Form-Driven AI in Generative Art: A study of co-evolving morphologies

<p xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" class="first" dir="auto" id="d931711e55">This paper presents the design and implementation of a nine-piece generative art installation, conceptualized as a family of intelligent shapes. Each shape is represented by a distinct 3D mesh that interprets and transforms a shared set of AI signals based on its unique morphology. The installation explores the hypothesis that ‘the way an entity is shaped affects the way it thinks’. An AI system broadcasts identical parameter signals to all meshes, but each shape processes these signals in a way that reflects its structure. The AI continuously monitors each shape’s deformation, creating a feedback loop in which morphological changes influence subsequent signal processing on the part of the AI. This results in a range of diverse evolutionary behaviours, demonstrating how form shapes computational ‘thought’ processes in autonomous systems. This interplay between uniform inputs and form-specific responses suggests that a geometric mesh’s physical properties can serve as inputs for reasoning, with emergent shape changes reflecting cognitive-like processes. The paper details the conceptual motivation, system architecture, technical implementation, and observed outcomes, offering insights into how morphology guides information processing in generative art and AI, and proposing new directions for form-driven intelligence.