Biological systems are ergodic, possess a Markov blanket, exhibit active inference, and are autopoietic.

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• Life requires only a boundary (Markov blanket), ergodicity, active inference capacity, and autopoiesis—not reproduction or DNA.claim0.849
  Reframes definition of life focusing on dynamical self-organization rather than genetic reproduction.
• If systems are ergodic and possess a Markov blanket, they will show lifelike behaviour.hypothesis0.848
  The main hypothesis the paper attempts to verify heuristically and with simulations.
• Any ergodic random dynamical system that possesses a Markov blanket will appear to actively maintain its structural and dynamical integrity.claim0.793
  The lemma that leads to the main claim.
• Minimum entropy Markov blankets may characterize biological systems.claim0.788
  Conjecture about what distinguishes living from non-living systems.
• Most biological systems consist of multiple nested selves, not oneclaim0.781
  Levin critiques Integrated Information Theory's implication of singular unified self, arguing Scale-Free Cognition requires recognition of nested agents at each organizational level.
• Under the Markov blanket assumption together with NESS, a generalised synchrony appears, such that the dynamics of internal states can be cast as performing inference over external states via minimisation of variational free energy.claim0.767
  Key theoretical claim linking active inference to physics in Section 2.
• Biology's robustness, open-endedness, evolvability, and unique complexity likely depend on the fact that evolution works with an agential material.claim0.766
  Central claim linking life's properties to the inherent competencies of its material substrate.
• Multiscale systems like those prevalent in biology are capable of organizing into complex patterns, whereas rudimentary language models are challenged by long sequences of outputs.claim0.764
  Conclusion about why biology organizes complexity well and flat LLMs do not