. It correctly listed the norms' definitions and use cases, but failed to generalize the concept and made up some bullshit reason why they are named like that. Took me some time down the Wikipedia and Google rabbit hole to find out about Lp spaces and substitute different p values in the definition of p-norm to get the real reason

Do you expect the model to learn subtle details useful for classification from a relatively small training dataset? Wouldn't it be a better approach to train a defect detector for the model to know what is important on your images and then classify found features? Maybe this is the reason why large classification models are not widely used?