If the goal is to bring AI to IoT and edge computing then there should be WiFi. I don’t understand NVIDIA’s decision there and I don’t believe it should be up to the end user of the product to “bring their own WiFi adapter”. …and if that’s the case, why is there not a WiFi adapter on the device? The NVIDIA Jetson Nano is marketed as being a powerful IoT and edge computing device for Artificial Intelligence… Secondly, when it comes to your 5V 2.5A MicroUSB power supply, in their documentation NVIDIA specifically recommends this one from Adafruit.įinally, you will need an ethernet cable when working with the Jetson Nano which I find really, really frustrating. I, therefore, recommend a 32GB micro-SD card for your Nano. The first time I configured my Jetson Nano I used a 16GB card, but that space was eaten up fast, particularly when I installed the Jetson Inference library which will download a few gigabytes of pre-trained models.
I really want to stress the minimum of a 16GB micro-SD card. Before you get started with the Jetson Nanoīefore you can even boot up your NVIDIA Jetson Nano you need three things:
We’ll then wrap up the tutorial with a brief discussion on the Jetson Nano - a full benchmark and comparison between the NVIDIA Jetson Nano, Google Coral, and Movidius NCS will be published in a future blog post. I’ll then show you how to access the camera on your Jetson Nano and even perform image classification and object detection on the Nano as well. I’ll then show you how to install the required system packages and prerequisites.įrom there you will configure your Python development library and learn how to install the Jetson Nano-optimized version of Keras and TensorFlow on your device. In the first part of this tutorial, you will learn how to download and flash the NVIDIA Jetson Nano. At around $100 USD, the device is packed with capability including a Maxwell architecture 128 CUDA core GPU covered up by the massive heatsink shown in the image. To learn how to get started with the NVIDIA Jetson Nano, just keep reading! Getting started with the NVIDIA Jetson Nano Figure 1: In this blog post, we’ll get started with the NVIDIA Jetson Nano, an AI edge device capable of 472 GFLOPS of computation. I’ll also provide my commentary along the way, including what tripped me up when I set up my Jetson Nano, ensuring you avoid the same mistakes I made.īy the time you’re done with this tutorial, your NVIDIA Jetson Nano will be configured and ready for deep learning!
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