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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AWS Machine Learning Blog

MARCH 15, 2024

Therefore, ML creates challenges for AWS customers who need to ensure privacy and security across distributed entities without compromising patient outcomes. Solution overview We deploy FedML into multiple EKS clusters integrated with SageMaker for experiment tracking. As always, AWS welcomes your feedback.

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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

NOVEMBER 30, 2023

The number of companies launching generative AI applications on AWS is substantial and building quickly, including adidas, Booking.com, Bridgewater Associates, Clariant, Cox Automotive, GoDaddy, and LexisNexis Legal & Professional, to name just a few. Innovative startups like Perplexity AI are going all in on AWS for generative AI.

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AWS Machine Learning Blog

FEBRUARY 7, 2025

The implementation uses Slacks event subscription API to process incoming messages and Slacks Web API to send responses. Key AWS services used include: Amazon Bedrock Including Anthropics Claude 3.5 By keeping all data within the AWS ecosystem, weve eliminated dependencies on third-party AI tools and mitigated associated risks.

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IBM Journey to AI blog

JANUARY 16, 2024

To aid in building more sustainable IT estates, IBM has partnered up with Amazon Web Services (AWS) to facilitate sustainable cloud modernization journeys. To read about other key scenarios and entry points of IBM Consulting® Custom Lens for Sustainability, check out the blog post: Sustainable App Modernization Using AWS Cloud.

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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.

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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. We focus on the operational excellence pillar in this post.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

This capability allows for the seamless addition of SageMaker HyperPod managed compute to EKS clusters, using automated node and job resiliency features for foundation model (FM) development. FMs are typically trained on large-scale compute clusters with hundreds or thousands of accelerators.

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IBM Journey to AI blog

MARCH 20, 2024

Perhaps you need to discover what’s happening in your business and respond quickly to events. In the rest of this paper, we will explore how Cloud Pak for Integration, deployed on Red Hat OpenShift is the best way to provide integrations deploying in AWS. ROSA is jointly engineered and supported by AWS and Red Hat.

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AWS Machine Learning Blog

AUGUST 8, 2023

You can run Spark applications interactively from Amazon SageMaker Studio by connecting SageMaker Studio notebooks and AWS Glue Interactive Sessions to run Spark jobs with a serverless cluster. With interactive sessions, you can choose Apache Spark or Ray to easily process large datasets, without worrying about cluster management.

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AWS Machine Learning Blog

JANUARY 17, 2024

It can represent a geographical area as a whole or it can represent an event associated with a geographical area. We then discuss the various use cases and explore how you can use AWS services to clean the data, how machine learning (ML) can aid in this effort, and how you can make ethical use of the data in generating visuals and insights.

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AWS Machine Learning Blog

FEBRUARY 5, 2025

The listing writer microservice publishes listing change events to an Amazon Simple Notification Service (Amazon SNS) topic, which an Amazon Simple Queue Service (Amazon SQS) queue subscribes to. The listing indexer AWS Lambda function continuously polls the queue and processes incoming listing updates.

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AWS Machine Learning Blog

APRIL 19, 2024

The architecture deploys a simple service in a Kubernetes pod within an EKS cluster. The Kubernetes Event Driven Autoscaler ( KEDA ) is configured to automatically scale the number of service pods, based on the custom metrics available in Prometheus. The service is exposed behind a reverse-proxy using Traefik.

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AWS Machine Learning Blog

MAY 16, 2024

The main AWS services used are SageMaker, Amazon EMR , AWS CodeBuild , Amazon Simple Storage Service (Amazon S3), Amazon EventBridge , AWS Lambda , and Amazon API Gateway. The subsequent role of EventBridge was to dispatch events, instigated by the alteration of the buildspec.yml file, leading to running CodeBuild.

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AWS Machine Learning Blog

AUGUST 8, 2024

Webex by Cisco is a leading provider of cloud-based collaboration solutions, including video meetings, calling, messaging, events, polling, asynchronous video, and customer experience solutions like contact center and purpose-built collaboration devices. Webex works with the world’s leading business and productivity apps—including AWS.

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AWS Machine Learning Blog

OCTOBER 23, 2024

SnapLogic uses Amazon Bedrock to build its platform, capitalizing on the proximity to data already stored in Amazon Web Services (AWS). To address customers’ requirements about data privacy and sovereignty, SnapLogic deploys the data plane within the customer’s VPC on AWS.

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AWS Machine Learning Blog

JANUARY 13, 2023

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository.

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AWS Machine Learning Blog

APRIL 18, 2024

It’s straightforward to deploy in your AWS account. Prerequisites You need to have an AWS account and an AWS Identity and Access Management (IAM) role and user with permissions to create and manage the necessary resources and components for this application. Everything you need is provided as open source in our GitHub repo.

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Smart Data Collective

AUGUST 17, 2022

You can safely use an Apache Kafka cluster for seamless data movement from the on-premise hardware solution to the data lake using various cloud services like Amazon’s S3 and others. Amazon’s AWS Glue is one such tool that allows you to consume data from Apache Kafka and Amazon-managed streaming for Apache Kafka (MSK).

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AWS Machine Learning Blog

MAY 1, 2024

Virginia) AWS Region. The diagram details a comprehensive AWS Cloud-based setup within a specific Region, using multiple AWS services. The primary interface for the chatbot is a Streamlit application hosted on an Amazon Elastic Container Service (Amazon ECS) cluster, with accessibility managed by an Application Load Balancer.

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AWS Machine Learning Blog

DECEMBER 18, 2023

Make sure you have the following prerequisites: Create an S3 bucket Configure MongoDB Atlas cluster Create a free MongoDB Atlas cluster by following the instructions in Create a Cluster. In his role Igor is working with strategic partners helping them build complex, AWS-optimized architectures. Note we have two folders.

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AWS Machine Learning Blog

SEPTEMBER 12, 2024

In this post, we explore the journey that Thomson Reuters took to enable cutting-edge research in training domain-adapted large language models (LLMs) using Amazon SageMaker HyperPod , an Amazon Web Services (AWS) feature focused on providing purpose-built infrastructure for distributed training at scale. So, for example, a 6.6B

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AWS Machine Learning Blog

MARCH 6, 2023

These factors require training an LLM over large clusters of accelerated machine learning (ML) instances. In the past few years, numerous customers have been using the AWS Cloud for LLM training. We recommend working with your AWS account team or contacting AWS Sales to determine the appropriate Region for your LLM workload.

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AWS Machine Learning Blog

NOVEMBER 3, 2023

This process comprises two key components: event data and optical tracking data. Event data collection entails gathering the fundamental building blocks of the game. For the precision needed in shot speed calculations, we must ensure that the ball’s position aligns precisely with the moment of the event.

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AWS Machine Learning Blog

APRIL 5, 2024

Geobox enables city departments to do the following: Improved climate adaptation planning – Informed decisions reduce the impact of extreme heat events. SageMaker Processing enables the flexible scaling of compute clusters to accommodate tasks of varying sizes, from processing a single city block to managing planetary-scale workloads.

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AWS Machine Learning Blog

MAY 3, 2023

AWS customer Vericast is a marketing solutions company that makes data-driven decisions to boost marketing ROIs for its clients. Dynamic scaling of feature engineering jobs – A combination of various AWS services is used for this, but most notably SageMaker Processing.

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Data Science Dojo

JULY 24, 2023

Clusters : Clusters are groups of interconnected nodes that work together to process and store data. Clustering allows for improved performance and fault tolerance as tasks can be distributed across nodes. Amazon S3: Amazon Simple Storage Service (S3) is a scalable object storage service provided by Amazon Web Services (AWS).

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Towards AI

AUGUST 17, 2023

Each environment has a dedicated AWS account with its own cluster and ArgoCD installation. Potential Solutions At the outset, two potential solutions were proposed: ECR Cross Account Replication: AWS’s ECR natively supports replicating images between two accounts. Source: Image by the author. hook: PreSync argocd.argoproj.io/hook-delete-policy:

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AWS Machine Learning Blog

DECEMBER 15, 2023

Prerequisites To implement this solution, complete the following prerequisites: Have AWS Cloud admin access with an AWS Identity and Access Management (IAM) user with permissions required to complete the integration. Enter a connection name such as demo and choose your desired Amazon DocumentDB cluster. Choose Add connection.

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AWS Machine Learning Blog

SEPTEMBER 11, 2024

The following figure illustrates the idea of a large cluster of GPUs being used for learning, followed by a smaller number for inference. Examples of other PBAs now available include AWS Inferentia and AWS Trainium , Google TPU, and Graphcore IPU. Suppliers of data center GPUs include NVIDIA, AMD, Intel, and others.

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IBM Journey to AI blog

FEBRUARY 15, 2024

Logs Logs include discrete events recorded every time something occurs in the system, such as status or error messages, or transaction details. Autoscaling When traffic spikes, Kubernetes can automatically spin up new clusters to handle the additional workload. Kubernetes logs can be written in both structured and unstructured text.

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AWS Machine Learning Blog

FEBRUARY 24, 2023

AWS recently released Amazon SageMaker geospatial capabilities to provide you with satellite imagery and geospatial state-of-the-art machine learning (ML) models, reducing barriers for these types of use cases. Given the highly parallel needs, we chose Lambda to process our images.

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AWS Machine Learning Blog

APRIL 25, 2024

We provide a comprehensive guide on how to deploy speaker segmentation and clustering solutions using SageMaker on the AWS Cloud. Solution overview Amazon Transcribe is the go-to service for speaker diarization in AWS. Make sure the AWS account has a service quota for hosting a SageMaker endpoint for an ml.g5.2xlarge instance.

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AWS Machine Learning Blog

NOVEMBER 16, 2023

This is a joint blog with AWS and Philips. Since 2014, the company has been offering customers its Philips HealthSuite Platform, which orchestrates dozens of AWS services that healthcare and life sciences companies use to improve patient care.

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AWS Machine Learning Blog

SEPTEMBER 18, 2023

With Ray and AIR, the same Python code can scale seamlessly from a laptop to a large cluster. The full code can be found on the aws-samples-for-ray GitHub repository. Prepare the source data for the feature store by adding an event time and record ID for each row of data. You can specify resource requirements in actors too.

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AWS Machine Learning Blog

JANUARY 6, 2023

Many AWS media and entertainment customers license IMDb data through AWS Data Exchange to improve content discovery and increase customer engagement and retention. We downloaded the data from AWS Data Exchange and processed it in AWS Glue to generate KG files. Background. That’s an out-of-catalog search experience!

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