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Daily Dose of Data Science | Avi Chawla | Substack

Zep introduces a temporally-aware knowledge graph for AI agents, addressing real-time knowledge updates and fast data retrieval. The architecture comprises three layers: episodic memory for storing raw data, semantic memory for extracting entities and relationships, and community memory for summarizing related entities. This design improves accuracy by up to 18.5% and reduces latency by 90% compared to traditional approaches like MemGPT.

Build Human-like Memory for Your AI Agents

I would encourage readers of this and similar write-ups to not call these systems “human-like.” It’s good for AI attention engagement but misrepresents what’s being done.
Strategy is definitely interesting and pratical; implementing RAG sources for storing information from interactions and separately both buiding networks of facts and connecting those networks to others.
It doesn’t really work the same way as human memory though and doesn’t make a model that uses it “human-like.”