Amid the festivities at the GTC Fall 2022 conference, Nvidia took the lids off new robotics-related devices and services aimed at companies developing and testing machines across industries such as manufacturing. The company said that Isaac Sim, Nvidia’s robotics simulation platform, will soon be available in the cloud. And Nvidia’s lineup of the system expands on units with the Jetson Orin Nano, a system designed for low-power robotics — as well as a new platform called IGX.
Isaac Sim, which launched in open beta last June, allows designers to simulate the interaction of robots with real-world mockups (think digitally recreating warehouses and factory floors). Users can create data sets from simulated sensors to train models on real-world robots, and leverage synthetic data from sets of unique, parallel simulations to improve model performance.
It’s not just marketing, necessarily. Some research suggests that synthetic data has the potential to address many of the development challenges faced by companies trying to power AI. MIT researchers recently found a way to do this Classification of images using synthetic dataand almost every major independent car company Uses simulation data To supplement the real world data they collect from cars on the road.
Nvidia says that the upcoming version of Isaac Sim — available on AWS RoboMaker and Nvidia NGC, where it can be deployed in any public cloud, and soon on Nvidia’s Omniverse Cloud platform — will include the company’s real-time mission to the company’s fleet and route planning engine, Nvidia cuOpt, to improve Android route planning.
“With Isaac Sim in the cloud…teams can be around the world while sharing a virtual world to simulate and train bots,” Nvidia Senior Director of Product Marketing Gerard Andrews 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 set up, manage and review simulation results.”
Jetson Oren Nano
This past March, Nvidia introduced the Jetson Orin, the company’s next generation of personal computers based on the company’s high-end computing use cases. The first in the group was Jetson AGX Orin, and Orin Nano expanded the wallet with more affordable configurations.
Said Orin Nano delivers up to 40 trillion operations per second (TOPS) – the number of computing operations a chip can handle at 100% utilization – in Jetson’s smallest form factor to date. It sits on the entry-level side of the Jetson family, which now includes six Orin-based production units dedicated to a range of bots and local offline computing applications.
Orin Nano comes in modules compatible with Nvidia’s previously announced Orin NX, and supports AI application pipelines with Ampere GPU architecture – Ampere is the GPU architecture that Nvidia launched in 2020. Two versions will be available in January starting at $199: Orin Nano 8GB, which offers up to 40 TOPS with configurable power from 7W to 15W, and Orin Nano 4GB, which offers up to 20 TOPS with low power options from 5W to 10W.
“More than 1,000 customers and 150 partners have adopted the Jetson AGX Orin since Nvidia announced its availability just six months ago, and Orin Nano will greatly expand that adoption,” Nvidia Vice President of Embedded and Advanced Computing Deepu Talla said in a statement. (Compared to the Orin Nano, the Jetson AGX Orin costs over a thousand dollars — needless to say, a big delta.) “With a massive increase in performance for millions of high-end AI and [robotics] Developers Jetson Orin Nano sets a new standard for robotics and AI for beginners.”
In news that almost slipped from under our radar, Nvidia previewed IGX, a platform for “high-resolution” artificial intelligence — especially manufacturing and logistics applications. The company claims that it provides an additional layer of security and AI performance with low latency in highly regulated environments, such as factories, warehouses, clinics, and hospitals.
The IGX platform includes the IGX Orin, an artificial intelligence chip for autonomous industrial and medical devices. Developer kits will be available early next year for organizations to model and test products, Nvidia says, each with an integrated GPU, CPU, and software suite with security and security capabilities that can be programmed and configured for different use cases.
Nvidia says it is working with operating system partners such as Canonical, Red Hat, and SUSE to provide integrated, long-term support for IGX.
“As humans increasingly work with robots, industries are setting new job security standards for artificial intelligence 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.”