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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.
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...
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...
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...
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...
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...
Structure-guided NER optimization for enterprise GraphRAG systems The post Proxy-Pointer RAG: Eliminating Wasteful Entity & Relations Extraction in Knowledge Graphs appeared fi...
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...
Юридический домен требует понимания многочисленных связей между сущностями, рассеянными по множеству документов. Поэтому кажется, что область знаний, организованная таким образом,...
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 ...
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...
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...
You join a new team. The codebase has 200,000 lines of code, no docs worth reading, and the one engineer who knew everything just left. Where do you start? That exact problem is w...
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...
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...
Юридический домен требует понимания многочисленных связей между сущностями, рассеянными по множеству документов. Поэтому кажется, что область знаний, организованная таким образом,...
Сравниваем нативный Property Graph в Spanner с рекурсивными CTE в AlloyDB — и объясняем, почему для персональной wiki второй подход оказался практичнее Читать далее
In this post, we explore how Graph-based Retrieval Augmented Generation (GraphRAG) is transforming scientific research by combining graph databases with generative AI. With this ap...
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...
Use coding agents to power your knowledge base The post How to Build a Powerful LLM Knowledge Base appeared first on Towards Data Science.
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...
Exposing the Limitations of Google Knowledge Graph: Why AI Can Still Struggle to Recognize Human IdentityContinue reading on Medium »
SciGraph показывает, почему GraphRAG для научных статей — это не только про графы и LLM, но и про честные метрики. В статье — разбор системы, которая связывает PDF, авторов, методы...
Google’s introduction of the Open Knowledge Format (OKF) addresses persistent challenges in managing large language model (LLM) wikis. Inspired by Andrej Karpathy’s concept of meta...
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