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Introducing AWS MCP Servers for code assistants (Part 1)

AWS Machine Learning - AI

Were excited to announce the open source release of AWS MCP Servers for code assistants a suite of specialized Model Context Protocol (MCP) servers that bring Amazon Web Services (AWS) best practices directly to your development workflow. Developers need code assistants that understand the nuances of AWS services and best practices.

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Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion

AWS Machine Learning - AI

Through advanced data analytics, software, scientific research, and deep industry knowledge, Verisk helps build global resilience across individuals, communities, and businesses. Verisk has a governance council that reviews generative AI solutions to make sure that they meet Verisks standards of security, compliance, and data use.

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How BQA streamlines education quality reporting using Amazon Bedrock

AWS Machine Learning - AI

Manually reviewing and processing this information can be a challenging and time-consuming task, with a margin for potential errors. BQA reviews the performance of all education and training institutions, including schools, universities, and vocational institutes, thereby promoting the professional advancement of the nations human capital.

Education 112
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EBSCOlearning scales assessment generation for their online learning content with generative AI

AWS Machine Learning - AI

The goal was ambitious: to create an automated solution that could produce high-quality, multiple-choice questions at scale, while adhering to strict guidelines on bias, safety, relevance, style, tone, meaningfulness, clarity, and diversity, equity, and inclusion (DEI). Sonnet in Amazon Bedrock. Sonnet model in Amazon Bedrock.

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What is a Workflow?

xmatters

In software, workflows can exist within or between multiple tools, known as a DevOps toolchain. Discover how xMatters Flow Designer facilitates the creation of automated, no-code workflows that seamlessly integrate with other tools. These workflows are commonly used in software development to keep complex, multi-step projects on track.

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

AWS Machine Learning - AI

By following these guidelines, data teams can implement high fidelity ground truth generation for question-answering use case evaluation with FMEval. There are three user inputs to the step function: A custom name for the ground truth dataset The input Amazon S3 prefix for the source data The percentage to sample for review.

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Model customization, RAG, or both: A case study with Amazon Nova

AWS Machine Learning - AI

In this post, we seek to address this growing need by offering clear, actionable guidelines and best practices on when to use each approach, helping you make informed decisions that align with your unique requirements and objectives. On the Review and create page, review the settings and choose Create Knowledge Base.