Machine Learning Mastery
Beyond Vector Search: Building a Deterministic 3-Tiered Graph-RAG System
âĸ1 min readâĸ
#rag#deployment#compute
Level:Advanced
For:ML Engineers, Data Scientists, AI Researchers
âĻTL;DR
This article discusses the development of a deterministic 3-tiered Graph-RAG (G-RAG) system, which moves beyond traditional vector search methods by incorporating a multi-layered graph structure to improve search efficiency and accuracy. The proposed system consists of three tiers, enabling a more robust and scalable approach to information retrieval and knowledge graph construction.
⥠Key Takeaways
- The 3-tiered G-RAG system is designed to overcome the limitations of vector search by providing a more structured and deterministic approach to information retrieval.
- The system consists of a bottom tier for data storage, a middle tier for graph construction, and a top tier for query processing and ranking.
- The use of a graph structure allows for more efficient and accurate search results, particularly in applications involving complex relationships and entities.
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