NVIDIA and AWS Collaborate to Accelerate AI, Robotics, and Quantum Computing

NVIDIA DGX Cloud Comes to AWS

NVIDIA and Amazon Web Services (AWS) have announced the availability of NVIDIA DGX Cloud on AWS, marking a significant advancement in cloud-based AI computing 1

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. This fully managed, high-performance platform is designed to help enterprises train and customize AI models at scale. Available through AWS Marketplace Private Offers, DGX Cloud provides flexible terms and direct access to NVIDIA experts, enabling businesses to rapidly scale their AI capabilities 1

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Enhanced AI Tools and Microservices

The collaboration introduces NVIDIA NIM microservices across key AWS AI services, aiming to support faster AI inference and lower latency for generative AI applications 3

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. These microservices are now accessible through AWS Marketplace, Amazon Bedrock Marketplace, and Amazon SageMaker JumpStart, simplifying deployment for developers 2

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. The NIM microservices support a wide range of AI models and can be deployed across various AWS services, including Amazon EC2, Amazon EKS, and Amazon SageMaker 3

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Advancements in Robotics Simulation

NVIDIA is expanding its reach in robotics development with NVIDIA Isaac Sim, now running on high-performance Amazon EC2 G6e instances accelerated by NVIDIA L40S GPUs 1

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. This reference application, built on NVIDIA Omniverse, allows developers to simulate and test AI-driven robots in physically based virtual environments 1

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. The integration of OpenUSD NIM microservices further accelerates the synthetic data generation pipeline, from scene creation to data augmentation 1

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Quantum Computing and Drug Discovery

In the realm of quantum computing, NVIDIA CUDA-Q is now integrated with Amazon Braket, streamlining quantum computing development 1

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. This integration allows CUDA-Q users to access Amazon Braket's quantum processors, while Braket users can utilize CUDA-Q's GPU-accelerated workflows for development and simulation 1

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For drug discovery, NVIDIA BioNeMo NIM microservices and AI Blueprints are now integrated into AWS HealthOmics, a fully managed biological data compute and storage service 1

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. This collaboration provides researchers with access to AI models and scalable cloud infrastructure tailored to drug discovery workflows 1

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Liquid Cooling and Next-Generation Hardware

AWS has developed solutions for configurable liquid-to-chip cooling across its data centers, which will seamlessly integrate air- and liquid-cooling capabilities for powerful rack-scale AI supercomputing systems like NVIDIA GB200 NVL72 1

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. This cooling solution is designed to provide maximum performance and efficiency for running AI models and will be used for the next-generation NVIDIA Blackwell platform 1

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Real-Time AI Blueprints and Industry Applications

NVIDIA's latest AI Blueprints are available for instant deployment on AWS, offering ready-to-deploy options for various applications such as video search, cybersecurity, and more 1

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. These blueprints enable developers to easily integrate AI capabilities into existing workflows, speeding up deployments 1

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Several companies are already leveraging these new technologies. For instance, SoftServe has developed six generative AI solutions fully deployed on AWS and accelerated by NVIDIA NIM and AWS services 3

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. In the robotics field, companies like Field AI, Vention, and Cobot are using NVIDIA Isaac Sim on AWS to advance their robotics development 4

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This collaboration between NVIDIA and AWS represents a significant step forward in making advanced AI, robotics, and quantum computing technologies more accessible and efficient for developers and enterprises across various industries.