machine learning News - Page 7 of 21 - CNX Software

July 18, 2023July 18, 2023 by Jean-Luc Aufranc (CNXSoft) - 13 Comments

ESP32-S3 based Arduino Nano ESP32 board supports Arduino and MicroPython programming

The Arduino Nano ESP32 is an ESP32-S3-based WiFi and Bluetooth microcontroller board designed for IoT applications for hobbyists and enterprise use cases. The new Nano board comes with 8 MB PSRAM and 16 MB flash storage and can be programmed with either the Arduino or MicroPython languages. It’s not the first ESP32 board from Arduino, as the Nano RP2040 Connect pairs a Raspberry Pi RP2040 MCU with an ESP32 module from u-Blox and the just-released Arduino UNO R4 WiFi marries a Renesas RA4M1 Arm Cortex-M33 MCU with an ESP32-S3-MINI-1 module. But the Arduino Nano ESP32 is different since it’s the first ESP32 board from Arduino where the Espressif chip is the only microcontroller onboard and handles both wireless connectivity and GPIOs. Arduino Nano ESP32 specifications: Wireless module – u-Blox NORA-W106-10B with MCU – ESP32-S3 dual-core Xtensa LX7 microcontroller @ up to 240 MHz with vector extensions, 512KB SRAM, 384KB ROM, […]

June 22, 2023June 22, 2023 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

Particle launches Photon 2 Realtek RTL8721DM dual-band WiFi and BLE IoT board, Particle P2 module

Particle has launched the Photon 2 dual-band WiFi and BLE IoT board powered by a 200 MHz Realtek RTL8721DM Arm Cortex-M33 microcontroller, as well as the corresponding Particle P2 module for integration into commercial products. The original “Spark Photon” WiFi IoT board was launched in 2014 with an STM32 MCU and a BCM43362 wireless module, but the market and company name have changed since then, and Particle has now launched the Photon 2 board and P2 module with a more modern Cortex-M33 WiFi & BLE microcontroller with support for security features such as Arm TrustZone. Particle Photon 2 specifications: Wireless MCU – Realtek RTL8721DM CPU – Arm Cortex-M33 core @ 200 MHz Memory – 4.5MB embedded SRAM of which 3072 KB (3 MB) is available to user applications Connectivity – Dual-band WiFi 4 up to 150Mbps and Bluetooth 5.0 Security Hardware Engine Arm Trustzone-M Secure Boot SWD Protection Wi-Fi WEP, […]

June 17, 2023June 17, 2023 by Jean-Luc Aufranc (CNXSoft) - 9 Comments

i-Pi SMARC 1200 (MediaTek Genio 1200) devkit tested with a Yocto Linux image

i-Pi SMARC 1200 Yocto Linux glmark2 benchmark

Last weekend I received ADLINK’s i-Pi SMARC 1200 development kit powered by MediaTek Genio 1200 Octa-core Cortex-A78/A55 AIoT processor, checked out the hardware and wanted to install the Yocto Linux image but stopped in my tracks because it looked like I had to install Ubuntu 18.04 first in a Virtual Machine or another computer. But finally, the documentation has been updated to clarify “Ubuntu 18.04 or greater” is required, and I had no problem flashing the image from a Ubuntu 22.04 laptop after installing dependencies and tools as follows:

$ sudo apt install android-tools-adb android-tools-fastboot
$ echo 'SUBSYSTEM=="usb", ATTR{idVendor}=="0e8d", ATTR{idProduct}=="201c", MODE="0660", $ GROUP="plugdev"' | sudo tee -a /etc/udev/rules.d/96-rity.rules
$ echo -n 'SUBSYSTEM=="usb", ATTR{idVendor}=="0e8d", ATTR{idProduct}=="201c", MODE="0660", TAG+="uaccess"
SUBSYSTEM=="usb", ATTR{idVendor}=="0e8d", ATTR{idProduct}=="0003", MODE="0660", TAG+="uaccess"
SUBSYSTEM=="usb", ATTR{idVendor}=="0403", MODE="0660", TAG+="uaccess" SUBSYSTEM=="gpio", MODE="0660",
TAG+="uaccess" ' | sudo tee /etc/udev/rules.d/72-aiot.rules
$ sudo udevadm control --reload-rules
$ sudo udevadm trigger
$ sudo usermod -a -G plugdev $USER
$ pip3 install -U -e "git+https://gitlab.com/mediatek/aiot/bsp/aiot-tools.git#egg=aiot-tools"

$ sudo apt install android-tools-adb android-tools-fastboot

$ echo 'SUBSYSTEM=="usb", ATTR{idVendor}=="0e8d", ATTR{idProduct}=="201c", MODE="0660", $ GROUP="plugdev"' | sudo tee -a /etc/udev/rules.d/96-rity.rules

$ echo -n 'SUBSYSTEM=="usb", ATTR{idVendor}=="0e8d", ATTR{idProduct}=="201c", MODE="0660", TAG+="uaccess"

SUBSYSTEM=="usb", ATTR{idVendor}=="0e8d", ATTR{idProduct}=="0003", MODE="0660", TAG+="uaccess"

SUBSYSTEM=="usb", ATTR{idVendor}=="0403", MODE="0660", TAG+="uaccess" SUBSYSTEM=="gpio", MODE="0660",

TAG+="uaccess" ' | sudo tee /etc/udev/rules.d/72-aiot.rules

$ sudo udevadm control --reload-rules

$ sudo udevadm trigger

$ sudo usermod -a -G plugdev $USER

$ pip3 install -U -e "git+https://gitlab.com/mediatek/aiot/bsp/aiot-tools.git#egg=aiot-tools"

That’s it for the tools. Eventually, the development kit will support three images: Yocto Linux, Android 13 (July 2023), and Ubuntu 20.04 (Q3 2023). So that means only the Yocto Linux image is available from the download page at this time, and that’s what I’ll be using today. We’ll need to connect the micro USB to USB cable between the […]

June 13, 2023June 13, 2023 by Jean-Luc Aufranc (CNXSoft) - 2 Comments

CompuLab UCM-iMX93 – A miniature NXP i.MX 93 module with WiFi 5 & Bluetooth 5.3

CompuLab UCM-iMX93 is a miniature system-on-module powered by the new NXP i.MX93 Cortex-A55 AI processor family with up to 2GB RAM and 64GB eMMC flash. The tiny 38x28mm features a Gigabit Ethernet PHY, a WiFi 5 and Bluetooth 5.3 wireless modules, and plenty of multimedia, communication, and peripheral interfaces through two 100-pin high-density connectors including display and camera interfaces, USB ports, CAN FD, and up to 79 GPIOs. UCM-iMX93 specifications: SoC – NXP i.MX9352 or i.MX9331 dual-core/single-core Arm Cortex-A55 @ 1.5 GHz (industrial) / 1.7 GHz (commercial) with Arm Cortex-M33 real-time core @ 250 MHz, Arm Ethos U65 microNPU System Memory – 512MB to 2GB LPDDR4 Storage – 8GB to 64GB eMMC flash Networking Gigabit Ethernet PHY Certified WiFi 5 (802.11ac) and Bluetooth 5.3 BLE module (NXP 88W8997) 2x 100-pin 0.4mm pitch high-density UCM connectors Display 4-lane MIPI-DSI up to 1920 x 1080 @ 60Hz 4-lane LVDS up to 1366 […]

May 23, 2023May 23, 2023 by Jean-Luc Aufranc (CNXSoft) - No Comments

FireBeetle 2 ESP32-S3 camera board ships 16MB flash, 8MB PSRAM, PCB or external antenna

DFRobot “FireBeetle 2 ESP32-S3” is a 2MP camera board with ESP32-S3N16R8 dual-core WiFi and Bluetooth microcontroller fitted with 16MB flash and 8MB PSRAM, and offered in two versions: a more compact variant with a PCB antenna, and one with an external antenna offering a better signal quality. The FireBeetle 2 ESP32-S3 also features two rows of I/Os with GPIO, I2C, SPI, ADC, USB 2.0, etc…, a USB-C port for power and programming, a few buttons, and support for a LiPo battery through a 2-pin JST connector and a charging circuit. FireBeetle 2 ESP32-S3 specifications: ESP32-S3-WROOM-1 wireless module SoC – ESP32-S3FN16R8 dual-core Tensilica LX7 microcontroller @ 240 MHz with 2.4 GHz 802.11n WiFI 4 and Bluetooth 5.0 LE connectivity Memory – 8MB PSRAM Storage – 16MB SPI flash Camera – Camera connector fitted with 2MP OV2640 camera with 68° FoV, up to 1600×1200 resolution Display – GDI connector for optional 1.54-inch, […]

May 18, 2023May 18, 2023 by Jean-Luc Aufranc (CNXSoft) - No Comments

AndesAIRE AnDLA I350 AI/ML IP block is configurable from 64 GOPS to 8TOPS for Edge AI SoCs

Andes Technology has just announced the AndesAIRE product line, where AndesAIRE stands for Andes AI Runs Everywhere, comprised of the AndesAIRE AnDLA I350 (Andes Deep Learning Accelerator) AI/ML hardware accelerator intellectual property (IP) and the AndesAIRE NN SDK with neural network software tools and runtimes. AndesAIRE AnDLA I350 AnDLA I350 specifications: Configurable MACs from 32 to 4096 (INT8) Maximum performance – 8 TOPS at 1GHz Configurable local memory – 16KB to 4MB Multi-dimension DMA Four 64-bit AXI bus interfaces NN type – CNN inference NN models Image and Video: AlexNet, VGG-16/19, MobileNet-v1/v2/v3, ResNet-8/50, Tiny YOLO v1/v2, YOLO v1/v2/v3/v4/v5, SSD MobileNet v1/v2, Inception v2, EfficientNet-lite, MobileFaceNet, BlazeNet Speech/Voice and audio: LSTM, RNN, GRU Operators: Conv2d, depthwise convolution, pointwise convolution, transpose convolution, dilated convolution, element-wise (add, sub, mul), fully-connected, activation (ReLU, leaky ReLU, sigmoid, Tanh, ReLU6, SiLU), pooling (max, ave), upsample, concatenation, batch normalization, channel padding Operator fusion NHWC data format The IP […]

May 16, 2023 by Jean-Luc Aufranc (CNXSoft) - 6 Comments

STMicro unveils STM32MP2 Arm Cortex-A35/M33 MPU family starting with STM32MP25

STMicro has introduced its second generation of its STM32 MPUs (microprocessors) with the STM32MP2 moving to a 64-bit Arm architecture with Edge AI acceleration, multimedia features, graphics processing, and digital connectivity targeting industrial and IoT edge applications. The new family follows the STM32MP1 Arm Cortex-A7/M4 series introduced in 2019, and the first member of the family is the STM32MP25 with up to two 1.5 GHz Cortex-A35 cores coupled with an Arm Cortex-M33 real-time core clocked at 400 MHz, a 3D GPU, and a 1.35 TOPS NPU for AI acceleration. STM32MP25 key features and specifications: CPU – Single or dual Arm Cortex-A35 cores running up to 1.5 GHz Real-time MCU – Arm Cortex-M33 core running up to 400 MHz GPU – Unnamed 3D GPU for “advanced HMI” with support for the Vulkan API VPU – H.264 hardware video decoder and encoder AI accelerator – 1.35 TOPS NPU (Neural processing unit) System […]

May 8, 2023 by Jean-Luc Aufranc (CNXSoft) - 5 Comments

Lolin S3 Mini – Tiny $5 ESP32-S3 board follows Wemos D1 Mini form factor

LOLIN S3 Mini is a tiny ESP32-S3 WiFi and Bluetooth IoT development board that follows the Wemos D1 Mini form factor and supports its equally tiny stackable shields to add relays, displays, sensors, and so on. Wemos/LOLIN introduced their first ESP32-S3 board last year with the LOLIN S3 board with plenty of I/Os and an affordable $7 price tag. But I prefer the company’s Mini form factor because of its size and the ability to select add-on boards to easily add a range of features to your projects. So I’m pleased to find out the company has now launched the LOLIN S3 Mini following the ESP32-C3 powered LOLIN C3 Mini board unveiled in March 2022. LOLIN S3 Mini specifications: WiSoC – Espressif Systems ESP32-S3FH4R2 CPU – dual-core Tensilica LX7 @ up to 240 MHz with vector instructions for AI acceleration Memory – 512KB RAM, 2MB PSRAM Storage – 4MB QSPI […]