Exploring Graph Databases
Kirk discusses the potential of graph databases, emphasizing their ability to reveal relationships that traditional relational databases might miss. He highlights the importance of metadata in enhancing data retrieval, particularly in geospatial contexts, and expresses optimism about the evolving landscape of graph-based data exploration. The conversation also touches on the integration of various data types and the innovative queries that can emerge from this enriched data environment.In this clip
From this podcast
The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
GraphRAG: Knowledge Graphs for AI Applications with Kirk Marple - 681
Related Questions
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data as discussed in the episode Vectoring in on Pinecone with Cohere co-founder Nick Frosst on building LLM apps for business?
Can you help me with suggesting particular paths for building and populating a Knowledge Graph using LLMs that includes time-dependent data, such as retrieving the "current" President of the USA and previous presidents? I'm considering using this Knowledge Graph for Retrieval Augmented Generation (RAG) to help with business goals or clever User Interfaces (UIs).
Do I get it right that a Retrieval Augmented Generation (RAG) system can retrieve data in addition to its training data as discussed in the episode with Cohere co-founder Nick Frosst on building LLM apps for business?