  We examine two recent artificial intelligence (AI) based deep learning
algorithms for visual blending in convolutional neural networks (Mordvintsev et
al. 2015, Gatys et al. 2015). To investigate the potential value of these
algorithms as tools for computational creativity research, we explain and
schematize the essential aspects of the algorithms' operation and give visual
examples of their output. We discuss the relationship of the two algorithms to
human cognitive science theories of creativity such as conceptual blending
theory and honing theory, and characterize the algorithms with respect to
generation of novelty and aesthetic quality.
