Category: Graphs and Data Stores – Blog Posts

Halving Hallucinations: Jacek Cala on NIC-D’s Breakthrough Research into Graph-Based RAG and What It Means for Enterprise AI

Q1. Your team’s research shows that introducing graph-based tools into a RAG system can significantly increase the precision and recall of factual correctness, halve the number of hallucinated answers, and achieve the highest fine-grained...

On Ontologies and AI.  Q&A with Mattia Ferrini

Q1. You’ve spent two decades working on decision science systems, and ontologies play a critical role in both data management and AI. Can you discuss how you approach the generation and maintenance of ontologies...

On Graph Databases, Gen AI and the Cloud. Q&A with Jim Webber

Q1. The demand for graph databases is being regarded as essential infrastructure for AI systems. Why? Large Language Models (LLMs) are incredibly powerful for AI systems, but businesses have to balance the models’ creativity...

On Data Infrastructure at LinkedIn. Q&A with Kartik Paramasivam

This is all real.  Trillions of events are processed every day by stream processing applications at LinkedIn. Q1. You are VP – Data Infrastructure at LinkedIn. What are your responsibilities at LinkedIn? And what...