Author: kissdev
The Adafruit BrainCraft HAT is a powerful accessory designed to enhance the Raspberry Pi’s capabilities for machine learning and AI applications[1][2]. This HAT (Hardware Attached on Top) features a 240×240 IPS TFT display, stereo speakers, microphones, and various input/output options, making it an ideal platform for developing audio and video AI projects[1][3]. Key features of the BrainCraft HAT include: 1.54″ IPS TFT display (240×240 resolution) Stereo speaker and headphone outputs Stereo microphone input with a mechanical on/off switch 5-way joystick and button for user interface Three RGB DotStar LEDs for visual feedback Two 3-pin STEMMA connectors and a STEMMA QT…
Banana Pi BPI-M64 is a powerful single-board computer (SBC) with AI capabilities, powered by the Allwinner A64 SoC. This open-source hardware platform is designed to cater to developers and tech enthusiasts who seek a versatile and expandable computing solution. Key Features Processor: The BPI-M64 is equipped with a 64-bit Quad-Core ARM Cortex-A53 CPU clocked at 1.2 GHz, providing robust processing power for various applications[1][2]. Memory: It includes 2GB of DDR3 SDRAM, ensuring smooth multitasking and efficient performance[1][2]. Storage: The board features 8GB of onboard eMMC flash storage and a microSD slot that supports up to 256GB of additional storage[1][2]. Graphics:…
The Xilinx Kria KV260 Vision AI Starter Kit is a comprehensive development platform designed for AI and vision applications, leveraging Xilinx’s adaptive computing technology. This kit is ideal for developers looking to quickly prototype and deploy advanced vision AI solutions without needing extensive hardware design expertise. Key Features Vision Ready: The kit supports multi-camera setups with up to 8 interfaces, including 3 MIPI sensor interfaces and USB cameras. It also features built-in ISP components for image processing and outputs through HDMI and DisplayPort[1]. Flexible Connectivity: It includes 1 Gb Ethernet and USB 3.0/2.0 ports, allowing for versatile connectivity options[1]. Expandable:…
The Google AIY Vision Kit is a do-it-yourself (DIY) kit designed for building AI-powered vision projects. This kit allows users to create an intelligent camera capable of recognizing objects and faces using machine learning. Components and Assembly The AIY Vision Kit includes: – Vision Bonnet – Raspberry Pi Zero WH – Raspberry Pi Camera v2 – Long and short flex cables – Push button and button harness – Micro USB cable – Piezo buzzer – Privacy LED – Micro SD card – Various nuts, standoffs, and a cardboard camera box for assembly Assembly of the kit takes approximately 1.5 hours.…
The LattePanda Alpha is a powerful mini PC that combines an Intel Core processor with an Arduino co-processor, offering the capabilities of a full Windows or Linux computer alongside Arduino development features[1][2]. At its core, the Alpha 800s model utilizes an Intel Core m3-8100Y processor, which can burst up to 3.4GHz, paired with 8GB of LPDDR3 RAM[2][4]. This compact single-board computer measures just 115 x 78 x 14mm, making it highly portable while still providing impressive performance[1]. The integrated Intel HD Graphics 615 supports 4K video output through HDMI and USB-C DisplayPort connections[2][4]. What sets the LattePanda Alpha apart is…
The ODROID-N2 stands out as a powerful single-board computer (SBC) well-suited for AI and machine learning projects[1]. Featuring an Amlogic S922X processor with a quad-core ARM Cortex-A73 CPU cluster and a dual-core Cortex-A53 cluster, the N2 delivers impressive performance for its compact size[1]. Its Mali-G52 GPU further enhances its capabilities for graphics-intensive tasks[1]. With up to 4GB of DDR4 RAM and eMMC storage options ranging from 8GB to 128GB, the N2 provides ample memory and storage for running complex AI algorithms and handling large datasets[1]. The board’s efficient heat dissipation design, utilizing a metal housing as a heatsink, allows for…
The Rock Pi N10 is a powerful single-board computer (SBC) designed for AI and deep learning applications, featuring the Rockchip RK3399Pro system-on-chip (SoC). This SoC integrates a CPU, GPU, and Neural Processing Unit (NPU), making it particularly well-suited for edge computing tasks. Key Features High-Performance AI Hardware The RK3399Pro SoC includes a six-core CPU with dual Cortex-A72 cores running at 1.8GHz and quad Cortex-A53 cores at 1.4GHz. The GPU is a Mali T860MP4, supporting various graphics APIs such as OpenGL ES and Vulkan. The standout feature is the NPU, which delivers up to 3.0 TOPS (Tera Operations Per Second) of…
Intel Neural Compute Stick 2: Accelerating AI at the Edge The Intel Neural Compute Stick 2 (NCS 2) is a USB-based device designed to accelerate AI inference on edge devices[1][4]. This compact, fanless deep learning tool enables developers to prototype and deploy computer vision and AI applications quickly and efficiently[2]. Powered by the Intel Movidius Myriad X Vision Processing Unit (VPU), the NCS 2 offers up to 8x performance improvement over its predecessor for running deep neural networks[1][5]. It features a dedicated neural compute engine, which is a hardware accelerator specifically built for deep neural network inferences[3]. Key features of…
BeagleBone AI-64 is a powerful single-board computer designed specifically for AI and machine learning applications[2]. Built on the proven BeagleBoard.org open source Linux platform, it leverages the Texas Instruments TDA4VM SoC to deliver impressive AI performance in a compact form factor[2][4]. Key Features Dual 64-bit Arm Cortex-A72 processors C7x DSP core for accelerated AI processing 8 TOPS neural network performance[3][4] 4GB RAM PCIe and M.2 expansion capabilities BeagleBone cape header compatibility[2][3] The AI-64 provides developers with a complete system for building intelligent embedded applications. Its 8 TOPS of neural network performance enables advanced computer vision, machine learning, and autonomous robotics…
TDK Corporation has unveiled a groundbreaking solid-state battery technology with an impressive energy density of 1,000 watt-hours per liter, approximately 100 times greater than their conventional solid-state batteries[1][2]. This high-capacity, long-life battery is designed for IoT and AI devices, particularly wearables like wireless earphones, hearing aids, and smartwatches[2][4]. The new battery utilizes an all-ceramic material with oxide-based solid electrolytes and lithium alloy anodes, providing several key advantages[1]: Extremely safe due to the use of oxide-based solid electrolyte Smaller size and higher capacitance, enabling more compact devices with longer operating times Potential to replace coin cell batteries, complying with EU regulations…