Content related to Translating AI from Concept to Reality: Five Keys to Implementing AI for Knowledge, Content, and Data
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
Scaling Knowledge Graph Architectures with AI
Sara Nash and Urmi Majumder, Principal Consultants at Enterprise Knowledge, presented “Scaling Knowledge Graph Architectures with AI” on November 9th, 2023 at KM World in Washington D.C. In this presentation, Sara and Urmi defined a Knowledge Graph architecture and reviewed … Continue reading
The Journey of Data: From Raw Numbers to Actionable Insights with LLMs
Wondering how to take your data from its raw, decontextualized state and actually leverage it to produce actionable insights through the power of a Large Language Model (LLM)? The infographic below provides a visual overview of the 10 steps to … Continue reading
Secure LLM Powering Semantic Search for a Multinational Development Bank
The Challenge A multinational development bank with 48 member countries provides loans, grants, and technical assistance to its members for a wide range of development projects to reduce poverty and inequality in the region. The projects cover many topics, including … Continue reading
Semantic LLM Accelerator
With the right context, Large Language Models (LLMs) can be a powerful tool to accelerate enterprise digital transformations. Knowledge graphs provide that enterprise context, giving organizations the ability to understand and trust LLMs to take advantage of their powerful applications. … Continue reading
How a Knowledge Graph Supports AI: Technical Considerations
In 2023, ChatGPT’s explosive popularity made Artificial Intelligence (AI) language models a household name. In essence, these models are a key component of natural language processing (NLP), a field of AI, focused on enabling computers to understand and generate human … Continue reading
Five Ways to Demonstrate the Value of KM [In the Age of AI]
Knowledge management (KM) is steadily growing beyond its traditional role of providing the framework for sharing, using, and managing the knowledge and information of an organization: it now also serves as the foundation for advancements in Artificial Intelligence (AI). We … Continue reading
AI Beyond a Prototype
How to take an AI Project Beyond a Prototype Before going “all in,” we often advise our clients to first understand and quickly validate the value proposition for adopting advanced Artificial Intelligence (AI) and Machine learning (ML) solutions within their … Continue reading
Knowledge AI: Content Recommender and Chatbot Powered by Auto-Tagging and an Enterprise Knowledge Graph
The Challenge A global development bank needed a better way to disseminate information and in-house expertise to all of their staff to support the efficient completion of projects, while also providing employees with an intuitive knowledge sharing tool that is … Continue reading
Enterprise AI Readiness Assessment
Understand your organization’s priority areas before committing resources to mature your information and data management solutions. Enterprise Knowledge’s AI Readiness Assessment considers your organization’s business and technical ecosystem, and identifies specific priority and gap areas to help you make
targeted investments and gain tangible value from your data and information. Continue reading