Enhance Your Development Projects with the NVIDIA Jetson Nano Developer Kit (945-13450-0000-100) Review

This board wipes the floor with the best of the Raspberry Pi. It's so responsive and efficient. It doesn't stutter like the Pi with average use. You can actually play YouTube videos on it and forget it's an embedded computer. The built-in heatsink is sufficient for any CPU usage, but if you plan to power this machine-learning GPU, you'll need a fan.

I received this unit a few weeks ago and when I turned it on everything was fine. I downloaded the operating system according to the instructions on the Nvidia website and everything went fine. Until I put the SD card in, I turned it on and the first picture above is what I got. I got another SD card and booted the OS again on the second SD card and the second picture above is what I got. I'm not sure what these error codes and crashes mean and there is no description of their meaning anywhere.

This thing seems totally pos constant boot errors "Flashing OS crashes and burns micro SD cards" , Thing has 3 known good micro SD cards welded. Good luck, I'll get mine back.

Pros: Can handle 4K at 60Hz Cons: I have no idea how to power this unit. Power mode 10W. I tried my 5.25V 3A power supply which works reliably with my Tinker Board S - gas warning. I tried a desktop power supply (5A max) - throttle warning. I tried increasing the voltage to 5.4V - not much difference, it still throttles in 10W mode under load. The voltage is well above 4.75V, I don't see any voltage drop on the exposed 5V/GND pins. For the peripherals connected to the device, there is a…

The Jetson Nano is one of the most underrated single board computers on the market. First, as a generic Ubuntu 18.04 LTS desktop, it's great. Yes, the image is based on an earlier LTS and not the recently released 20.04, but it's a very polished image that Nvidia provides. Even with 4GB of RAM it runs very well thanks to the right set of Nvidia drivers that offer fully accelerated composite window management and WebGL acceleration in Chromium. Nano tends to be fast when running a full-featured…

Jetson Nano is not only great for robotics/edge AI, you can also use ML for scientific purposes like medical imaging or environmental data to speed up the work process . From personal experience, even dual-core power saving mode at a reduced frequency on the Jetson Nano still runs CUDA AI/ML tasks faster than on the Raspberry Pi 4, but your workflow may differ. If you're using AI/ML that isn't optimized for CUDA, the Pi 4's raw CPU calculations can crowd out the Nano in some cases. I would say…

This is my fourth purchase of Jetson Nano and is perfect for AI classification and detection for deep learning using OpenCv or Tensor Flow.

Nvidia Jetson Nano Development Kit is a kit like flour is a chocolate cake kit. An item marked as a kit must have the necessary components to perform certain functions. The Nano is just a board, not a full PC and cannot perform any function on its own.

The most powerful SBC that handles AI/ML tasks for its price. I love edge computing and have many RPIs that I use for my experiments and some of them for building smart home hubs. I bought this to add intelligence to a smart home hub to automatically control my home devices with AI. I gave it a 4 star rating due to the lack of built-in WiFi, which is a very basic requirement, and even the RPi has built-in WiFi. Overall a decent product at a decent price.

I got this unit a few weeks ago and when I turned it on everything was fine. I downloaded the operating system according to the instructions on the Nvidia website and everything went fine. So far I've inserted the SD card, turned it on and the first picture above is what I got. I got another SD card and booted the OS again on the second SD card and the second picture above is what I got. I'm not sure what these error codes and crashes mean and there is no description of their meaning anywhere…

It took a bit of effort but I managed to get VNC working here and so now I have Remote UI access from my Windows machine. I have several Rpis doing different things so I compare them to them. Granted, they're all B models, but this thing is way faster than the ones on the download. I haven't tested anything and don't have the latest rpi to compare, but I suspect they are very similar. That being said, I bought this to do ML. So I wanted to use Anaconda Navigator since that's what I used on…

Jetson Nano is not only great for robotics/edge AI, you can also use ML for scientific purposes such as medical imaging or environmental data to enhance your workflow to accelerate . From personal experience, even dual-core power saving mode at a reduced frequency on the Jetson Nano still runs CUDA AI/ML tasks faster than on the Raspberry Pi 4, but your workflow may differ. If you're using AI/ML that isn't optimized for CUDA, the Pi 4's raw CPU calculations can crowd out the Nano in some cases.