All posts by jetson

Component

• microSD card (at least 16 GB)
  As Jetson Nano uses a microSD card as a boot device and it need to be fast and large.
• Micro USB Power supply of 5V 2A or DC Power adapter of 5V 4A
  There is compulsorily requirement of actual 5V 2A micro USB or 5V 4A DC adapter, Power supply in which fluctuation occur are not allowed.
• Wired or Wireless USB mouse and Keyboard.
• HDMI screen and cable.
• Network adapter (Optional)

Burn Image to SD card

Formatting of SD card

• First of all you need to format a SD card using SD card formatter
  You download it from : https://www.sdcard.org/downloads/formatter_4/eula_windows/
• Download and install it. 

• Select card drive.
• Select Quick format.
• You can give a name in volume label or you can leave it blank.
• Click Format to start formatting, and “Yes” on the warning dialog.
• After doing this you done with formatting of your SD card, now let’s have a look on how to burn image to SD card.

Write image to MicroSD card

• Now to write image on Sd card you need Etcher
  You can download it from : https://www.balena.io/etcher
• Download and install it. after that the software look like
• As you can in image you need to select image file
  You can download it from : https://developer.nvidia.com/jetson-nano-sd-card-image-r3221
• Here not that you don’t need to unzip the file you can directly select it.
• Then select your SD card in which you want to write image.
• After that press Flash to start writing.
• It will take some time to burn.
• After completing Flash, your SD card is ready to use with Jetson Nano.

Setup and Boot

• Now insert SD card into Jetson Nano Board.
• Connect mouse, keyboard, HDMI cable and Power supply
• After coonecting Power supply it will automatically boot, you can see right bottom side one green LED will blink.

Now you need to configure all basic things first like
First of all accept term and condition and click on continue
after that it will ask you to select country, keyboard etc. you can choose as you preference.
After that you need to enter a name and password for user and that’s it

• Now you can enjoy the development on Jetson Nano

Troubleshooting

Power supply

• If you are using USB power supply than you need good quality power supply and if you want to use DC adapter power supply than in middle left side of Jetson nano you need to connect a Jumper.

Nvidia’s Jetson series of development kits are most likely within range for new companies or devoted enthusiasts, however till recently, it was genuinely hard to get a device able to do any significant AI functionality without shedding a few hundred dollars. But with the Jetson Nano Developer kit the situation has surely changed due to its affordable pricing.

Anybody acquainted with single board PCs (SBC) should feel right comfortable with the Nano. A compact, low voltage System on Chip (SoC) designed to carry out programmed instructions. These kinds of microcomputers are extraordinary for single-purpose computing, or for a modest bunch of assignments with generally low hardware necessities. What’s more, it’s likely reasonable to say that the Nano will have a significant influence in the next stage of evolution for the Maker community.

AI in the Palm of Your Hand

Nvidia has been at the tip of the spear in creating hardware for AI and artificial neural networks, and they’ve downsized a portion of that tech into an incredibly little piece of kit. Taking everything into account. It couldn’t be any more obvious, the Nano itself is only the module underneath that seems as though a beefed up adaptation of PC RAM. The other piece of PCB, the layer with ports and  headers soldered on, is only the development board, which exists to uncover the entirety of the Nano’s inputs and outputs for testing and prototyping.

On that little chip is a 128 Core GPU utilizing Nvidia’s Maxwell architecture, equipped for 472GFLOPS. (Also 4GB of RAM and a quad-center ARM A57 CPU.) FLOPS (or FLoating point OPerations each Second) are an estimation computational power of a processor, and 400 72 billion of them is very useful for a PC more modest than your phone. In case you’re thinking about what GPUs have to do with AI, indeed, the appropriate response truly isn’t that straightforward, however we should attempt to clarify it in any case:

GPUs, obviously, have processor centers and that are genuinely specific for crunching graphic data, however they regularly have an enormous number of such centers. Nvidia team figured out that practically any kind of information, and with the correct calculations , make that data look like graphic data to the GPU, so it could crunch that information productively enough to be helpful. In this way the idea of General Purpose figuring on Graphics Processing Units was conceived.

In the event that you’ve been tracking, at this point you’ll have understood this incorporates AI algorithms. This implies that, basically, Skynet will unavoidably be a thing since you just needed to have a video card that could run Crysis on Ultra settings.

Cool Things to Do With Your Nano

The simplest thing is simply to utilize your Nano as an essential PC. Most other SBCs either have no GUI and can just execute a pre-streaked program, or have a beautiful fundamental, low-goal GUI. Nano, then again, runs practically full Ubuntu Linux, except for the part being incorporated for the ARM processor, and some additional libraries Nvidia chose were imperative to have on their introduce picture.

The coolest thing to do is make a robot, since that is AI as well. Nano can gather and run Python code, and eventually, GPIO pins are GPIO pins.You can add cameras to your robot, and utilize its Nano cerebrum for machine vision. Wire in any sensor you can envision to make your Nano considerably more astute. One you get the hang of some coding and some gadgets, the breaking point is basically your own creative mind.

Future of IOT

With AI-proficient microcomputers like Nvidia’s Jetson Nano, you can play with the cutting edge of AI in your family room. Quite a bit this is open source at the present time, and keeping in mind that nobody will say that any of this stuff is easy to master, but it’s not difficult to begin with in case you’re interested. With the affordability of the Jetson Nano, there will never be been a better time

Artificial Intelligence and Robotics are the two crucial technologies the world is betting on. AI has the potential to create things that could help in creating mind bobbling innovations for the betterment of mankind. In a quest to make the world a better place with the power of AI NVIDIA has introduced Jetson Nano™ 2GB Developer Kit

A part of NVIDIA® Jetson™ AI at the Edge platform, Jetson Nano™ 2GB is an entry-level developer kit that opens the doors of innovation for all. It is an entry-level developer kit is designed for developers, educators, students, and hobbyists to teach and learn AI by creating hands-on projects in areas such as robotics and intelligent IoT.

Aimed at supporting the efforts to make AI accessible to all, NVIDIA has also launched free online training and AI certification programs. These certification programs offer many open-source projects, how-tos and videos contributed by thousands of developers in the vibrant Jetson community. The Jetson Nano™ 2GB Developer Kit is the perfect tool for all those tech freaks who are keen to create innovative robotics solutions.

Getting started with NVIDIA Jetson Nano™ 2GB Developer Kit

Deep Dive into NVIDIA Jetson Nano™ 2GB Developer Kit

Small Size, Big AI Discoveries: The NVIDIA® Jetson Nano™ 2GB Developer Kit is ideal for learning, building, and teaching AI and robotics. It is built for creators and priced for everyone making it accessible to all who aspire to innovate and create solutions for real-time problems. With a familiar Linux environment, easy-to-follow tutorials, and ready-to-build open-source projects created by an active community, it’s the perfect tool for learning by doing.

Flexibility and Performance: The NVIDIA® Jetson Nano™ 2GB Developer Kit can run a diverse set of Al models with powerful performance. This includes an incredible 472 GFLOPS of compute from its 128-core NVIDIA Maxwell™ GPU and 64-bit quad-core Arm A57 CPU. It allows usage of many popular machine learning frameworks such as TensorFlow, PyTorch, MXNet, and others.

Multiple Technology Support: The developer kit supports cloud-native technologies such as containers for easy software install and development environment setup. Also, many popular peripherals for robotics and other Al projects are supported out of the box, including Raspberry Pi, Intel Real-sense, and ZED 30 cameras.

Watch: How developers use Jetson Nano to transform yoga instruction

Modern Software for Modern Al: The Jetson Nano 2GB Developer Kit is powered by the NVIDIA JetPack™ Software Development Kit (SOK) with a familiar Linux desktop environment for designing and building projects. JetPack includes the full NVIDIA stack with GPU-accelerated libraries and SDKs like NVIDIA DeepStream to help you build truly end-to-end Al applications. And it is powered by the same NVIDIA CUDA-X™ accelerated computing stack used to create breakthrough AI products in such fields as self-driving cars, industrial IoT, healthcare, smart cities and more.

Watch: How to build a Robot that Interacts with the World

*Free Jetson Al Course and Certifications: Get certified as a Jetson Al Specialist or Jetson Al Ambassador by completing the Jetson Al Fundamentals course and publishing an open-source Jetson project as part of the assessment. NVIDIA also offers the freely available curriculum and open-source platforms for educators to custom­ build their Al courses.

The Jetson Nano 2GB Developer Kit is truly driving the biggest revolution in industrial AIoT. With the new Jetson Nano 2GB, NVIDIA opens up AI learning and development to a broader audience, using the same software stack as its data center AI computing platform.

NVIDIA Jetson Xavier NX is the world’s smallest, most advanced embedded AI supercomputer designed for autonomous robotics and edge computing devices. Ideal for think mobile robots, drones, smart cameras, portable medical equipment, embedded IoT systems, Jetson Xavier NX is capable of deploying server-class performance in a compact 70x45mm form-factor. It delivers up to 21 TOPS of compute under 15W of power, or up to 14 TOPS of compute under 10W.

XAVIER PERFORMANCE. NANO SIZE

At 70 mm x 45 mm, Jetson Xavier NX packs the power of an NVIDIA Xavier SoC into a module the size of a Jetson Nano. This small module combines exceptional performance and power advantages with a rich set of IOs—from high-speed CSI and PCIe to low-speed I2Cs and GPIOs. Take advantage of the small form factor, sensor-rich interfaces, and big performance to bring new capability to all your embedded AI and edge systems.

POWERFUL 21 TOPS AI PERFORMANCE

Jetson Xavier NX delivers up to 21 TOPS, making it ideal for high-performance compute and AI in embedded and edge systems. You get the performance of 384 NVIDIA CUDA® Cores, 48 Tensor Cores, 6 Carmel ARM CPUs, and two NVIDIA Deep Learning Accelerators (NVDLA) engines. Combined with over 59.7GB/s of memory bandwidth, video encoded, and decode, these features make Jetson Xavier NX the platform of choice to run multiple modern neural networks in parallel and process high-resolution data from multiple sensors simultaneously.

INCREDIBLE POWER EFFICIENCY

Jetson Xavier NX supports multiple power modes, including low-power modes for battery-operated systems, and delivers up to 14 TOPs for AI applications in as little as 10 W. This leaves more of your power budget for sensors and peripherals, while still letting you use the entire NVIDIA software stack. You now have the performance to run all modern AI networks and frameworks with accelerated libraries for deep learning, computer vision, computer graphics, multimedia, and more.

DEVELOP BREAKTHROUGH AI PRODUCTS

Jetson Xavier NX opens up new opportunities for deploying next-generation autonomous systems and intelligent edge devices that require high-performance AI and complex DNN’s in a small, low-power footprint – think mobile robots, drones, smart cameras, portable medical equipment, embedded IoT systems, and more. NVIDIA’s JetPack SDK with support for CUDA-X provides the complete tools to develop cutting-edge AI solutions and scale your application between the cloud and edge with world-leading performance.

DEVELOPER KIT CONTENTS

• NVIDIA Jetson Xavier NX module and reference carrier board
• 19V power supply
• 802.11 plug-in WLAN and Bluetooth® module with antennas (assembled underneath the carrier board)
• Small paper card with quick start and support information

NVIDIA® Jetson™ TX2 series modules give an exceptional speed and power-efficiency in an embedded AI computing device. The Jetson™ TX2 NX delivers the next step in AI performance for entry-level embedded and edge products. It provides up to 2.5X the performance of Jetson Nano, and shares form-factor and pin compatibility with Jetson Nano and Jetson Xavier™ NX.

This small module packs hardware accelerators for the entire AI pipeline, and NVIDIA JetPack™ SDK provides the tools you need to use them for your application. Custom AI network development is easy with pre-trained AI models from NVIDIA NGC™ and the NVIDIA Transfer Learning Toolkit, and containerized deployments make updates for your product flexible and seamless.

Ease of development and speed of deployment—plus a unique combination of form-factor, performance, and power advantage—make Jetson TX2 NX the ideal mass-market AI product platform.

NVIDIA® Jetson™ TX2 series

The extended Jetson TX2 family of embedded modules provides up to 2.5X the performance of Jetson Nano in as little as 7.5 W. Jetson TX2 NX offers pin and form-factor compatibility with Jetson Nano, while Jetson TX2, TX2 4GB, and TX2i all share the original Jetson TX2 form-factor. The rugged Jetson TX2i is ideal for settings including industrial robots and medical equipment.

With Jetson TX2, you can now run large, deep neural networks for higher accuracy on edge devices. At just 7.5 watts, it delivers 25X more energy efficiency than a state-of-the-art desktop-class CPU. This makes it ideal for real-time processing in applications where bandwidth and latency can be an issue. These include factory robots, commercial drones, enterprise collaboration devices, intelligent cameras for smart cities. You can Compare between different Modules here: https://developer.nvidia.com/embedded/jetson-modules

For Comparison of different Modules click below:
https://developer.nvidia.com/embedded/jetson-modules

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