Fanghua Yu, Field Engineer, Neo4j Apr 25 11mins read
What LLM & Graph May Bring to the Future of Knowledge GraphsNight light at Federation Square in Melbourne, photo by AuthorAbstractIn the last several decades, when people consider building a knowledge-related solution, they tend to look into two distinct directions based… Read more →
Alex Gilmore, Consulting Engineer, Neo4j Apr 09 6mins read
Learn when to use graph data models, like parent-child, question-based, and topic-summary, for RAG applications powered by knowledge graphs. Read more →
Martin O’Hanlon, Technical Curriculum Developer, Neo4j Mar 30 2mins read
Learn how Neo4j can help you make sense of your unstructured data. Enroll in this new free course on GraphAcademy.There’s a new course on GraphAcademy: Introduction to Vector Indexes and Unstructured Data.This course teaches you to understand unstructured data using… Read more →
Tomaž Bratanič, Graph ML and GenAI Research, Neo4j Mar 28 10mins read
Learn how to retrieve information that spans across multiple documents through multi-hop question answering using knowledge graphs and LLMs. Read more →
Jennifer Reif, Developer Relations Engineer at Neo4j Mar 05 6mins read
Learn how to write graph retrieval queries that supplement or ground the LLM’s answer for your RAG application, using Python and Langchain. Read more →
Fanghua Yu, Field Engineer, Neo4j Jan 05 10mins read
Exploring the Shortcomings of Text Embedding Retrieval for LLM GenerationLoch Awe in Scotland, photo by author.AbstractExternal knowledge is the key to resolving the problems of LLMs such as hallucination and outdated knowledge, which can make LLMs generate more accurate and reliable… Read more →
As the final blog post of the Project NaLLM blog series, we reflect on the positive aspects and challenges encountered during this project. Read more →
NeoDash 2.3 is finally here! This update brings a fresh new look, improved performance for large dashboards, and exciting visualization features. Read more →
