Paper 2606.27382v1 proposes an AI-Model Network to solve interaction bottlenecks between distributed, domain-specific models. High training costs now drive a shift toward lightweight, private architectures over monolithic systems. This framework aims to standardize how heterogeneous models share data. Practitioners can use these protocols to reduce deployment complexity in multi-model environments.