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Introducing guardrails in Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Knowledge Bases for Amazon Bedrock is a fully managed capability that helps you securely connect foundation models (FMs) in Amazon Bedrock to your company data using Retrieval Augmented Generation (RAG). In the following sections, we demonstrate how to create a knowledge base with guardrails.

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Build a self-service digital assistant using Amazon Lex and Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Generative artificial intelligence (AI)-powered chatbots play a crucial role in delivering human-like interactions by providing responses from a knowledge base without the involvement of live agents. You can simply connect QnAIntent to company knowledge sources and the bot can immediately handle questions using the allowed content.

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Use RAG for drug discovery with Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

Knowledge Bases for Amazon Bedrock allows you to build performant and customized Retrieval Augmented Generation (RAG) applications on top of AWS and third-party vector stores using both AWS and third-party models. If you want more control, Knowledge Bases lets you control the chunking strategy through a set of preconfigured options.

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Knowledge Bases for Amazon Bedrock now supports hybrid search

AWS Machine Learning - AI

At AWS re:Invent 2023, we announced the general availability of Knowledge Bases for Amazon Bedrock. With a knowledge base, you can securely connect foundation models (FMs) in Amazon Bedrock to your company data for fully managed Retrieval Augmented Generation (RAG).

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Build an end-to-end RAG solution using Knowledge Bases for Amazon Bedrock and the AWS CDK

AWS Machine Learning - AI

RAG models retrieve relevant information from a large corpus of text and then use a generative language model to synthesize an answer based on the retrieved information. Solution overview The solution provides an automated end-to-end deployment of a RAG workflow using Knowledge Bases for Amazon Bedrock.

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Leveraging Standardization and Automation to Facilitate DevOps Testing in Multi-Code Environments

CIO

To remain resilient to change and deliver innovative experiences and offerings fast, organizations have introduced DevOps testing into their infrastructures. However, introducing DevOps to mainframe infrastructure can be nearly impossible for companies that do not adequately standardize and automate testing processes before implementation.

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Streamline generative AI development in Amazon Bedrock with Prompt Management and Prompt Flows (preview)

AWS Machine Learning - AI

These features are designed to accelerate the development, testing, and deployment of generative artificial intelligence (AI) applications, enabling developers and business users to create more efficient and effective solutions that are easier to maintain.