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efficient, adaptive use of multistable networks, offering an alternative to energy-intensive digital systems with rigid bits and separated memory and computation. In this project, we aim to design and realize
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that counteract changes in the environment and the aging of their own parts. We will study how to make these materials learn continually by adapting functions over their lifetime without forgetting old lessons
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