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Principal Financial Group uses QnABot on AWS and Amazon Q Business to enhance workforce productivity with generative AI

AWS Machine Learning - AI

With the QnABot on AWS (QnABot), integrated with Microsoft Azure Entra ID access controls, Principal launched an intelligent self-service solution rooted in generative AI. This data includes manuals, communications, documents, and other content across various systems like SharePoint, OneNote, and the company’s intranet.

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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. This post is the first in a series covering AWS MCP Servers.

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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.

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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. The security measures are inherently integrated into the AWS services employed in this architecture.

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Enhance customer support with Amazon Bedrock Agents by integrating enterprise data APIs

AWS Machine Learning - AI

This allows the agent to provide context and general information about car parts and systems. Developer tools The solution also uses the following developer tools: AWS Powertools for Lambda – This is a suite of utilities for Lambda functions that generates OpenAPI schemas from your Lambda function code. Python 3.9 or later Node.js

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

AWS Machine Learning - AI

An AWS Batch job reads these documents, chunks them into smaller slices, then creates embeddings of the text chunks using the Amazon Titan Text Embeddings model through Amazon Bedrock and stores them in an Amazon OpenSearch Service vector database. Verisk also has a legal review for IP protection and compliance within their contracts.