Amazon SageMakerAmazon
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Amazon SageMaker HyperPodAmazon
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Related Products
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About
Amazon SageMaker is an advanced machine learning service that provides an integrated environment for building, training, and deploying machine learning (ML) models. It combines tools for model development, data processing, and AI capabilities in a unified studio, enabling users to collaborate and work faster. SageMaker supports various data sources, such as Amazon S3 data lakes and Amazon Redshift data warehouses, while ensuring enterprise security and governance through its built-in features. The service also offers tools for generative AI applications, making it easier for users to customize and scale AI use cases. SageMaker’s architecture simplifies the AI lifecycle, from data discovery to model deployment, providing a seamless experience for developers.
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About
Amazon SageMaker HyperPod is a purpose-built, resilient compute infrastructure that simplifies and accelerates the development of large AI and machine-learning models by handling distributed training, fine-tuning, and inference across clusters with hundreds or thousands of accelerators, including GPUs and AWS Trainium chips. It removes the heavy lifting involved in building and managing ML infrastructure by providing persistent clusters that automatically detect and repair hardware failures, automatically resume workloads, and optimize checkpointing to minimize interruption risk, enabling months-long training jobs without disruption. HyperPod offers centralized resource governance; administrators can set priorities, quotas, and task-preemption rules so compute resources are allocated efficiently among tasks and teams, maximizing utilization and reducing idle time. It also supports “recipes” and pre-configured settings to quickly fine-tune or customize foundation models.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Machine learning engineers, data scientists, and organizations seeking to develop, deploy, and scale AI solutions efficiently and securely
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Audience
Data scientists, AI engineers, and organizations interested in a solution to accelerate training and deployment while minimizing operational overhead
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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PricingTry free for two months
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationAmazon
Founded: 1994
United States
aws.amazon.com/sagemaker/
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Company InformationAmazon
Founded: 1994
United States
aws.amazon.com/sagemaker/ai/hyperpod/
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Categories |
Categories |
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Data Labeling Features
Human-in-the-loop
Labeling Automation
Labeling Quality
Performance Tracking
Polygon, Rectangle, Line, Point
SDK
Supports Audio Files
Task Management
Team Collaboration
Training Data Management
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Integrations
AWS EC2 Trn3 Instances
Amazon Web Services (AWS)
AWS Deep Learning Containers
Amazon EC2 P4 Instances
Amazon EC2 P5 Instances
Amazon Redshift
Amazon SageMaker Autopilot
Amazon SageMaker Data Wrangler
Amazon SageMaker Ground Truth
Amazon SageMaker Model Deployment
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Integrations
AWS EC2 Trn3 Instances
Amazon Web Services (AWS)
AWS Deep Learning Containers
Amazon EC2 P4 Instances
Amazon EC2 P5 Instances
Amazon Redshift
Amazon SageMaker Autopilot
Amazon SageMaker Data Wrangler
Amazon SageMaker Ground Truth
Amazon SageMaker Model Deployment
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