In the world of AI, it’s clearly RAG time. The surge to put Retrieval Augmented Generation (RAG)-elevated injection into new and existing AI models is fast apace. Many software engineers are understandably keen to draw on RAG’s ability to externally validate large language model (LLM) data and align GenAI engines towards internal proprietary data chains where needed.
Read more: https://techstrong.ai/generative-ai/neo4j-charts-simpler-route-to-rag-with-graphrag-ecosystem-tools/
Keywords: Generative AI GraphRAG Large Language Model Thought Leadership