Evolution often produces general-purpose problem-solving machines whose capacities cannot be inferred from the default invariant course of development.

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• Evolution learns to generalize beyond default morphologies, producing problem-solving machines.claim0.899
  Argues that evolutionary learning goes beyond specific adaptations.
• Evolution does not simply make hardwired machines that execute a predetermined set of steps; instead, it produces problem-solving hardware.claim0.849
  Key insight about the nature of evolved systems.
• Evolution makes problem-solving agents, not solutions; commitment to mutation and uncontrollable environments as ratchet for intelligenceclaim0.837
• Evolution was using developmental bioelectricity long before neurons and muscles appeared, to solve the problem of creating and repairing complex bodies.claim0.810
  Claim about the primacy of bioelectric morphogenesis.
• A multi-scale competency architecture facilitates evolution of robust problem-solving, living machines.claim0.807
  Key proposal linking multi-scale agency to evolutionary advantage.
• Biology's robustness, open-endedness, evolvability, and unique complexity likely depend on the fact that evolution works with an agential material.claim0.806
  Central claim linking life's properties to the inherent competencies of its material substrate.
• How does evolution capitalize on the laws of physics and computation to generalize so well from specific examples to highly diverse possible instantiations?question0.804
  Question about the deep principles enabling evolvability.
• Evolution actually searches not only genotype space but a more tractable space of behavior-shaping signals that exploit cellular intelligence.claim0.804
  Central thesis of the paper.