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At its GTC event today, Nvidia debuted Jetson AGX Orin, which it claims is among the world’s smallest, most energy-efficient AI accelerators for robotics and edge devices. Built on Nvidia’s Ampere architecture, Jetson AGX Orin delivers a claimed 6 times the processing power of its predecessor, Jetson AGX Xavier: up to 200 trillion operations per second.
The launch of Jetson AGX Orin comes as the market for edge computing hardware climbs steeply during the pandemic. Edge computing brings computation, data storage, and power closer to the source of data generation, allowing for more immediate insights from connected systems. In addition, edge computing affords potential savings from reduced cloud costs and greater reliability in the event of network disruptions.
According to IBM, companies expect investments in edge computing to yield a positive return on investment within three years. Meanwhile, Statista anticipates that the edge computing market will be worth $10.96 billion by 2026.
“As robotics and embedded computing transform manufacturing, healthcare, retail, transportation, smart cities, and other essential sectors of the economy, the demand for processing continues to surge,” Nvidia’s VP and general manager of embedded and edge computing Deepu Talla said. “Jetson AGX Orin addresses this need, enabling the 850,000 Jetson developers and over 6,000 companies building commercial products on it to create and deploy autonomous machines and edge AI applications that once seemed impossible.”
Jetson AGX Orin features an Ampere GPU and Arm Cortex-A78AE CPUs, along with “next-generation” AI and vision accelerators. High-speed interfaces and faster memory bandwidth, plus multimodal sensor support, provide the ability to feed multiple concurrent AI application pipelines, Nvidia says.
Jetson AGX Orin powers Nvidia’s Clara Holoscan, a new platform for the health care industry that allows developers to build software-defined medical devices that run low-latency streaming applications on the edge. “The new Jetson platform brings the performance and versatility of the Ampere architecture to enable even further advancements in [systems] for a wide range of applications,” Tirias Research principal analyst Jim McGregor said in a statement, “ranging from agriculture and manufacturing to health care and smart cities.”
Edge computing offers several advantages compared with cloud-based technologies, but it isn’t without challenges. Keeping data locally means more locations to protect, with increased physical access allowing for different kinds of cyberattacks. (Some experts argue the decentralized nature of edge computing leads to increased security.) And compute is limited at the edge, which restricts the number of tasks that can be performed.
Even so, Gartner predicts that more than 50% of large organizations will deploy at least one edge computing application to support the internet of things (IoT) or immersive experiences by the end of 2021, up from less than 5% in 2019. The number of edge computing use cases will jump even further in the upcoming years, with the firm expecting that more than half of large enterprises will have at least six edge computing use cases deployed by the end of 2023.
According to Nvidia, the Jetson AGX Orin module and developer kit will be available in the first quarter of 2022.