Parametric Optimization via Local AI Inference
Blog post from Rescale
Rescale previews upcoming local AI Physics inference capabilities that allow engineers to connect geometry, surrogate models, and outputs for lightweight parametric studies and optimization loops on local workstations. The tooling is designed to help users explore design options more quickly without relying on inference servers or high-performance computing clusters, and the post invites readers to view a demonstration and learn more about the planned features.
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