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Google's Knowledge Graph is powered by an extensive database of IDs. Here's how to find them for any person, place, or thing.
Ask your vector RAG pipeline "what are the main themes in this corpus?" and watch it return three random chunks that share a keyword. Flat vector retrieval is built for "find me th...
Large language models (LLMs) are impressive — until they are not. If you ask one about your internal data, your product catalog, or your users' reviews, it will either hallucinate...
Retrieval-augmented generation (RAG) has become the de facto standard for grounding large language models (LLMs) in private data. The standard architecture — chunking documents, em...
In this AL TV Interview with NetDocuments’ CPO Dan Hauck we talk about agents, KM and knowledge graphs. The central point here is that to ...
Building a context layer between enterprise data stores and AI agents is bespoke work, with no standard service to automate or maintain the graphs over time. Amazon is making a dir...
Google's Open Knowledge Format turns your website's ideas into a linked graph agents can traverse. Here's what that means for how machines understand your site. The post Google’s O...
In this post, we show you how to build a semantic ontology that helps your AI assistants navigate enterprise data efficiently. You’ll learn how to structure a property graph store...
Юридический домен требует понимания многочисленных связей между сущностями, рассеянными по множеству документов. Поэтому кажется, что область знаний, организованная таким образом,...
As foundation models continue to improve, the lack of relevant context often limits what they can do, especially as they are used to build agentic systems. While these models can h...
In this tutorial, we will generate knowledge graphs from plain text, conversations, and multiple source documents using kg-gen. We start by setting up the required dependencies and...
This article is part 1 of a 4-part series on 'Engineering Closed-Loop Graph-RAG Systems.' Most teams don't have a knowledge graph at first. They just have a bunch of documents, a...
AI can infer relationships from content, but first-party knowledge is more accurate. Here's why organizations need to own that layer explicitly. The post The Integrity Graph: The M...
Юридический домен требует понимания многочисленных связей между сущностями, рассеянными по множеству документов. Поэтому кажется, что область знаний, организованная таким образом,...
A scalable semantic localization layer for entity and relationship reconciliation The post Proxy-Pointer RAG: Solving Entity and Relationship Sprawl in Large Knowledge Graphs appe...
Google Open Knowledge Format turns organizational knowledge into a shared format for AI agents, tools, and teams. The post Google Cloud Announces The Open Knowledge Format appeared...
As enterprises adopt agentic AI, they need to shift from reactive systems of intelligence to proactive systems of action to equip the agents they’re building with the context and p...
Keyword search struggles with natural language and exploratory questions. Daniel walked the DrupalSouth 2026 audience through how OpenSearch and Skpr enable semantic search that un...
KMWorld recently held a webinar with Fluid Topics and Guru who discussed why different knowledge domains require different approaches and solutions
Use coding agents to power your knowledge base The post How to Build a Powerful LLM Knowledge Base appeared first on Towards Data Science.
KMWorld recently held a webinar with Matt Garren at Guru who discussed how pairing AI-assisted maintenance with human oversight creates an AI source of truth
Я изучаю AEO/GEO (продвижение брендов в ответах нейросетей) и наткнулся на разбор про странную вещь: нейросети называют одни бренды и будто не замечают другие, причём качество прод...
Agentic AI is exposing a foundational gap in most enterprise data strategies: Data without meaning is unusable for autonomous systems. Agents don’t just retrieve data — they interp...
In the ever-evolving landscape of urban transportation, accurate predictions of passenger travel patterns have become a paramount concern. The ability to foresee the next station a...
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