Copyright 2024 Kurt Cagle / The Cagle Report From one of my readers: Hi Kurt, have you written any article on how a knowledge graph differ from inventory built using graph. We are in constant struggle to differentiate knowledge graph from inventory apps? Questions like can inventory systems built us
**!!!! Great Talk with Bradley Rees NVIDIA RAPIDS cuGraph lead at KDD 24 Conference !!** We had an excellent discussion about the cuGraph user experience in…
Google's Semantic Search: Going to the Dogs? | LinkedIn
Google is the undisputed leader in web search – technically a monopoly in fact. The coverage of web properties (good and bad) is vast – about 400 billion documents – so in quantitative terms it's really very good.
Fact Finder -- Enhancing Domain Expertise of Large Language Models...
Recent advancements in Large Language Models (LLMs) have showcased their proficiency in answering natural language queries. However, their effectiveness is hindered by limited domain-specific...
Introducing SEOntology: A Universal Framework for SEO Data | LinkedIn
We're excited to announce the first release of SEOntology, an open-source framework developed to unify and standardize SEO data across the industry. SEOntology aims to address one of the pressing challenges in modern SEO: data fragmentation.
Common Elements of Data Quality in the Age of AI - DQLabs
[vc_row][vc_column width=”1/2″ css=”.vc_custom_1724344160150{padding-right: 70px !important;}”][vc_column_text]In the era of AI, data quality has become a critical factor for successful implementations. A study by MIT Sloan Management Review found that 85% of executives believe AI will offer significant competitive advantages, yet only 39% have an AI strategy in place. This gap highlights the importance of foundational elements […]
We-KNOW RAG 𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 to 𝗥𝗔𝗚 leverages a 𝗴𝗿𝗮𝗽𝗵-𝗯𝗮𝘀𝗲𝗱 method
Passing this along (because I think it shows how this field is evolving) but also to make a point. RAG is only half the story. Use RDF2Vec or a similar encoder…
𝗮𝗴𝗲𝗻𝘁𝗶𝗰 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 to 𝗥𝗔𝗚 leverages a 𝗴𝗿𝗮𝗽𝗵-𝗯𝗮𝘀𝗲𝗱 method
Triple your knowledge graph speed with RDF linked data and openCypher using Amazon Neptune Analytics | Amazon Web Services
There are numerous publicly available Resource Description Framework (RDF) datasets that cover a wide range of fields, including geography, life sciences, cultural heritage, and government data. Many of these public datasets can be linked together by loading them into an RDF-compatible database. In this post, we demonstrate how to build knowledge graphs with RDF linked data and openCypher using Amazon Neptune Analytics.
Recently, Retrieval-Augmented Generation (RAG) has achieved remarkable success in addressing the challenges of Large Language Models (LLMs) without necessitating retraining. By referencing an...
Here are the slides from our tutorial today at #kdd2024! Notebooks are available at the tutorial website: https://lnkd.in/ejTrYtfe | 16 comments on LinkedIn
Now that W3C RDF Star will put Semantic Graphs on-par with Labelled Property Graphs, it is time to address the final barrier, and that is the developer…
Recent advancements in LLMs have sparked excitement about their potential to organize and utilize Knowledge Graphs. Microsoft's GraphRAG is a good starting… | 10 comments on LinkedIn
Taxonomies, Ontologies, and Semantics in Tech Comm’s World of AI
Technical communicators: understand these AI skills to form your new portfolio: terminology management, taxonomy, ontology, semantic layer, knowledge graph and knowledge management in general
Microsoft's GraphRAG is costly to implement due to high computational expenses
Microsoft's GraphRAG architecture surpasses traditional #RAG systems by integrating knowledge graphs with vector stores. By structuring information… | 24 comments on LinkedIn
Microsoft's GraphRAG is costly to implement due to high computational expenses