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트럼프, 한·미 회담 위해 연설 30분 늦춰…즉석 ‘골프 부킹’ 지시도

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.

Written by urgent.news from Dev.to's reporting — not their text. Machine-written — may contain errors; check the original before relying on it.

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