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About

Every physical object is unique. Our technology can distinguish any solid object from even visually identical items based on the object itself – there is no need for serialization, bar codes, RFID, etc. It can be used for object identification and authentication at low cost with statistically perfect results. This new branch of machine vision is called FeaturePrint™. As each person has unique fingerprints, every physical object has unique surface characteristics that distinguish it from all other items. Once an object is registered, its FeaturePrint is stored securely in the cloud. At any time, the object’s identity can be confirmed using something as pervasive as a smartphone. Our patented technology uses advanced machine vision, neural networks, and deep learning to identify each object from its unique properties without dependence on RFID, bar codes or other proxies. The identification of the object is inherent in the object itself.

About

NVIDIA PhysicsNeMo is an open source Python deep-learning framework for building, training, fine-tuning, and inferring physics-AI models that combine physics knowledge with data to accelerate simulations, create high-fidelity surrogate models, and enable near-real-time predictions across domains such as computational fluid dynamics, structural mechanics, electromagnetics, weather and climate, and digital twin applications. It provides scalable, GPU-accelerated tools and Python APIs built on PyTorch and released under the Apache 2.0 license, offering curated model architectures including physics-informed neural networks, neural operators, graph neural networks, and generative AI–based approaches so developers can harness physics-driven causality alongside observed data for engineering-grade modeling. PhysicsNeMo includes end-to-end training pipelines from geometry ingestion to differential equations, reference application recipes to jump-start workflows.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Companies and governments that want to eliminate the threat of counterfeit products and to deliver rich and valuable layers of metadata unique to every part

Audience

Researchers, engineers, and developers who need an open source Python AI framework to build, train, fine-tune, and deploy physics-informed machine learning models for simulation, digital twins, and real-time prediction

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Alitheon
Founded: 2015
United States
www.alitheon.com

Company Information

NVIDIA
Founded: 1993
United States
developer.nvidia.com/physicsnemo

Alternatives

Alternatives

RFIDAeroTrack

RFIDAeroTrack

Technology Solutions
FEATool Multiphysics

FEATool Multiphysics

Precise Simulation
COMSOL Multiphysics

COMSOL Multiphysics

Comsol Group

Categories

Categories

Integrations

PyTorch
Python

Integrations

PyTorch
Python
Claim Alitheon FeaturePrint and update features and information
Claim Alitheon FeaturePrint and update features and information
Claim NVIDIA PhysicsNeMo and update features and information
Claim NVIDIA PhysicsNeMo and update features and information