NVIDIA Nano is a $99 computer for AI developers
Nvidia has unveiled the Jetson Nano, a US$99 computer for running modern AI (artificial intelligence) workloads for the edge
The CUDA-X AI delivers 472 GFLOPS of compute performance for running modern AI workloads. Processing power is sufficient for neural networks, high-res sensors, and other robotic features while consuming as little as five watts.
It’s also Linux-ready out of the box, and supports popular AI frameworks, making it easy for developers to integrate preferred models and frameworks into the product.
Unveiled at the GPU Technology Conference by NVIDIA founder and CEO Jensen Huang, Jetson Nano comes in two versions: the US$99 devkit for developers, makers and enthusiasts, and the US$129 production-ready module for companies looking to create mass-market edge systems.
Nvidia Jetson Nano: the Raspberry Pi of AI? https://t.co/fsA8ZQm4X0 pic.twitter.com/NG5PLDnTEi
— Tom’s Hardware (@tomshardware) March 19, 2019
As such, the Nano is aimed at a broad audience of enterprises, startups and researchers, according to NVIDIA, who introduced the computer alongside its two other other models, the AGX Xavier for fully-autonomous machines and TX2 for AI at the edge.
“Jetson Nano makes AI more accessible to everyone — and is supported by the same underlying architecture and software that powers our nation’s supercomputers”, said Deepu Talla, vice president and general manager of Autonomous Machines at NVIDIA.
“Bringing AI to the maker movement opens up a whole new world of innovation, inspiring people to create the next big thing,” Talla added.
The Nano’s low-cost means that it could enable what the company hopes will be a “new wave of innovation” from makers, inventors, developers, and students, who previously could not afford or access the technology needed for AI projects. Its creator’s imagined use cases include mobile robots, drones, digital assistants, automated appliances, and more.
“The Jetson Nano Developer Kit is exciting because it brings advanced AI to the DIY movement in a really easy-to-use way,” said Chris Anderson of DIY Robocars, DIY Drones and the Linux Foundation’s Dronecode project.
“We’re planning to introduce this technology to our maker communities because it’s a powerful, fun and affordable platform that’s a great way to teach deep learning and robotics to a broader audience.”
The Jetson Nano module is expected to bring life to a new world of embedded applications, including network video recorders, home robots, and intelligent gateways will full analytics.
One software stack is used across the entire Jetson family, and the NVIDIA Cuda-X has accelerated libraries for deep learning, computer vision, computer graphics, and multimedia processing.