  This paper provides a concise description of the free energy principle,
starting from a formulation of random dynamical systems in terms of a Langevin
equation and ending with a Bayesian mechanics that can be read as a physics of
sentience. It rehearses the key steps using standard results from statistical
physics. These steps entail (i) establishing a particular partition of states
based upon conditional independencies that inherit from sparsely coupled
dynamics, (ii) unpacking the implications of this partition in terms of
Bayesian inference and (iii) describing the paths of particular states with a
variational principle of least action. Teleologically, the free energy
principle offers a normative account of self-organisation in terms of optimal
Bayesian design and decision-making, in the sense of maximising marginal
likelihood or Bayesian model evidence. In summary, starting from a description
of the world in terms of random dynamical systems, we end up with a description
of self-organisation as sentient behaviour that can be interpreted as
self-evidencing; namely, self-assembly, autopoiesis or active inference.
