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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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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. This strategy results in more robust, versatile, and efficient applications that better serve diverse user needs and business objectives.

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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 this post, we set up the custom solution for observability and evaluation of Amazon Bedrock applications.

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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. The following diagram illustrates the conceptual architecture of an AI assistant with Amazon Bedrock IDE.

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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 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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Accelerate AWS Well-Architected reviews with Generative AI

AWS Machine Learning - AI

In this post, we explore a generative AI solution leveraging Amazon Bedrock to streamline the WAFR process. We demonstrate how to harness the power of LLMs to build an intelligent, scalable system that analyzes architecture documents and generates insightful recommendations based on AWS Well-Architected best practices.