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Automate emails for task management using Amazon Bedrock Agents, Amazon Bedrock Knowledge Bases, and Amazon Bedrock Guardrails

AWS Machine Learning - AI

Solution overview This section outlines the architecture designed for an email support system using generative AI. High Level System Design The solution consists of the following components: Email service – This component manages incoming and outgoing customer emails, serving as the primary interface for email communications.

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Medical content creation in the age of generative AI

AWS Machine Learning - AI

The solution has been designed using the following services: Amazon Elastic Container Service (ECS) : to deploy and manage our Streamlit UI. Amazon Lambda : to run the backend code, which encompasses the generative logic. In step 5, the lambda function triggers the Amazon Textract to parse and extract data from pdf documents.

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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

Ground truth data in AI refers to data that is known to be factual, representing the expected use case outcome for the system being modeled. By providing an expected outcome to measure against, ground truth data unlocks the ability to deterministically evaluate system quality. .

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Knowledge Bases for Amazon Bedrock now supports advanced parsing, chunking, and query reformulation giving greater control of accuracy in RAG based applications

AWS Machine Learning - AI

Now that you understand the concepts for semantic and hierarchical chunking, in case you want to have more flexibility, you can use a Lambda function for adding custom processing logic to chunks such as metadata processing or defining your custom logic for chunking. Make sure to create the Lambda layer for the specific open source framework.

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Create a generative AI-based application builder assistant using Amazon Bedrock Agents

AWS Machine Learning - AI

The agent can recommend software and architecture design best practices using the AWS Well-Architected Framework for the overall system design. Create and associate an action group with an API schema and a Lambda function. Recommend AWS best practices for system design with the AWS Well-Architected Framework guidelines.

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High-performance computing on AWS

Xebia

Integration with AWS Services: AWS Batch seamlessly integrates with other AWS services, such as Amazon S3, AWS Lambda, and Amazon DynamoDB. Each job references a job definition. It’s built on serverless services (API Gateway / Lambda) and provides the same functionality as the CLI tool pcluster.

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AWS empowers sales teams using generative AI solution built on Amazon Bedrock

AWS Machine Learning - AI

Consider the following system design and optimization techniques: Architectural considerations : Multi-stage prompting – Use initial prompts for data retrieval, followed by specific prompts for summary generation. For example, “Cross-reference generated figures with golden source business data.” Don’t make up any statistics.”