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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. This request contains the user’s message and relevant metadata.

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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning - AI

The solution also uses Amazon Cognito user pools and identity pools for managing authentication and authorization of users, Amazon API Gateway REST APIs, AWS Lambda functions, and an Amazon Simple Storage Service (Amazon S3) bucket. Authentication is performed against the Amazon Cognito user pool.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

The Amazon Q Business pre-built connectors like Amazon Simple Storage Service (Amazon S3), document retrievers, and upload capabilities streamlined data ingestion and processing, enabling the team to provide swift, accurate responses to both basic and advanced customer queries.

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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. It contains services used to onboard, manage, and operate the environment, for example, to onboard and off-board tenants, users, and models, assign quotas to different tenants, and authentication and authorization microservices.

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Enhance speech synthesis and video generation models with RLHF using audio and video segmentation in Amazon SageMaker

AWS Machine Learning - AI

Annotators can precisely mark and evaluate specific moments in audio or video content, helping models understand what makes content feel authentic to human viewers and listeners. At its core, Amazon Simple Storage Service (Amazon S3) serves as the secure storage for input files, manifest files, annotation outputs, and the web UI components.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

Scalable architecture Uses AWS services like AWS Lambda and Amazon Simple Queue Service (Amazon SQS) for efficient processing of multiple reviews. The workflow consists of the following steps: WAFR guidance documents are uploaded to a bucket in Amazon Simple Storage Service (Amazon S3).

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Access control for vector stores using metadata filtering with Knowledge Bases for Amazon Bedrock

AWS Machine Learning - AI

The access ID associated with their authentication when the chat is initiated can be passed as a filter. To ensure that end-users can only chat with their data, metadata filters on user access tokens—such as those obtained through an authentication service—can enable secure access to their information.