Amid celebrations at its GTC conference in fall 2022, Nvidia unveiled new robotics-related hardware and services aimed at companies that design and test machines in various industries such as manufacturing. Isaac Sim, Nvidia’s robotics simulation platform, will soon be available in the cloud, the company said. And Nvidia’s range of system-on-modules expands with Jetson Orin Nano, a system designed for low-power robots – plus a new platform called IGX.
Isaac Sim, which launched in open beta last June, allows designers to simulate robots interacting with real-world models (think digital recreations of warehouses and factory floors). Users can generate datasets from simulated sensors to train the models on real robots, using synthetic data from batches of parallel unique simulations to improve the model’s performance.
It’s not necessarily just marketing babble. Some research suggests that synthetic data has the potential to address many of the development challenges faced by organizations trying to operationalize AI. MIT researchers recently found a way to classify images using synthetic data, and nearly all major autonomous vehicle companies use simulation data to supplement the real-world data they collect from cars on the road.
Nvidia says the forthcoming release of Isaac Sim — which is available on AWS RoboMaker and Nvidia NGC, from where it can be deployed to any public cloud, and soon on Nvidia’s Omniverse Cloud platform — will be the company’s real-time fleet task assignment will include and route planning engine Nvidia cuOpt to optimize robot path planning.
“With Isaac Sim in the cloud…teams can be located around the world while sharing a virtual world in which to simulate and train robots,” wrote Gerard Andrews, Nvidia’s senior product marketing manager, in a blog post. “Running Isaac Sim in the cloud means developers are no longer tied to a powerful workstation to run simulations. Any device will be able to set up, manage and review the results of simulations.”
Jetson Orin Nano
Back in March, Nvidia Jetson introduced Orin, the company’s next-generation Arm-based single-board PCs for edge computing use cases. First in line was the Jetson AGX Orin, and Orin Nano expands the portfolio with more affordable configurations.
The aforementioned Orin Nano delivers up to 40 trillion operations per second (TOPS) — the number of arithmetic operations the chip can handle at 100% utilization — in the smallest Jetson form factor yet. It sits at the entry-level of the Jetson family, which now includes six Orin-based production modules intended for a range of robotics and offline local computing applications.
Available in modules compatible with Nvidia’s previously announced Orin NX, the Orin Nano supports AI application pipelines with Ampere architecture GPU – Ampere is the GPU architecture Nvidia launched in 2020. Two versions will be available in January starting at $199: Orin Nano 8GB, which delivers up to 40 TOPS with power configurable from 7W to 15W, and the Orin Nano 4GB, which delivers up to 20 TOPS with power options from only reaches 5W to 10W.
“Over 1,000 customers and 150 partners have chosen Jetson AGX Orin since Nvidia announced its availability just six months ago, and Orin Nano will significantly expand that adoption,” said Deepu Talla, Nvidia’s VP of Embedded and Edge Computing, in an explanation. (Compared to the Orin Nano, the Jetson AGX Orin costs well over a thousand dollars—a significant delta, of course.) “With an order of magnitude increase in performance for millions of edge AI and [robotics] Developer Jetson Orin Nano is setting new standards for entry-level edge AI and robotics.”
In news that nearly slipped under our radar, Nvidia previewed IGX, a platform for “high-precision” edge AI – specifically manufacturing and logistics applications. The company claims it offers an additional layer of security and low-latency AI performance in highly regulated environments such as factories, warehouses, clinics and hospitals.
The IGX platform includes IGX Orin, an AI chip for autonomous industrial machines and medical devices. Developer kits will be available early next year for companies to prototype and test products, Nvidia says, each with an integrated GPU and CPU and a software stack with security features that can be programmed and configured for different use cases.
Nvidia says it’s working with OS partners like Canonical, Red Hat, and SUSE to provide long-term, full-stack support for IGX.
“As humans increasingly work with robots, industries are setting new functional safety standards for AI and computing,” Nvidia CEO Jensen Huang said in a statement. “IGX will help companies build the next generation of software-defined industrial and medical devices that operate safely in the same environment as humans.”