Autonomous Experiments for Structural Design in 3d Printing

Autonomous Experiments for Structural Design in 3d Printing

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Canada LLMs Explained - Aggregate Intellect - AI.SCIENCE
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Published on ● Video Link: https://www.youtube.com/watch?v=X-TI19l2pNU


Duration: 57:03
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For slides and more information on the paper, visit https://ai.science/e/bear-autonomous-experiments-for-structural-design-in-3d-printing--2021-05-18-ryan

Speaker: Keith Brown; Host: Ryan Cohn

Motivation:
- Active learning was used to optimize the mechanical properties of a 3d printed part with fewer experiments than other approaches
- Combining physical simulation with active learning reduced the number of experiments required to discover the optimal design by an order of magnitude compared to active learning alone, and two orders of magnitude compared to an experimental grid search approach
- The active learning system was used to power an experimental setup that designed, fabricated, and tested components completely autonomously
- The results demonstrate promise for drastically improving efficiency and reducing the cost and time required to develop components that are optimized for specific applications



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