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Average Ratings 0 Ratings

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ease
features
design
support

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Description

Our real-time deep learning platform has been meticulously crafted to provide unparalleled speed in detection, effectiveness, and comprehensive coverage, establishing a groundbreaking benchmark for cyber defense. We harness global threat intelligence that we have meticulously gathered from various sources, including threat repositories, the dark web, our own deployments, and collaborations with partners, to train our neural networks. Similar to how layers of neural networks can recognize images in photographs, our unique neural network architecture is adept at pinpointing threats in both payloads and headers. Blue Hexagon Labs rigorously tests and confirms the precision of our models daily against emerging threats in the environment. Our advanced neural networks are capable of detecting a broad spectrum of threats, including both file and fileless malware, exploits, command and control communications, and malicious domains across multiple platforms such as Windows, Android, and Linux. Additionally, deep learning, a specialized area within machine learning, leverages complex, multi-layered artificial neural networks to comprehend and represent data effectively. This innovative approach enhances our ability to adapt to the ever-evolving landscape of cybersecurity challenges.

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

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
GigaSECURE
Gigamon
Kubernetes
Microsoft Azure
PyTorch
Python

Integrations

Amazon Web Services (AWS)
GigaSECURE
Gigamon
Kubernetes
Microsoft Azure
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

Blue Hexagon

Founded

2017

Country

United States

Website

bluehexagon.ai/products/

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/physicsnemo

Product Features

Product Features

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