One blocker to more widespread deployment of knowledge graphs in AI is the belief that they are inherently a discrete form of knowledge…

A few years ago we started the "RDF community" to create a vendor-neutral place to discuss RDF, Knowledge Graphs, Semantic Web and Linked Data. I've finally…

The Rise of Graph Jobs, The Disappearance of Graph Technology? Join me for this fun presentation at KGC on May 8, 2024, in NYC, where I delve into a "State of…

This new era of « Active MetaData Era» could have been named GO Era for « Graphs & Ontologies ». Active metadata refers to metadata that is dynamic and…

Scientific Data - An open source knowledge graph ecosystem for the life sciences

The W3C RDF-star WG is currently debating a design issue which may greatly affect our chances of having a better alignment between RDF graphs and Labeled… | 13 comments on LinkedIn

AI Answers Questions on Any Knowledge Graph - No Training Required ... Imagine being able to ask complex questions about any knowledge graph and get accurate…

Entity resolved knowledge graphs result from applying entity resolution technology to graph data, resulting in graphs with much more utility.

A straightforward introduction to integrating language models (LLMs) with knowledge graphs (KGs) for enhanced intelligence.

In response to my last blog, LLMs and Knowledge — the study continues, I got a lot of questions LinkedIn, which I decided to answer in…

A practical guide to constructing and retrieving information from knowledge graphs in RAG applications with Neo4j and LangChain

Learn more about what graph embeddings are and how they're used to accelerate real-time analytics. Find out about graph embedding algorithms and storage.

The next frontier of LLM applications: Structured Knowledge Representation

In this article we look at Research Graph as an information model , and an approach to connect and capture the connections between research outputs, researchers and research activities. We explore…

Unlocking the power of knowledge graphs in research catalogues

Harvesting the Power and Knowledge of Large Language Models

Large language models require your data in a graph; let me try to explain why. Behind the power of large language models is an architecture known as the… | 37 comments on LinkedIn

Exploring the Potential of AI-Powered Knowledge Graphs with MindGraph ... Have you ever wondered how we can harness the power of AI to create and explore…

Knowledge Discovery and Generation: Synergizing Knowledge Graphs and Large Language Models 💡 In today’s era of information explosion, the volume of… | 14 comments on LinkedIn

Unlocking the Secrets of Scientific Discovery with AI and Knowledge Graphs ... Have you ever wondered how AI could revolutionize the way we conduct scientific… | 17 comments on LinkedIn

Watch this insightful talk on Entity Resolved Knowledge Graphs, and learn how entity resolution can add insight and utility to graph data.

Using your sample questions as the basis for Knowledge Graph creation, simplifying the creation of structured and deterministic knowledge.

RDF data model, its virtues, vices, and applications.

Linked Data in Production: Moving Beyond Ontologies - Download as a PDF or view online for free

When Large Language Models Meet Knowledge Graphs

Graph Neural Prompting with Large Language Models

Here is my third blog entry of 2024. In this blog, I consider the slow pace of taxonomy and ontology building vs the rapid pace of machine learning models… | 24 comments on LinkedIn

Long-Context models, such as Google Gemini Pro 1.5 or Large World Model, are probably changing the way we think about RAG (retrieval-augmented generation)… | 12 comments on LinkedIn

Wow, in Jensen Huang (CEO) his keynote at NVIDIA #GTC24, he calls out three sources of data to integrate with LLMs: 1) vector databases, 2) ERP / CRM and 3)…

I want to thank Jay (JieBing) Yu, PhD for his hard work in creating a Mini-Me (https://lnkd.in/g6TR543j), a virtual assistant built on his fantastic LLM work…