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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...
Over 80% of enterprise data lives in unstructured form — PDFs, emails, reports, regulatory filings. Most of the time, such sources contain critical business information, yet they r...
Google doesn’t rank pages anymore. It ranks understanding. Behind every search result is the knowledge graph, a system that maps entities, relationships, and meaning across the web...
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 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...
GraphTalker advances Neuro-Symbolic AI with an agentic natural-language interface
Юридический домен требует понимания многочисленных связей между сущностями, рассеянными по множеству документов. Поэтому кажется, что область знаний, организованная таким образом,...
In a knowledge-driven economy, competitive advantage no longer lies in technology alone. It lies in the ability to capture, structure, and reuse knowledge across projects, teams, a...
Most organizations believe they have an AI problem when the real issue is their knowledge architecture. Microsoft Copilot deployments are exposing a deeper enterprise challenge: or...
RAG brings books to the exam. Knowledge Engineering teaches Agents to study. Memory architecture matters more than retrieval tuning. Everyone says the Agent era is about better...
Building a knowledge base for AI models isn’t a one-time task but an iterative process of refinement. The post How to Build an Efficient Knowledge Base for AI Models appeare...
AI vibe coders have yet another reason to thank Andrej Karpathy, the coiner of the term. The former Director of AI at Tesla and co-founder of OpenAI, now running his own independen...
Traditional data catalogs were built as manual inventories for technical users, focusing on table structures rather than the deep context that AI agents need. When agents lack busi...
The vector database category is undergoing a shift in response to the needs of agentic AI. The retrieval-augmented generation (RAG)-to-vector database pipeline doesn't cut it anymo...
Traditional RAG evaluation relies on human-annotated "standard answers," but in the GraphRAG era, this approach is losing its relevance. What Is a Gold Answer? A Gold...
Last week, a coding agent on a shared repo did something weirdly familiar: it opened the right files, read the right docs, and still made the wrong change. Not because the model w...
Nexus moves the reasoning upstream, from retrieval to knowledge compilation
Beyond the Chatbot: Why Financial Services Firms Need Causal Knowledge Graphs — Not Just Language
Understanding the modern knowledge lifecycle and protecting sensitive information were two approaches to ensuring trust explained at the KMWorld Europe conference.
LLM-поиск товаров: R&D применения технологий RAG и Knowledge Graph Search для продвинутого поиска товаров по сложным текстовым запросам. Как LLM и Knowledge Graph ищут товары
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...
Most enterprise systems are very good at answering one question: “What happened?” They are surprisingly bad at answering a more important one: “Why did it happen?”
In this tutorial, we explore how to build and query a local knowledge base with OpenKB using a free, open model via OpenRouter. We securely retrieve the API key with getpass, set u...
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