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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Although an individual LLM can be highly capable, it might not optimally address a wide range of use cases or meet diverse performance requirements. In contrast, more complex questions might require the application to summarize a lengthy dissertation by performing deeper analysis, comparison, and evaluation of the research results.

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

AWS Machine Learning - AI

Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message. After it’s authenticated, the request is forwarded to another Lambda function that contains our core application logic. in the GitHub repository you cloned to your local machine during deployment.

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

AWS Machine Learning - AI

This engine uses artificial intelligence (AI) and machine learning (ML) services and generative AI on AWS to extract transcripts, produce a summary, and provide a sentiment for the call. Amazon DynamoDB is a fully managed NoSQL database service that provides fast and predictable performance with seamless scalability.

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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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Build a multi-tenant generative AI environment for your enterprise on AWS

AWS Machine Learning - AI

It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. If it leads to better performance, your existing default prompt in the application is overridden with the new one. Refer to Perform AI prompt-chaining with Amazon Bedrock for more details.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

The agents also automatically call APIs to perform actions and access knowledge bases to provide additional information. The Lambda function runs the database query against the appropriate OpenSearch Service indexes, searching for exact matches or using fuzzy matching for partial information.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

Step Functions orchestrates AWS services like AWS Lambda and organization APIs like DataStore to ingest, process, and store data securely. The workflow includes the following steps: The Prepare Map Input Lambda function prepares the required input for the Map state. The fetched data is put into an S3 data store bucket for processing.