  Tangle machines are a topologically inspired diagrammatic formalism to
describe information flow in networks. This paper begins with an expository
account of tangle machines motivated by the problem of describing `covariance
intersection' fusion of Gaussian estimators in networks. It then gives two
examples in which tangle machines tell stories of adiabatic quantum
computations, and discusses learning tangle machines from data.
