Amazon SageMakerAmazon
|
||||||
Related Products
|
||||||
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.
|
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.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
Machine learning engineers, data scientists, and organizations seeking to develop, deploy, and scale AI solutions efficiently and securely
|
Audience
AI builders and enterprise teams that need to train, adapt, and own models without manually managing complex research loops
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
PricingTry free for two months
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationAmazon
Founded: 1994
United States
aws.amazon.com/sagemaker/
|
Company InformationAutoScientist
United States
www.adaptionlabs.ai/blog/autoscientist
|
|||||
Alternatives |
Alternatives |
|||||
|
|
|
|||||
|
|
||||||
|
|
|
|||||
|
|
||||||
Categories |
Categories |
|||||
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
|
||||||
Integrations
AWS Deep Learning Containers
AWS EC2 Trn3 Instances
Amazon Augmented AI (A2I)
Amazon EC2 G4 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Amazon SageMaker Clarify
Amazon SageMaker Unified Studio
|
Integrations
AWS Deep Learning Containers
AWS EC2 Trn3 Instances
Amazon Augmented AI (A2I)
Amazon EC2 G4 Instances
Amazon EC2 Inf1 Instances
Amazon EC2 Trn1 Instances
Amazon EC2 Trn2 Instances
Amazon EC2 UltraClusters
Amazon SageMaker Clarify
Amazon SageMaker Unified Studio
|
|||||
|
|
|