Amazon Bedrock is a sophisticated and fully managed service provided by AWS, designed to facilitate the development and scaling of generative AI applications. Some key improvements have been launched at AWS Re:Invent this week. We’ll dive deeper into those later. First let’s look at the key elements that make up the bedrock of Bedrock.
Foundation Models (FMs): Bedrock offers access to a selection of high-performing foundation models from prominent AI companies, including AI21 Labs, Anthropic, Cohere, Stability AI, and Amazon. These models form the backbone of Bedrock, enabling developers to leverage advanced AI capabilities.
Customization and Continued Pre-training: A notable feature of Amazon Bedrock is the ability to customize foundation models. For instance, the service includes continued pre-training capabilities that allow users to train models like Amazon Titan Text Express and Amazon Titan Text Lite using their own unlabeled data. This customization takes place in a secure and managed environment, ensuring the integrity and privacy of the data used.
Knowledge Bases and Retrieval Augmented Generation (RAG): Amazon Bedrock has integrated fully managed Knowledge Bases, which securely connect foundation models to internal company data sources. This integration enhances the models’ ability to deliver context-specific and accurate responses through Retrieval Augmented Generation, thereby improving the relevance and precision of the AI’s output.
API Access and Scalability: Bedrock is designed with scalability in mind, allowing developers to build and expand their generative AI applications efficiently. The service provides API access to foundation models, streamlining the development process by abstracting away the complexities of managing underlying infrastructure. This feature is especially beneficial for developers seeking to integrate AI capabilities into their applications without delving into the intricacies of AI model management.
AWS Bedrock is a comprehensive and robust platform for developers looking to harness the power of generative AI. Its combination of high-quality foundation models, customization options, secure data integration, and easy scalability makes it a valuable tool for a wide range of AI applications.
The Reinvention of Bedrock
At the 2023 AWS re:Invent, Amazon introduced several new features for Bedrock, enhancing its capabilities in generative AI application development.
Guardrails for Amazon Bedrock: This feature enables the implementation of customized safeguards in line with specific use cases and responsible AI policies. It aims to promote safer interactions between users and generative AI applications, ensuring that the applications align with ethical and organizational guidelines.
Agents for Amazon Bedrock: With the introduction of Agents, Amazon Bedrock now offers improved control over the orchestration of multistep tasks and enhanced visibility into the reasoning process. This feature is designed to accelerate the development of generative AI applications by facilitating more complex and sophisticated task management.
Customization with Own Data: Amazon Bedrock now allows users to customize foundation models using their own data. This feature supports fine-tuning and continued pre-training, enabling the creation of applications that are tailored to specific domains, organizations, or use cases. This customization is executed privately and securely within the Bedrock environment.
Fully Managed RAG Experience in Knowledge Bases: The Knowledge Bases feature in Amazon Bedrock has been updated to deliver a fully managed Retrieval Augmented Generation (RAG) experience. This enhancement allows for a secure connection of foundation models to company data, thereby improving the relevance and context of generative AI responses.
These updates to Amazon Bedrock signify a substantial advancement in the development and customization of generative AI applications, providing users with more control, security, and flexibility.
Configuring and maximizing the potential of Bedrock can seem daunting. Foghorn is here to help. Reach out to discuss your use case and get seasoned advice from one of our experts.
