  We explore the intersection of human and machine creativity by generating
sculptural objects through machine learning. This research raises questions
about both the technical details of automatic art generation and the
interaction between AI and people, as both artists and the audience of art. We
introduce two algorithms for generating 3D point clouds and then discuss their
actualization as sculpture and incorporation into a holistic art installation.
Specifically, the Amalgamated DeepDream (ADD) algorithm solves the sparsity
problem caused by the naive DeepDream-inspired approach and generates creative
and printable point clouds. The Partitioned DeepDream (PDD) algorithm further
allows us to explore more diverse 3D object creation by combining point cloud
clustering algorithms and ADD.
