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What is BioNeMo?

BioNeMo is a cloud-based platform designed for drug discovery that harnesses artificial intelligence and employs NVIDIA NeMo Megatron to enable the training and deployment of large biomolecular transformer models at an impressive scale. This service provides users with access to pre-trained large language models (LLMs) and supports multiple file formats pertinent to proteins, DNA, RNA, and chemistry, while also offering data loaders for SMILES to represent molecular structures and FASTA for sequences of amino acids and nucleotides. In addition, users have the flexibility to download the BioNeMo framework for local execution on their own machines. Among the notable models available are ESM-1, which is based on Meta AI’s state-of-the-art ESM-1b, and ProtT5, both fine-tuned transformer models aimed at protein language tasks that assist in generating learned embeddings for predicting protein structures and properties. Furthermore, the platform will incorporate OpenFold, an innovative deep learning model specifically focused on forecasting the 3D structures of new protein sequences, which significantly boosts its capabilities in biomolecular exploration. Overall, this extensive array of tools establishes BioNeMo as an invaluable asset for researchers navigating the complexities of drug discovery in modern science. As such, BioNeMo not only streamlines research processes but also empowers scientists to make significant advancements in the field.

What is AQBioSim?

AQBioSim is a cutting-edge cloud platform developed by SandboxAQ that employs Large Quantitative Models (LQMs) grounded in the principles of physics and chemistry to revolutionize the processes of discovering and optimizing materials. By integrating methodologies like Density Functional Theory (DFT), Iterative Full Configuration Interaction (iFCI), Generative AI, Bayesian Optimization, and Chemical Foundation Models, AQBioSim enables exceptionally precise simulations of molecular and material behaviors in practical applications. Its diverse functionalities allow for the prediction of performance under various stressors, refinement of formulation processes through in silico testing, and exploration of environmentally friendly chemical strategies. A remarkable highlight of AQBioSim is its significant advancements in battery technology, achieving a staggering 95% reduction in the time required for lithium-ion battery end-of-life predictions, along with an impressive 35 times increase in accuracy while utilizing only 50 times less data. This exceptional platform not only accelerates the pace of material innovation but also plays a vital role in fostering advancements in sustainable energy solutions, paving the way for a greener future. Furthermore, the implications of these innovations extend into various industries, demonstrating AQBioSim's potential to influence a wide range of applications.

Media

Media

Integrations Supported

Evo 2
NVIDIA AI Foundations
NVIDIA Clara
NVIDIA NeMo Megatron

Integrations Supported

Evo 2
NVIDIA AI Foundations
NVIDIA Clara
NVIDIA NeMo Megatron

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

NVIDIA

Date Founded

1993

Company Location

United States

Company Website

www.nvidia.com/en-us/gpu-cloud/bionemo/

Company Facts

Organization Name

SandboxAQ

Date Founded

2021

Company Location

United States

Company Website

www.sandboxaq.com/solutions/aqbiosim

Categories and Features

Categories and Features

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