This video introduces the world’s first mechanical neural network that can learn its behavior. It consists of a lattice of compliant mechanisms that constitute an artificial intelligent (AI) architected material that gets better and better at acquiring desired behaviors and properties with increased exposure to unanticipated ambient loading conditions. It is a physical version of an artificial neural network used in current machine learning technologies.

To learn more about the content of this video, I encourage you to read the following publications, which can be accessed at the provided links:

[1] Lee, R.H., Mulder, E.A.B., Hopkins, J.B., 2022, “Mechanical Neural Networks: Architected Materials that Learn Behaviors,” Science Robotics, 7(71): pp. 1-9
https://www.science.org/stoken/author...

[2] Lee, R.H., Sainaghi, P., Hopkins, J.B., 2023, “Comparing Mechanical Neural-network Learning Algorithms,” Journal of Mechanical Design, 145(7): 071704 (7 pages)
https://asmedigitalcollection.asme.or...

Part files to fabricate the mechanical neural network can be downloaded on Thingiverse using this link:
https://www.thingiverse.com/thefactso...

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Acknowledgements:
Special thanks to Ryan Lee, Erwin Mulder, and Pietro Sainaghi who helped fabricate, test, and simulate the mechanical neural network in the video. I am also grateful to my AFOSR program officer, “Les” Lee, who funded the research that this video features.

Brain Scan Attribution:
Christian R. Linder, CC BY-SA 3.0 http://creativecommons.org/licenses/b..., via Wikimedia Commons
https://commons.wikimedia.org/wiki/Fi...
https://upload.wikimedia.org/wikipedi...
Microstructure Image Attribution:
Edward Pleshakov, CC BY 3.0 https://creativecommons.org/licenses/..., via Wikimedia Commons
https://commons.wikimedia.org/wiki/Fi...
https://upload.wikimedia.org/wikipedi...
Body Armor Attribution:
https://commons.wikimedia.org/wiki/Fi...
https://upload.wikimedia.org/wikipedi...

Disclaimer:
Responsibility for the content of this video is my own. The University of California, Los Angeles is not involved with this channel nor does it endorse its content.