The world of graph technology is vast and evolving. We're here to help you make sense of the key trends and players.

Calling all data scientists, developers, and managers! 📢 Looking to level up your team's knowledge of graph technology? We're excited to share the recorded 2-part training series, "Graph Tech Demystified" with the amazing Paco Nathan. This is your chance to get up to speed on graph fundamentals: In Part 1: Intro to Graph Technologies, you'll learn: - Core concepts in graph tech. - Common pitfalls and what graph technology won't solve. - Focus of graph analytics and measuring quality. 🎥 Recording https://lnkd.in/gCtCCZH5 📖 Slides https://lnkd.in/gbCnUjQN In Part 2: Advanced Topics in Graph Technologies, we explore: - Sophisticated graph patterns like motifs and probabilistic subgraphs. - Intersection of Graph Neural Networks (GNNs) and Reinforcement Learning. - Multi-agent systems and Graph RAG. 🎥 Recording https://lnkd.in/g_5B8nNC 📖 Slides https://lnkd.in/g6iMbJ_Z Insider tip: The resources alone are enough to keep you busy far longer the time it takes to watch the training!

Guest Author: André Vermeij, Founder of Kenedict Innovation Analytics & Developer of...

This blog post provides a hands-on guide for AI engineers and developers on how to build an initial KYC agent prototype with the OpenAI Agents SDK. We'll explore how to equip our agent with a suite of tools (including MCP Server tools) to uncover and investigate potential fraud patterns.

In large Knowledge Graphs (KGs), measuring the importance of each entity is essential for improving search, navigation, and reasoning…

6 years after, where are we? Interested by your feedback concerning the evolution of the graph technologies landscape and about what the current landscape is. https://lnkd.in/eEPkExH | 25 comments on LinkedIn

One of the few things I love as much as Knowledge Graphs (KGs) is basketball (and LEGO bricks, but that’s another story)! So it made…

Learn about different types of graphs and their applications in data management and AI, as well as common misconceptions, in this article by Lulit Tesfaye.

Ashley Faith hosted Amy Hodler and me on a recent episode about “2025 Predictions” — here are notes I prepared, to review in 2026…

Graph is increasingly driving the Agentic space, which I see as being a very good sign. Recently, a programmer asked why graphs would be superior to using…

A curated list of resources for graph-related topics, including graph databases, analytics and science - graphgeeks-lab/awesome-graph-universe

Intelligence analysis utilizing Esri’s analytical, graph, and motion imagery capabilities, all within the same workflow.

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…

A semantic layer for end-to-end, intelligent automation

Graph-based data is ubiquitous in enterprise, across the industry verticals, and increasingly needed for machine learning use cases…

Understanding data points through the context of their relationships

Siren promises the benefits of knowledge graphs, without the hassle of reinventing your existing data management and infrastructure

State of the art in analytics and AI can help address some of the most pressing issues in scientific research. Here is how top scientists are using them to facilitate coronavirus research.

A sui generis, multi-model open source database, designed from the ground up to be distributed. ArangoDB keeps up with the times and uses graph, and machine learning, as the entry points for its offering.

Knowledge graphs are probably the best technology we have for data integration. But what about application integration? Knowledge graphs can help there, too, argues EnterpriseWeb.

In the new knowledge-based digital world, encoding and making use of business and operational knowledge is the key to making progress and staying competitive. Here's a shortlist of technologies and processes that can support this transition, and what they are about.

Graphs are everywhere. That has been the motto of graph aficionados for years, and now the world seems to be waking up to this.

It can be hard to work out from Wikipedia if an Ontologist is a philosopher, a physicist or something completely different

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

vendors company,url,SPARQL,RDF-Star,Gremlin,Cypher,misc query,distrib,open source,parent,speaker,notes AgensGraph,a href="https://bitnine.net/agensgraph/"https://bitnine.net/agensgraph//a,Y,SQL,Bitnine AllegroGraph,a href="https://allegrograph.com/products/allegrograph/"https://allegrograp...

Graphs. Such a simple idea. Map a problem onto a graph then solve it by searching over the graph or by exploring the structure of the graph. What could be easier? Turns out, however, that working with graphs is a vast and complex field. Keeping up is challenging. To help keep up, you just need an editor who knows most people working with graphs, and have that editor gather nearly 70 researchers to summarize their work with graphs. The result is the book Massive Graph Analytics. — Timothy G. Mattson, Senior Principal Engineer, Intel Corp Expertise in massive-scale graph analytics is key for solving real-world grand challenges from healthcare to sustainability to detecting insider threats, cyber defense, and more. This book provides a comprehensive introduction to massive graph analytics, featuring contributions from thought leaders across academia, industry, and government. Massive Graph Analytics will be beneficial to students, researchers, and practitioners in academia, national

Knowledge graphs, the technology powering Google, Facebook and Apple, is now unlocking value across the financial sector. Knowledge graphs are transforming critical capabilities and enterprises are increasingly looking to the technology to enhance their tax strategy, perform compliance and improve customer service.