A grid artwork is created, where for the central work, the AI develops a sense of form from studying examples of whole paintings in
its dataset of European still lives of floral arrangements. In the surrounding works, the AI develops its aesthetics by only studying random details in the still life paintings, where i randomly zoom into the paintings and limit the region the AI trains on. I further create a distinction for these, by altering the training process for both, using a slower learning rate for the central piece (allowing larger time for the AI to learn details) and faster learning rate for the outer pieces (not giving the AI enough scope to pick up on details).
An experiment in understanding computer vision (and an attempt towards advancing the field of AI art), this work tries to start to teach AI the conceptual distinction between the compositional and the painterly. In
any painting what is the relation of the part (as fetish) to the whole (as icon)? How can one teach a computer compositional structure and painterly texture? This work tries to start poking into these set of questions.
