Aetina unveils NVIDIA Jetson Orin Nano and Orin NX edge embedded systems

Aetina AIE-KO21/31 AIE-KN31/41

Aetina has recently announced several embedded systems based on NVIDIA Jetson Orin NX and Orin Nano which they showcased at CES 2023. We’ll specifically have a look at the AIE-KO21/31 and AIE-KN31/41 edge devices designed for mainstream and entry-level edge AI computing. NVIDIA introduced the NVIDIA Jetson Orin NX SO-DIMM modules in March 2022 and followed up with the lower-cost pin-compatible Jetson Orin Nano modules in September with mass production scheduled for Q4 2022 and Q1 2023 respectively. Last week, we covered the first NVIDIA Jetson Orin NX edge AI computer we had seen, namely Seeed Studio reComputer J4012, but it turns out Aetina also announced their own Jetson Orin NX/Orin Nano industrial embedded computers around the same time. Aetina AIE-KO21, AIE-KO31, AIE-KN31, and AIE-KN41 specifications: System-on-module AIE-KO21 – NVIDIA Jetson Orin Nano 4GB with up to 20 TOPS of AI performance AIE-KO31 – NVIDIA Jetson Orin Nano 8GB with […]

Aetina launches ASIC-based Edge AI system with a 16 TOPS Blaize P1600 embedded SoM

Aetina AIE-CP1A-A1 is a compact, ASIC-based Edge AI system powered by the Blaize Pathfinder P1600 embedded system-on-module (SoM) equipped with dual-core Cortex-A53 processor, the Blaize Graph Streaming Processor (GSP) architecture delivering up to 16 TOPS, and 4GB RAM. The Aetina AI inference system also comes with 8GB eMMC flash, HDMI video output, Gigabit Ethernet, two USB 3.2 ports, and a serial interface, with the small-sized embedded computer targetting computer vision applications such as object detection, human motion detection, and automated inspection. Aetina AIE-CP1A-A1 specifications System-on-Module – Blaize PathFinder P1600 SoM SoC – Blaize 1600 dual ArmCortex A53 processor with H.264/H.265 encode and decode, MIPI CSI/DSI camera interfaces, PCIe Gen 3.0, Blaize GSP 16 TOPS AI accelerator supporting  INT8, INT16, BF16, FP16, FP32, and FP64 data formats System Memory – 4GB LPDDR4 Storage – 64 MB Quad SPI NOR Flash Carrier board interface – 400-pin board-to-board connector Cooling – Thermal transfer […]

Aetina DeviceEdge Mini Edge AI computers support NVIDIA Jetson SO-DIMM modules

NVIDIA Jetson modules offer a wide range of AI performance starting from the entry-level 492 GFLOPS Jetson Nano module up to the 32 TOPS Jetson AGX Xavier platform. That’s probably Aetina decided to offer its DeviceEdge Mini AI edge solution with either Jetson Xavier NX, Jetson Nano, or Jetson TX2 NX pin-compatible SO-DIMM modules designed for applications in smart transportation, factories, retail, healthcare, AIoT, robotics, etc… The three models M1, M2, and M3 can all take the Jetson modules listed above, and come in a very similar form factor with the following key features: Common features: Storage – 128GB M.2 NVMe SSD (default) Video Output – Micro HDMI 1.4 connector Networking – Gigabit Ethernet RJ45 port, optional WiFi/Bluetooth M.2 module USB – 1x USB Type-C OTG only port Expansion 1x M.2 2242 M-key socket fitted with NVMe SSD 1x M.2 2230 E-key socket for optional Wifi/BT function 1x DB15 male […]

NVIDIA Jetson TX2i Module is Designed for Industrial Environments

NVIDIA Jetson TX2 “Artificial Intelligence Computer” module was announced in March 2017 with a Tegra X2 hexa-core processor, a 256-core Pascal GPU, 8GB RAM, 32GB storage, and support for 4K 60 fps encoding and decoding. But it turns out NVIDIA announced an rugged version of the module dubbed Jetson TX2i designed for reliable operation in harsh industrial environments in March of this year. NVIDIA Jetson TX2 and TX2i are pin-to-pin compatible, and can run the same software, but TX2i has been designed and tested for rougher conditions. Feature Jetson TX2 Jetson TX2i Shock 140G, 2ms 140G, 2ms Vibration 10Hz ~200Hz, 1g & 2g RMS Random: 5g RMS 10 to 500Hz Sinusoidal: 5g RMS 10 to 500Hz Temp Range -25°C – 80°C -40°C – 85°C Humidity 85°C / 85% RH, 168 hours -10°C to 65°C / 95% RH, 240 hours Operating Life 5 Years (GB at 35C: MTBF=1,747,520 hours GF at […]