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Introducing the latest Machine Learning Lens for the AWS Well-Architected Framework

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Today, we are delighted to introduce the latest version of the AWS Well-Architected Machine Learning (ML) Lens whitepaper. The AWS Well-Architected Framework provides architectural best practices for designing and operating ML workloads on AWS.

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Build generative AI apps using AWS Step Functions and Amazon Bedrock

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Today we are announcing two new optimized integrations for AWS Step Functions with Amazon Bedrock. Step Functions is a visual workflow service that helps developers build distributed applications, automate processes, orchestrate microservices, and create data and machine learning (ML) pipelines.

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DeepSeek-R1 models now available on AWS

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During this past AWS re:Invent, Amazon CEO Andy Jassy shared valuable lessons learned from Amazons own experience developing nearly 1,000 generative

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Generative AI on AWS – Generative AI, LLMs, and Foundation Models – AWS

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Transform your business with generative AI Boost productivity, build differentiated experiences, and innovate faster with AWS Get started with …

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Get started quickly with AWS Trainium and AWS Inferentia using AWS Neuron DLAMI and AWS Neuron DLC

AWS Machine Learning Blog

Starting with the AWS Neuron 2.18 release , you can now launch Neuron DLAMIs (AWS Deep Learning AMIs) and Neuron DLCs (AWS Deep Learning Containers) with the latest released Neuron packages on the same day as the Neuron SDK release. AWS Systems Manager Parameter Store support Neuron 2.18 and TensorFlow 2.10

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AWS bets on liquid cooling for its AI servers

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It’s AWS re:Invent this week, Amazon’s annual cloud computing extravaganza in Las Vegas, and as is tradition, the company has so much to announce, it can’t fit everything into its five (!) Ahead of the show’s official opening, AWS on Monday detailed a number of updates to its overall data …

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Federated learning on AWS using FedML, Amazon EKS, and Amazon SageMaker

AWS Machine Learning Blog

Many organizations are implementing machine learning (ML) to enhance their business decision-making through automation and the use of large distributed datasets. The need for federated learning in healthcare Healthcare relies heavily on distributed data sources to make accurate predictions and assessments about patient care.

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