Biomimicry of Brains “Forgetfullness” Inspires Breathing Material for Computing

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Biomimicry of Brains “Forgetfullness” Inspires Breathing Material for Computing

Silicon based technologies will no longer be able to keep up with the demands for exponentially increasing computational power. Science must look to nature for examples on how to improve and balance our technologies. Super-computing strives to reach the efficiency of the human brain yet attempts to do so with silicon based infrastructure.  The human brain, a biological water cavity filled with fractal protein scaffolding, acts as the most advanced computational system known.

The brains ability to forget through neural synaptic plasticity, known as habituation, allows for learning and behavioral formation from the most basic of cellular organisms to humans. A novel meta-material known as “quantum perovskite” is a  charged lattice that dynamically breathes with the additions or removal of “protons”, mimicking the habituation process of neural synapses.




A central characteristic of living beings is the ability to learn from and respond to their environment leading to habit formation and decision making. This behavior, known as habituation, is universal among all forms of life with a central nervous system, and is also observed in single-cell organisms that do not possess a brain. Here, we report the discovery of habituation-based plasticity utilizing a perovskite quantum system by dynamical modulation of electron localization. Microscopic mechanisms and pathways that enable this organismic collective charge-lattice interaction are elucidated by first-principles theory, synchrotron investigations, ab initio molecular dynamics simulations, and in situ environmental breathing studies. We implement a learning algorithm inspired by the conductance relaxation behavior of perovskites that naturally incorporates habituation, and demonstrate learning to forget: a key feature of animal and human brains. Incorporating this elementary skill in learning boosts the capability of neural computing in a sequential, dynamic environment.




By |2018-03-21T19:45:28+00:00March 21st, 2018|Artificial Intelligence, Biology, Consciousness|

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