Remove Generative AI Remove Knowledge Base Remove Metrics
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Evaluating RAG applications with Amazon Bedrock knowledge base evaluation

AWS Machine Learning - AI

Although automated metrics are fast and cost-effective, they can only evaluate the correctness of an AI response, without capturing other evaluation dimensions or providing explanations of why an answer is problematic. Human evaluation, although thorough, is time-consuming and expensive at scale.

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Empower your generative AI application with a comprehensive custom observability solution

AWS Machine Learning - AI

Recently, we’ve been witnessing the rapid development and evolution of generative AI applications, with observability and evaluation emerging as critical aspects for developers, data scientists, and stakeholders. In the context of Amazon Bedrock , observability and evaluation become even more crucial.

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

AWS Machine Learning - AI

Building generative AI applications presents significant challenges for organizations: they require specialized ML expertise, complex infrastructure management, and careful orchestration of multiple services. Consider a global retail site operating across multiple regions and countries.

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Track, allocate, and manage your generative AI cost and usage with Amazon Bedrock

AWS Machine Learning - AI

As enterprises increasingly embrace generative AI , they face challenges in managing the associated costs. With demand for generative AI applications surging across projects and multiple lines of business, accurately allocating and tracking spend becomes more complex.

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5 tips for better business value from gen AI

CIO

Instead, CIOs must partner with CMOs and other business leaders to help quantify where gen AI can drive other strategic impacts especially those directly connected to the bottom line. CIOs should return to basics, zero in on metrics that will improve through gen AI investments, and estimate targets and timeframes.

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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

As Principal grew, its internal support knowledge base considerably expanded. 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 allowed fine-tuned management of user access to content and systems.

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How to Use Generative AI and LLMs to Improve Search

TechEmpower CTO

Artificial Intelligence (AI), and particularly Large Language Models (LLMs), have significantly transformed the search engine as we’ve known it. With Generative AI and LLMs, new avenues for improving operational efficiency and user satisfaction are emerging every day. Strive for a balanced outcome.