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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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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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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

However, this method presents trade-offs. However, it also presents some trade-offs. This architecture workflow includes the following steps: A user submits a question through a web or mobile application. The architecture of this system is illustrated in the following figure. 70B and 8B.

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WordFinder app: Harnessing generative AI on AWS for aphasia communication

AWS Machine Learning - AI

The following diagram illustrates the solution architecture on AWS. Amazon Rekognition analyzes the image, identifying objects present and returning labels with confidence scores. In this architecture, the frontend of the word finding app is hosted on Amplify.

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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.

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

AWS Machine Learning - AI

This post presents a solution where you can upload a recording of your meeting (a feature available in most modern digital communication services such as Amazon Chime ) to a centralized video insights and summarization engine. 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 architecture seamlessly integrates multiple AWS services with Amazon Bedrock, allowing for efficient data extraction and comparison. The following diagram illustrates the solution architecture. The text summarization Lambda function is invoked by this new queue containing the extracted text.

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