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Build and deploy a UI for your generative AI applications with AWS and Python

AWS Machine Learning - AI

The emergence of generative AI has ushered in a new era of possibilities, enabling the creation of human-like text, images, code, and more. Solution overview For this solution, you deploy a demo application that provides a clean and intuitive UI for interacting with a generative AI model, as illustrated in the following screenshot.

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AI market evolution: Data and infrastructure transformation through AI

CIO

AI a primary driver in IT modernization and data mobility AI’s demand for data requires businesses to have a secure and accessible data strategy. However, 93% of respondents recognize the importance of an edge strategy for AI, and 83% plan to increase investments in edge technology over the next one to three years.

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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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Supercharge your auto scaling for generative AI inference – Introducing Container Caching in SageMaker Inference

AWS Machine Learning - AI

Today at AWS re:Invent 2024, we are excited to announce the new Container Caching capability in Amazon SageMaker, which significantly reduces the time required to scale generative AI models for inference. In our tests, we’ve seen substantial improvements in scaling times for generative AI model endpoints across various frameworks.

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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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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. Based on the classifier LLMs decision, the Lambda function routes the question to the appropriate downstream LLM, which will generate an answer and return it to the user.

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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

Building cloud infrastructure based on proven best practices promotes security, reliability and cost efficiency. In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process. This allows teams to focus more on implementing improvements and optimizing AWS infrastructure.