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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize their growing cloud environments. In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process.

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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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The key to operational AI: Modern data architecture

CIO

Today, enterprises are leveraging various types of AI to achieve their goals. Just as DevOps has become an effective model for organizing application teams, a similar approach can be applied here through machine learning operations, or “MLOps,” which automates machine learning workflows and deployments.

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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. Building a generative AI application SageMaker Unified Studio offers tools to discover and build with generative AI.

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Multi-LLM routing strategies for generative AI applications on AWS

AWS Machine Learning - AI

Organizations are increasingly using multiple large language models (LLMs) when building generative AI applications. For example, consider a text summarization AI assistant intended for academic research and literature review. Such queries could be effectively handled by a simple, lower-cost model.

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Unlocking the full potential of enterprise AI

CIO

Despite the huge promise surrounding AI, many organizations are finding their implementations are not delivering as hoped. 1] The limits of siloed AI implementations According to SS&C Blue Prism , an expert on AI and automation, the chief issue is that enterprises often implement AI in siloes.

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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. To move faster, enterprises need robust operating models and a holistic approach that simplifies the generative AI lifecycle.