Generative AI and foundation models (FMs) are offering new possibilities for content generation, particularly in areas such as answering questions and summarizing documents. Companies such as Amazon, Anthropic, AI21 Labs, Cohere, and Meta supply these models. Amazon Bedrock, a fully managed service, streamlines the process of building and scaling generative AI applications. It provides access to high-performing FMs from these leading AI providers through a single API, and allows users to customize the FMs with their own data using methods such as fine-tuning and Retrieval Augmented Generation (RAG).
RAG enhances the content generation process by using retrieval techniques, allowing a Natural Language Generation model to produce more informed and contextually unique responses. Implementing RAG requires several key components: foundation models, a vector store database for similarity search, a retriever module, and an embedder model to encode source documents into vector representations. Specific AWS services, such as Amazon OpenSearch Service and Amazon RDS for PostgreSQL, can support these requirements.
Amazon offers end-to-end RAG workflow support through Knowledge Bases for Amazon Bedrock. This allows organizations to augment the generative AI responses with their own company’s private data sources. For organizations to equip their FMs with up-to-date information, RAG can fetch data from company sources and augment the prompts. Thereby, providing more relevant and accurate responses.
A single interface conversational chatbot solution is described, using Amazon Bedrock to offer choice and flexibility in user experience. This chatbot uses RAG to offer diverse conversational abilities, and a single user interface gives users the ability to choose from different large language models based on their data input format. The full code for this solution is available on GitHub, along with an AWS CloudFormation template.
The continued advancement in generative AI technology presents numerous possibilities for businesses in terms of creating more personalized, automated, and efficient responses. Given the variety of vendors supplying FMs and the ability to customize these models using private data, businesses are increasingly equipped to take advantage of artificial intelligence technology.
