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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

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How Carrier predicts HVAC faults using AWS Glue and Amazon SageMaker

AWS Machine Learning Blog

In this post, we show how the Carrier and AWS teams applied ML to predict faults across large fleets of equipment using a single model. We first highlight how we use AWS Glue for highly parallel data processing. AWS Glue allowed us to easily run parallel data preprocessing and feature extraction. Additionally, 10.4%

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Simple guide to training Llama 2 with AWS Trainium on Amazon SageMaker

AWS Machine Learning Blog

Llama2 by Meta is an example of an LLM offered by AWS. To learn more about Llama 2 on AWS, refer to Llama 2 foundation models from Meta are now available in Amazon SageMaker JumpStart. Virginia) and US West (Oregon) AWS Regions, and most recently announced general availability in the US East (Ohio) Region.

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Generative AI Models Are Built to Hallucinate: The Question is How to Control Them

insideBIGDATA

In this contributed article, Stefano Soatto, Professor of Computer Science at the University of California, Los Angeles and a Vice President at Amazon Web Services, discusses generative AI models and how they are designed and trained to hallucinate, so hallucinations are a common product of any generative model.

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Scale and simplify ML workload monitoring on Amazon EKS with AWS Neuron Monitor container

AWS Machine Learning Blog

Amazon Web Services is excited to announce the launch of the AWS Neuron Monitor container , an innovative tool designed to enhance the monitoring capabilities of AWS Inferentia and AWS Trainium chips on Amazon Elastic Kubernetes Service (Amazon EKS).

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Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1

AWS Machine Learning Blog

In this two-part series, we demonstrate how you can deploy a cloud-based FL framework on AWS. We have developed an FL framework on AWS that enables analyzing distributed and sensitive health data in a privacy-preserving manner. In this post, we showed how you can deploy the open-source FedML framework on AWS. Conclusion.

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Amazon EC2 P5e instances are generally available

AWS Machine Learning Blog

To address customer needs for high performance and scalability in deep learning, generative AI, and HPC workloads, we are happy to announce the general availability of Amazon Elastic Compute Cloud (Amazon EC2) P5e instances, powered by NVIDIA H200 Tensor Core GPUs. Karthik Venna is a Principal Product Manager at AWS.

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