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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

GigaChat is adept at addressing user inquiries, engaging in conversations, generating program code, and producing written content and images based on provided descriptions, all within a cohesive framework. In contrast to other neural networks, GigaChat is designed from the ground up to facilitate multimodal interactions and demonstrates superior proficiency in the Russian language. The foundation of GigaChat lies in the NeONKA (NEural Omnimodal Network with Knowledge-Awareness) model, which consists of a diverse array of neural network systems and employs techniques such as supervised fine-tuning and reinforcement learning enhanced by human feedback. As a result, Sber's innovative neural network is capable of tackling a variety of cognitive challenges, including maintaining engaging dialogues, generating informative texts, and answering factual queries. Moreover, the integration of the Kandinsky 2.1 model within this ensemble enhances its capabilities, enabling the creation of intricate images based on user prompts, thereby expanding the potential applications of the service. This multifaceted functionality positions GigaChat as a versatile tool in the realm of artificial intelligence.

Description

The NVIDIA Deep Learning GPU Training System (DIGITS) empowers engineers and data scientists by making deep learning accessible and efficient. With DIGITS, users can swiftly train highly precise deep neural networks (DNNs) tailored for tasks like image classification, segmentation, and object detection. It streamlines essential deep learning processes, including data management, neural network design, multi-GPU training, real-time performance monitoring through advanced visualizations, and selecting optimal models for deployment from the results browser. The interactive nature of DIGITS allows data scientists to concentrate on model design and training instead of getting bogged down with programming and debugging. Users can train models interactively with TensorFlow while also visualizing the model architecture via TensorBoard. Furthermore, DIGITS supports the integration of custom plug-ins, facilitating the importation of specialized data formats such as DICOM, commonly utilized in medical imaging. This comprehensive approach ensures that engineers can maximize their productivity while leveraging advanced deep learning techniques.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Caffe
Dask
GigaChat 3 Ultra
NetApp AIPod
TensorFlow
Torch
Unleash live

Integrations

Caffe
Dask
GigaChat 3 Ultra
NetApp AIPod
TensorFlow
Torch
Unleash live

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Sberbank

Founded

1841

Country

Russia

Website

giga.chat/

Vendor Details

Company Name

NVIDIA DIGITS

Founded

1993

Country

United States

Website

developer.nvidia.com/digits

Product Features

Chatbot

Call to Action
Context and Coherence
Human Takeover
Inline Media / Videos
Machine Learning
Natural Language Processing
Payment Integration
Prediction
Ready-made Templates
Reporting / Analytics
Sentiment Analysis
Social Media Integration

Conversational AI

Code-free Development
Contextual Guidance
For Developers
Intent Recognition
Multi-Languages
Omni-Channel
On-Screen Chats
Pre-configured Bot
Reusable Components
Sentiment Analysis
Speech Recognition
Speech Synthesis
Virtual Assistant

Product 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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