Systems and methods for cognitive inferencing for large language models

This system gives a large language model (LLM) a memory of its past conversations without changing the core model itself. It does this by creating an unchangeable, chronological record of insights from user interactions, which the claims specify as an "immutable sequential listing." This record then serves as extra context for the LLM's future responses, allowing it to build on previous exchanges by providing "contextual prompts."