Amazon SageMaker HyperPodAmazon
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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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About
AutoScientist is a system that self-improves and automates the full research loop behind model training and alignment, making it possible for more teams to shape and refine the AI they depend on. Model training and reinforcement learning are among the most powerful ways to shape a model, but they are also among the hardest to get right outside a frontier lab because attempts can fail through catastrophic forgetting, overfitting on small or low-quality datasets, and conflicting training signals. AutoScientist co-optimizes data and model training recipes automatically, self-improving across both until quality converges on the user’s objective. Where Adaptive Data shapes the inputs, AutoScientist shapes the model, running the full research loop end-to-end so users walk away with models adapted to their goal. The loop runs itself: data and recipes are co-optimized in lockstep, iterating until the model converges on the behavior described.
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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
Data scientists, AI engineers, and organizations interested in a solution to accelerate training and deployment while minimizing operational overhead
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Audience
AI builders and enterprise teams that need to train, adapt, and own models without manually managing complex research loops
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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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Pricing
No information available.
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/ai/hyperpod/
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Company InformationAutoScientist
United States
www.adaptionlabs.ai/blog/autoscientist
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Categories |
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Integrations
AWS EC2 Trn3 Instances
AWS Trainium
Amazon SageMaker
Amazon Web Services (AWS)
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Integrations
AWS EC2 Trn3 Instances
AWS Trainium
Amazon SageMaker
Amazon Web Services (AWS)
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