NVIDIA Jetson Nano Developer Kit - AI Computer for Learning & Making Expand

NVIDIA Jetson Nano Developer Kit - AI Computer for Learning & Making

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The incredible NVIDIA Jetson Nano Developer Kit lets you dive headfirst into AI Development, allowing you to learn AI whilst Making awesome projects!

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Here at DIYElectronics, although we certainly love to fiddle and tinker with Electronics, sometimes we also like to go a bit deeper into the coding side, as hardware can only take projects so far before needing some software to take it further. This is why we have been making a concerted effort to bring in exciting new software-based electronics, with this NVIDIA Jetson Nano Developer Kit – The AI Computer Designed for Learning & Making – being one of the most exciting AI/IoT products that we’ve ever had the pleasure of carrying.

This awesome AI & Deep Learning Development Board is designed by the world-famous NVIDIA corporation, the inventors of the world’s first GPU, but instead of focussing on graphics like the graphics cards that many of us have in our personal computers, the NVIDIA Jetson Nano utilises the extremely capable GPU for parallel computing instead. This allows Makers to simultaneously Learn about AND Make AI and Machine Learning, with an absolute mountain-load of support and open-source software that is all meant to help both newbies and veterans in mastering the AI world. In fact, NVIDIA have done such an impressive job at providing support and resources for this platform that they have a comprehensive “Two Days to a Demo” Tutorial Project that anyone can utilise to create an entire deep learning project from absolute scratch, in as little as two days depending on how quickly you can grasp the concepts.

In terms of the actual functionality of the NVIDIA Jetson Nano, this board is capable of so much more than any Arduino or Raspberry Pi, with a core focus on AI Development, parallel computing and various machine learning processes like simulation generation, object identification and classification, as well as segmentation. This makes it an ideal board for learning all the in’s and out’s of machine learning, while also being able to cater to professional applications too – allowing you to learn, create, enhance, and then start the cycle over once again as you develop your skills and ultimately master the world of AI Frameworks and Deep Learning.


How Does the NVIDIA Jetson Nano Compare to Other AI Platforms?

With such an impressive company behind this AI Development Platform, it’s not surprising that this is one of the most supported and well-documented platforms available to not just Makers, but everyone! Additionally, with NVIDIA’s mastery of the GPU, you can be certain that the GPU within the NVIDIA Jetson Nano is quite literally the very best parallel computing module that could possibly be used for a module in this price range.

Furthermore, in terms of functionality and diverse capabilities, the NVIDIA Jetson Nano is also equipped with rather unique parts, with the 40-Pin (Raspberry Pi style) GPIO being a welcome addition that lets it control actuators, receive from Sensors, and interact with many other types of modules, with built-in compatibility for many of the popular Modules from Adafruit, SparkFun and other top names. In addition to that, it also features both a DisplayPort and an HDMI port to cater to a wider range of display units, a dedicated MIPI CSI-2 Port for connecting up  IMX219 Camera Modules, broken out pins for I2C, I2S, ISP and UART, and even two options for powering the device via Micro USB or Barrel Jack. These fantastic ports and onboard features, along with four USB 3.0 ports for connecting up a diverse range of different peripherals, makes the NVIDIA Jetson Nano one of the most versatile and capable AI Development Boards on the market – which can still fit snugly into a hobbyist’s budget.

We must admit though, that if there’s one thing that’s sorely missing from the NVIDIA Jetson Nano, it’s a dedicated audio port for audio and speech processing. However, with that being said, you can still use the 40-Pin GPIO Header or serial interfaces to connect Audio Modules like microphones, amplifier modules, DAC modules and other audio-based components, although it may not be quite as easy as it would if there was a dedicated audio input port.

As a final note, when taking a closer look at the mechanical specifications of the board, it certainly does look very well-crafted, clean and neatly laid out to be aesthetically striking and “beefy”. All of the parts, upon inspection, are high quality Components, and it seems like NVIDIA have done extremely well in actually considering what the end user would want from the board. As such, it has pleasantly surprised us, as we weren’t expecting such high quality from such a nicely-priced board, and with a 1 Year manufacturer warranty to boost the value just that little bit more, we understand why so many AI Makers consider this to be the best introduction board into the world of AI Frameworks and Deep Learning.

Please Note: While experimenting with one of the amazing boards, we found that it was best practice to plug all of the peripherals, displays and other extras in before plugging in the power. This is because the NVIDIA Jetson Nano automatically boots up once power is plugged in, and if some peripherals aren’t connected during startup, they may not behave like you expect.


NVIDIA Jetson Nano Developer Kit  -  Technical Specifications:

  • GPU                                                        

– 128-Core NVIDIA Maxwell

  • GPU Frequency (Typical)

– 921MHz

  • CPU

– 64-bit Quad-Core ARM Cortex-A57 MPCore

  • CPU Frequency (Typical)

– 1.43GHz

  • Memory

– 4GB 64-bit LPDDR4 RAM

  • Memory Frequency

– 1600MHz

  • AI Performance

– 472 GFLOPs

  • Internal Storage

– N/A

  • External Storage

– MicroSD Card Support (Min. 16GB UHS-1)

  • Display Support

– HDMI 2.0

– DisplayPort 1.2 | eDP 1.4

  • Video Encoding Support

– H.264 / H.265

– 4K @ 30fps

– 4 x 1080p @ 30fps

– 9 x 720p @ 30fps

  • Video Decoding Support

H.264 / H.265

– 4K @ 60fps

– 2 x 4K @ 30fps

– 8 x 1080p @ 30fps

– 18 x 720p @ 30fps

  • USB Ports

– 4 x USB 3.0 Ports

  • Connectivity Support

– Gigabit Ethernet Support (PoE Capable)

– M.2 Slot (PCIe x1) for WiFi Card

– USB Ports for Dongles (Not All Dongles Supported)

  • Camera Support

– MIPI CSI-2 Port (IMX219 Camera Compatible)

  • Additional Interface Ports

– 3 x I2C Pin Sets

– 2 x SPI Pin Sets

– 1 x UART Pin Set

– 1 x I2S Pin Set

– 1 x 40-Pin GPIO Header (Raspberry Pi Layout)

  • Power Input (Micro USB)

– 5V 2A

  • Power Input (DC Barrel Jack)

– 5V 4A

  • Breakout Board Version

– A02 (Single MIPI Port | Includes UART Pins)

  • Included Extras

– Handy Foldout Paper Stand

– Quick Start Card

– Informational & Support Card

  • What You Will Need

– MicroSD Card (Minimum: 16GB UHS-1)

– 5V 2A Micro USB PSU // 5V 4A DC Barrel Jack PSU

– USB Keyboard & Mouse

– Computer Display (HDMI or DP Compatible)

– Access to Computer to Flash MicroSD Card

– USB or IMX219 Camera is Recommended

  • Included Warranty

– 1 Year: Be Sure to Keep Packaging

  • Weight (Packaged)

– ±250g

  • Dimensions (Core Module)

– 69.6 x 45mm

  • Dimensions (Assembled)

– 95.3 x 76.2mm

  • Dimensions (Packaged)

– 100 x 80 x 29mm


Additional Resources:

  • If you’re really eager to dive deep into the technical specifications, benchmarks and more in-depth details about this board, check out this NVIDIA Jetson Nano Dev’ Blog, which offers insights into almost anything you might need to know about this beautiful little computer.
  • Once you’ve gathered all of those juicy details, this next link is a “Two Days to a Demo” GitHub Page, which is a tutorial project designed to help you get a good grasp of machine learning, so that you can ideally deploy your first machine learning project in two days or less.
  • This next link is for those who already know what they’re doing, or for those who have completed the tutorial project in the previous link, and is the primary NVIDIA AI IoT GitHub Page, which is a true treasure trove of awesome resources, tools and more.
  • Finally, this is the Waveshare NVIDIA Jetson Nano Wiki Page, which offers even more links to great resources, forums and repositories, as well as links to further courses and development as well.


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