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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. This time efficiency translates to significant cost savings and optimized resource allocation in the review process.

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Create generative AI agents that interact with your companies’ systems in a few clicks using Amazon Bedrock in Amazon SageMaker Unified Studio

AWS Machine Learning - AI

Lets look at an example solution for implementing a customer management agent: An agentic chat can be built with Amazon Bedrock chat applications, and integrated with functions that can be quickly built with other AWS services such as AWS Lambda and Amazon API Gateway. Update the due date for a JIRA ticket.

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

AWS Machine Learning - AI

They have structured data such as sales transactions and revenue metrics stored in databases, alongside unstructured data such as customer reviews and marketing reports collected from various channels. This includes setting up Amazon API Gateway , AWS Lambda functions, and Amazon Athena to enable querying the structured sales data.

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Amazon Q Business simplifies integration of enterprise knowledge bases at scale

AWS Machine Learning - AI

The service users permissions are authenticated using IAM Identity Center, an AWS solution that connects workforce users to AWS managed applications like Amazon Q Business. It enables end-user authentication and streamlines access management. The Process Data Lambda function redacts sensitive data through Amazon Comprehend.

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

AWS Machine Learning - AI

In the first part of the series, we showed how AI administrators can build a generative AI software as a service (SaaS) gateway to provide access to foundation models (FMs) on Amazon Bedrock to different lines of business (LOBs). It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker.

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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. Pre-annotation and post-annotation AWS Lambda functions are optional components that can enhance the workflow. Give your job a name.

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CBRE and AWS perform natural language queries of structured data using Amazon Bedrock

AWS Machine Learning - AI

In this post, we describe how CBRE partnered with AWS Prototyping to develop a custom query environment allowing natural language query (NLQ) prompts by using Amazon Bedrock, AWS Lambda , Amazon Relational Database Service (Amazon RDS), and Amazon OpenSearch Service. A user sends a question (NLQ) as a JSON event.

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