Safety RAG (SRAG) is how we get to 100% hallucination-free answers.

RAG is popular but unfit for many enterprise use cases and I explain both of those things.

Utilizing knowledge graphs is one popular solution to drive up the performance of AI applications. We work closely together with other key players such as Emil…

An open-source model for 10x cheaper knowledge graph construction

Large Language Models (LLMs) have demonstrated unprecedented prowess across various natural language processing tasks in various application domains. Recent studies show that LLMs can be leveraged...

Using knowledge graphs to improve the performance of RAG systems by optimising retrieval design architectures and collaborative filtering.

Knowledge Graph Embedding (KGE) algorithms can improve the performance of LLMs in understanding relationships as a context for Q&As.

Learn how to use unstructured.io for PDF document parsing, extracting, and ingestion into the Neo4j graph database for GenAI applications.

Let’s talk about the new graph-based approach to processing complex datasets for context-rich LLM responses

𝗥𝗔𝗚 𝗜𝗺𝗽𝗹𝗲𝗺𝗲𝗻𝘁𝗮𝘁𝗶𝗼𝗻𝘀 𝗙𝗮𝗶𝗹 𝗗𝘂𝗲 𝗧𝗼 𝗜𝗻𝘀𝘂𝗳𝗳𝗶𝗰𝗶𝗲𝗻𝘁 𝗙𝗼𝗰𝘂𝘀 𝗢𝗻 𝗤𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗜𝗻𝘁𝗲𝗻𝘁 𝘛𝘩𝘦 𝘔𝘪𝘯𝘥𝘧𝘶𝘭-𝘙𝘈𝘎… | 12 comments on LinkedIn

The Advantages of Small Graphs for Construction, Retrieval, Maintenance and Scaling KG RAG systems.

When we progress from data to knowledge, there is what physicists call a phase change like the change from water to ice or from mud to brick. The ingredients are the same throughout the transition, but we compress and restructure these ingredients into something entirely new with dramatically differ

Ten Arguments

🥳 The Wait is Over! As promised from my last post (https://lnkd.in/g9_-9i8D), I took MSFT open-source GraphRAG for a 🏎️💨 road test via my JAM4RAG (Just… | 12 comments on LinkedIn

Many people have asked about loading Microsoft Research #GraphRAG data into Neo4j. I wrote a quick notebook last night to import Documents, Chunks (TextUnit)… | 27 comments on LinkedIn

Examples of KG + RAG & Schemas that are used by various systems across different domains, for inspirational purposes.

We switched from building simple LLM agents to graph-based AI solutions this year. In our experience, agentic graphs are the only way to 1) ensure high… | 44 comments on LinkedIn

There is a lot of noise about #KnowledgeGraphs for LLM apps. But we haven't seen an enterprise-grade implementation. This approach could be one. "The… | 11 comments on LinkedIn

This is something very cool! 3. GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models "GraphReader addresses the…

See how to combine structured and unstructured semantic queries and to use large language models to orchestrate question answering over a knowledge graph.

Recently, Microsoft announced with a post their GraphRAG offering. This article provides a brief overview of their approach, how it compares to other Graph RAG varieties, what problems it can address and what it cannot.

Knowledge graphs (KGs) are a specific type of #data structure designed to represent entities and the connections between them. They move beyond simply storing… | 14 comments on LinkedIn

Combine text extraction, network analysis, and LLM prompting and summarization for improved RAG accuracy

The Programmable Neuro-Symbolic AGI that lets you program its behavior using Graph-based Prompt Programming: for people who want AI to behave as expected - SynaLinks/HybridAGI

Ask your (research) question against 76 Million scientific articles: https://ask.orkg.org Open Research Knowledge Graph (ORKG) ASK (Assistant for Scientific…

Copyright 2024 Kurt Cagle / The Cagle Report Recently, I've spent a lot of time talking with clients about the need for knowledge graphs in LLMs, why they are not "graphlike," and why we may need to rethink the whole transformer model. I think this topic is worth exploring, and I'd like to have a po

Predicting the architecture of intelligent organizations

Our paper "Are Large Language Models a Good Replacement of Taxonomies?" was just accepted to VLDB'2024! This finished our last stroke of study on how knowledgeable LLMs are and confirmed our recommendation for the next generation of KGs. How knowledgeable are LLMs? 1.

Can LLMs understand graphs? The results might surprise you. Graphs are everywhere, from social networks to biological pathways. As AI systems become more…

What Could Go Wrong When We Start Using LLMs to Organize Knowledge? 7 Pain Points of GraphRAG Alright, tech enthusiasts and AI aficionados. We need to discuss… | 43 comments on LinkedIn