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What is NVIDIA PhysicsNeMo?

NVIDIA's PhysicsNeMo is an open-source deep-learning framework built in Python that facilitates the design, training, fine-tuning, and inference of AI models that marry physical laws with data, thereby improving simulations, creating precise surrogate models, and enabling near-real-time predictions across a variety of domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather forecasting, climate science, and digital twin technologies. It boasts robust GPU-accelerated performance and offers Python APIs based on the PyTorch framework, all distributed under the Apache 2.0 license, featuring a variety of pre-designed model architectures, including physics-informed neural networks, neural operators, graph neural networks, and generative AI methods, allowing developers to effectively harness the causal relationships present in physics along with empirical data for superior engineering modeling. Furthermore, PhysicsNeMo includes extensive training pipelines that cover all aspects from geometry ingestion to the implementation of differential equations, in addition to providing reference application recipes that assist users in rapidly kickstarting their development processes. This unique integration of powerful features positions PhysicsNeMo as a vital resource for engineers and researchers aiming to push the boundaries of physics-based AI applications. Overall, its capabilities make it a crucial asset for anyone looking to innovate in fields that rely on the intersection of artificial intelligence and physical modeling.

What is Anahita?

Anahita functions as a dynamic platform and framework aimed at developing applications that focus on open science and the sharing of knowledge, all grounded in social networking principles. Through Anahita, users can create networks designed for online education and knowledge sharing, provide information access regarding people, places, and objects, and launch initiatives related to open science and open data, in addition to establishing collaborative online environments and cloud back-ends for mobile apps. It boasts a genuine nodes and graphs architecture, complete with specific design patterns optimized for crafting social networking applications. Moreover, Anahita's native framework features a graph-based architecture and fundamental design patterns that facilitate the seamless integration of social applications. Unlike conventional web applications, Anahita structures data as a web of interconnected nodes and graphs, making it particularly adept at supporting real-time analytics. The platform is built using open-source technologies, such as the LAMP stack and JavaScript, which are easily accessible to developers around the globe, thereby promoting a collaborative development atmosphere. This open accessibility not only stimulates innovation but also nurtures a lively ecosystem of applications developed on the Anahita framework, providing endless possibilities for users and developers alike. Ultimately, Anahita stands out as a robust solution for anyone looking to harness the power of collaborative knowledge sharing in a modern digital landscape.

Media

Media

Integrations Supported

PyTorch
Python

Integrations Supported

API Availability

Has API

API Availability

Pricing Information

Free
Free Version

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support
Web-Based Support

Customer Service / Support

Standard Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

developer.nvidia.com/physicsnemo

Company Facts

Organization Name

Anahita

Date Founded

2011

Company Location

Canada

Company Website

www.getanahita.com

Categories and Features

AI Science

Not specified

Categories and Features

Social Networking

Not specified

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