The problem: Generative AI Large Language Models (LLMs) can only answer questions or complete tasks based on what they been trained on - unless they’re given access to external knowledge, like your ...

Wanted: Chief Disinformation Officer to pollute company knowledge graphs Researchers affiliated with universities in China and Singapore have devised a technique to make stolen knowledge graph data ...

Daniel D. Gutierrez, Editor-in-Chief & Resident Data Scientist, insideAI News, is a practicing data scientist who’s been working with data long before the field came in vogue. He is especially excited ...

Retrieval-augmented generation breaks at scale because organizations treat it like an LLM feature rather than a platform ...

RAG is an approach that combines Gen AI LLMs with information retrieval techniques. Essentially, RAG allows LLMs to access external knowledge stored in databases, documents, and other information ...

Through natural language queries and graph-based RAG, TigerGraph CoPilot addresses the complex challenges of data analysis and the serious shortcomings of LLMs for business applications. Data has the ...

Knowledge graph startup Diffbot Technologies Corp., which maintains one of the largest online knowledge indexes, is looking to tackle the problem of hallucinations in artificial intelligence chatbots ...

While Large Language Models (LLMs) like LLama 2 have shown remarkable prowess in understanding and generating text, they have a critical limitation: They can only answer questions based on single ...

The figure depicts the four-step，Graph-based Retrieval - Augmented Generation (RAG) process for the RSA - KG system, which aims to integrate multimodal data for RSA diagnosis and treatment. Recurrent ...