LLMs like Llama 2, Flan T5, and Bloom are essential for conversational AI use cases, but updating their knowledge requires retraining, which is time-consuming and expensive. However, with Retrieval Augmented Generation (RAG) using Amazon Sagemaker JumpStart and Pinecone vector database, LLMs can be deployed and kept up to date with relevant information to prevent AI Hallucination.
Conversational AI has evolved with generative AI and large language models, but lacks specialized knowledge for accurate answers. Retrieval Augmented Generation (RAG) connects generic models to internal knowledge bases, enabling domain-specific AI assistants. Amazon Kendra and OpenSearch Service offer mature vector search solutions for implementing RAG, but analytical reasoning questions requir...