edge impulse

Posted on by Jean-Luc Aufranc (CNXSoft) - 2 Comments on reComputer J4012 mini PC features NVIDIA Jetson Orin NX for AI Edge applications

reComputer J4012 mini PC features NVIDIA Jetson Orin NX for AI Edge applications

reComputer J4021 mini PC

reComputer J4012 is a mini PC or “Edge AI computer” based on the new NVIDIA Jetson Orin NX, a cost-down version of the Jetson AGX Orin, delivering up to 100 TOPS modern AI performance. The mini PC is based on the Jetson Orin NX 16GB, comes with a 128GB M.2 SSD preloaded with the NVIDIA JetPack SDK and offers Gigabit Ethernet, four USB 3.2 ports, and HDMI 2.1 output. Wireless connectivity could be added through the system’s M.2 Key E socket. reComputer J4012 / J401 specifications: SoM – NVIDIA Jetson Orin NX 16GB with CPU – 8x Arm Cortex-A78AE core @ up to 2.0 GHz with 2MB L2 + 4MB L3 cache GPU/AI 1024-core NVIDIA Ampere GPU with 32 Tensor Cores @ up to 918 MHz 2x NVDLA v2.0 @ 614 MHz PVA v2 vision accelerator 100 TOPS AI performance (sparse) Video Encoder  (H.265) 1x 4Kp60 | 3x 4Kp30 6x […]

Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Arducam OCam AI camera adds context to video streams in real-time with the PhysicO platform

Arducam OCam AI camera adds context to video streams in real-time with the PhysicO platform

Arducam OCam, whose name stands for Object Camera, is an AI camera with 3 TOPS of AI performance and designed to work with OStream‘s PhysicO Edge AI media platform that adds context to MP4 video streams in real-time. The camera supports resolutions from QVGA to 2K, takes USB or PoE power, comes with a drag-and-drop AI pipeline for easy programming/configuration, and is also compatible with common AI tools such as TensorFlow, PyTorch, Edge Impulse, and others. Arducam OCam specifications: Resolution – QVGA up to 2K Frame Rate – Up to 60 fps FoV – 80° Audio – Dual beamforming AI processing power – Up to 3 TOPS Power Supply 5V via USB PoE Power Consumption – Up to 5 Watts Dimensions – 10 cm Φ x 3 cm Weight – 400 grams As I understand it, the AI pipeline – named ObjectAgent – runs on the camera itself, and adds […]

Posted on by Jean-Luc Aufranc (CNXSoft) - No Comments on Edge Impulse Enables Machine Learning on Cortex-M Embedded Devices

Edge Impulse Enables Machine Learning on Cortex-M Embedded Devices

Artificial intelligence used to happen almost exclusively in the cloud, but this introduces delays (latency) for the users and higher costs for the provider, so it’s now very common to have on-device AI on mobile phones or other systems powered by application processors. But recently there’s been a push to bring machine learning capabilities to even lower-end embedded systems powered by microcontrollers, as we’ve seen with GAP8 RISC-V IoT processor or Arm Cortex-M55 core and the Ethos-U55 micro NPU for Cortex-M microcontrollers, as well as Tensorflow Lite. Edge Impulse is another solution that aims to ease deployment of machine learning applications on Cortex-M embedded devices (aka Embedded ML or TinyML) by collecting real-world sensor data, training ML models on this data in the cloud, and then deploying the model back to the embedded device. The company collaborated with Arduino and announced support for the Arduino Nano 33 BLE Sense and […]

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