AI builds a ‘wiki’ to remember facts from multiple documents

A typical large language model will deliver fifty disconnected answers when presented with fifty related documents, treating each upload as a fresh start with no memory of previous information. Andrej Karpathy describes this limitation as a break from a typical loop, envisioning an AI that instead maintains a structured, cross-linked knowledge base. Karpathy explains, “LLMs don’t get bored, don’t forget to update a cross-reference, and can touch 15 files in one pass.” To test this “wiki” approach, one researcher specifically stress-tested the system using The Hound of the Baskervilles, evaluating its ability to update knowledge as new plot details emerged. Maintaining three distinct layers, raw source documents, a dynamically updated wiki, and a governing schema, is a deliberate architectural choice of the system, and it is important for persistent knowledge retention. Unlike typical large language model interactions where each uploaded document is treated as a fresh start, this design prioritizes building a continuously refined knowledge…