A chatbot for financial services can be built using Amazon SageMaker JumpStart, Llama 2, and Amazon OpenSearch Serverless with Vector Engine. SageMaker JumpStart offers customization capabilities, data security, regulatory controls, and a variety of ML models. RAG is a framework that improves the quality of text generation by
Table of contents
Advantages of using SageMaker JumpStartLimitations of large language modelsRetrieval Augmented GenerationSolution overviewPrerequisitesDeploy the ML models using SageMaker JumpStartChunk data and create a document embeddings objectQuestion and answering over documentsCleanupConclusionSort: