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ease
features
design
support

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Description

Differential Bio is an innovative virtual platform designed to enhance bioprocess optimization by making microbial growth more predictable, scalable, and economically viable, utilizing robotic laboratory automation and insights driven by artificial intelligence. The process initiates with automated, high-throughput experiments that replicate large-scale stress conditions within microliter settings, thereby producing relevant wet-lab data via liquid handling, fermentation, and measurement techniques. Tailored AI algorithms analyze this data to forecast various outcomes, including biomass growth, protein production, cell viability, titer, production rate, yield, and associated costs. Users can access the web-based platform to set their optimization targets and parameter limits, conduct limitless in-silico simulations, compare the results of simulated fermentation processes, engage in multi-objective optimization, and pinpoint the optimal conditions for scaling up production. This comprehensive approach not only streamlines the optimization workflow but also empowers teams to make data-informed decisions in bioprocess development.

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

PyTorch
Python

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

Differential Bio

Country

Germany

Website

www.differential.bio/

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/physicsnemo

Product Features

Product Features

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