Nvidia Corp. and Amazon Web Services Inc. announced the expansion of the two companies’ collaboration on new chip technology, networking, cloud infrastructure and open models and physical AI.

Fueling scale-up in infrastructure and custom silicon, AWS said at its re:Invent conference today that it would support Nvidia’s NVLink Fusion, a custom central processing unit and accelerator designed for scaling artificial intelligence data centers. It will be used in deploying custom silicon, including AWS’s upcoming Tranium4 chips for AI inference and model training and Graviton central processing units.

“GPU compute demand is skyrocketing — more compute makes smarter AI, smarter AI drives broader use and broader use creates demand for even more compute,” said Nvidia founder and Chief Executive Jensen Huang. “The virtuous cycle of AI has arrived.”

In conjunction, AWS is expanding its accelerating computing offerings with Nvidia Blackwell architecture, including Nvidia HGX B300 and GB300 NVL72 graphics processing units.

The company said these GPUs will be added to the AWS infrastructure backbone for AI Factories, a new AI cloud offering for customers worldwide, providing secure, regionally sovereign AI infrastructure for globally situated companies. For the public sector, AI factories will help transform the federal supercomputing and AI landscape with a unified architecture.

With these global datacenters, AWS plans to provide access to advanced AI services and capabilities to deploy and train massive models while maintaining absolute control of proprietary data.

Nvidia Nemotron and AI software expansion

The partnership also expands the integration of Nvidia software with the AWS AI ecosystem. Nvidia Nemotron open models will now be available on Amazon Bedrock, the company’s fully managed service providing access to a large number of foundation models.

Developers can now create generative AI applications and agents using Nemotron Nano 2 and Nemotron Nano 2 VL to build specialized agent-based AI applications capable of processing text, code, images, and videos at scale.

The two companies will also work together to co-engineer the software layer to accelerate data ingestion and processing for enterprise companies by combining technologies.

Amazon OpenSearch Service, a managed, scalable search and analytics service, will now offer serverless GPU acceleration for vector index building, powered by Nvidia cuVS, an open-source library for GPU-accelerated vector search and data clustering.

Production-ready agentic AI will gain from combining Strands Agents for agent development, Nvidia NeMo Agent Toolkit for deep profiling and performance tuning and Amazon Bedrock AgentCore providing scalable agent infrastructure.

Bringing robots to life with physical AI and AWS

Advancing AI-powered robotics requires high-quality and diverse datasets for training foundation models for physical AI, as well as frameworks for testing and validating them in simulation before deploying to the real world.

Physical AI refers to artificial intelligence systems and models designed to interact with the real world through sensing, reasoning and acting through physical machines. These machines can include robots, self-driving cars, smart buildings and intelligent assistants that can interact with the physical world.

Nvidia Cosmos, world foundation models used to simulate the real world virtually for training and the production of synthetic data that’s difficult to gather. The platform speeds up the process of turning small amounts of visual data into large training sets for a wide variety of scenarios.

Cosmos world foundation models are now available as Nvidia NIM microservices on Amazon EKS, the company’s managed Kubernetes service. This will enable real-time robotics control and simulation workloads in the cloud.

The platform also includes models that comprehend real-world physics, object interactions and motion, enabling reasoning about complex situations and predicting outcomes. This capability allows for the development of AI agents that can perform tasks with a deeper understanding of the real world.

Image: SiliconANGLE/Microsoft Designer