Nvidia integrates its AI microservices with AWS

As part of Nvidia’s AI Enterprise software available on AWS Marketplace, developers get access to a growing AI model library via standard APIs.

This integration with Amazon Sagemaker and AWS parallel cluster is designed to streamline the implementation and management of machine learning models and powerful computer clusters on AWS.

In addition, NIMs can be orchestrated using AWS Healthomics, tailor-made for organic data analysis.

In a blog post In announcing the integration, NVIDIA noted that NIM includes genomics models derived from Parabricks, a software platform developed by NVIDIA that specializes in accelerating and optimizing genomic data analysis.

These workflows are also accessible at AWS Healthomics such as Ready2Run-Workflows, so that customers can implement in advance built pipelines.

NIM microservices provide optimized AI models for decoding proteins and genomic sequences, as well as conversational AI and visual GenAI for avatars and digital humans.

These assistants are trained in organizational-specific data using techniques such as Retrieval-Auguste Generation and can tap into internal data sources to synthesize research.

The company said these applications could improve patient support and physician assistance, using organization-specific data to synthesize research and improve productivity.

Why this is important
A streamlined development of Genai tools could have in-depth consequences for health care and the Biosheschain sector.

Multiple startups already use the potential to speed up the workflow for discovering medicines, to train generative models for protein design and help researchers with cloud-based data analysis.

Despite ongoing concerns about the accuracy of AI and the broader implications of integrating a relatively new technology into all aspects of healthcare, an April Wolters Kluwer Health survey found that nearly 70% of physicians enthusiastically embrace the benefits of GenAI .

THE BIG TREND
In March, NVIDIA Healthcare introduced 25 new cloud-agnostic microservices, allowing healthcare developers to integrate GenAI into their applications across different use cases and digital health initiatives, whether deployed in the cloud or on-premises.

A partnership with Johnson & Johnson MedTech ensures the integration of NVIDIAs AI technology for surgical procedures to improve real-time analytics and broaden the application of AI algorithms in surgical decision-making, education and collaboration within operating rooms.

About a year ago, the company integrated its AI Enterprise platform with Microsoft Azure machine learning, providing healthcare customers with comprehensive support for building, deploying, and managing custom AI applications using more than 100 NVIDIA AI frameworks and tools.

ON THE RECORD
“Easy access to NIM will enable the thousands of healthcare and life sciences companies already using AWS to deploy generative AI more quickly, without the complexity of model development and packaging for production,” NVIDIA said in the blog post. “It will also help developers build workflows that combine AI models with different modalities, such as amino acid sequences, MRI images and patient records in flat text.”