Natural selection can be understood through the lens of dynamic kinetic stability, where thermodynamic principles govern the replicator dynamics. In this framework, replicators have a fitness advantage and are more likely to persist over time compared to non-replicators, which may be eliminated by entropy or random mutations. This perspective expands the traditional view of natural selection, suggesting that the entire 'tape' or sequence of interactions resembles a genome, highlighting the complexity of how information is transmitted and transformed in evolutionary processes.
Understanding how life began on Earth involves questions of chemistry, geology, planetary science, physics, and more. But the question of how random processes lead to organized, self-replicating, information-bearing systems is a more general one. That question can be addressed in an idealized world of computer code, initialized with random sequences and left to run. Starting with many such random systems, and allowing them to mutate and interact, will we end up with "lifelike," self-replicating programs? A new paper by Blaise Agüera y Arcas and collaborators suggests that the answer is yes. This raises interesting questions about whether computation is an attractor in the space of relevant dynamical processes, with implications for the origin and ubiquity of life.
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Blog post with transcript: https://www.preposterousuniverse.com/podcast/2024/08/19/286-blaise-aguera-y-arcas-on-the-emergence-of-replication-and-computation/
Blaise Agüera y Arcas received a B.A. in physics from Princeton University. He is currently a vice-president of engineering at Google, leader of the Cerebra team, and a member of the Paradigms of Intelligence team. He is the author of the books Ubi Sunt and Who Are We Now?, and the upcoming What Is Intelligence?
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