“‘한국어 말뭉치’ 구축에 힘 되려 30년 세월 바쳤죠”

The article discusses the challenges of creating companion AI that can maintain long-term memories and avoid the "30-round memory loss" and "persona drift" issues. It introduces a four-layer memory engine design called DreamTalk, which includes working memory, episodic memory, semantic knowledge graph, and reflection & consolidation layers.

The working memory layer maintains the recent 6-10 rounds of dialogue, while the episodic memory layer assigns high weights to significant life events and generates structured event embeddings. The semantic knowledge graph maintains the user-role relationship and constraints, and the reflection & consolidation layer generates a higher-level cognitive summary based on the user's recent emotional state.

The article also describes a Python implementation of the core memory retrieval and prompt assembly module, as well as a double-prevention mechanism to prevent the AI from devolving into a generic assistant during extended conversations.