Photo credit: Gretchen Ertl
MIT researchers have developed Style2Fab, a generative AI-driven tool that lets makers rapidly customize 3D-printable objects without hampering their functionality. Customizing existing user-generated 3D models has never been easy since it requires pricey CAD software, but this solution uses AI to add custom design elements using only natural language prompts.
Style2Fab makes use of deep-learning algorithms that automatically splits the model into aesthetic and functional segments. In other words, the system analyzes the model’s topology to track the frequency of changes in geometry like curves ot angles where two planes connect. This means that a user could easily change the appearance of a thumb splint so it blends in with their clothing.
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For someone with less experience, the essential problem they faced has been: Now that they have downloaded a model, as soon as they want to make any changes to it, they are at a loss and don’t know what to do. Style2Fab would make it very easy to stylize and print a 3D model, but also experiment and learn while doing it,” said Faraz Faruqi, a computer science graduate student and lead author of a paper introducing Style2Fab.
