Navigating CLIPedia: Architectonic instruments for querying and questing a latent encyclopedia

This paper introduces CLIPedia, an entirely local, highly scalable, multimodal search engine that integrates the structured knowledge of Wikipedia into the latent embedding space of OpenCLIP. Alongside its technical development, the paper offers a theoretical framing, positing AI not merely as a tool for information access but as an architectonic instrument for invention and discovery. Built on a two-tiered Self-Organizing Map (SOM) architecture—comprising toroidal and ring-shaped layers—CLIPedia organizes over 30 million data points for fast unimodal and cross-modal retrieval. It achieves sub-second response times on standard hardware with minimal working memory footprint, delivering local performance comparable to cloud-based vector search systems and excelling on queries that return many relevant results. Beyond queries, CLIPedia enables latent journeys—termed quests—across high-dimensional embedding space. For this, the paper introduces a set of navigational metaphors and computational mechanisms—termed Orthodromes, Diadromes, Archidromes, and Thelodromes—to trace both linear and non-linear trajectories through the latent space of digitally encoded encyclopedic knowledge. The paper is accompanied by an open-source code repository.