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What is Amazon SageMaker Unified Studio?

Amazon SageMaker Unified Studio is an all-in-one platform for AI and machine learning development, combining data discovery, processing, and model creation in one secure and collaborative environment. It integrates services like Amazon EMR, Amazon SageMaker, and Amazon Bedrock, allowing users to quickly access data, process it using SQL or ETL tools, and build machine learning models. SageMaker Unified Studio also simplifies the creation of generative AI applications, with customizable AI models and rapid deployment capabilities. Designed for both technical and business teams, it helps organizations streamline workflows, enhance collaboration, and speed up AI adoption.

What is Amazon SageMaker HyperPod?

Amazon SageMaker HyperPod is a powerful and specialized computing framework designed to enhance the efficiency and speed of building large-scale AI and machine learning models by facilitating distributed training, fine-tuning, and inference across multiple clusters that are equipped with numerous accelerators, including GPUs and AWS Trainium chips. It alleviates the complexities tied to the development and management of machine learning infrastructure by offering persistent clusters that can autonomously detect and fix hardware issues, resume workloads without interruption, and optimize checkpointing practices to reduce the likelihood of disruptions—thus enabling continuous training sessions that may extend over several months. In addition, HyperPod incorporates centralized resource governance, empowering administrators to set priorities, impose quotas, and create task-preemption rules, which effectively ensures optimal allocation of computing resources among diverse tasks and teams, thereby maximizing usage and minimizing downtime. The platform also supports "recipes" and pre-configured settings, which allow for swift fine-tuning or customization of foundational models like Llama. This sophisticated framework not only boosts operational effectiveness but also allows data scientists to concentrate more on model development, freeing them from the intricacies of the underlying technology. Ultimately, HyperPod represents a significant advancement in machine learning infrastructure, making the model-building process both faster and more efficient.

Media

Media

Integrations Supported

Amazon SageMaker
Amazon Web Services (AWS)
AWS EC2 Trn3 Instances
AWS Glue
AWS Trainium
Amazon Athena
Amazon Bedrock
Amazon EMR
Amazon Q Developer
Amazon SageMaker Autopilot
Amazon SageMaker Clarify
Amazon SageMaker Edge
Amazon SageMaker Feature Store
Amazon SageMaker Ground Truth
Amazon SageMaker JumpStart
Cohere
Hugging Face
LightOn
PyTorch
Stability AI

Integrations Supported

Amazon SageMaker
Amazon Web Services (AWS)
AWS EC2 Trn3 Instances
AWS Glue
AWS Trainium
Amazon Athena
Amazon Bedrock
Amazon EMR
Amazon Q Developer
Amazon SageMaker Autopilot
Amazon SageMaker Clarify
Amazon SageMaker Edge
Amazon SageMaker Feature Store
Amazon SageMaker Ground Truth
Amazon SageMaker JumpStart
Cohere
Hugging Face
LightOn
PyTorch
Stability AI

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/unified-studio/

Company Facts

Organization Name

Amazon

Date Founded

1994

Company Location

United States

Company Website

aws.amazon.com/sagemaker/ai/hyperpod/

Categories and Features

Data Science

Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports

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