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A secure approach to generative AI with AWS

AWS Machine Learning Blog

Generative artificial intelligence (AI) is transforming the customer experience in industries across the globe. At AWS, our top priority is safeguarding the security and confidentiality of our customers’ workloads. With the AWS Nitro System , we delivered a first-of-its-kind innovation on behalf of our customers.

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Migrate Amazon SageMaker Data Wrangler flows to Amazon SageMaker Canvas for faster data preparation

AWS Machine Learning Blog

Amazon SageMaker Data Wrangler provides a visual interface to streamline and accelerate data preparation for machine learning (ML), which is often the most time-consuming and tedious task in ML projects. About the Authors Charles Laughlin is a Principal AI Specialist at Amazon Web Services (AWS).

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PEFT fine tuning of Llama 3 on SageMaker HyperPod with AWS Trainium

AWS Machine Learning Blog

To simplify infrastructure setup and accelerate distributed training, AWS introduced Amazon SageMaker HyperPod in late 2023. In this blog post, we showcase how you can perform efficient supervised fine tuning for a Meta Llama 3 model using PEFT on AWS Trainium with SageMaker HyperPod. architectures/5.sagemaker-hyperpod/LifecycleScripts/base-config/

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Tackling AI’s data challenges with IBM databases on AWS

IBM Journey to AI blog

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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How Northpower used computer vision with AWS to automate safety inspection risk assessments

AWS Machine Learning Blog

Specifically, we cover the computer vision and artificial intelligence (AI) techniques used to combine datasets into a list of prioritized tasks for field teams to investigate and mitigate. Data preparation SageMaker Ground Truth employs a human workforce made up of Northpower volunteers to annotate a set of 10,000 images.

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Pre-training genomic language models using AWS HealthOmics and Amazon SageMaker

AWS Machine Learning Blog

In this blog post and open source project , we show you how you can pre-train a genomics language model, HyenaDNA , using your genomic data in the AWS Cloud. Amazon SageMaker Amazon SageMaker is a fully managed ML service offered by AWS, designed to reduce the time and cost associated with training and tuning ML models at scale.

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Apply fine-grained data access controls with AWS Lake Formation in Amazon SageMaker Data Wrangler

AWS Machine Learning Blog

You can streamline the process of feature engineering and data preparation with SageMaker Data Wrangler and finish each stage of the data preparation workflow (including data selection, purification, exploration, visualization, and processing at scale) within a single visual interface. Choose Create stack.

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