[hansword]

Content note: surgery gore

a) thousands of hours is far far far too little data. This is a total ballpark estimate, with only knowledge of the ML and basically zero knowledge of the surgery side, but I would expect three to six orders of magnitude greater, i.e. millions to billions of hours necessary to train a machine learning model to do something like that, to a standard.

b) the big problem is not the procedures themselves, but edge cases and things going a little bit wrong.

c) you are fine with tiny flukes in your generated images, but you won't be very happy with an ML model whose tiny flukes lead to internal bleeding.

d) unfortunately (with contemporary models) we can't easily explore latent space, which might possibly contain regions corresponding to catastrophic robot arm movements. the chance isn't that high, but it's not a chance most'd be willing to take at this point.