0

 

NVIDIA, a company that’s commonly known within gaming circles is actually an 800-pound gorilla in the deep learning, machine learning, and AI space.

At the latest GPU Technology Conference, NVIDIA made a slew of announcements including the launch of Jetson Nano, a low-footprint, extremely affordable computer designed for AI workloads (I was supposed to be at the event, but couldn’t make it due to some last minute changes).

Powered by NVIDIA’s CUDA-X AI chip the ‘board’ offers over 472 GFLOPS of computing performance while sipping only 5 watts. There are two members of the Jetson Nano family – the $99 devkit and the $129 production-ready module.

Hardware specs of the Jetson Nano family:

  • GPU: 128-core NVIDIA Maxwell architecture-based GPU
  • CPU: Quad-core ARM A57
  • Video: 4K @ 30 fps (H.264/H.265) / 4K @ 60 fps (H.264/H.265) encode and decode
  • Camera: MIPI CSI-2 DPHY lanes, 12x (Module) and 1x (Developer Kit)
  • Memory: 4 GB 64-bit LPDDR4; 25.6 gigabytes/second
  • Connectivity: Gigabit Ethernet
  • OS Support: Linux for Tegra
  • Module Size: 70mm x 45mm
  • Developer Kit Size: 100mm x 80mm

The $99 devkit supports desktop Linux for development and supports a plethora of peripherals and accessories. While devkit is targeted at developers and makers, the $129 module is targeted at businesses to integrated this production-ready module into their own devices.

“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.”

On the other hand, the $129 module is designed for companies wanting to integrate into their devices.

You can order the devkit on Seed Studio.

Get latest updates in your inbox, subscibe to our daily newsletter.

Swapnil Bhartiya
I have more than 12 years of experience covering Enterprise Open Source, Cloud, Containers, IoT, Machine Learning and general tech. My stories cover a very broad spectrum - traditional Linux, data center and Free Software to contemporary emerging technologies like 'serverless'. Widely Read: My stories have appeared in a multitude of leading publications including CIO, InfoWorld, Network World, The New Stack, Linux Pro Magazine, ADMIN Magazine, HPE Insights, Raspberry Pi Geek Magazine, SweetCode, Linux For You, Electronics For You and more.