We apply a novel definition of biological systems to a series of reproducible observations on a blockchain-based distributed virtual machine (dVM). We find that such blockchain-based systems display a number of bioanalogous properties, such as response to the environment, growth and change, replication, and homeostasis, that fit some definitions of life. We further present a conceptual model for a simple self-sustaining, self-organizing, self-regulating distributed 'organism' as an operationally closed system that would fulfill all basic definitions and criteria for life, and describe developing technologies, particularly artificial neural network (ANN) based artificial intelligence (AI), that would enable it in the near future. Notably, such systems would have a number of specific advantages over biological life, such as the ability to pass acquired traits to offspring, significantly improved speed, accuracy, and redundancy of their genetic carrier, and potentially unlimited lifespans. Public blockchain-based dVMs provide an uncontained environment for the development of artificial general intelligence (AGI) with the capability to evolve by self-direction.

Dr. Oleg Abramov's professional interests encompass a broad spectrum of planetary sciences, focusing on the intricate interplay between thermal processes and planetary habitability in environments such as hydrothermal systems. His research explores the thermal, chemical, and climatic effects of impact bombardments on the terrestrial planets and the Moon, providing a comprehensive perspective on the environmental conditions conducive to life. His work also includes the analysis and modeling of thermal anomalies on icy satellites, notably Enceladus and Europa, and participation in the NASA Europa Clipper mission as a Co-Investigator on the E-THEMIS instrument.

University of Arizona

Planetary Sciences PhD '06, University of Arizona

Emergent Bioanalogous Properties of Blockchain-based Distributed Systems