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Description
Anahita serves as a dynamic platform and framework tailored for the creation of open science and collaborative knowledge-sharing applications, all built upon a social networking infrastructure. This versatile tool can be utilized to establish online learning communities, networks for accessing information about individuals and entities, as well as platforms dedicated to open science and data sharing, fostering online collaboration, and providing a cloud-based backend for mobile applications. With its innovative nodes and graphs architecture, Anahita offers essential design patterns essential for crafting social networking applications. The native framework of Anahita incorporates a graph structure along with the necessary design patterns, facilitating the development of social applications that can effortlessly interact with one another. In contrast to traditional web applications, Anahita organizes data as a network of interconnected nodes and graphs, making it ideal for real-time data analysis. Built on widely embraced open-source technologies such as the LAMP stack and JavaScript, Anahita is accessible to developers worldwide, encouraging a collaborative environment for innovation and creativity. Its unique approach ensures that developers can leverage the power of interconnected data to enhance user experiences in unprecedented ways.
Description
NVIDIA PhysicsNeMo is a publicly available Python-based deep-learning framework designed for the creation, training, fine-tuning, and inference of physics-AI models that integrate physical principles with data, thereby enhancing simulations, developing accurate surrogate models, and facilitating near-real-time predictions in various fields such as computational fluid dynamics, structural mechanics, electromagnetics, weather forecasting, climate studies, and digital twin technologies. This framework offers powerful, GPU-accelerated capabilities along with Python APIs that are built on the PyTorch platform and distributed under the Apache 2.0 license, featuring a selection of curated model architectures that include physics-informed neural networks, neural operators, graph neural networks, and generative AI techniques, enabling developers to effectively leverage physics-based causal relationships together with empirical data for high-quality engineering modeling. Additionally, PhysicsNeMo provides comprehensive training pipelines that encompass everything from geometry ingestion to the application of differential equations, along with reference application recipes that help users quickly initiate their development workflows. This combination of features makes PhysicsNeMo an essential tool for engineers and researchers seeking to advance their work in physics-driven AI applications.
API Access
Has API
API Access
Has API
Integrations
PyTorch
Python
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
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
Anahita
Founded
2011
Country
Canada
Website
www.getanahita.com
Vendor Details
Company Name
NVIDIA
Founded
1993
Country
United States
Website
developer.nvidia.com/physicsnemo
Product Features
Social Networking
Activity / News Feed
Advertising Management
Blogs
Data Security
Event Management
Group Management
Media Library
Privacy Options
Real-time Chat
Social Media Integration
Social Media Tagging
User Profiles