  This paper details a developing artistic practice around an ongoing series of
works called (un)stable equilibrium. These works are the product of using
modern machine toolkits to train generative models without data, an approach
akin to traditional generative art where dynamical systems are explored
intuitively for their latent generative possibilities. We discuss some of the
guiding principles that have been learnt in the process of experimentation,
present details of the implementation of the first series of works and discuss
possibilities for future experimentation.
