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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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2025 Middle East tech trends: How CIOs will drive innovation with AI

CIO

The Middle East is rapidly evolving into a global hub for technological innovation, with 2025 set to be a pivotal year in the regions digital landscape. AI and machine learning are poised to drive innovation across multiple sectors, particularly government, healthcare, and finance.

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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 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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9 IT resolutions for 2025

CIO

Innovate Shane McDaniel, CIO for the City of Seguin, Texas, says his city has grown by about 35% since the 2020 census. McDaniel says this work also creates a strong launchpad for more IT innovation in the upcoming year. Were embracing innovation, he explains. Heres what they resolve to do in the upcoming 12 months.

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Unleash the power of generative AI with Amazon Q Business: How CCoEs can scale cloud governance best practices and drive innovation

AWS Machine Learning - AI

To maintain their competitive edge, organizations are constantly seeking ways to accelerate cloud adoption, streamline processes, and drive innovation. Readers will learn the key design decisions, benefits achieved, and lessons learned from Hearst’s innovative CCoE team.

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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.