What set of concepts and formalizations might one use to make a practically useful, theoretically rigorous theory of generally intelligent systems? We present a novel perspective motivated by the OpenCog AGI architecture, but intended to have a much broader scope. Types of memory are viewed as categories, and mappings between memory types as functors. Memory items are modeled using probability distributions, and memory subsystems are conceived as “mindspaces” – geometric spaces corresponding to different memory categories. Two different metrics on mindspaces are considered: one based on algorithmic information theory, and another based on traditional (Fisher information based) “information geometry”. Three hypotheses regarding the geometry of mind are then posited: 1) a syntax-semantics correlation principle, stating that in a successful AGI system, these two metrics should be roughly correlated; 2) a cognitive geometrodynamics principle, stating that on the whole intellige...