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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. However, this method presents trade-offs. However, it also presents some trade-offs. Before migrating any of the provided solutions to production, we recommend following the AWS Well-Architected Framework.

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Transcribe, translate, and summarize live streams in your browser with AWS AI and generative AI services

AWS Machine Learning - AI

Recognizing this need, we have developed a Chrome extension that harnesses the power of AWS AI and generative AI services, including Amazon Bedrock , an AWS managed service to build and scale generative AI applications with foundation models (FMs).

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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.

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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. Principal also used the AWS open source repository Lex Web UI to build a frontend chat interface with Principal branding.

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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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Create a generative AI–powered custom Google Chat application using Amazon Bedrock

AWS Machine Learning - AI

AWS offers powerful generative AI services , including Amazon Bedrock , which allows organizations to create tailored use cases such as AI chat-based assistants that give answers based on knowledge contained in the customers’ documents, and much more. The following figure illustrates the high-level design of the solution.

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Build a video insights and summarization engine using generative AI with Amazon Bedrock

AWS Machine Learning - AI

This post presents a solution where you can upload a recording of your meeting (a feature available in most modern digital communication services such as Amazon Chime ) to a centralized video insights and summarization engine. Many commercial generative AI solutions available are expensive and require user-based licenses.