Mortal Computation: A Foundation for Biomimetic Intelligence

TL;DR

This paper introduces a theoretical framework for biomimetic intelligence based on mortal computation, emphasizing the role of mortality, inference, and learning in creating sentient, brain-inspired AI systems.

Contribution

It recasts neuroscience-inspired AI and biomimetic computing within a formal mortal computation framework using the free energy principle.

Findings

Framework based on Markov blanket formalism and circular causality.

Guides the development of neuromorphic and chimeric agents.

Potential to revolutionize embodied AI and cognition research.

Abstract

This review motivates and synthesizes research efforts in neuroscience-inspired artificial intelligence and biomimetic computing in terms of mortal computation. Specifically, we characterize the notion of mortality by recasting ideas in biophysics, cybernetics, and cognitive science in terms of a theoretical foundation for sentient behavior. We frame the mortal computation thesis through the Markov blanket formalism and the circular causality entailed by inference, learning, and selection. The ensuing framework -- underwritten by the free energy principle -- could prove useful for guiding the construction of unconventional connectionist computational systems, neuromorphic intelligence, and chimeric agents, including sentient organoids, which stand to revolutionize the long-term future of embodied, enactive artificial intelligence and cognition research.