Learning to Generate Shapes

As we delve further into the intersection of artificial intelligence and engineering, we are turning our attention to the work carried out by Karl D.D. Willis and his team at the Autodesk Research AI Lab.

Pushing the boundaries of 3D generative AI research, Willis and his colleagues are not just focusing on how AI can assist in the 3D creation and modeling process, but also on its potential role in the context of full mechanical systems assemblies.

This approach moves beyond much of the current research that explores what a geometry ‘might’ look like, to a more nuanced understanding of how components ‘should’ function or be modeled.

From generating parametric CAD, to using simulation for obtaining performant results beyond the constraints of training data, to envisioning what ‘Clippy’ for engineering might look like, Willis offers his insights into the future of AI in mechanical engineering.