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- NVIDIA Jetson Nano Developer Kit
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ერთეულის #:
11825723
NVIDIA Jetson Nano Developer Kit
ერთეულის #:
11825723
GEL 1099
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NVIDIA Jetson Nano Developer Kit delivers the compute performance to run modern AI workloads at unprecedented size, power, and cost.
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What Stands Out
Powerful GPU
Equip your projects with a 128-core Maxwell GPU, delivering impressive performance for deep learning and image processing tasks in a compact, energy-efficient format.
Ease of Use
Designed for developers, the Jetson Nano Kit simplifies integrating AI into various applications, offering a plug-and-play experience with extensive community support and resources for rapid development.
Affordable AI
Access high-performance AI capabilities without breaking the bank. The NVIDIA Jetson Nano provides exceptional value for developers and hobbyists looking to create innovative projects at an affordable price.
Პროდუქტის აღწერილობა
- NVIDIA Jetson Nano developer kit is a low-cost AI computer. It delivers the compute performance to run modern AI workloads at unprecedented size. It is incredibly power-efficient, consuming as little as 5 watts.
- It is supported by NVIDIA Jetpack, used across the entire NVIDIA Jetson family of products, reducing complexity and overall effort for developers, learners, and makers.
- "NVIDIA Jetson Nano Developer Kit delivers the compute performance to run modern AI workloads at unprecedented size, power, and cost. The developer kit can be powered by micro-USB and comes with extensive I/Os, ranging from GPIO to CSI. This makes it simple for developers to connect a diverse set of new sensors to enable a variety of AI applications. It’s incredibly power-efficient, consuming as little as 5 watts. Jetson Nano is also supported by NVIDIA Jet Pack, available using an easy-to-flash SD card image, making it fast and easy to get started. This proven software stack reduces complexity and overall effort for developers. Jetson Xavier is designed for robots, drones and other autonomous machines that need maximum compute at the edge to run modern AI workloads and solve problems in manufacturing, logistics, retail, service, agriculture and more. Jetson Xavier is also suitable for smart city applications and portable medical devices. The NVIDIA Jetson Xavier Developer Kit includes: Jetson Xavier module: > 512-core NVIDIA Volta GPU with tensor cores > 64-bit 8-core NVIDIA Carmel CPU > 16GB 256-bit wide LPDDR4X Memory > 32GB eMMC 5. 1 Storage Reference carrier board with I/O: > USB 3. 1 Type A/eSATA with 5V power > 2 USB Type C (DP/USB 3. 1) > Micro USB (for UART console access) > HDMI > M. 2 Key E > M. 2 Key M > Combined Micro SD/UFS > PCIe x8 controller on a x16 connector > Gigabit Ethernet > GPIOs, UART, I2C, I2S, SPI, CAN* > Camera Expansion Connector* > Automation Header* > Audio Panel Header* 65W power supply with AC cord Type A to Type C cable (USB 3. 1 Gen2) Type A to Type C adapter, (USB 3. 1 Gen 1) * Refer to product documentation for specification of I/O Expansion Headers "
| RAM Memory Installed | 4 GB |
| Memory Storage Capacity | 16 GB |
| Connectivity Technology | GPIO, USB |
| Operating System | Ubuntu |
| Processor Brand | ARM |
| Wireless Compability | Bluetooth |
| Compatible Devices | Camera |
| RAM Memory Technology | DDR SDRAM |
| Processor Count | 4 |
| Total Usb Ports | 4 |
| Brand | NVIDIA |
| Model Name | Nano |
| Built-In Media | 2x 15-pin 2-lane MIPI CSI-2 camera connectors |
| UPC | 812674023809 |
| Global Trade Identification Number | 00812674023809 |
| Model Number | 945-13450-0000-000 |
| Mfr Part Number | 945-13450-0000-000 |
| Manufacturer | NVIDIA |
| Item Weight | 249 Grams |
| Ram Memory Installed Size | 4 GB |
| Package Weight | 1.27 Pound |
What's in the box
2x 15-pin 2-lane MIPI CSI-2 camera connectors
Who Should Buy?
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AI Developers
Ideal for developers designing AI applications, offering powerful GPU capabilities and ease of integration with existing platforms.
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Robotics Enthusiasts
Perfect for hobbyists and professionals building robots, providing necessary computational power for real-time processing and machine learning.
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Education Purposes
Great for students and educators focusing on AI and robotics, offering an accessible introduction to deep learning technologies.
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Casual Users
Not suitable for users seeking simple computing tasks as it requires programming knowledge and familiarity with AI development.
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High-End Gaming
Not designed for gaming, as its performance may not meet the demands of modern gaming applications and graphics.
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Large Scale Deployments
Less ideal for industrial applications needing high compute power, as Jetson Nano is geared towards smaller projects and prototypes.
პროდუქტის აღწერილობა
გაქვთ რაიმე შეკითხვა? მოგვმართეთ ჩათში
მომხმარებელთა შეკითხვები და პასუხები
-
კითხვა:
What is the NVIDIA Jetson Nano Developer Kit used for?
პასუხი: The NVIDIA Jetson Nano Developer Kit is a powerful platform designed for machine learning and AI projects. It enables developers to build applications that require deep learning capabilities, such as robotics, smart cameras, and IoT devices. With a 128-core GPU and support for popular ML frameworks like TensorFlow and PyTorch, this kit allows you to execute complex models efficiently, making it ideal for students, educators, and hobbyists exploring the fields of AI and robotics. -
კითხვა:
What kind of projects can I build with the NVIDIA Jetson Nano?
პასუხი: You can create a variety of innovative projects with the NVIDIA Jetson Nano, including autonomous robots, intelligent drones, and advanced image recognition systems. The kit's versatility supports applications in healthcare, agriculture, and smart cities. For instance, you can develop a real-time object detection system for a drone or a home automation system that utilizes AI to learn and automate tasks based on user behavior, showcasing the kit's potential in diverse settings. -
კითხვა:
What are the main specifications of the NVIDIA Jetson Nano Developer Kit?
პასუხი: The NVIDIA Jetson Nano Developer Kit features a quad-core ARM Cortex-A57 CPU and a 128-core Maxwell GPU, providing exceptional processing power for AI tasks. Additionally, it includes 4GB of LPDDR4 RAM and supports various interfaces such as USB 3.0, HDMI, and GPIO. This configuration offers a perfect balance of performance and efficiency, allowing developers to run multiple applications simultaneously while managing energy consumption effectively. -
კითხვა:
How do I get started with the NVIDIA Jetson Nano?
პასუხი: Starting with the NVIDIA Jetson Nano involves setting up the development environment, which includes installing the JetPack SDK. You’ll need a microSD card for the operating system, which you can easily flash with NVIDIA's tools. Once configured, you can access various sample projects and tutorials provided by NVIDIA, helping you learn the fundamentals of AI programming and project development, paving the way for your innovative applications. -
კითხვა:
Can the NVIDIA Jetson Nano be used for deep learning training?
პასუხი: While the NVIDIA Jetson Nano is primarily designed for deploying pre-trained models, it can perform some lightweight training tasks. Its architecture allows for inference and fine-tuning of models but is not suitable for training large models from scratch due to limitations in power and memory. Users often employ it to run smaller scale experiments or to understand the deployment pipeline in real-world scenarios before using more powerful GPUs for extensive training. -
კითხვა:
What accessories are recommended for the NVIDIA Jetson Nano?
პასუხი: Recommended accessories for the NVIDIA Jetson Nano include a microSD card with a minimum of 16GB for optimal performance, a compatible power supply, and a cooling solution, as it can heat up under load. Additionally, expansion boards and USB peripherals can enhance your development experience. For instance, a camera module can enable computer vision projects, while an external keyboard and mouse are essential for initial setup and coding. -
კითხვა:
Is the NVIDIA Jetson Nano suitable for beginners?
პასუხი: Yes, the NVIDIA Jetson Nano is beginner-friendly, especially for those interested in AI and robotics. It comes with comprehensive documentation, tutorials, and a supportive community, making it accessible for newcomers. Hands-on learning through pre-built sample applications helps new users grasp core concepts while providing a platform for more advanced exploration as they grow their skills in machine learning and AI development. -
კითხვა:
What is the power consumption of the NVIDIA Jetson Nano?
პასუხი: The NVIDIA Jetson Nano consumes approximately 5 to 10 watts of power, depending on the tasks it is performing. This low-power design makes it suitable for battery-operated applications in robotics and IoT devices. As a practical example, users often deploy it on drones or edge devices where energy efficiency is crucial, allowing extended operation without the need for frequent recharging or power sources. -
კითხვა:
Can I run Linux on the NVIDIA Jetson Nano?
პასუხი: Absolutely! The NVIDIA Jetson Nano is powered by a customized version of Ubuntu Linux, specifically optimized for NVIDIA's AI capabilities. Users can leverage the JetPack SDK to access a rich set of libraries and tools tailored for AI and machine learning development. This Linux environment not only supports a variety of programming languages but also allows for seamless integration with other Linux software and libraries, enhancing the development process. -
კითხვა:
Where can I buy the NVIDIA Jetson Nano Developer Kit in Georgia?
პასუხი: You can purchase the NVIDIA Jetson Nano Developer Kit from Ubuy, which offers a reliable platform for buying electronic gadgets and components. They provide a range of products including the latest developer kits, ensuring you get access to genuine items and assistance throughout your purchase. Ubuy’s convenient interface makes it easy to search for the Jetson Nano and other essential accessories for your projects.
NVIDIA Single Board Computers 945-13450-0000-000 Editorial Review
The NVIDIA Jetson Nano, a single-board computer for AI applications, is reviewed and questioned in this article. The board is said to come with no power adapter, and a strong adapter is recommended, as adapters that are too cheap should be avoided. As for programming, users can develop on it with Python and C, but must consider that the board is an ARM architecture. Additionally, the board can run Ubuntu Linux and several neural networks with GPU acceleration. However, there are some complaints about its value and difficulty in utilizing its hardware acceleration capabilities.
Customer Reviews & Ratings
277 მომხმარებლის შეფასება
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5 ვარსკვლავი
79%
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4 ვარსკვლავი
11%
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3 ვარსკვლავი
6%
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2 ვარსკვლავი
1%
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1 ვარსკვლავი
3%
ამ პროდუქტის მიმოხილვა
გაუზიარეთ თქვენი აზრები სხვა მომხმარებლებს
Დადებითი
- Ideal for AI applications
- Plenty of memory and processing power
- Strong compatibility as well as tutorials available
- Upgradeable operating system
მინუსები
- No power adapter included
Product Price History
მნიშვნელოვანი ინფორმაცია
- შეზღუდვები: გთხოვთ, გაითვალისწინოთ, რომ საზღვარგარეთ გაგზავნილი პროდუქტებისთვის მწარმოებლის გარანტია შეიძლება არ იყოს მოქმედი; მწარმოებლის მომსახურების პარამეტრები შეიძლება არ იყოს ხელმისაწვდომი; პროდუქტის ინსტრუქციები და უსაფრთხოების გაფრთხილებები შეიძლება არ იყოს დანიშნულების ქვეყნის ენაზე; პროდუქტები (და მასთან დაკავშირებული მასალები) შეიძლება არ იყოს შემუშავებული დანიშნულების ქვეყნის სტანდარტების, სპეციფიკაციებისა და მარკირების მოთხოვნების შესაბამისად; და პროდუქტები შეიძლება არ შეესაბამებოდეს დანიშნულების ქვეყნის ძაბვისა და სხვა ელექტრო სტანდარტებს (საჭიროების შემთხვევაში საჭიროა ადაპტერი ან გადამყვანი). მიმღები პასუხისმგებელია უზრუნველყოს, რომ პროდუქტი კანონიერად შემოიტანოს დანიშნულების ქვეყანაში. Ubuy-ს ან მისი აფილირებული პირების მეშვეობით შეკვეთისას მიმღები არის რეგისტრირებული იმპორტიორი და მან უნდა გაითვალისწინოს დანიშნულების ქვეყნის ყველა კანონი და დებულება.
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მახასიათებლები და უპირატესობები
- Low-cost AI computer
- Incredibly power-efficient
- Supported by NVIDIA Jetpack
- Extensive I/Os available
- Fast and easy to get started
- Proven software stack