1d ago · 14 min read · This is Part 2 of a two-part series on practical RAG optimization. If you missed Part 1 on indexing strategies, start there first — the techniques here build on that foundation. In Part 1, we covered
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Apr 24 · 8 min read · Original: GraphRAG: Unlocking LLM discovery on narrative private data - Microsoft Research In early 2024, Microsoft published a technical blog post. The core message boils down to one sentence: Traditional RAG falls short with complex data, and Gra...
Join discussionApr 24 · 9 min read · You thought the hardest part of GraphRAG was "building the graph." In reality, the hardest part is "assigning entity types" — even when you've predefined a strict type schema. 1. A Real-World Dataset We ran GraphRAG entity extraction on 3GPP TS 23.5...
Join discussionApr 24 · 6 min read · When AI stops just "looking things up" and starts truly "understanding" your question. 1. Let's Start with an Everyday Scenario Imagine you're a new employee at a company. On your first day, you want to know "the most important project updates from ...
Join discussionApr 9 · 2 min read · GraphRAG Beats Vector Search by 86% — But 92% of Teams Are Building It Wrong GraphRAG beats flat vector search by 86% on multi-hop queries — but most teams are building it wrong. They bolt Neo4j onto LangChain and call it done. Missing: Entity resol...
Join discussionApr 9 · 7 min read · GraphRAG Beats Vector Search by 86% — But 92% of Teams Are Building It Wrong Microsoft's GraphRAG paper showed that graph-structured retrieval with community summarization significantly outperforms flat vector search on multi-hop and thematic queries...
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Mar 26 · 6 min read · We organize Hack4Bengal, one of the largest in-person hackathons in Eastern India every year. Every edition, two things go wrong that no amount of spreadsheet wizardry can fix: Mentor matching is a gu
Join discussionMar 25 · 4 min read · Most modern data stacks are broken in a subtle way. Not because they lack tools — but because they separate things that should be connected. You have: SQL for structured data RAG for documents APIs
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