From Noise to Life: Exploring the Origins

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The field of artificial life, particularly in its endeavor to simulate the origins of life, is largely overlooked. Unlike traditional studies that begin with replicators already in existence, it is crucial to explore models that initiate with randomness or noise to understand how complexity and replication emerge. This approach has rarely been undertaken and is hindered by both conceptual and practical barriers. Critics argue that without a focus on chemistry, the investigation may not yield significant insights into the actual origins of life.

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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