Artificial Voxel Intelligence

<p><strong>Voxel printing offers a previously underexplored depth of detail and materiality within additive manufacturing, allowing for realistic imitations of biological structures in fabricated form. However, this approach is often overlooked due to the vast data requirements and specialised knowledge needed to create complex, meaningful models. This research investigates what new forms of meaning can emerge when machine learning algorithms are used to structure matter, and what occurs when algorithms are given the ability to perceive and respond to three-dimensional form. Using a primarily Research through Design approach, the project evolved through rigorous experimentation and iterative development. Unsupervised machine learning presents an intelligent alternative to manually placing voxels, algorithmically identifying hidden relationships and clustering them accordingly. This research provides insight into how voxel printing can be harnessed to generate form more efficiently, enabling greater detail and nuance in digitally fabricated outcomes.</strong></p>