Artificially evolved neural networks and robots often lack modularity unless it is directly selected for, and exhibit inefficiencies from evolutionarily duplicated sub-structures.

Entities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.

• If the universality hypothesis is broadly true, it raises the exciting possibility that artificial neural networks could predict features previously unknown in biological neural networks.claim0.798
  Speculative extension of universality to neuroscience, with high-low frequency detectors as a candidate prediction
• Conceptual advances in the links between machine learning and evolution now provide quantitative formalisms with which to begin to develop testable models of collective intelligence across scales.claim0.787
  Asserts that the time is ripe for formal models.
• Morphogenetic and behavioral problem-solving share deep algorithmic and mechanistic symmetries, with bioelectric networks serving both developmental and neural functions via evolutionary pivot.hypothesis0.784
  Testable prediction that insights from developmental bioelectricity can illuminate behavioral cognition and vice versa; grounds portability of neuroscience tools across tissue types.
• Many recent discussions of AI, and its impact on individuals and on society, are importantly incomplete because they neglect Diverse Intelligence, synthetic morphology, and developmental biology.claim0.783
  Central thesis of the paper — the framing premise from which all other arguments follow
• Biology's robustness, open-endedness, evolvability, and unique complexity likely depend on the fact that evolution works with an agential material.claim0.783
  Central claim linking life's properties to the inherent competencies of its material substrate.
• Evolution often produces general-purpose problem-solving machines whose capacities cannot be inferred from the default invariant course of development.claim0.783
  A claim about the outcome of the MCA-enhanced process.
• Neural bioelectric networks achieve a critical separation of hardware and software: the same molecular substrate can instantiate different informational content based on history, enabling minds to arise from matter.claim0.780
  Foundational for understanding how physiology becomes meaning; decoupling of material state from information content is prerequisite for emergence of cognitive Self.
• Open-ended evolution of intelligence is possible because agents are collectives without fixed essencehypothesis0.779
  Follows from observation that intelligent systems lack context-transcendent core; their maxima are not contingent on permanent character.