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Posted on by Jean-Luc Aufranc (CNXSoft) - 2 Comments on Axelera Metis Compute Board pairs Rockchip RK3588 SoC with 214 TOPS Metis AI accelerator

Axelera Metis Compute Board pairs Rockchip RK3588 SoC with 214 TOPS Metis AI accelerator

Metis Compute Board

Axelera Metis Computer Board is a Rockchip RK3588 mini-ITX motherboard equipped with a Metis AIPU (AI Processing Unit) capable of delivering up to 214 TOPS, 16GB LPDDR4 memory for the CPU, and 4GB LPDDR4x RAM for the AI accelerator. I first came across the Axelera Metis AIPU in M.2 and PCIe card in 2023, and I was rather impressed with the advertised 214 TOPS of AI performance promised in this form factor and relatively affordable $149 price tag considering the price-to-performance ratio. At the time, it was still hard to source the chip and module due to limited quantities, and in 2024, it became easier to evaluate the solution with the Axelera Metis PCIe Arm AI evaluation kit based on a Firefly ITX-3588J mini-ITX motherboard equipped with a 214 TOPS Metis AIPU PCIe card. The new Metis Compute Board is similar, but in a more compact form factor since the […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 1 Comment on STMicro STM32MP23 Cortex-A35/M33 MPU features a 600 GOPS NPU for industrial IoT and ML applications

STMicro STM32MP23 Cortex-A35/M33 MPU features a 600 GOPS NPU for industrial IoT and ML applications

STM32MP235 block diagram

STMicroelectronics STM32MP23 is a dual-core Cortex-A35 general-purpose microprocessor (MPU) with a Cortex-M33 real-time core, and 600 GOPS of performance operating at up to 125°C and designed for industrial and Internet-of-Things (IoT) edge computing, advanced HMI, and machine-learning (ML) applications. It follows the STM32MP25 series unveiled in 2023 and launched the following year as the first member of the STM32MP2 family. The STM32MP23 is a cost-down version of the STM32MP25 with similar specifications (and pin-to-pin compatible packages), but the new family has a weaker 0.6 TOPS NPU, and tops at two Ethernet ports for the high-end parts instead of three. Ditto for CAN Bus interfaces (2x vs 3x). Other changes include a 16-bit memory interface and the lack of PCIe and USB 3.0 interfaces. STM32MP23 specifications: CPU – Single or dual Arm Cortex-A35 cores running at up to 1.5 GHz or 1.2 GHz with 512KB L2 cache Real-time MCU – Arm […]

Posted on by Debashis Das - No Comments on Waveshare ESP32 robotic arm kit with 5+1 DoF supports ROS2, LeRobot, and Jetson Orin NX integration

Waveshare ESP32 robotic arm kit with 5+1 DoF supports ROS2, LeRobot, and Jetson Orin NX integration

RoArm M3 Pro and RoArm M3 S High Torque Serial Bus Servo Robotic Arm Kit

Waveshare has recently released the RoArm-M3-Pro and RoArm-M3-S, a 5+1 DOF high-torque ESP32 robotic arm kit. The main difference between the two is that the RoArm-M3-Pro features all-metal ST3235 bus servos for durability and longevity, on the other hand, the RoArm-M3-S uses standard servo motors which are less durable for long-term use. These robotic arms feature a lightweight structure, a 360° omnidirectional base, and five flexible joints, which together create a 1m workspace with a 200 grams @ 0.5m payload. A 2-DOF wrist joint enables multi-dimensional clamping and precise force control. It integrates an ESP32 MCU, supporting multiple wireless control modes via a web app, it also supports inverse kinematics for accurate positioning, curve velocity control for smooth motion, and adaptive force control. The design is open source and with ROS2 compatibility, it allows secondary development via JSON commands and ESP-NOW for multi-device communication. Compatible with the LeRobot AI framework, […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 14 Comments on Orange Pi AIPro (8T) SBC features a 8 TOPS Huawei Ascend AI SoC, runs Ubuntu or openEuler

Orange Pi AIPro (8T) SBC features a 8 TOPS Huawei Ascend AI SoC, runs Ubuntu or openEuler

Orange Pi AIPro (8T)

Orange Pi AIPro (8T) is a new single board computer for AI applications that features an unnamed Huawei Ascend AI quad-core 64-bit processor delivering up to 8 TOPS (INT8) of AI inference performance, although there’s also a 20 TOPS (INT8) variant of the SoC. The SBC comes with up to 16GB LPDDR4X and a 32MB SPI flash but also supports other storage options such as a microSD card, an eMMC flash module, and/or an M.2 NVMe or SATA SSD. The board also features two HDMI 2.0 ports, one MIPI DSI connector, a 3.5mm audio jack, two MIPI CSI camera interfaces, Gigabit Ethernet and WiFi 5 connectivity, a few USB ports, and a 40-pin GPIO header for expansion. Orange Pi AIPro specifications: SoC – Huawei Ascend quad-core 64-bit processor delivering up to 8 TOPS (INT8) AI performance and equipped with an unnamed 3D GPU; Likely Ascend 310B with Arm Cortex-A76 equivalent […]

Posted on by Debashis Das - 1 Comment on Seeed Studio introduces ESP32-C3-based Modbus Vision RS485 and SenseCAP A1102 LoRaWAN outdoor Edge AI cameras

Seeed Studio introduces ESP32-C3-based Modbus Vision RS485 and SenseCAP A1102 LoRaWAN outdoor Edge AI cameras

Seeed Studio's Modbus Vision RS485 and SenseCAP A1102 outdoor Edge AI cameras

Seeed Studio has recently released the Modbus Vision RS485 and SenseCAP A1102 (LoRaWAN) outdoor Edge AI cameras based on ESP32-C3 SoC through the XIAO-ESP32C3 module for WiFi and the Himax WiseEye2 processor for vision AI. Both are IP66-rated AI vision cameras designed for home and industrial applications. The RS485 camera is designed for industrial systems and features a Modbus interface, making it suitable for factory automation and smart buildings. The SenseCAP A1102 uses LoRaWAN for long-range, low-power monitoring in remote locations. Both offer advanced AI for tasks like object detection and facial recognition. Besides its built-in RS485 interface, the Modbus Vision RS485 also supports LoRaWAN and 4G LTE connectivity via external Data Transfer Units (DTUs). With over 300 pre-trained AI models, the camera can do object detection and classification tasks making it suitable for industrial automation, smart agriculture, environmental monitoring, and other AI-driven applications requiring high performance. The SenseCAP A1102 […]

Posted on by Debashis Das - No Comments on Firefly’s CSB1-N10 series AI cluster servers can deliver up to 1000 TOPS of AI power with Rockchip or NVIDIA Jetson Modules

Firefly’s CSB1-N10 series AI cluster servers can deliver up to 1000 TOPS of AI power with Rockchip or NVIDIA Jetson Modules

CSB1 N10 series AI cluster servers

Firefly has recently introduced the CSB1-N10 series AI cluster servers designed for applications such as natural language processing, robotics, and image generation. These 1U rack-mounted servers are ideal for data centers, private servers, and edge deployments. The servers have multiple computing nodes, featuring either energy-efficient processors (Rockchip RK3588, RK3576, or SOPHON BM1688) or high-performance NVIDIA Jetson modules (Orin Nano, Orin NX). With 60 to 1000 TOPS AI power, the CSB1-N10 servers can handle the demands of large AI models, including language models like Gemma-2B and Llama3, as well as visual models like EfficientVIT and Stable Diffusion. CSB1-N10 series specifications All CSB1-N10 AI servers have the same interfaces, and the only differences are the CPU, memory, storage, multimedia, AI capabilities, and related software support. So it’s likely Firefly has made Rockchip system-on-modules compatible with NVIDIA Jetson SO-DIMM form factor, and indeed we previously noted that Firefly designed Core-1688JD4, Core-3576JD4, or Core-3588JD4 […]

Posted on by Jean-Luc Aufranc (CNXSoft) - 3 Comments on Getting Started with Raspberry Pi AI HAT+ (26 TOPS) and Raspberry Pi AI camera

Getting Started with Raspberry Pi AI HAT+ (26 TOPS) and Raspberry Pi AI camera

Raspberry Pi AI HAT+ and AI camera review

Raspberry Pi recently launched several AI products including the Raspberry Pi AI HAT+ for the Pi 5 with 13 TOPS or 26 TOPS of performance and the less powerful Raspberry Pi AI camera suitable for all Raspberry Pi SBC with a MIPI CSI connector. The company sent me samples of the AI HAT+ (26 TOPS) and the AI camera for review, as well as other accessories such as the Raspberry Pi Touch Display 2 and Raspberry Pi Bumper, so I’ll report my experience getting started mostly following the documentation for the AI HAT+ and AI camera. Hardware used for testing In this tutorial/review, I’ll use a Raspberry Pi 5 with the AI HAT+ and a Raspberry Pi Camera Module 3, while I’ll connect the AI camera to a Raspberry Pi 4. I also plan to use one of the boards with the new Touch Display 2. Let’s go through a […]

Posted on by Kumpee Teeravech - 5 Comments on BeagleY-AI SBC review with Debian 12, TensorFlow Lite, other AI demos

BeagleY-AI SBC review with Debian 12, TensorFlow Lite, other AI demos

BeagleY-AI review

Today I’ll be reviewing the BeagleY-AI open-source single-board computer (SBC) developed by BeagleBoard.org for artificial intelligence applications. It is powered by a Texas Instruments AM67A quad-core Cortex-A53 processor running at 1.4 GHz along with an ARM Cortex-R5F processor running at 800 MHz for handling general tasks and low-latency I/O operations. The SoC is also equipped with two C7x DSP units and a Matrix Multiply Accelerator (MMA) to enhance AI performance and accelerate deep learning tasks. Each C7x DSP delivers 2 TOPS, offering a total of up to 4 TOPS. Additionally, it includes an Imagination BXS-4-64 graphics accelerator that provides 50 GFlops of performance for multimedia tasks such as video encoding and decoding. For more information, refer to our previous article on CNX Software or visit the manufacturer’s website. BeagleY-AI unboxing The BeagleY-AI board was shipped from India in a glossy-coated, printed corrugated cardboard box. Inside, the board is protected by […]

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