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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. In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process.

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Automate Amazon Bedrock batch inference: Building a scalable and efficient pipeline

AWS Machine Learning - AI

Refer to Supported Regions and models for batch inference for current supporting AWS Regions and models. 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.

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Security is dead: Long live risk management

CIO

Unfortunately, many organizations still approach information security this way waiting until development is nearly complete before conducting security reviews, penetration tests, and compliance checks. This means creating environments that enable secure development while ensuring system integrity and regulatory compliance.

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AI dominates Gartner’s 2025 predictions

CIO

“AI deployment will also allow for enhanced productivity and increased span of control by automating and scheduling tasks, reporting and performance monitoring for the remaining workforce which allows remaining managers to focus on more strategic, scalable and value-added activities.”

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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

Companies of all sizes face mounting pressure to operate efficiently as they manage growing volumes of data, systems, and customer interactions. The chat agent bridges complex information systems and user-friendly communication. Update the due date for a JIRA ticket. Review and choose Create project to confirm.

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Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval

AWS Machine Learning - AI

Ground truth data in AI refers to data that is known to be factual, representing the expected use case outcome for the system being modeled. By providing an expected outcome to measure against, ground truth data unlocks the ability to deterministically evaluate system quality.

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How GoDaddy built a category generation system at scale with batch inference for Amazon Bedrock

AWS Machine Learning - AI

In this collaboration, the Generative AI Innovation Center team created an accurate and cost-efficient generative AIbased solution using batch inference in Amazon Bedrock , helping GoDaddy improve their existing product categorization system. For detailed information, refer to the Security Best Practices section of this post.