Near-future machines will be built on the principles of multi-scale competency in a fluid 'society' of components that communicate, trade, cooperate, compete, and barter information and energy resources as do living components of an organism.

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

• Near-future systems will contain swarms of robots and organisms in which biological units reproduce and evolve while mechanical units self-replicate and evolve, making binary life/machine division impossible.hypothesis0.842
  Extreme future-pointing scenario used to argue binary categorization will become incoherent
• A multi-scale competency architecture facilitates evolution of robust problem-solving, living machines.claim0.798
  Key proposal linking multi-scale agency to evolutionary advantage.
• Self-similarity and multi-scale competency currently remain a real feature that distinguishes living systems from machines, though there is no deep reason preventing engineered artifacts from exploiting it.claim0.784
  The one property the authors acknowledge still distinguishes life from machines, but frame as contingent not essential
• We hypothesize that general computational machines with sufficient resources possess the necessary and sufficient means to implement consciousness, and that successful implementation can be established via analysis or testing.hypothesis0.773
  The central hypothesis of the paper
• Progress in theory and practice requires a novel conception of 'machines as they could be,' based on the profound lessons of biology at all scales.claim0.771
  The paper's overarching constructive goal, paralleling Langton's 'life as it could be'
• A realization of our own multiscale, nested architecture naturally leads to the conclusion that care needs to be extended to all sentient beings.claim0.769
  Extends ethical concern based on the collective nature of selves.
• General computational machines with sufficient resources possess the necessary and sufficient means to implement consciousnesshypothesis0.766
  CIMC's central testable hypothesis grounding the entire research program
• 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.claim0.765
  Asserts that the time is ripe for formal models.