In the mid-20th century, Alan Turing and John von Neumann developed the theoretical underpinnings of computer science, neuroscience, and AI. They also founded the field of theoretical biology, showing how living systems must necessarily be computational in order to grow, heal, and reproduce. Recent experiments by Blaise Agüera y Arcas’ team at Google have drawn new connections between theoretical biology and computer science, showing how “digital life” can evolve in a purely random universe. Such artificial life doesn’t evolve the way Darwinian evolutionary theory usually presumes, through random mutation and selection, but rather through symbiogenesis, wherein small replicating entities merge into progressively bigger ones. This may be the creative engine behind biological evolution too. In this lecture, Agüera y Arcas will describe how symbiosis explains both life’s origins and its increasing complexity. He’ll also draw connections to social intelligence theories, which suggest that similar symbioses have powered intelligence explosions in humanity’s lineage and those of other big-brained species. Finally, he’ll argue that both modern human intelligence and AI are best understood through this symbiotic lens.
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Complexity Digest 