On Artificial Life and Emergent Computation in Physical Substrates

TL;DR

This paper explores how artificial life principles can be used to understand and harness emergent computation in physical substrates, aiming to develop new high-performance, massively parallel computing technologies beyond traditional limits.

Contribution

It introduces the potential of artificial life methodologies for uncovering and utilizing the computational power of physical substrates in unconventional computing.

Findings

Discussion of biological neurons and nanomagnet ensembles as computational substrates

Illustration of artificial life tools applied to unconventional computing

Philosophical insights on learning from artificial life in computation

Abstract

In living systems, we often see the emergence of the ingredients necessary for computation -- the capacity for information transmission, storage, and modification -- begging the question of how we may exploit or imitate such biological systems in unconventional computing applications. What can we gain from artificial life in the advancement of computing technology? Artificial life provides us with powerful tools for understanding the dynamic behavior of biological systems and capturing this behavior in manmade substrates. With this approach, we can move towards a new computing paradigm concerned with harnessing emergent computation in physical substrates not governed by the constraints of Moore's law and ultimately realize massively parallel and distributed computing technology. In this paper, we argue that the lens of artificial life offers valuable perspectives for the advancement of high-performance computing technology. We first present a brief foundational background on artificial life and some relevant tools that may be applicable to unconventional computing. Two specific substrates are then discussed in detail: biological neurons and ensembles of nanomagnets. These substrates are the focus of the authors' ongoing work, and they are illustrative of the two sides of the approach outlined here -- the close study of living systems and the construction of artificial systems to produce life-like behaviors. We conclude with a philosophical discussion on what we can learn from approaching computation with the curiosity inherent to the study of artificial life. The main contribution of this paper is to present the great potential of using artificial life methodologies to uncover and harness the inherent computational power of physical substrates toward applications in unconventional high-performance computing.