Nvidia Jetson AGX Xavier Developer Kit

Can a tiny black box really be at the heart of Nvidia’s attempt to crack open the artificial intelligence market? Gareth Halfacree investigates.

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Mention the name Nvidia and most people will immediately think of gaming. Mention the name around Linux users, and some may bring to mind Linus Torvalds’ infamous gesticulation-punctuated rant against the company’s poor Linux support, during a 2012 question-and-answer session at the Finnish Aalto Centre for Entrepreneurship.

While the bulk of Nvidia’s revenue does, indeed, come from the gaming market, and the company’s support for Linux on its mainstream product families has, indeed, been traditionally lacklustre, that’s not the full story. For several years now the company has been working on its own Linux platform called Linux4Tegra, a tweaked version of Canonical’s Ubuntu, as part of an attempt to become the de facto provider of high-performance embedded hardware for deep learning and artificial intelligence tasks.

“AI-powered autonomous machines and intelligent systems are going to impact nearly every industry,” Nvidia’s Jesse Clayton claimed during a recent press briefing. “In manufacturing, today about 10 per cent of tasks are automated and the remaining 90 per cent can’t be automated because they’re too hard for today’s fixed function robots. But using GPUs and AI, our customers are starting to take on that remaining 90 per cent.”

Some AI tasks are best given over to cloud servers or high-end workstations, but autonomous vehicles, smart robots and other local devices don’t have that option. The solution is edge computing: high performance, low-power hardware that can provide AI-focused computation without the space or power requirements of a traditional workstation.