Graph databases and social graph Graph databases are the most scalable, high-performance way to query and store highly interconnected data. They help improve intelligence, predictive analytics, social network analysis, and decision and process management – which all involve highly connected data with lots of relationships. A relevant use case for graph databases is the social graph. more

In the era of big data, large language models (LLMs) are becoming increasingly important for tasks like question answering, document analysis, and chatbot development. However, traditional LLMs can often struggle with factual accuracy, reasoning, and handling complex information. more

In a world where visuals dominate, what if mythological storytelling could speak back—literally? This talk explores how I reimagined the Mahabharata using a blend of knowledge graphs and Large Language Models (LLMs), layered with real-time Hindi voice responses. Instead of static text or pre-recorded audio, users can converse with the epic: ask questions about characters, events, or timelines, an… more

“Demystifying the Mahabharata with GraphRAG” takes you on a journey where ancient wisdom meets modern AI innovation. This session delves into how GraphRAG — an emerging approach that fuses knowledge graphs with Large Language Models (LLMs) — can be used to decode the vast narrative universe of the Mahabharata. By structuring the relationships between characters, events, and moral dilemmas in grap… more