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Responsible AI in action: How Data Reply red teaming supports generative AI safety on AWS

AWS Machine Learning - AI

Red teaming , an adversarial exploit simulation of a system used to identify vulnerabilities that might be exploited by a bad actor, is a crucial component of this effort. Specifically, we discuss Data Replys red teaming solution, a comprehensive blueprint to enhance AI safety and responsible AI practices. What is red teaming?

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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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Boost team productivity with Amazon Q Business Insights

AWS Machine Learning - AI

The Unsuccessful query responses and Customer feedback metrics help pinpoint gaps in the knowledge base or areas where the system struggles to provide satisfactory answers. Organizations looking to quantify financial benefits can develop their own ROI calculators tailored to their specific needs.

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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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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. As a result, building such a solution is often a significant undertaking for IT teams. Responsible AI components promote the safe and responsible development of AI across tenants.

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How Cato Networks uses Amazon Bedrock to transform free text search into structured GraphQL queries

AWS Machine Learning - AI

With the Amazon Bedrock serverless experience, you can get started quickly, privately customize FMs with your own data, and quickly integrate and deploy them into your applications using AWS tools without having to manage the infrastructure. These filters need to be added and updated manually for each query.

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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.