AWS Machine Learning Blog

MARCH 15, 2024

However, the sharing of raw, non-sanitized sensitive information across different locations poses significant security and privacy risks, especially in regulated industries such as healthcare. Insecure networks lacking access control and encryption can still expose sensitive information to attackers.

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AWS Machine Learning Blog

JULY 31, 2024

Amazon Web Services (AWS) is committed to supporting the development of cutting-edge generative artificial intelligence (AI) technologies by companies and organizations across the globe. Let’s dive in and explore how these organizations are transforming what’s possible with generative AI on AWS.

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AWS Machine Learning Blog

APRIL 4, 2023

AWS provides various services catered to time series data that are low code/no code, which both machine learning (ML) and non-ML practitioners can use for building ML solutions. In this post, we seek to separate a time series dataset into individual clusters that exhibit a higher degree of similarity between its data points and reduce noise.

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AWS Machine Learning Blog

MAY 1, 2024

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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AWS Machine Learning Blog

JANUARY 24, 2024

Despite their wealth of general knowledge, state-of-the-art LLMs only have access to the information they were trained on. This can lead to factual inaccuracies (hallucinations) when the LLM is prompted to generate text based on information they didn’t see during their training.

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AWS Machine Learning Blog

MAY 31, 2023

With containers, scaling on a cluster becomes much easier. In late 2022, AWS announced the general availability of Amazon EC2 Trn1 instances powered by AWS Trainium accelerators, which are purpose built for high-performance deep learning training. For more information, refer to the Neuron Setup Guide.

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Flipboard

JUNE 20, 2023

For reference, GPT-3, an earlier generation LLM has 175 billion parameters and requires months of non-stop training on a cluster of thousands of accelerated processors. The Carbontracker study estimates that training GPT-3 from scratch may emit up to 85 metric tons of CO2 equivalent, using clusters of specialized hardware accelerators.

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AWS Machine Learning Blog

JUNE 25, 2024

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). The Container Insights dashboard also shows cluster status and alarms.

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AWS Machine Learning Blog

APRIL 29, 2024

Close collaboration with AWS Trainium has also played a major role in making the Arcee platform extremely performant, not only accelerating model training but also reducing overall costs and enforcing compliance and data integrity in the secure AWS environment. Our cluster consisted of 16 nodes, each equipped with a trn1n.32xlarge

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AWS Machine Learning Blog

MAY 30, 2024

Organizations across media and entertainment, advertising, social media, education, and other sectors require efficient solutions to extract information from videos and apply flexible evaluations based on their policies. This solution, powered by AWS AI and generative AI services, meets these needs.

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AWS Machine Learning Blog

DECEMBER 12, 2023

In this post, we’ll summarize training procedure of GPT NeoX on AWS Trainium , a purpose-built machine learning (ML) accelerator optimized for deep learning training. M tokens/$) trained such models with AWS Trainium without losing any model quality. We’ll outline how we cost-effectively (3.2 billion in Pythia.

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AWS Machine Learning Blog

MAY 30, 2024

Because Amazon Bedrock is serverless, you don’t have to manage infrastructure, and you can securely integrate and deploy generative AI capabilities into your applications using the AWS services you are already familiar with. AWS Prototyping developed an AWS Cloud Development Kit (AWS CDK) stack for deployment following AWS best practices.

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IBM Journey to AI blog

OCTOBER 26, 2023

In this journey, we are seeing an increased interest in migrating and deploying MAS on AWS Cloud. The growing need for Maximo migration to AWS Cloud Migrating to cloud helps organizations to drive the operational resiliency and reliability, at the same time keeping software up to date with minimal upgrade effort and infrastructure constraint.

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Smart Data Collective

FEBRUARY 20, 2022

AWS (Amazon Web Services), the comprehensive and evolving cloud computing platform provided by Amazon, is comprised of infrastructure as a service (IaaS), platform as a service (PaaS) and packaged software as a service (SaaS). With its wide array of tools and convenience, AWS has already become a popular choice for many SaaS companies.

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AWS Machine Learning Blog

NOVEMBER 13, 2024

A reverse image search engine enables users to upload an image to find related information instead of using text-based queries. The AWS Command Line Interface (AWS CLI) installed on your machine to upload the dataset to Amazon S3. For more information on managing credentials securely, see the AWS Boto3 documentation.

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AWS Machine Learning Blog

MAY 23, 2023

For information about how to use JumpStart models programmatically, see Use SageMaker JumpStart Algorithms with Pretrained Models. In April 2023, AWS unveiled Amazon Bedrock , which provides a way to build generative AI-powered apps via pre-trained models from startups including AI21 Labs , Anthropic , and Stability AI.

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FEBRUARY 16, 2023

Modern model pre-training often calls for larger cluster deployment to reduce time and cost. In October 2022, we launched Amazon EC2 Trn1 Instances , powered by AWS Trainium , which is the second generation machine learning accelerator designed by AWS. The following diagram shows an example.

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AWS Machine Learning Blog

AUGUST 21, 2023

Data is frequently kept in data lakes that can be managed by AWS Lake Formation , giving you the ability to implement fine-grained access control using a straightforward grant or revoke procedure. This data represents transaction data for products and includes information such as customer demographics, inventory, web sales, and promotions.

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AWS Machine Learning Blog

SEPTEMBER 8, 2023

Whether you’re in Human Resources looking for specific clauses in employee contracts, or a financial analyst sifting through a mountain of invoices to extract payment data, this solution is tailored to empower you to access the information you need with unprecedented speed and accuracy. It consists of one AWS Lambda function.

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AWS Machine Learning Blog

NOVEMBER 30, 2023

Building foundation models (FMs) requires building, maintaining, and optimizing large clusters to train models with tens to hundreds of billions of parameters on vast amounts of data. SageMaker HyperPod integrates the Slurm Workload Manager for cluster and training job orchestration.

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AWS Machine Learning Blog

APRIL 1, 2024

Distributed model training requires a cluster of worker nodes that can scale. In this blog post, AWS collaborates with Meta’s PyTorch team to discuss how to use the PyTorch FSDP library to achieve linear scaling of deep learning models on AWS seamlessly using Amazon EKS and AWS Deep Learning Containers (DLCs).

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AWS Machine Learning Blog

FEBRUARY 2, 2024

Embeddings capture the information content in bodies of text, allowing natural language processing (NLP) models to work with language in a numeric form. In this post, you’ll see an example of performing drift detection on embedding vectors using a clustering technique with large language models (LLMS) deployed from Amazon SageMaker JumpStart.

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IBM Journey to AI blog

JANUARY 16, 2024

As carbon emissions reporting becomes common worldwide, IBM is committed to assisting its clients in making informed decisions that can help address their energy demands and associated carbon impact while reducing costs. It helps identify energy or carbon hotspots to develop an optimization roadmap.

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Flipboard

NOVEMBER 17, 2023

Set up a MongoDB cluster To create a free tier MongoDB Atlas cluster, follow the instructions in Create a Cluster. Refer to Review knnVector Type Limitations for more information about the limitations of the knnVector type. Delete the MongoDB Atlas cluster. As always, AWS welcomes feedback.

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AWS Machine Learning Blog

MAY 31, 2024

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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AWS Machine Learning Blog

SEPTEMBER 3, 2024

Cost optimization – The serverless nature of the integration means you only pay for the compute resources you use, rather than having to provision and maintain a persistent cluster. SageMaker Studio runs inside an AWS managed virtual private cloud ( VPC ), with network access for SageMaker Studio domains, in this setup configured as VPC-only.

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AWS Machine Learning Blog

MAY 7, 2024

Veritone’s current media search and retrieval system relies on keyword matching of metadata generated from ML services, including information related to faces, sentiment, and objects. We use AWS Step Functions to orchestrate the entire pipeline. The metadata is generated at the shot level for a video.

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IBM Journey to AI blog

AUGUST 30, 2023

To ease this transition for customers unfamiliar with running containers in production, Amazon Web Services (AWS) has partnered with IBM and Red Hat to develop an IBM MAS on Red Hat OpenShift Service for AWS (ROSA) reference architecture. Why ROSA for Maximo in AWS? There are several advantages of IBM MAS SaaS on AWS.

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AWS Machine Learning Blog

JULY 17, 2023

As described in the AWS Well-Architected Framework , separating workloads across accounts enables your organization to set common guardrails while isolating environments. Organizations with a multi-account architecture typically have Amazon Redshift and SageMaker Studio in two separate AWS accounts. Select VPC Only , then choose Next.

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Flipboard

NOVEMBER 27, 2024

Analysts can use this information to provide incentives to buyers and sellers who frequently use the site, to attract new users, and to drive advertising and promotions. To implement this solution, complete the following steps: Set up Zero-ETL integration from the AWS Management Console for Amazon Relational Database Service (Amazon RDS).

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AWS Machine Learning Blog

DECEMBER 4, 2024

Solution overview Implementing the solution consists of the following high-level steps: Set up your environment and the permissions to access Amazon HyperPod clusters in SageMaker Studio. You can now use SageMaker Studio to discover the SageMaker HyperPod clusters, and view cluster details and metrics.

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IBM Journey to AI blog

MARCH 20, 2024

But without integration, the data would be locked into siloes; and the applications would be isolated and overloaded with complexity as fragile, tightly coupled connections were added to allow applications to work together and share information. Your business might want to access and share information quickly and simply using APIs.

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AWS Machine Learning Blog

MAY 1, 2024

For handling more intricate queries, achieving comprehensive answers demands information sourced from both documentation and databases. This integration allows for the synthesis of combined information, resulting in detailed and exhaustive answers. Virginia) AWS Region. file for deploying the solution using the AWS CDK.

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AWS Machine Learning Blog

OCTOBER 2, 2024

In this post, we share AWS guidance that we have learned and developed as part of real-world projects into practical guides oriented towards the AWS Well-Architected Framework , which is used to build production infrastructure and applications on AWS. To learn more, see Log Amazon Bedrock API calls using AWS CloudTrail.

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Smart Data Collective

MARCH 2, 2022

Kubernetes is based on a control node combined with multiple worker nodes to facilitate its cluster architecture. With the emergence of serverless technologies, there is growing interest in utilizing serverless within Kubernetes both to manage workloads and provide the cluster itself. Deploying Serverless Workloads in Kubernetes.

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Flipboard

DECEMBER 3, 2024

Bloomberg Markets "Bloomberg Markets" is focused on bringing you the most important global business and breaking markets news and information as it …

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AWS Machine Learning Blog

APRIL 17, 2023

Using RStudio on SageMaker and Amazon EMR together, you can continue to use the RStudio IDE for analysis and development, while using Amazon EMR managed clusters for larger data processing. In this post, we demonstrate how you can connect your RStudio on SageMaker domain with an EMR cluster. Choose Create stack.

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