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The spaghetti has been cooking, and while there's still some work to do, I'm pleased to be able to share the 2024 DBMS Spaghetti chart (covering data from… | 29 comments on LinkedIn

🗣 TALK ALERT for GraphGeeks 🈂 Decoding Kanji Relationships 📅  April 30th 🕘  09:00 am PT | 18:00 CEST Registration 👉  https://lnkd.in/gkwGCczF  👈 Join…

The distinction between types and individuals is key to most conceptual modeling techniques and knowledge representation languages. Despite that, there are a number of situations in which modelers navigate this distinction inadequately, leading to pr

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…

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