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Rather than simulating chemical gradients, EndlessForms stores a “genome” for each object that describes a collection of simple mathematical functions analogous to these gradients, so that, for example, a sine function takes the place of a repeating chemical gradient. The website produces variations on objects by mutating this mathematical DNA. By summing the contributions from all the functions described by the genome, and checking whether the result is above a threshold value, EndlessForms determines whether blocks of 3-D space called voxels are either filled or left empty in an object.

Currently, EndlessForms can generate only a limited range of novelty shapes. To contain computational costs, the system uses a relatively small number of voxels for each object. And because each object is initially randomly generated, a user with a specific shape in mind may need to do quite a bit of selecting and evolving to produce something close to that shape. However, the Cornell group and collaborators plan to develop the system to enable a user to input a 3-D scan of an existing object and then evolve variants from that. This would allow, for example, a designer to scan in a pair of sunglasses and use the system to evolve new styles.

The technology is “very impressive,” says Neri Oxman, director of the MIT Media Lab’s Mediated Matter research group. She believes the user-friendliness of the evolutionary approach could help drive the broader adoption of 3-D printing technologies, similar to how easy-to-use image editors fueled the growth of digital photography and graphic manipulation. “People could scan their own toothbrushes or other objects and evolve various designs of such items for members of their family,” says Oxman, noting that this could ultimately have an impact on design similar to the impact that blogs and social media have had on journalism, opening the field to the general public.

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Credit: Cornell University

Tagged: Computing, materials, manufacturing, 3-D printing, printing technology

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