Amid the festivities at its fall 2022 GTC conference, Nvidia unveiled new robotics-related hardware and services for companies developing and testing machines in industries like manufacturing. Isaac Sim, Nvidia’s robotics simulation platform, will soon be available in the cloud, the company has announced. And Nvidia’s system-on-module lineup is growing with Jetson Orin Nano, a system designed for low-powered robots, as well as a new platform called IGX.
Isaac Sim, which launched in open beta last June, lets designers simulate robots interacting with real-world mockups (think digital recreations of warehouses and factories). Users can generate datasets from simulated sensors to train the models on real-world robots, leveraging synthetic data from unique parallel simulation batches to improve model performance.
It’s not just marketing bluster, necessarily. Some research suggests that synthetic data has the potential to solve many of the development challenges plaguing companies trying to operationalize AI. MIT researchers recently found a way to classify images using synthetic data, and nearly every major autonomous vehicle company uses simulation data to supplement the real-world data they collect from cars on the road.
Nvidia says the next version of Isaac Sim – which is available on AWS RoboMaker and Nvidia NGC, from which it can be deployed to any public cloud, and soon on Nvidia’s Omniverse Cloud platform – will include the company’s real-time fleet task assignment 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,” Gerard Andrews, product marketing manager at Nvidia, wrote in a blog post. . “Running Isaac Sim in the cloud means that developers will no longer be tied to a powerful workstation to run simulations. Any device will be able to configure, manage and review simulation results.
Jetson Music Nano
In March, Nvidia introduced Jetson Orin, the company’s next generation of Arm-based single-board PCs for edge computing use cases. First in the 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 computing operations the chip can handle at 100% utilization – in the smallest Jetson form factor yet. It sits on the entry-level side of the Jetson family, which now includes six Orin-based production modules for a range of off-line local robotics and computing applications.
Shipped in modules compatible with the Orin NX previously announced by Nvidia, the Orin Nano supports AI application pipelines with the Ampere GPU architecture – Ampere being the GPU architecture that Nvidia launched in 2020. Two versions will be available in January starting at $199: the Orin Nano 8GB, which delivers up to 40 TOPS with configurable power from 7W to 15W, and the Orin Nano 4GB, which achieves up to 20 TOPS with optional power as low as 5W to 10W.
“More than 1,000 customers and 150 partners have adopted Jetson AGX Orin since Nvidia announced its availability just six months ago, and Orin Nano will greatly expand that adoption,” said Deepu Talla, Nvidia vice president of embedded and cutting-edge computing, in a press release. (Compared to the Orin Nano, the Jetson AGX Orin costs well over a thousand dollars – needless to say, a substantial delta.) “With an order-of-magnitude increase in performance for millions of cutting-edge AIs and [robotics] Jetson Orin Nano developers are setting a new standard for advanced entry-level robotics and AI.
In news that nearly flew under our radar, Nvidia previewed IGX, a platform for cutting-edge “high precision” AI – specifically manufacturing and logistics applications. The company says it provides an extra 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 machinery and medical devices. According to Nvidia, development kits will be available early next year to allow companies to prototype and test products, each with an integrated GPU and CPU and a software stack with security and safety capabilities that can be programmed and configured for different use cases.
Nvidia says it’s working with operating system partners like Canonical, Red Hat, and SUSE to provide full, long-term 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 can safely operate in the same environment as humans.
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