Any system that exists will appear to minimize free energy and therefore engage in active inference. Furthermore, this apparently inferential or mindful behaviour is (almost) inevitable.

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• Any system that exists will appear to minimize free energy and therefore engage in active inference.claim0.920
  The reworked argument that free energy minimization is a corollary of existence, not a prerequisite.
• Any system minimizing free energy will appear to engage in implicit Bayesian inference of hidden external causes.hypothesis0.839
  Predicts that internal states encode posterior beliefs about external world through gradient descent on free energy.
• Active inference has no random or stochastic aspects; everything changes to minimize variational free energy in accord with Hamilton's principle of least action.claim0.839
  Ontological claim about the deterministic nature of active inference agents in these simulations
• In brief, active inference proposes that agents achieve this by optimising two complementary objective functions, a variational free energy and an expected free energy.quote0.825
  Concise statement of the core hypothesis from Section 2.
• Active inference provides a principled account of epistemic exploration and intrinsic motivation as minimizing uncertainty.claim0.824
  §1, listing contributions.
• Active inference offers an attractive natural adaptation mechanism for non-stationary environments due to its Bayesian model updating properties.claim0.824
  §3, after non-stationary results.
• Active inference achieves Bayes-optimal behavior in non-stationary environments through online belief updating.hypothesis0.823
  Tested via FrozenLake experiments; predicts superior performance when environment dynamics change.
• Active inference postulates that agents achieve survival by optimising two complementary objective functions, a variational free energy and an expected free energy.claim0.821
  Core claim of active inference stated in Section 2.