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Develop IoT and AI Applications with NVIDIA Jetson Nano

NVIDIA Jetson Nano lets you bring incredible new capabilities to millions of small, power-efficient AI systems. It opens new worlds of embedded IoT applications, including entry-level Network Video Recorders (NVRs), home robots, and intelligent gateways with full analytics capabilities. It is also the perfect tool to start learning about AI and robotics in real-world settings.

NVIDIA Jetson Nano lets you bring incredible new capabilities to millions of small, power-efficient AI systems.

Nvidia Jetson Nano vs. Raspberry Pi

  • Performance – The Jetson Nano has a much more powerful processor than the Raspberry Pi and the Coral Board with Edge TPU, both of which have Arm Cortex A53-based CPUs, while the Nano’s uses the more advanced Cortex A57 platform. The Nano also has 4GB of RAM as compared to just 1GB of its competitors. Even if you are not running AI applications and you just want to run Linux applications, you would get more power from Nvidia’s computer.
  • Computer on SODIMM Card – It is quite easy to see that the CPU and GPU are actually on a separate board that plugs into a 260-pin SODIMM slot on the main PCB that houses the ports and connectors. Considering this Nvidia also makes a standalone Jetson Nano compute unit, which has 16GB of onboard storage with a powerful RAM of 4GB DDR4.
  • Size and Weight – The Jetson Nano Developer kit board is much larger than the largest Raspberry Pi, the Pi 3B+. Obviously, it needs the added space, particularly because of the heat sink and the SODIMM slot. Nvidia Jetson Nano board is 3.8 x 3 inches (95.3 x 76.2 mm) and weighs 4.8 ounces (136 grams) while the Pi 3B+ is a mere 3.4 x 2.3 inches (87 × 58.5 mm) and weighs just 1.8 ounces (49.7 grams).
  • Linux OS – The official operating system for the Jetson Nano and other Jetson boards is called Linux4Tegra, which is actually a version of Ubuntu 18.04 that is designed to run on Nvidia’s hardware. Raspberry Pi OS (previously called Raspbian) is our official supported operating system for Raspberry Pi.
  • AI Experience – Jetson Nano has the ability to perform AI workloads such as object identification, motion tracking and video smoothing. It boasts of an Nvidia Maxwell 128 CUDA core GPU that is optimized for machine learning. This offers 472 GFLOPS for AI performance as opposed to the 21.4 GFLOPs you get from Raspberry Pi model 3B+.

Conclusion

The Jetson Nano Developer Kit provides an affordable, yet powerful way to start developing not only AI and IoT Applications but also to deploy them. If you are a machine learning and IoT enthusiast, and you want your mini-board to process the data, Jetson Nano is a perfect choice. With the addition of GPU, Jetson does look promising.

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