Developing more intelligent robots in the cloud is about to get a speed multiplier.
NVIDIA Isaac Sim and NVIDIA L40S GPUs are coming to Amazon Web Services, enabling developers to build and deploy accelerated robotics applications in the cloud. Isaac Sim, an extensible simulator for AI-enabled robots, is built on the NVIDIA Omniverse development platform for building and connecting OpenUSD applications.
Combining powerful AI compute with graphics and media acceleration, the L40S GPU is built to power the next generation of data center workloads. Based on the Ada Lovelace architecture, the L40S enables ultrafast real-time rendering delivering up to a 3.8x performance leap for Omniverse compared with the previous generation, boosting engineering and robotics teams.
The generational leap in acceleration results in 2x faster performance than the A40 GPU across a broad set of robotic simulations tasks when using Isaac Sim.
L40S GPUs can also be harnessed for generative AI workloads, from fine-tuning large language models within a matter of hours, to real-time inferencing for text-to-image and chat applications.
New Amazon Machine Images (AMIs) on the NVIDIA L40S in AWS Marketplace will enable roboticists to easily access preconfigured virtual machines to operate Isaac Sim workloads.
Robotics development in simulation is speeding the process of deploying applications, turbocharging industries such as retail, food processing, manufacturing, logistics and more.
Revenue from mobile robots in warehouses worldwide is expected to explode, more than tripling from $11.6 billion in 2023 to $42.2 billion by 2030, according to ABI Research.
Robotics systems have played an important role across fulfillment centers to help meet the demands of online shoppers and provide a better workplace for employees. Amazon Robotics has deployed more than 750,000 robots in its warehouses around the world to improve the experience for employees supporting package fulfillment and its customers.
Simulation technology plays a critical role in how we develop, test and deploy our robots. said Brian Basile, head of virtual systems at Amazon Robotics. At Amazon Robotics we continue to increase the scale and complexity of our simulations. With the new AWS L40S offering we will push the boundaries of simulation, rendering and model training even further.
Accelerated Robotics Development With Isaac Sim Robotics systems can demand large datasets for precision operation in deployed applications. Gathering these datasets and testing them in the real world is time-consuming, costly and impractical.
Robotics simulation drives the training and testing of AI-based robotic applications. With synthetic data, simulations are enabling virtual advances like never before. Simulations can help verify, validate and optimize robot designs, systems and their algorithms before operation. It can also be used to optimize facility designs before construction or remodeling starts for maximum efficiencies, reducing costly manufacturing change orders.
Isaac Sim offers access to the latest robotics simulation tools and capabilities as well as cloud access, enabling teams to collaborate more effectively. Access to the Omniverse Replicator synthetic data generation engine in Isaac Sim allows machine learning engineers to build production-ready synthetic datasets for training robust deep learning perception models.
Customer Adoption of Isaac Sim on AWS AWS early adopters tapping into the Isaac Sim platform include Amazon Robotics, Soft Robotics and Theory Studios.
Amazon Robotics has begun using Omniverse to build digital twins for automating, optimizing and planning its autonomous warehouses in virtual environments before deploying them into the real world.
Using Isaac Sim for sensor emulation, Amazon Robotics will accelerate development of its Proteus autonomous mobile robot, improving it to help the online retail giant efficiently manage fulfillment.
Learn more about Isaac Sim, powered by NVIDIA Omniverse.
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Developing more intelligent robots in the cloud is about to get a speed multiplier.
