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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…

See how TigerGraph has integrated their massively parallel processing graph database and analytics platform with NVIDIA cuGraph to deliver 100x performance

Large-scale graph neural network (GNN) training presents formidable challenges, particularly concerning the scale and complexity of graph data. These challenges extend beyond the typical concerns of…

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

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Are you tired of manually tracing package vulnerabilities across applications? The #AmazonNeptune team has a solution! As part of the newest release of the…

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.

𝐔𝐧𝐥𝐞𝐚𝐬𝐡𝐢𝐧𝐠 𝐭𝐡𝐞 𝐏𝐨𝐰𝐞𝐫 𝐨𝐟 𝐆𝐫𝐚𝐩𝐡 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬: 𝟐𝟓 𝐓𝐨𝐩 𝐏𝐲𝐭𝐡𝐨𝐧 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬, 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬, 𝐓𝐲𝐩𝐞𝐬 𝐚𝐧𝐝… | 27 comments on LinkedIn

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

Code for all my videos: https://github.com/sponsors/adumb-codes/Twitter: https://twitter.com/adumb_codesA deep dive into the network of Wikipedia and some of...

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…

🔍 How can we design neural networks that take neural network parameters as input? This fundamental question arises in applications as diverse as generating…

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

Reflects company’s strong business momentum and rising AI demand for vector and graph databases

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

How to create synthetic datasets to improve graph-based anomaly detection models? Amazon researchers developed a new method for synthesizing training data for…