Shared Translation

Emphasizing the principles of continuity and pragmatism, and using morphogenesis as a tractable model system in which to develop these ideas, I explore the implications of the following ideas:(A) Evolution favors living forms that exploit powerfultruths of mathematics and computation as affordances, which contribute as causes of morphologicaland behavioralfeatures. (B) Cognitive patterns arean evolutionary pivot of the collective intelligence of cells;given this symmetry between neuroscience and developmental biology, I propose that the relationship between mind and brain is the same as the relationship between mathematical patterns and the morphogenetic outcomes they guide. (C) Many mathematicians, and a non-mysterian approach to science in general, suggest that these patterns are not random facts to bemerely cataloged as “emergence” when found, but rather can be systematically discovered within a structured, ordered (non-physical) space. Therefore, I hypothesize that:(1)instances of embodied cognition likewise ingress from a Platonic space, which contains not only low-agency patterns like facts about triangles and prime numbers, but also higheragency ones such as kinds of minds; (2)we take seriously for developmental, synthetic, and behavioral biologythe kindsof non-physicalist ideas that are already a staple of Platonist mathematics;(3) what evolution (and bioengineering, and possiblyAI) produces are pointers into that Platonic space –physical interfacesthat enable the ingression of specific patternsof body and mind.This provides a new perspective on the organicist/mechanist debate by explaining why traditional computationalist views of life and mind are insufficient, while at the same time erasing artificial distinctions between life and machine, since both are in-formed by diverse patterns from the latent space. I sketch a research program, already begun, of using the tools of the fields of synthetic morphologyand diverse intelligence to map out key regions of the Platonic space. Understanding the mapping between the architecture of physical embodiments and the patterns to which they point has massive implications for evolutionary biology, regenerative medicine, AI, and the ethics of synthbiosis with the forthcomingimmensediversity of morally important be

Emphasizing the principles of continuity and pragmatism, and using hypothesis generation as a tractable model system in which to develop these ideas, I explore the implications of the following ideas: (A) Scientific discovery favors hypothesis generators that exploit powerful truths of mathematics and computation as affordances, which contribute as causes of novel and explanatory hypotheses. (B) Conceptual patterns are a pivotal axis of the collective intelligence of scientific communities; given this symmetry between mathematical structure and hypothesis generation, I propose that the relationship between abstract mathematical truths and generated hypotheses is analogous to the relationship between mathematical patterns and the scientific outcomes they guide. (C) Many mathematicians, and a non-mysterian approach to science in general, suggest that these patterns are not random facts to be merely cataloged as "emergence" when found, but rather can be systematically discovered within a structured, ordered (non-physical) space. Therefore, I hypothesize that: (1) instances of scientific insight likewise ingress from a Platonic space, which contains not only low-agency patterns like facts about triangles and prime numbers, but also higher-agency ones such as classes of explanatory hypotheses; (2) we take seriously for hypothesis generation and scientific discovery the kinds of non-physicalist ideas that are already a staple of Platonist mathematics; (3) what scientific inquiry (and computational modeling, and possibly AI-driven discovery) produces are pointers into that Platonic space—conceptual interfaces that enable the ingression of specific patterns of explanatory hypotheses. This provides a new perspective on the rationalist/empiricist debate by explaining why traditional computationalist views of scientific discovery are insufficient, while at the same time erasing artificial distinctions between human and machine-generated hypotheses, since both are informed by diverse patterns from the latent space. I sketch a research program, already begun, of using the tools of computational hypothesis generation and diverse intelligence to map out key regions of the Platonic space. Understanding the mapping between the architecture of hypothesis-generating systems and the patterns to which they point has massive implications for scientific methodology, computational discovery, AI-driven science, and the ethics of collaboration with the forthcoming immense diversity of scientifically important conceptual agents.