NVIDIA announced at AWS re:Invent that Isaac Sim now runs on Amazon Elastic Cloud Computing (EC2) G6e instances accelerated by NVIDIA L40S GPUs.
And with the NVIDIA OSMO cloud-native orchestration platform, developers can manage their complex robotics workflows across their AWS computing infrastructure.
Smoother development options through EC2
Field AI is building robot brains that enable robots to autonomously manage a wide range of industrial processes.
Vention creates pre-trained skills to ease the development of robotic tasks.
And Cobot offers Proxie, its AI-powered cobot, designed to handle material movement and adapt to dynamic environments, working seamlessly alongside humans.
These robotics startups are all using NVIDIA Isaac Sim on Amazon Web Services. Isaac Sim is a reference application built on NVIDIA Omniverse for developers to simulate and test AI-driven robots in physically based virtual environments.
This combination of NVIDIA-accelerated hardware and software - available on the cloud - allows teams of any size to scale their physical AI workflows.
NVIDIA describes “physical AI” as AI models that can understand and interact with the physical world. The company says it embodies the next wave of autonomous machines and robots, such as self-driving cars, industrial manipulators, mobile robots, humanoids and even robot-run infrastructure like factories and warehouses.
With physical AI, developers are embracing a three-computer workflow for training, simulation and inference to make breakthroughs.
Yet physical AI for robotics systems requires robust training datasets to achieve precision inference in deployment. Developing such datasets, however, and testing them in real situations can be impractical and costly.
Simulation offers an answer, NVIDIA says, as it can significantly accelerate the training, testing and deployment of AI-driven robots.
Harnessing L40S GPUs in the cloud to scale robotics simulation, training
Simulation is used to verify, validate and optimize robot designs as well as their systems and algorithms before deployment. Simulation can also optimize facility and system designs before construction or remodeling starts to maximize efficiency and reduce costly manufacturing change orders.
NVIDIA says that Amazon EC2 G6e instances accelerated by NVIDIA L40S GPUs provide a 2x performance gain over the prior architecture, while allowing the flexibility to scale as scene and simulation complexity grows.
The instances are used to train many computer vision models that power AI-driven robots. This means the same instances can be extended for various tasks, from data generation to simulation to model training.
Using NVIDIA OSMO in the cloud allows teams to orchestrate and scale complex robotics development workflows across distributed computing resources, whether on premises or in the AWS cloud.
Isaac Sim provides access to the latest robotics simulation capabilities and the cloud, fostering collaboration. One of the critical workflows is generating synthetic data for perception model training.
Learning to be robots in simulation
While Isaac Sim enables developers to test and validate robots in physically accurate simulation, Isaac Lab, an open-source robot learning framework built on Isaac Sim, provides a virtual playground for building robot policies that can run on AWS Batch.
Because these simulations are repeatable, developers can troubleshoot and reduce the number of cycles required for validation and testing.
Several robotics developers, including Standard Bots, Swiss Mile, Cohesive Robotics, Aescape and more are using NVIDIA Isaac on AWS to develop physical AI for a variety of reasons.
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