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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

Traditionally, building frontend and backend applications has required knowledge of web development frameworks and infrastructure management, which can be daunting for those with expertise primarily in data science and machine learning. For more information on how to manage model access, see Access Amazon Bedrock foundation models.

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Authentication in Serverless Apps—What Are the Options?

DevOps.com

Serverless applications are growing in popularity among DevOps engineers. However, serverless applications present unique security challenges, one of them being authentication. However, serverless applications present unique security challenges, one of them being authentication.

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

AWS Machine Learning - AI

The workflow includes the following steps: The process begins when a user sends a message through Google Chat, either in a direct message or in a chat space where the application is installed. Before processing the request, a Lambda authorizer function associated with the API Gateway authenticates the incoming message.

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Faultless with serverless: Cloud best practices for optimized returns

CIO

As enterprises increasingly embrace serverless computing to build event-driven, scalable applications, the need for robust architectural patterns and operational best practices has become paramount. Likewise, a social media platform could have separate functions to handle user authentication, content moderation, and push notifications.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Building generative AI applications presents significant challenges for organizations: they require specialized ML expertise, complex infrastructure management, and careful orchestration of multiple services. Building a generative AI application SageMaker Unified Studio offers tools to discover and build with generative AI.

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Build a reverse image search engine with Amazon Titan Multimodal Embeddings in Amazon Bedrock and AWS managed services

AWS Machine Learning - AI

In this post, you will learn how to extract key objects from image queries using Amazon Rekognition and build a reverse image search engine using Amazon Titan Multimodal Embeddings from Amazon Bedrock in combination with Amazon OpenSearch Serverless Service. An Amazon OpenSearch Serverless collection.

AWS 115
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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

Consistency and enhanced accuracy The approach provides a consistent application of AWS Well-Architected principles across reviews, reducing human bias and oversight. Using Amazon Bedrock Knowledge Base, the sample solution ingests these documents and generates embeddings, which are then stored and indexed in Amazon OpenSearch Serverless.