이란, 트럼프 거부에도 “외교적 해법만 답…뉴욕서 30일까지 대기”
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.
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