The science behind deterministic AI for hardware.
Traditional generative AI models optimize for perceptual quality. Manufacturing requires exact dimensional compliance. Our research focuses on hybrid systems that combine neural networks with physics-based constraint solvers.
Key innovations include:
CADBench Research Team • Internal Whitepaper • 2024
We propose a framework for generating manufacturable 3D geometry by inverting the typical generative AI pipeline. Instead of predicting geometry from latent space, we solve constraint satisfaction problems.
Read PaperCADBench Research Team • Internal Benchmark • 2024
A systematic evaluation of leading AI CAD tools on a dataset of 500 real-world manufacturing specifications. We measure dimensional accuracy, tolerance compliance, and manufacturing feasibility.
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