Amazon has recently introduced the Fire TV Stick 4K Select media streamer with a MediaTek MT8698 quad-core Cortex-A55 processor, 1GB RAM, 8GB eMMC flash, HDMI 2.1 video output, and WiFi 5 and Bluetooth 5.0 connectivity. However, the most interesting part of the announcement is the software, as Amazon has dropped the Android-based Fire OS used in its previous devices and instead relies on the new Linux-based Vega OS for the Fire TV Stick 4K Select. Amazon Fire TV Stick 4K Select (AFTCA002) specifications: SoC – MediaTek MT8698 MCM CPU – Quad-core Arm Cortex-A55 clocked up to 1.7 GHz GPU – Mali G310v2 up to 500 MHz with OpenGL ES 3.1 support VPU (hardware video decoder) AV1 up to 3840x2160p (4K) @ 60 fps, 100 Mbps, 8-bit and 10-bit input with HDR10, HDR10+, and HLG H.265 (HEVC) up to 3840x2160p (4K) @ 60 fps, 35 Mbps, 8-bit and 10-bit input with […]
Axelera Metis M.2 Max Edge AI module doubles LLM and VLM processing speed
Axelera AI’s Metis M.2 Max is an M.2 module based on an upgraded Metis AI processor unit (AIPU) delivering twice the memory bandwidth of the current Metis M.2 module for compute-intensive Edge AI inference applications such as large language models (LLMs) and vision language models (VLMs). The new Metis M.2 Max also offers a slimmer profile, advanced thermal management features, and additional security capabilities. It is equipped with up to 16 GB of memory, and versions for both a standard operating temperature range (-20°C to +70°C) and an extended operating temperature range (-40°C to +85°C) will be offered. These enhancements make Metis M.2 Max ideal for applications in industrial manufacturing, retail, security, healthcare, and public safety. Axelera AI Metis M.2 Max specifications and host requirements: Accelerator – Metis AIPU’ System Memory – 1GB, 4GB, 8GB, or 16GB memory Host Interface – M.2 2280 M-key edge connector with PCIe Gen. 3.0 […]
Getting Started with Quectel EC200U 4G LTE Cat 1 IoT board using the QNavigator and the QuecOpen SDK
CNXSoft: This is a guest post by Eicut showing how to get started with a Quectel EC200U 4G TLE Cat 1 IoT development board using QNavigator and the QuecOpen SDK. In IoT projects—and across embedded systems in general—we’ve seen a growing demand for higher data exchange rates, along with broader frequency band coverage. These advancements are critical for enhancing the reliability of a device’s communication link with the network. As a result, 4G modules with fallback capability to 2G and 4G networks have emerged as a leading solution in this space. But the key question remains: Which modules should we use to leverage this technology, and what features do they offer? Exploring the Quectel EC200U LTE Cat 1 Module for IoT In this section of the EC200U tutorial, we’ll take a closer look at one of the most popular and dependable options in the IoT space—Quectel’s EC200U module. If you’ve […]
Arm neural technology to add AI acceleration to Arm GPUs, enable “Neural Super Sampling” for lower bandwidth/higher FPS
Arm neural technology will add dedicated neural/AI accelerators to Arm GPUs launched in 2026 and beyond to deliver up to 50% GPU workload reduction for mobile games and other graphics-intensive apps. The first application is called Arm Neural Super Sampling (NSS). It’s a kind of AI Super Resolution implementation for games, where rather than upscaling videos, the AI accelerator upscales graphics to lower the required bandwidth and increase the frame rate (or lower the power consumption) with no impact on the rendering quality. Watch the video below to see a demo rendered at 540p resolution by the GPU and upscaled to 1080p resolution by Arm neural technology with no obvious defects. The upscaler will introduce some lag, but only about 4ms per frame in sustained performance conditions, as explained in a technical blog about the Arm Neural and NSS announcement: We assume a target of 10 TOP/s per-watt of neural acceleration […]
GigaDevice GD32C231 entry-level Arm Cortex-M23 MCU ships with 12KB ECC SRAM, 32KB or 64KB ECC flash
GigaDevice GD32C231 entry-level microcontroller is built around a 48 MHz Arm Cortex-M23 core with up to 64KB ECC flash, 12KB ECC SRAM, and is offered in 20-pin to 48-pin packages with up to 45 GPIOs, a range of peripherals, analog inputs, and timers. The company says the GD32C231 series targets cost-effective small home appliances, BMS (Battery Management Systems), small-screen display devices, battery-powered handhelds, industrial auxiliary controls, and automotive aftermarket systems. GigaDevice GD32C231 key features and specifications: Core – Arm Cortex-M23 @ up to 48 MHz Memory – 12KB SRAM with ECC Storage – 32KB or 64KB flash with ECC Audio – 1x I2S Low-speed Peripherals Up to 45x GPIO Up to 3x USART, 2x I2C, 2x SPI Analog 12-bit ADC with 13 channels 2x analog comparators Timers 4x 16-bit general-purpose (GP) timers 16-bit Advanced (AD) timer RTC IWDG, WWDG 24-bit SysTick Misc – CRC module Supply Voltage – 2.3 to […]
$24 Banana Pi BPI-Forge1 industrial SBC is powered by Rockchip RK3506J tri-core SoC
The Banana Pi BPI-Forge1, also known as the ArmSoM Forge1, is an industrial SBC (single board computer) powered by the Rockchip RK3506J triple-core Cortex-A7 processor designed for Smart Audio, HMI, and factory automation applications. The Forge1 is equipped with 512MB RAM, 512MB NAND flash, two Fast Ethernet ports, a MIPI DSI display connector, USB Type-A and Type-C ports, an audio jack, a 40-pin GPIO header partially compatible with Raspberry Pi HATs, and a 14-pin header with speaker output, microphone input, RS-485, and CAN Bus. Banana Pi BPI-Forge1 specifications: SoC – Rockchip RK3506J CPU 3x Arm Cortex-A7 core up to 1.5 GHz Arm Cortex-M0 real-time core GPU – 2D GPU only No VPU, no NPU System Memory – 512MB DDR3L Storage 512MB SPI NAND flash MicroSD card Display Interface – 2-lane MIPI DSI connector up to 1280 x 1280@ 60FPS Audio 3.5mm audio jack Speaker and Mic via expansion header Networking […]
Axelera Metis Compute Board pairs Rockchip RK3588 SoC with 214 TOPS Metis AI accelerator
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 […]
Radxa Orion O6 Preview – Part 2: Debian 12 – What works, what doesn’t
I went through an unboxing and Debian 12 installation on the Radxa Orion O6 at the end of January, but decided to work on other reviews since software support still needed to be worked on. Since then, there’s been some work done, but no new image released. After waiting for almost two months, I’ve decided to carry on with the review by testing the Debian 12 image in a way similar to the Rock 5B SBC preview I did with Debian 11 in 2022 to check what works and what doesn’t on the Orion O6 at the time of the review. That will involve testing all ports, including 5GbE networking and the PCIe slot with an (old) NVIDIA graphics card, running some benchmarks, and also trying the Debian 12 image with a self-built Linux 6.13 kernel using ACPI instead of UEFI for the default image. Orion O6 SBC benchmarks on […]






