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What is RAIC?

Models can now be created, trained, and implemented within minutes rather than taking months to complete. Initiate your search by uploading just one image of an object, and RAIC will efficiently locate similar items within an unlabeled dataset. The findings are contextually related to the original image, enabling you to enhance AI performance through intuitive human feedback. You can categorize your data based on specific detection criteria, whether it's focused on a single item or multiple objects. Once items are contextually linked, RAIC empowers you to organize and classify them into distinct categories, facilitating the training process. Subsequently, RAIC will generate either a detection model or a classification model based on your selection of Quick Train for urgent needs or Deep Train for a more conventional, accuracy-focused approach when time constraints are less pressing. This flexibility allows users to tailor their training methods to best suit their project requirements.

What is NVIDIA DIGITS?

The NVIDIA Deep Learning GPU Training System (DIGITS) enhances the efficiency and accessibility of deep learning for engineers and data scientists alike. By utilizing DIGITS, users can rapidly develop highly accurate deep neural networks (DNNs) for various applications, such as image classification, segmentation, and object detection. This system simplifies critical deep learning tasks, encompassing data management, neural network architecture creation, multi-GPU training, and real-time performance tracking through sophisticated visual tools, while also providing a results browser to help in model selection for deployment. The interactive design of DIGITS enables data scientists to focus on the creative aspects of model development and training rather than getting mired in programming issues. Additionally, users have the capability to train models interactively using TensorFlow and visualize the model structure through TensorBoard. Importantly, DIGITS allows for the incorporation of custom plug-ins, which makes it possible to work with specialized data formats like DICOM, often used in the realm of medical imaging. This comprehensive and user-friendly approach not only boosts productivity but also empowers engineers to harness cutting-edge deep learning methodologies effectively, paving the way for innovative solutions in various fields.

Media

Media

Integrations Supported

Caffe
Dask
NetApp AIPod
TensorFlow
Torch
Unleash live

Integrations Supported

Caffe
Dask
NetApp AIPod
TensorFlow
Torch
Unleash live

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

RAIC Labs

Date Founded

2019

Company Location

United States

Company Website

raiclabs.com

Company Facts

Organization Name

NVIDIA DIGITS

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/digits

Categories and Features

Categories and Features

Deep Learning

Convolutional Neural Networks
Document Classification
Image Segmentation
ML Algorithm Library
Model Training
Neural Network Modeling
Self-Learning
Visualization

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