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Enhanced observability for AWS Trainium and AWS Inferentia with Datadog

AWS Machine Learning Blog

AWS AI chips, Trainium and Inferentia, enable you to build and deploy generative AI models at higher performance and lower cost. The Datadog dashboard offers a detailed view of your AWS AI chip (Trainium or Inferentia) performance, such as the number of instances, availability, and AWS Region.

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AWS Widens Data Pipelines + Creates Amazon Q Gen-AI Assistant

Adrian Bridgwater for Forbes

Because data exists in so varied a set of structures and forms that we can do much with it - but, that means we need ways to connect all our data.

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Evaluate large language models for your machine translation tasks on AWS

AWS Machine Learning Blog

It is critical for AI models to capture not only the context, but also the cultural specificities to produce a more natural sounding translation. The following sample XML illustrates the prompts template structure: EN FR Prerequisites The project code uses the Python version of the AWS Cloud Development Kit (AWS CDK).

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Shaping the future: OMRON’s data-driven journey with AWS

AWS Machine Learning Blog

At the heart of this transformation is the OMRON Data & Analytics Platform (ODAP), an innovative initiative designed to revolutionize how the company harnesses its data assets. The robust security features provided by Amazon S3, including encryption and durability, were used to provide data protection.

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Build generative AI applications quickly with Amazon Bedrock IDE in Amazon SageMaker Unified Studio

AWS Machine Learning Blog

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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AWS Machine Learning: A Beginner’s Guide

How to Learn Machine Learning

If you’re diving into the world of machine learning, AWS Machine Learning provides a robust and accessible platform to turn your data science dreams into reality. Today, we’ll explore why Amazon’s cloud-based machine learning services could be your perfect starting point for building AI-powered applications.

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Real value, real time: Production AI with Amazon SageMaker and Tecton

AWS Machine Learning Blog

Businesses are under pressure to show return on investment (ROI) from AI use cases, whether predictive machine learning (ML) or generative AI. Only 54% of ML prototypes make it to production, and only 5% of generative AI use cases make it to production. This post is cowritten with Isaac Cameron and Alex Gnibus from Tecton.

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