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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

By implementing this architectural pattern, organizations that use Google Workspace can empower their workforce to access groundbreaking AI solutions powered by Amazon Web Services (AWS) and make informed decisions without leaving their collaboration tool. This request contains the user’s message and relevant metadata.

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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

To address this consideration and enhance your use of batch inference, we’ve developed a scalable solution using AWS Lambda and Amazon DynamoDB. We walk you through our solution, detailing the core logic of the Lambda functions. Amazon S3 invokes the {stack_name}-create-batch-queue-{AWS-Region} Lambda function.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

Solution overview The following architecture diagram represents the high-level design of a solution proven effective in production environments for AWS Support Engineering. The following diagram illustrates an example architecture for ingesting data through an endpoint interfacing with a large corpus.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. The solution incorporates the following key features: Using a Retrieval Augmented Generation (RAG) architecture, the system generates a context-aware detailed assessment.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

We walk through the key components and services needed to build the end-to-end architecture, offering example code snippets and explanations for each critical element that help achieve the core functionality. You can invoke Lambda functions from over 200 AWS services and software-as-a-service (SaaS) applications.

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How BQA streamlines education quality reporting using Amazon Bedrock

AWS Machine Learning - AI

The collaboration between BQA and AWS was facilitated through the Cloud Innovation Center (CIC) program, a joint initiative by AWS, Tamkeen , and leading universities in Bahrain, including Bahrain Polytechnic and University of Bahrain. The following diagram illustrates the solution architecture.

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Extend large language models powered by Amazon SageMaker AI using Model Context Protocol

AWS Machine Learning - AI

We will deep dive into the MCP architecture later in this post. Using a client-server architecture (as illustrated in the following screenshot), MCP helps developers expose their data through lightweight MCP servers while building AI applications as MCP clients that connect to these servers.