The chAIr Project is a series of four chairs created using a generative neural network (GAN) trained on a dataset of iconic 20th-century chairs with the goal to “generate a classic”. The results are semi-abstract visual prompts for a human designer who used them as a starting point for actual chair design concepts.
The project is a collaboration between Philipp Schmitt, Steffen Weiss, and two neural networks exploring the reversal of human and machine roles in the design process and industrial production. It explores co-creativity between humans and AI, taking the chair — the archetype of a designed object — as an example.
The training data set contained 562 20th-century chair designs scraped from Pinterest. The AI used a visual system and only considered aesthetics. This stands in contrast to other procedural design approaches like Autodesk’s Project Dreamcatcher that optimizes designs for functional requirements, e.g. maximum stability at lowest weight. The goal was not to generate a functional chair, but to generate an engaging ‘visual prompt’ for a human designer. The project is a case study for Philipp’s Augmented Imagination research project which explores the use of machine learning as an art and design tool for mind bending — like Surrealist frottage; one that caters to the subconscious, the associative, the imaginary rather than the rational.
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