Evolution & Foundation: AI Shares Creative Control
For artists and designers, this framework reduces manual effort in generative design by leveraging AI for aesthetic judgment, though it is an incremental integration of existing methods.
This paper introduces a framework that combines genetic algorithms with multimodal AI foundation models to automate the evolution of aesthetically pleasing 3D organic forms, shifting the artist's role from direct selection to system design and enabling rapid exploration of parameter space based on semantic targets.
This paper investigates the creative process of automated design and artistic evaluation using an evolutionary system. We consider how a multimodal artificial intelligence (AI) model can communicate and guide a combined generative and evolutionary computational system. This creates a framework for the evolution of aesthetically pleasing complex 3D organic forms by integrating genetic algorithms with the visual reasoning capabilities of large-scale AI foundation models. The framework shifts the artist role from that of intensive direct selection to one of system design; transferring detailed step-by-step curation to an AI agent capable of multimodal aesthetic judgement. This framework enables the human artist/designer to rapidly traverse large areas of multi-dimensional evolutionary parameter space to find creative outcomes based on their semantic targets. Detailed audit trails of the AI's aesthetic reasoning are generated for each experiment. Interactive visualisation tools, together with AI-generated summaries and evolutionary narratives, enable deep exploration into each evolutionary experiment and providing a transparent insight into the AI-guided process.