Dear LinkedIn Fam, We need to have a conversation about something… Label Property Graphs (LPGs) are not ontological-based knowledge graphs because they lack…

Watch the first podcast of Paco Nathan's Graph Power Hour. This week's topic - Understanding Graph Rag: Enhancing LLM Applications Through Knowledge Graphs.

The Power of Graph-Native Intelligence for Agentic AI Systems How Entity Resolution, Knowledge Fusion, and Extension Frameworks Transform Enterprise AI ⚡…

I want to emphasize some things that most people don't seem to understand, specially managers in the AI space. 1. Knowledge Graph/Ontologies without a way to… | 14 comments on LinkedIn

Working with RDF on LLMs ================== The following is a quick reference list of things I've found when trying to work with the RDF stack on LLMs *… | 14 comments on LinkedIn

Unlocking universal reasoning across knowledge graphs. Knowledge graphs (KGs) are powerful tools for organizing and reasoning over vast amounts of… | 11 comments on LinkedIn

Making LLM Knowledge Graph building fast & dynamic: challenges, design decisions, and solutions

Image by David from Pixabay Mobile phones make it possible to secure and manage personal data on-device, which opens up a novel opportunity for both phone owners and device manufacturers: AI personalization via a data resource that stays on the phone. With the right design, personal knowledge graph on-device could provide contextualization while at the… Read More »Samsung and Apple’s knowledge-centric approaches to secure, personalized AI on phones

WhyHow’s Knowledge Graph Studio for modular agentic RAG systems.

My takeaways from the International Semantic Web Conference #iswc2024 Ioana keynote: Great example of data integration for journalism, highlighting the use of…

I'm coming around to the idea of ontologies. My experience with entity extraction with LLMs has been inconsistent at best. Even running the same request with… | 63 comments on LinkedIn

Beyond Vector Space : Knowledge Graphs and the New Frontier of Agentic System Accuracy ⛳ In the realm of agentic systems, a fundamental challenge emerges…

📑 I’ve been out of the grid the past few weeks to wrap up my upcoming book. 🚀 After 12 months of work that turned out to be more intense than I expected… | 20 comments on LinkedIn

A Python hands-on guide to understand the principles of generating new knowledge by following logical processes

15 November 2024 Bob Kasenchak, Factor As taxonomy consultants at Factor, we are frequently engaged to help our clients clean up and improve existing taxonomies; these have often developed ad hoc and, often, have not been constructed or managed by taxonomists. This is fine! Having controlled lists o

👉 Our paper "Understanding SPARQL Queries: Are We Already There?", explores the potential of Large Language Models (#LLMs) to generate natural-language…

Retrieval-augmented generation (RAG) helps AI systems provide more information to a large language model (LLM) when generating responses to user queries. A new method for conducting “global” queries can optimize the performance of global search in GraphRAG.

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Showcase of Data Transformation Process, Breakdown of 25 dev hours involved, Schemas used, Questions & Responses, and Graph created

Introduction

I spent the day in San Francisco yesterday attending part 2 of Neo4j's GenAI Graph Gathering. Along with the original session back in May, this was one of the…

Updating an ontology or graph data model has a lot of implications. How much change does the update cause, is the change breaking any up or downstream applic...

In Parallel’s Intelligent Operating Model uses AI to align strategy with execution, improving value creation and operational efficiency to meet today’s challenges.

AIs will only be safe for general use when they have and use goals and values that are identical to those of humans. In theory, the particular goals and values – very much like Asimov's original Laws of Robotics – could be legislated and enforced, so that we would all be safe from harm from AI.

It’s decision time for Galaxy users as Samsung responds to new iPhone threat.

A deep dive into LangChain’s implementation of graph construction with LLMs

While PuppyGraph is less than a year old, it is already witnessing success with several enterprises, including Coinbase, Clarivate, Dawn Capital and Prevelant AI.

Large Language Models (LLMs) are revolutionizing AI capabilities, but organizations face challenges in reducing inaccuracies and protecting valuable data. Knowledge Graphs offer a solution, helping improve LLM accuracy and safeguard organizational data assets. Learn how implementing Knowledge Graphs can address these critical issues and maintain competitiveness in the AI landscape.

A question-based extraction approach

We are launching a series of benchmarks to prove the value of GraphRAG for question & answering on complex documents. The process is simple, we ingest the…