That's cool, but how is it different from photoshops "content aware fill" that debuted 8 years ago?

I dunno ... he yelled at a friend of mine in an airport V.I.P. lounge once, so ... karma? I like to think so

I think one of the key things is that it was filling in the eyes with eyes. It was using completely different color eyes even and it knew where they needed to go. Content Aware only uses what's in the image, so it would just fill in that area with flesh and random bits of hair and mouth. This seems to pull from a neural network database thingymajigger.

As hamsteralliance says, ContentAware uses proximity matching and relative area matching. If you tried to fill in the white space with ContentAware, it'd be full of everything except eyes. They nVidia folks used thousands of images to train the neural net (ie generate the model using training data) which has more discrete sequential or spatial relationships between features (ie. eyes go to either side of the nose, below the eyebrows, level, interpupilary distance etc etc). The neural approach ALWAYS needs training data sets - it doesn't appear to (from reading the paper) any adaptive or learning algorithm outside of the neural framework (so, it's not AI in the sense that it learns from any environmental stimulus and alters its response... that I can see anyway. The paper doesn't get into the minutiae). But I'd still date her, if only she'd have me.