  Coordinated inference problems are being introduced as a basis for a neural
network representation of the locality problem in the holographic bulk. It is
argued that a type of problem originating in the "prisoners and hats" dilemma
involves certain non-local structures to be found in the AdS/CFT duality. The
neural network solution to this problem introduces a new approach that can be
flexible enough to identify holographic dualities beyond AdS/CFT. Neural
networks are shown to have a significant role in the connection between the
bulk and the boundary, being capable of inferring sufficient information
capable of explaining the pre-arrangement of observables in the bulk that would
lead to non-local precursor operators in the boundary.
