Post by Osama Atwi

Most "3D datasets" are useless for training engineering AI Pretty meshes. No construction history. No simulation. No manufacturing context. No assembly constraints. A model trained on that produces geometry that is useless for real world applications. Not all 3D models are created equal. What's actually needed: - Feature trees: the construction sequence that produced the part, not just the final geometry - Simulation-validated geometry: load cases, stresses, what the part can actually withstand - DfM metadata: how the part is meant to be manufactured, and the constraints that implies - Geometric and assembly constraints: how the part connects to other parts in assemblies Anything less is nice-looking meshes with no engineering content. If clean parametric 3D data is your bottleneck, let's talk.