  We outline a phenomenological theory of evolution and origin of life by
combining the formalism of classical thermodynamics with a statistical
description of learning. The maximum entropy principle constrained by the
requirement for minimization of the loss function is employed to derive a
canonical ensemble of organisms (population), the corresponding partition
function (macroscopic counterpart of fitness) and free energy (macroscopic
counterpart of additive fitness). We further define the biological counterparts
of temperature (biological temperature) as the measure of stochasticity of the
evolutionary process and of chemical potential (evolutionary potential) as the
amount of evolutionary work required to add a new trainable variable (such as
an additional gene) to the evolving system. We then develop a phenomenological
approach to the description of evolution, which involves modeling the grand
potential as a function of the biological temperature and evolutionary
potential. We demonstrate how this phenomenological approach can be used to
study the "ideal mutation" model of evolution and its generalizations. Finally,
we show that, within this thermodynamics framework, major transitions in
evolution, such as the transition from an ensemble of molecules to an ensemble
of organisms, that is, the origin of life, can be modeled as a special case of
bona fide physical phase transitions that are associated with the emergence of
a new type of grand canonical ensemble and the corresponding new level of
description
