They call it creative object generation, and here's how it works: The evolutionary algorithm generates a random blueprint from which it models a 3D image. It invariably resembles a misshapen blob of clay. The algorithm then passes a few snapshots of the blob over to the deep neural network (because the DNN can only comprehend 2D images), and basically asks, "What do you think of this?" The DNN compares the snapshots to the images in its vast database, decides if the object resembles anything it's familiar with, and gives the algorithm some feedback. At first, it's pretty harsh. Something like: "This looks .001% like a jellyfish." Most humans would probably drop ceramics at this point, but the algorithm soldiers on.