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

AWS Machine Learning - AI

While organizations continue to discover the powerful applications of generative AI , adoption is often slowed down by team silos and bespoke workflows. It also uses a number of other AWS services such as Amazon API Gateway , AWS Lambda , and Amazon SageMaker. They include features such as guardrails, red teaming, and model evaluation.

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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

Amazon SageMaker Ground Truth enables RLHF by allowing teams to integrate detailed human feedback directly into model training. 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

This allows teams to focus more on implementing improvements and optimizing AWS infrastructure. Depth of insight Advanced analysis can identify subtle patterns and potential issues that might be missed in manual reviews, providing deeper insights into architectural strengths and weaknesses.

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

AWS Machine Learning - AI

To address these challenges, we introduce Amazon Bedrock IDE , an integrated environment for developing and customizing generative AI applications. This approach enables sales, marketing, product, and supply chain teams to make data-driven decisions efficiently, regardless of their technical expertise. Choose Create project.

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Techniques and approaches for monitoring large language models on AWS

AWS Machine Learning - AI

Our proposed architecture provides a scalable and customizable solution for online LLM monitoring, enabling teams to tailor your monitoring solution to your specific use cases and requirements. The file saved on Amazon S3 creates an event that triggers a Lambda function. The function invokes the modules.

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How Mixbook used generative AI to offer personalized photo book experiences

AWS Machine Learning - AI

The raw photos are stored in Amazon Simple Storage Service (Amazon S3). Aurora MySQL serves as the primary relational data storage solution for tracking and recording media file upload sessions and their accompanying metadata. S3, in turn, provides efficient, scalable, and secure storage for the media file objects themselves.

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Asure’s approach to enhancing their call center experience using generative AI and Amazon Q in Quicksight

AWS Machine Learning - AI

Asure anticipated that generative AI could aid contact center leaders to understand their teams support performance, identify gaps and pain points in their products, and recognize the most effective strategies for training customer support representatives using call transcripts.