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    Yahboom Jetson Orin Nano 8GB SUB Super Developer Kit 67TOPS Support Super Kit Jetpack6.2 Linux with 256GB SSD, Power Supply, M.2 Wireless Network Card

    Limited time offer, ends 02/01 By Dazan Technology

    • Orin Nano 8GB SUB Camera Advanced Kit
    • Orin Nano 8GB SUB Developer Kit
    • Orin Nano 8GB SUB Mini PC Kit
    • Core ParametersAI Perf: 34/67 TOPS GPU:1024-core NVIDIA Ampere architecture GPU with 32 Tensor Cores CPU:6-core Arm Corte-A78AE v8.2 64-bit CPU 1.5MB L2 + 4MB L3 Memory:8GB 128-bit LPDDR5 68 GB/s Storage: external NVMe via M.2 Key M
    • Empowered by Large Al Model, Enhanced Human-Computer InteractionJetson Orin Super leverages three AI models and incorporates an AI voice interaction module. This multimodal visual system matches the scene being described, enabling environmental awareness and AI visual gameplay. Combined with a large-scale voice module and camera, it enables speech-to-text, semantic analysis, natural conversation, and real-time video analysis, enabling advanced embodied AI applications.
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    Any questions? Our AI beta will help you find out quickly.

    1. AI UpgradeJetson Orin Nano series modules are compact in size but can deliver up to 34-67 TOPS of AI performance, with power consumption ranging from 7 watts to 25 watts. Compared to the Jetson Nano B01, it offers up to 80 times the performance and sets a new standard for entry-level edge AI.
    2. Highly compatible carrier boardYahboom's carrier board is fully compatible with orin nano module. Compared to carrier boards that use Jetson Nano on the market, the newly upgraded circuit supports 25W power mode, which enables larger and more complex neural networks and fully leverages the performance of the core module. The resources, size, and interfaces of the Yahboom carrier board are consistent with the official board, with the only difference addition of power switch button.
    3. Tutorial materials providedThe JETSON system based on Ubuntu 22.04 provides a complete desktop Linux environment with accelerated graphics, supporting NVIDI-ACUDA 12.6, TensorRT 10.7.0, cuDNN 9.6.0, OpenCV 4.10.0, etc. The performance on AI LLM, VLM and visual Transformer is significantly improved compared with the previous generation.


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