Nature creates rich structured behaviour out of very complex systems of interrelated parts. The most interesting results come from systems that are almost out of control, on the edge of instability.
My work focuses on creating forms and structures by simulating growth processes at the level of individual cells. Engaging with systems like these is a matter of exploration, discovering types of emergent behaviour. At the SensiLab I’m working with Jon McCormack and Dilpreet Singh to see whether we can we use machine learning to transform the computer into an active collaborator in this process: categorizing behaviours and giving us natural tools to help explore the landscape of possibilities.
Can neural networks allow us to creatively work with these unruly systems? Can they change the way that we can engage with emergence, actively seeking novelty and liminality, the behaviours that often only exist at transitional states.