Learning in ensembles of proteinoid microspheres

TL;DR

This paper explores the potential of proteinoid microspheres as neuromorphic computing elements, demonstrating their ability to learn, memorize, and habituate through electrical and optical measurements, suggesting new avenues for bio-inspired computing.

Contribution

It introduces the concept of using ensembles of proteinoid microspheres for neuromorphic computing and provides experimental evidence of their learning and memory capabilities.

Findings

Proteinoid microspheres exhibit neuron-like spiking behavior.

Proteinoids can learn, memorize, and habituate.

Electrical properties vary with different proteinoid types.

Abstract

Proteinoids are thermal proteins which form microspheres in water in presence of salt. Ensembles of proteinoid microspheres exhibit passive non-linear electrical properties and active neuron-like spiking of electrical potential. We propose that various neuromorphic computing architectures can be prototyped from the proteinoid microspheres. A key feature of a neuromorphic system is a learning. Through the use of optical and resistance measurements, we study mechanisms of learning in ensembles of proteinoid microspheres. We anlyse 16 types of proteinoids, study their intrinsic morphology and electrical properties. We demonstrate that proteinoids can learn, memorize, and habituate, making them a promising candidate for novel computing.