This project attempts to develop and test a method for generating one-sided hybrid exterior building elevations using two designer’s base criteria and design ruleset as an input. Architects are using computational design to expedite the iteration process in an efficient manner. Optimization techniques utilizing genetic solvers within the architectural 3D model space have been around for the past decade. However, with the introduction of artificial intelligence the computational design niche within the architectural field can be expanded on. Generative Adversarial Networks (GAN) are used in this research to demonstrate artificial intelligence capabilities in the computational design realm. Can GAN networks dream of hybrid architectural elevations?