December 03, 2024 -- Expanding what’s possible for developers and enterprises in the cloud, NVIDIA and Amazon Web Services are converging at AWS re:Invent in Las Vegas this week to showcase new solutions designed to accelerate AI and robotics breakthroughs and simplify research in quantum computing development.

AWS re:Invent is a conference for the global cloud-computing community packed with keynotes and more than 2,000 technical sessions.

Announcement highlights include the availability of NVIDIA DGX Cloud on AWS and enhanced AI, quantum computing and robotics tools.

NVIDIA DGX Cloud on AWS for AI at Scale

The NVIDIA DGX Cloud AI computing platform is now available through AWS Marketplace Private Offers, offering a high-performance, fully managed solution for enterprises to train and customize AI models.

DGX Cloud offers flexible terms, a fully managed and optimized platform, and direct access to NVIDIA experts to help businesses scale their AI capabilities quickly.

Early adopter Leonardo.ai, part of the Canva family, is already using DGX Cloud on AWS to develop advanced design tools.

AWS Liquid-Cooled Data Centers With NVIDIA Blackwell

Newer AI servers benefit from liquid cooling to cool high-density compute chips more efficiently for better performance and energy efficiency. AWS has developed solutions that provide configurable liquid-to-chip cooling across its data centers.

The cooling solution announced today will seamlessly integrate air- and liquid-cooling capabilities for the most powerful rack-scale AI supercomputing systems like NVIDIA GB200 NVL72, as well as AWS’ network switches and storage servers.

This flexible, multimodal cooling design provides maximum performance and efficiency for running AI models and will be used for the next-generation NVIDIA Blackwell platform.

Blackwell will be the foundation of Amazon EC2 P6 instances, DGX Cloud on AWS and Project Ceiba.

NVIDIA Advances Physical AI With Accelerated Robotics Simulation on AWS

NVIDIA is also expanding the reach of NVIDIA Omniverse on AWS with NVIDIA Isaac Sim, now running on high-performance Amazon EC2 G6e instances accelerated by NVIDIA L40S GPUs.

Available now, this reference application built on NVIDIA Omniverse enables developers to simulate and test AI-driven robots in physically based virtual environments.

One of the many workflows enabled by Isaac Sim is synthetic data generation. This pipeline is now further accelerated with the infusion of OpenUSD NIM microservices, from scene creation to data augmentation.

Robotics companies such as Aescape, Cohesive Robotics, Cobot, Field AI, Standard Bots, Swiss Mile and Vention are using Isaac Sim to simulate and validate the performance of their robots prior to deployment.

In addition, Rendered.ai, SoftServe and Tata Consultancy Services are using the synthetic data generation capabilities of Omniverse Replicator and Isaac Sim to bootstrap perception AI models that power various robotics applications.

NVIDIA BioNeMo on AWS for Advanced AI-Based Drug Discovery

NVIDIA BioNeMo NIM microservices and AI Blueprints, developed to advance drug discovery, are now integrated into AWS HealthOmics, a fully managed biological data compute and storage service designed to accelerate scientific breakthroughs in clinical diagnostics and drug discovery.

This collaboration gives researchers access to AI models and scalable cloud infrastructure tailored to drug discovery workflows. Several biotech companies already use NVIDIA BioNeMo on AWS to drive their research and development pipelines.

For example, A-Alpha Bio, a biotechnology company based in Seattle, recently published a study in biorxiv describing a collaborative effort with NVIDIA and AWS to develop and deploy an antibody AI model called AlphaBind.

Using AlphaBind via the BioNeMo framework on Amazon EC2 P5 instances equipped with NVIDIA H100 Tensor Core GPUs, A-Alpha Bio achieved a 12x increase in inference speed and processed over 108 million inference calls in two months.

Additionally, SoftServe today launched Drug Discovery, its generative AI solution built with NVIDIA Blueprints, to enable computer-aided drug discovery and efficient drug development. This solution is set to deliver faster workflows and will soon be available in AWS Marketplace.

Real-Time AI Blueprints: Ready-to-Deploy Options for Video, Cybersecurity and More

NVIDIA’s latest AI Blueprints are available for instant deployment on AWS, making real-time applications like vulnerability analysis for container security, and video search and summarization agents readily accessible.

Developers can easily integrate these blueprints into existing workflows to speed deployments.

Developers and enterprises can use the NVIDIA AI Blueprint for video search and summarization to build visual AI agents that can analyze real-time or archived videos to answer user questions, generate summaries and enable alerts for specific scenarios.

AWS collaborated with NVIDIA to provide a reference architecture applying the NVIDIA AI Blueprint for vulnerability analysis to augment early security patching in continuous integration pipelines on AWS cloud-native services.

NVIDIA CUDA-Q on Amazon Braket: Quantum Computing Made Practical

NVIDIA CUDA-Q is now integrated with Amazon Braket to streamline quantum computing development. CUDA-Q users can  use Amazon Braket’s quantum processors, while Braket users can tap CUDA-Q’s GPU-accelerated workflows for development and simulation.

The CUDA-Q platform allows developers to build hybrid quantum-classical applications and run them on many different types of quantum processors, simulated and physical.

Now preinstalled on Amazon Braket, CUDA-Q provides a seamless development platform for hybrid quantum-classical applications, unlocking new potential in quantum research.

Enterprise Platform Providers and Consulting Leaders Advance AI With NVIDIA on AWS

Leading software platforms and global system integrators are helping enterprises rapidly scale generative AI applications built with NVIDIA AI on AWS to drive innovation across industries.

Cloudera is using NVIDIA AI on AWS to enhance its new AI inference solution, helping Mercy Corps improve the precision and effectiveness of its aid distribution technology.

Cohesity has integrated NVIDIA NeMo Retriever microservices in its generative AI-powered conversational search assistant, Cohesity Gaia, to improve the recall performance of retrieval-augmented generation. Cohesity customers running on AWS can take advantage of the NeMo Retriever integration within Gaia.

DataStax announced that Wikimedia Deutschland is applying the DataStax AI Platform to make Wikidata available to developers as an embedded vectorized database. The Datastax AI Platform is built with NVIDIA NeMo Retriever and NIM microservices, and available on AWS.

Deloitte’s C-Suite AI now supports NVIDIA AI Enterprise software, including NVIDIA NIM microservices and NVIDIA NeMo for CFO-specific use cases, including financial statement analysis, scenario modeling and market analysis.

RAPIDS Quick Start Notebooks Now Available on Amazon EMR

NVIDIA and AWS are also speeding data science and data analytics workloads with the RAPIDS Accelerator for Apache Spark, which accelerates analytics and machine learning workloads with no code change and reduces data processing costs by up to 80%.

Quick Start notebooks for RAPIDS Accelerator for Apache Spark are now available on Amazon EMR, Amazon EC2 and Amazon EMR on EKS. These offer a simple way to qualify Spark jobs tuned to maximize the performance of RAPIDS on GPUs, all within AWS EMR.

NVIDIA and AWS Power the Next Generation of Industrial Edge Systems

The NVIDIA IGX Orin and Jetson Orin platforms now integrate seamlessly with AWS IoT Greengrass to streamline  the deployment and running of AI models at the edge and to efficiently manage fleets of connected devices at scale. This combination enhances scalability and simplifies the deployment process for industrial and robotics applications.

Developers can now tap into NVIDIA’s advanced edge computing power with AWS’ purpose-built IoT services, creating a secure, scalable environment for autonomous machines and smart sensors. A guide for getting started, authored by AWS, is now available to support developers putting these capabilities to work.

The integration underscores NVIDIA’s work in advancing enterprise-ready industrial edge systems to enable rapid, intelligent operations in real-world applications.