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What is Intel Geti?

Intel® Geti™ software simplifies the process of developing computer vision models by providing efficient tools for data annotation and training. Among its features are smart annotations, active learning, and task chaining, which empower users to create models for various applications such as classification, object detection, and anomaly detection without requiring additional programming. Additionally, the platform boasts optimizations, hyperparameter tuning, and production-ready models that work seamlessly with Intel’s OpenVINO™ toolkit. Designed to promote teamwork, Geti™ supports collaboration by assisting teams throughout the entire lifecycle of model development, from data labeling to successful model deployment. This all-encompassing strategy allows users to concentrate on fine-tuning their models while reducing technical challenges, ultimately enhancing the overall efficiency of the development process. By streamlining these tasks, Geti™ enables quicker iterations and fosters innovation in computer vision applications.

What is Amazon SageMaker Ground Truth?

Amazon SageMaker offers a suite of tools designed for the identification and organization of diverse raw data types such as images, text, and videos, enabling users to apply significant labels and generate synthetic labeled data that is vital for creating robust training datasets for machine learning (ML) initiatives. The platform encompasses two main solutions: Amazon SageMaker Ground Truth Plus and Amazon SageMaker Ground Truth, both of which allow users to either engage expert teams to oversee the data labeling tasks or manage their own workflows independently. For users who prefer to retain oversight of their data labeling efforts, SageMaker Ground Truth serves as a user-friendly service that streamlines the labeling process and facilitates the involvement of human annotators from platforms like Amazon Mechanical Turk, in addition to third-party services or in-house staff. This flexibility not only boosts the efficiency of the data preparation stage but also significantly enhances the quality of the outputs, which are essential for the successful implementation of machine learning projects. Ultimately, the capabilities of Amazon SageMaker significantly reduce the barriers to effective data labeling and management, making it a valuable asset for those engaged in the data-driven landscape of AI development.

Media

Media

Integrations Supported

Intel Open Edge Platform
OpenVINO

Integrations Supported

Amazon SageMaker
Amazon SageMaker Unified Studio
ZenML

API Availability

Has API

API Availability

Pricing Information

Pricing not provided

Pricing Information

$0.08 per month

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Intel

Date Founded

1968

Company Location

United States

Company Website

www.intel.com/content/www/us/en/developer/tools/tiber/edge-platform/model-builder.html

Company Facts

Organization Name

Amazon Web Services

Date Founded

2006

Company Location

United States

Company Website

aws.amazon.com/es/sagemaker/data-labeling/

Categories and Features

Computer Vision

Not specified

Data Annotation

Not specified

Data Labeling

Not specified

Image Annotation

Not specified

Video Annotation

Not specified

Categories and Features

AI Infrastructure

Not specified

Data Annotation

Not specified

Data Labeling

Not specified

Image Annotation

Not specified

RLHF

Not specified

Video Annotation

Not specified

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