Analog computers could bring massive efficiency gains to machine learning

Regulating conductance between reference and electrolyte/ion source to control a time varying voltage is how actual neurons do analog processing. The convergence here seems remarkable. They’re trying to improve the digital models of neural networks and end up essentially reverse engineering the analog processors in our brains.

btw. The reason that biological nervous systems use analog processing in the first place is its much more energy efficient. The processor in a phone uses considerably more energy then our entire nervous system.

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