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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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How to Deploy Machine Learning Models on AWS Lambda Using Docker

Dzone - DevOps

Welcome to our tutorial on deploying a machine learning (ML) model on Amazon Web Services (AWS) Lambda using Docker. In this tutorial, we will walk you through the process of packaging an ML model as a Docker container and deploying it on AWS Lambda, a serverless computing service. So, let’s get started!

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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. You can invoke Lambda functions from over 200 AWS services and software-as-a-service (SaaS) applications.

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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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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

When API Gateway receives the request, it triggers an AWS Lambda The Lambda function sends the question to the classifier LLM to determine whether it is a history or math question. These embeddings are then saved as a reference index inside an in-memory FAISS vector store, which is deployed as a Lambda layer.

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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. Alternatively, you can use AWS Lambda and implement your own logic, or use open source tools such as fmeval. For example, in one common scenario with Cognito that accesses resources with API Gateway and Lambda with a user pool.

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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. An EventBridge rule invokes the Rectify & Notify Lambda function.