{"id":62108,"date":"2022-03-16T14:44:13","date_gmt":"2022-03-16T06:44:13","guid":{"rendered":"https:\/\/www.seeedstudio.com\/blog\/?p=62108"},"modified":"2022-03-30T13:41:46","modified_gmt":"2022-03-30T05:41:46","slug":"everything-you-want-to-know-before-getting-nvidia-agx-orin-dev-kit-on-hands","status":"publish","type":"post","link":"https:\/\/www.seeedstudio.com\/blog\/2022\/03\/16\/everything-you-want-to-know-before-getting-nvidia-agx-orin-dev-kit-on-hands\/","title":{"rendered":"NVIDIA Jetson AGX Orin: 275 TOPS, 2048 NVIDIA\u00ae CUDA\u00ae cores, 64 Tensor Cores, best AI performance of NVIDIA Jetson Family"},"content":{"rendered":"\n<div class=\"wp-block-image\"><figure class=\"aligncenter\"><img decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/NVIDIA-AGX-Orin-Dev-Kit.png\" alt=\"\"\/><\/figure><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">NVIDIA Jetson AGX Orin: A Giant Leap Forward for Robotics and Edge AI with 275 TOPS, 2048 NVIDIA\u00ae CUDA\u00ae cores, 64 Tensor Cores<\/h2>\n\n\n\n<p><strong>? Exciting news!  <a href=\"https:\/\/www.seeedstudio.com\/NVIDIA-Jetson-AGX-Orin-Developer-Kit-p-5314.html\">NVIDIA Jetson AGX Orin Developer Kit<\/a> is available to pre-order at Seeed now, be the first one get AGX Orin Dev kit now! <\/strong><\/p>\n\n\n\n<p>At GTC 2021 and 2022, NVIDIA introduced Jetson AGX Orin Module and Dev kit, the latest and the most powerful GPU so far in the Jetson family. <meta charset=\"utf-8\">Jetson AGX Orin is ready embedded into next-gen autonomous machines, robotics,<span style=\"font-size: revert; color: initial; font-family: -apple-system, BlinkMacSystemFont, &quot;Segoe UI&quot;, Roboto, Oxygen-Sans, Ubuntu, Cantarell, &quot;Helvetica Neue&quot;, sans-serif;\"> or drones working for retail, manufacturing, transportation, AgTech, smart city, aerospace, etc.<\/span> Let&#8217;s check out all the exciting features! <\/p>\n\n\n\n<ul class=\"wp-block-list\"><li>Most powerful member from Jetson family: NVIDIA Jetson AGX Orin is based on  Ampere architecture with 2048 NVIDIA\u00ae CUDA\u00ae cores and 64 Tensor Core.<\/li><li>Compact leap forword to edge AI: same form factor at 100mm x 87mm and same pin compatibility as compared to Jetson AGX Xavier, delivering 8x the AI performance with 270 TOPS.<\/li><li>Support large and complex deep learning models to solve problems such as natural language understanding, 3D perception, and multi-sensor fusion.<\/li><li>Supported by NVIDIA JetPack\u2122 and specific software platforms including Isaac for robotics, Clara for healthcare, and Metropolis for smart cities. <\/li><\/ul>\n\n\n\n<p>Stay tuned with us for more tutorials, applications and ecosystem updates around <meta charset=\"utf-8\">NVIDIA Jetson AGX Orin and all Jetson families! <\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-full is-resized\"><img fetchpriority=\"high\" decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/Jetson-AGX-Orin-1.png\" alt=\"\" class=\"wp-image-62115\" width=\"422\" height=\"248\" srcset=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/Jetson-AGX-Orin-1.png 562w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/Jetson-AGX-Orin-1-300x177.png 300w\" sizes=\"(max-width: 422px) 100vw, 422px\" \/><figcaption>Jetson AGX Orin<a href=\"https:\/\/emojipedia.org\/camera\/\">?<\/a>: <a href=\"https:\/\/nvidianews.nvidia.com\/news\/nvidia-sets-path-for-future-of-edge-ai-and-autonomous-machines-with-new-jetson-agx-orin-robotics-computer\">NVIDIA<\/a><\/figcaption><\/figure><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Jetson AGX Orin Module Technical Specifications<\/h2>\n\n\n\n<p>The Jetson AGX Orin is using the NVIDIA Ampere architecture GPU with 2048 NVIDIA\u00ae CUDA\u00ae cores and 64 Tensor cores and 12-core Arm Cortex-A78AE v8.2 64-bit CPU.<\/p>\n\n\n\n<p>AGX Orin developer kit contains a Jetson AGX Orin module with heat sink and reference carrier board, 802.11ac\/abgn wireless Network Interface Controller, USB-C power adapter, and cord together with a quick start and support guide.<\/p>\n\n\n\n<figure class=\"wp-block-table aligncenter is-style-stripes\"><table><tbody><tr><td>AI Performance<\/td><td class=\"has-text-align-left\" data-align=\"left\">275 TOPS (INT8)<\/td><\/tr><tr><td>GPU<\/td><td class=\"has-text-align-left\" data-align=\"left\">NVIDIA Ampere architecture<br>with 2048 NVIDIA<sup>\u00ae<\/sup>&nbsp;CUDA<sup>\u00ae<\/sup>&nbsp;cores and 64 Tensor Cores<\/td><\/tr><tr><td>Max GPU Freq<\/td><td class=\"has-text-align-left\" data-align=\"left\">1 GHz<\/td><\/tr><tr><td>CPU<\/td><td class=\"has-text-align-left\" data-align=\"left\">12-core Arm<sup>\u00ae<\/sup>&nbsp;Cortex<sup>\u00ae<\/sup>-A78AE v8.2 64-bit CPU<br>3MB L2 + 6MB L3<\/td><\/tr><tr><td>CPU Max Freq<\/td><td class=\"has-text-align-left\" data-align=\"left\">2 GHz<\/td><\/tr><tr><td>DL Accelerator<\/td><td class=\"has-text-align-left\" data-align=\"left\">2x NVDLA v2.0<\/td><\/tr><tr><td>Vision Accelerator<\/td><td class=\"has-text-align-left\" data-align=\"left\">PVA v2.0<\/td><\/tr><tr><td>Memory<\/td><td class=\"has-text-align-left\" data-align=\"left\">32GB 256-bit LPDDR5<br>204.8 GB\/s<\/td><\/tr><tr><td>Storage<\/td><td class=\"has-text-align-left\" data-align=\"left\">64GB eMMC 5.1<\/td><\/tr><tr><td>CSI Camera<\/td><td class=\"has-text-align-left\" data-align=\"left\">Up to 6 cameras (16 via virtual channels*)<br>16 lanes MIPI CSI-2<br>D-PHY 1.2 (up to 40Gbps) | C-PHY 1.1 (up to 164Gbps)<\/td><\/tr><tr><td>Video Encode<\/td><td class=\"has-text-align-left\" data-align=\"left\">2x 4K60 | 4x 4K30 | 8x 1080p60 | 16x 1080p30 (H.265)<\/td><\/tr><tr><td>Video Decode<\/td><td class=\"has-text-align-left\" data-align=\"left\">1x 8K30 | 3x 4K60 | 6x 4K30 | 12x 1080p60| 24x 1080p30 (H.265)<\/td><\/tr><tr><td>UPHY<\/td><td class=\"has-text-align-left\" data-align=\"left\">2 x8 (or 1&#215;8 + 2&#215;4), 1 x4, 2 x1 (PCIe Gen4, Root Port &amp; Endpoint)<br>3x USB 3.2<br>Single lane UFS<\/td><\/tr><tr><td>Networking<\/td><td class=\"has-text-align-left\" data-align=\"left\">1x GbE<br>4x 10GbE<\/td><\/tr><tr><td>Display<\/td><td class=\"has-text-align-left\" data-align=\"left\">1x 8K60 multi-mode DP 1.4a (+MST)\/eDP 1.4a\/HDMI 2.1<\/td><\/tr><tr><td>Other I\/O<\/td><td class=\"has-text-align-left\" data-align=\"left\">4x USB 2.0<br>4x UART, 3x SPI, 4x I2S, 8x I2C, 2x CAN, DMIC &amp; DSPK, GPIOs<\/td><\/tr><tr><td>Power<\/td><td class=\"has-text-align-left\" data-align=\"left\">15W | 30W | 50W<\/td><\/tr><tr><td>Mechanical<\/td><td class=\"has-text-align-left\" data-align=\"left\">100mm x 87mm<br>699-pin Molex Mirror Mezz Connector<br>Integrated Thermal Transfer Plate<\/td><\/tr><\/tbody><\/table><figcaption>Reference: <a href=\"https:\/\/www.nvidia.com\/en-us\/autonomous-machines\/embedded-systems\/jetson-agx-orin\/\">NVIDIA<\/a>, *Virtual Channel-related camera information for Jetson AGX Orin is not final and subject to change.<\/figcaption><\/figure>\n\n\n\n<p><strong>Jetson AGX Orin Reference Carrier Board<\/strong><\/p>\n\n\n\n<figure class=\"wp-block-table is-style-stripes\"><table><tbody><tr><td>Camera<\/td><td>16 lane MIPI CSI-2 connector<\/td><\/tr><tr><td>PCIe<\/td><td>x16 PCIe slot supporting x8 PCIe Gen4<\/td><\/tr><tr><td>RJ45<\/td><td>Up to 10 GbE<\/td><\/tr><tr><td>M.2 Key M<\/td><td>x4 PCIe Gen 4<\/td><\/tr><tr><td>USB Type-C<\/td><td>2x USB 3.2 Gen2 with USB-PD support<\/td><\/tr><tr><td>USB Type-A<\/td><td>4x USB 3.2 Gen2<\/td><\/tr><tr><td>USB Micro-B<\/td><td>USB 2.0<\/td><\/tr><tr><td>DisplayPort<\/td><td>DisplayPort 1.4a (+MST)<\/td><\/tr><tr><td>microSD slot<\/td><td>UHS-1 cards up to SDR104 mode<\/td><\/tr><tr><td>Other<\/td><td>40-pin header (I2C, GPIO, SPI, CAN, I2S, UART, DMIC)<br>12-pin automation header10-pin audio panel header<br>10-pin JTAG header<br>4-pin fan header<br>2-pin RTC battery backup connector<br>DC power jack<br>Power,<br>Force Recovery, and Reset buttons<\/td><\/tr><tr><td>Dimensions<\/td><td>110mm x 110mm x 71.65mm<br>(Height includes feet, carrier board, module, and thermal solution)<\/td><\/tr><\/tbody><\/table><\/figure>\n\n\n\n<p>We recommend you check the&nbsp;<a href=\"https:\/\/www.nvidia.com\/content\/dam\/en-zz\/Solutions\/gtcf21\/jetson-orin\/nvidia-jetson-agx-orin-technical-brief.pdf\">technical brief&nbsp;<\/a>to learn more about the new Jetson AGX Orin module.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Get started with Jetson Software with necessary ML tools <\/h2>\n\n\n\n<p>Jetson Platform includes all the necessary ML tools to accelerate your next AI product quickly to market. <meta charset=\"utf-8\">At the base of the software stack, JetPack SDK includes the Board Support Package (BSP), with boot loader, Linux kernel, drivers, toolchains, and a reference file system based on Ubuntu. <\/p>\n\n\n\n<p>Jetson Software comprises JetPack SDK, TAO &amp; Pretrained AI Models from the NVIDIA NGC\u2122 catalog, Triton Inference Server, NVIDIA Riva, DeepStream SDK, and NVIDIA Isaac. You could check the&nbsp;<a href=\"https:\/\/developer.nvidia.com\/embedded\/develop\/software\">Jetson Software website<\/a>&nbsp;for a more detailed explanation before getting your hands-on with Jetson AGX Orin. <\/p>\n\n\n\n<p>Jetson software also supports containers and container orchestration, which brings cloud-native to the edge. NVIDIA JetPack includes NVIDIA Container Runtime with Docker integration, enabling GPU accelerated containerized applications on Jetson platform. With NVIDIA Triton\u2122 Inference Server, you can also simplify models deployment for AI production at the scale. <\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter is-resized\"><a href=\"https:\/\/developer.nvidia.com\/embedded\/develop\/software\"><img decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/Jetson-ecosystem-1030x484.png\" alt=\"\" width=\"773\" height=\"363\"\/><\/a><figcaption>Jetson Software Ecosystem ?: <a href=\"https:\/\/developer.nvidia.com\/embedded\/develop\/software\">NVIDIA<\/a><\/figcaption><\/figure><\/div>\n\n\n\n<h2 class=\"wp-block-heading\">Accelerate inferencing on the GPU using NVIDIA TensorRT and cuDNN<\/h2>\n\n\n\n<p>NVIDIA<sup>\u00ae<\/sup>&nbsp;TensorRT\u2122 is an SDK for high-performance deep learning inference. It includes a deep learning inference optimizer and runtime that delivers low latency and high throughput for deep learning inference applications.<\/p>\n\n\n\n<p>With TensorRT, developers can focus on creating novel AI-powered applications rather than performance tuning for inference deployment.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-large is-resized\"><img decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-37-1030x615.png\" alt=\"\" class=\"wp-image-62234\" width=\"773\" height=\"461\" srcset=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-37-1030x615.png 1030w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-37-300x179.png 300w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-37-768x458.png 768w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-37-1536x917.png 1536w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-37-1024x611.png 1024w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-37.png 1578w\" sizes=\"(max-width: 773px) 100vw, 773px\" \/><figcaption>? NVIDIA: <a href=\"https:\/\/developer.nvidia.com\/tensorrt#features\">TensorRT<\/a><\/figcaption><\/figure><\/div>\n\n\n\n<p>cuDNN (CUDA Deep Neural Network library) is an acceleration library developed by NVIDIA for deep neural networks. It is a GPU acceleration library for deep neural networks. cuDNN enables high-performance GPU acceleration focused on training neural networks and developing software applications.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large\"><img loading=\"lazy\" decoding=\"async\" width=\"1030\" height=\"246\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-38-1030x246.png\" alt=\"\" class=\"wp-image-62235\" srcset=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-38-1030x246.png 1030w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-38-300x72.png 300w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-38-768x184.png 768w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-38-1536x367.png 1536w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-38-2048x489.png 2048w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/image-38-1024x245.png 1024w\" sizes=\"(max-width: 1030px) 100vw, 1030px\" \/><figcaption>?NVIDIA: <a href=\"https:\/\/developer.nvidia.com\/cudnn\">cuDNN Accelerated Frameworks<\/a><\/figcaption><\/figure>\n\n\n\n<h3 class=\"wp-block-heading\">New Jetpack 5.0<\/h3>\n\n\n\n<p>According to the Jetson software roadmap, JetPack 5.0 (the current latest version is <a href=\"https:\/\/developer.nvidia.com\/embedded\/jetpack\">JetPack 4.6.1<\/a>) will install Ubuntu 20.04, support Orin and Xavier Jetson modules. JetPack 5.0 preview release is targeted for Q1 2022 and the production release is targeted for the second half of 2022.<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/JetPack_Key_Features_2021-12-1030x579.png\" alt=\"\" class=\"wp-image-62238\" width=\"840\" height=\"472\" srcset=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/JetPack_Key_Features_2021-12-1030x579.png 1030w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/JetPack_Key_Features_2021-12-300x169.png 300w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/JetPack_Key_Features_2021-12-768x432.png 768w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/JetPack_Key_Features_2021-12-1024x576.png 1024w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/JetPack_Key_Features_2021-12.png 1152w\" sizes=\"(max-width: 840px) 100vw, 840px\" \/><figcaption>? NVIDIA: <a href=\"https:\/\/developer.nvidia.com\/sites\/default\/files\/akamai\/embedded\/images\/slides\/roadmap\/JetPack_Key_Features_2021-12.png\">Compare Jetpack 4.6 and Jetpack 5.0<\/a><\/figcaption><\/figure>\n\n\n\n<h2 class=\"wp-block-heading\">For next-gen autonomous machines<\/h2>\n\n\n\n<p>With Jetson AGX Orin Module that\u2019s having 200 TOPS AI processing power (as compared to AGX Xavier which has 32 TOPS) on the developer kit, developers can deploy machine learning models in solving demanding challenges in edge AI applications for manufacturing, logistics, retail, service, agriculture, smart city, healthcare, and life science<\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Autonomous driving vehicles<\/h3>\n\n\n\n<p>Robotics such as in \u201creal-time critical\u201d autonomous driving vehicles in the enterprise setting which generally need to have a response within a millisecond and only possible with a lot of TOPS. There are six levels of self-driving cars &#8211; L0 (no automation), L1 (driver assistance), L2 (partial automation), L3 (conditional automation), L4 (high automation), and L5 (full automation) and the<a href=\"https:\/\/www.gsaglobal.org\/forums\/autonomous-vehicles-and-ai-chip-innovation\/\">&nbsp;computing power required for each level of self-driving vehicle<\/a>&nbsp;will be less than 10 TOPS for L2, 30 to 60 TOPS for L3, more than 100 TOPS for L4, and predictions of around 1,000 TOPS for L5.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter is-resized\"><a href=\"https:\/\/www.gsaglobal.org\/forums\/autonomous-vehicles-and-ai-chip-innovation\/\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/sae.png\" alt=\"\" width=\"448\" height=\"172\"\/><\/a><figcaption>Computational Requirements for different SAE Levels ?: <a href=\"https:\/\/developer.nvidia.com\/embedded\/develop\/software\">GSAGLOBAL<\/a><\/figcaption><\/figure><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Retail<\/h3>\n\n\n\n<p>Using Machine Learning capabilities on NVIDIA Jetson platform, it can improve the <a href=\"https:\/\/www.nvidia.com\/en-us\/industries\/retail\/warehouse-logistics\/\">forecast accuracy for inventory management<\/a>. This has a significant impact on optimizing the supply chain.&nbsp; Machine Learning algorithms can be trained faster with NVIDIA\u2019S&nbsp;<a href=\"https:\/\/developer.nvidia.com\/rapids\">RAPIDS<\/a>&nbsp;open-source data processing and machine learning libraries, which enabled retailers to forecast the demand of the products for their stores more efficiently and restock accordingly according to the shopper trends. This helps in inventory cost savings at scale.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/nvidia-1030x579.jpg\" alt=\"\" class=\"wp-image-62129\" width=\"515\" height=\"290\" srcset=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/nvidia-1030x579.jpg 1030w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/nvidia-300x169.jpg 300w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/nvidia-768x432.jpg 768w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/nvidia-1024x576.jpg 1024w, https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/nvidia.jpg 1200w\" sizes=\"(max-width: 515px) 100vw, 515px\" \/><figcaption>Retail Solution ?: <a href=\"https:\/\/www.nvidia.com\/en-in\/industries\/retail\/\">NVIDIA<\/a><\/figcaption><\/figure><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Manufacturing<\/h3>\n\n\n\n<p>Manufacturing factories are making use of&nbsp; logistics robots running on <a href=\"https:\/\/resources.nvidia.com\/en-us-industrial-and-edge-ai\/bmw-to-redefine-fact?lb-mode=overlay&amp;lb-width=100&amp;lb-height=100\">NVIDIA\u2019s open Isaac robotics<\/a> software platform architecture to automate the production capabilities.&nbsp;With the advanced logistics robots, this enabled the transport of&nbsp; material autonomously, while manipulation robots select and organize parts. <\/p>\n\n\n\n<div class=\"wp-block-image is-style-default\"><figure class=\"aligncenter is-resized\"><a href=\"https:\/\/developer.nvidia.com\/isaac-sim\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/issac-1030x557.png\" alt=\"\" width=\"515\" height=\"279\"\/><\/a><figcaption>NVIDIA Isaac Sim ?: NVIDIA<\/figcaption><\/figure><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Traffic<\/h3>\n\n\n\n<p>The AI development pipeline can be accelerated with existing collected traffic data set with the pretrained&nbsp;<a href=\"https:\/\/ngc.nvidia.com\/catalog\/models\/nvidia:tlt_trafficcamnet\">TrafficCamNet<\/a>&nbsp;model from NGC, and the NVIDIA TAO Toolkit on the Jetson NVIDIA Jetson edge AI platform. This has helped cut development time to just a few weeks,&nbsp;<a href=\"https:\/\/developer.nvidia.com\/blog\/metropolis-spotlight-sighthound-enhances-traffic-safety-with-nvidia-gpu-accelerated-ai-technologies\/\">delivering a traffic safety solution <\/a>to the city that automatically detects, counts, and measures speed and tracks pedestrian, bicycle, and vehicle occupancy.<\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter is-resized\"><a href=\"https:\/\/catalog.ngc.nvidia.com\/orgs\/nvidia\/models\/tlt_trafficcamnet\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/traffic-1030x579.png\" alt=\"\" width=\"515\" height=\"290\"\/><\/a><figcaption>TrafficCamNet ?: <a href=\"https:\/\/ngc.nvidia.com\/catalog\/models\/nvidia:tlt_trafficcamnet\">NVIDIA<\/a><\/figcaption><\/figure><\/div>\n\n\n\n<h3 class=\"wp-block-heading\">Healthcare<\/h3>\n\n\n\n<p>The development and deployment of smart sensors with multimodal AI can be accelerated with the&nbsp;<a href=\"https:\/\/www.nvidia.com\/en-sg\/clara\/smart-hospitals\/\">NVIDIA Clara\u2122 Guardian<\/a>, an application framework and partner ecosystem.&nbsp;Clara Guardian enables real-time insights to ensure safety through social distancing, fever screening, protective gear detection, and high-risk patient monitoring&nbsp;through fusing <a href=\"https:\/\/resources.nvidia.com\/en-us-healthcare-and-edge-ai\/smarter-healthcare-solution-brief?lb-mode=overlay&amp;lb-width=100&amp;lb-height=100\">intelligent video analytics and conversational AI capabilities.<\/a><\/p>\n\n\n\n<div class=\"wp-block-image\"><figure class=\"aligncenter is-resized\"><a href=\"https:\/\/developer.nvidia.com\/clara-guardian\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/www.seeedstudio.com\/blog\/wp-content\/uploads\/2022\/03\/clara-1030x579.jpg\" alt=\"\" width=\"515\" height=\"290\"\/><\/a><figcaption>NVIDIA Clara Guardian ?: <a href=\"https:\/\/developer.nvidia.com\/clara-guardian\">NVIDIA<\/a><\/figcaption><\/figure><\/div>\n\n\n\n<p>At Seeed, you will find everything you want to work with&nbsp;<a href=\"https:\/\/www.seeedstudio.com\/tag\/nvidia.html\">NVIDIA Jetson Platform<\/a>&nbsp;\u2013 official NVIDIA Jetson Dev Kits, Seeed-designed carrier boards, and kits, as well as third-party boards and accessories.<\/p>\n\n\n\n<p>Seeed will continue working on the Jetson product line and will be ready to combine our partners\u2019 unique skills with Seeed\u2019s hardware expertise for an end-to-end solution.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>NVIDIA Jetson AGX Orin: A Giant Leap Forward for Robotics and Edge AI with 275<\/p>\n","protected":false},"author":3577,"featured_media":62093,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_lmt_disableupdate":"","_lmt_disable":"","_price":"","_stock":"","_tribe_ticket_header":"","_tribe_default_ticket_provider":"","_tribe_ticket_capacity":"0","_ticket_start_date":"","_ticket_end_date":"","_tribe_ticket_show_description":"","_tribe_ticket_show_not_going":false,"_tribe_ticket_use_global_stock":"","_tribe_ticket_global_stock_level":"","_global_stock_mode":"","_global_stock_cap":"","_tribe_rsvp_for_event":"","_tribe_ticket_going_count":"","_tribe_ticket_not_going_count":"","_tribe_tickets_list":"[]","_tribe_ticket_has_attendee_info_fields":false,"iawp_total_views":0,"footnotes":""},"categories":[1],"tags":[4222,1312,4224,1824],"class_list":["post-62108","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-agx-orin","tag-nvidia","tag-nvidia-agx-orin-dev-kit","tag-nvidia-jetson"],"yoast_head":"<!-- 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