Abstract A distributed inference architecture is disclosed in which a latent computational state propagates as a spatially-branching wavefront across a submesh of heterogeneous specialist-model nodes, operating on a unifying substrate comprising three cooperatively-operating elements: a shared-embedding latent-state carrier that propagates across physically-distinct specialist-model nodes; a fleet-wide Kuramoto-style order parameter that instruments the wavefront; and a slower-cadence auxiliary monitor population whose update rule depends on the fleet-wide order parameter. At each propagation cycle the wavefront fans out under a branching rule from fewer source nodes to more receiver nodes; each receiver performs a local specialist computation against the shared-embedding carrier and returns a contribution, a confidence, and a phase tag to an aggregator; the aggregator combines contributions under one of three enumerated aggregation mechanisms with phase-coded integration preferred; and the wavefront either propagates through successive cycles or terminates on a convergence criterion derived from the order parameter. The auxiliary monitor population performs pre-inference competence gating, post-inference output validation, lateral correlated-failure detection, and produces an architecturally-required multi-cadence provenance record. Dual-population cross-frequency phase coupling between the fast specialist population and the slow auxiliary monitor population is disclosed as the most architecturally novel element.
Desiderio Pina (Thu,) studied this question.