Content related to How a Knowledge Graph Supports AI: Technical Considerations
What is a Large Language Model (LLM)?
In late November of 2022, artificial intelligence (AI) research and development company OpenAI released ChatGPT, an AI chatbot powered by a Large Language Model (LLM). In the following year, the world witnessed a meteoric rise in the usage of … Continue reading
How to Prepare Content for AI
Artificial Intelligence (AI) enables organizations to leverage and manage their content in exciting new ways, from chatbots and content summarization to auto-tagging and personalization. Most organizations have a copious amount of content and are looking to use AI to improve … Continue reading
Graph Machine Learning Recommender POC for Public Safety Agency
The Challenge A government agency responsible for regulating and enforcing occupational safety sought to build a content recommender proof-of-concept (POC) that leverages semantic technologies to model the relevant workplace safety domains. The agency aimed to optimize project planning and construction … Continue reading
The Top 5 Reasons for a Semantic Layer
Implementing Semantic Layers has become a critical strategic plan for many of our most advanced data clients. A Semantic Layer connects all organizational knowledge assets, including content items (files, videos, media, etc.) via a well defined and standardized semantic framework. … Continue reading
Measuring the Value of your Semantic Layer: KPIs for Taxonomies, Ontologies, and Knowledge Graphs
Utilizing semantic applications in your business, such as an enterprise taxonomy, ontology, or knowledge graph, can increase efficiency, reduce cognitive load, and improve cohesion across the enterprise, among other benefits. While these benefits are extremely valuable they can be difficult … Continue reading
Generative AI-Assisted Taxonomy Development for a Global Investment Bank
The Challenge A multinational financial institution with a century-long legacy, celebrated for pioneering financial solutions and shaping the global economic landscape, relied on unstructured data for risk management. With a vast array of risks to consider, and a wealth of … Continue reading
What is a Semantic Layer? (Components and Enterprise Applications)
Over the last decade, many organizations went through expensive migrations – either moving data into a data lake, a data warehouse, a modern data stack, or to the cloud. Yet, the business problems that many are looking to solve through … Continue reading
Expert Analysis: Top 5 Considerations When Building a Modern Knowledge Portal
Knowledge Portals aggregate and present various types of content – including unstructured content, structured data, and connections to people and enterprise resources. This facilitates the creation of new knowledge and discovery of existing information. The following article highlights five key … Continue reading
The Role of Ontologies with LLMs
In today’s world, the capabilities of artificial intelligence (AI) and large language models (LLMs) have generated widespread excitement. Recent advancements have made natural language use cases, like chatbots and semantic search, more feasible for organizations. However, many people don’t understand … Continue reading
Case Studies: Applications of Data Governance in the Enterprise
Thomas Mitrevski, Senior Data Management and Governance Consultant and Lulit Tesfaye, Partner and Vice President of Knowledge and Data Services presented “Case Studies: Applications of Data Governance in the Enterprise” on December 6th, 2023 at DGIQ in Washington D.C. In … Continue reading