IMX8M Plus-Based Smart Pharmacy Vending Machine Design

Technical overview of smart pharmacy vending machines using an i.MX8M Plus carrier board: hardware, 2.3 TOPS NPU, connectivity, I/O, displays, storage, and OS support.

AIoT Connecting AI to the Physical World

Explains how AIoT links AI and physical devices via IP-based networks and application layers like Matter, and deployment considerations for scalable device connectivity.

RDK X3-Based Intelligent Care System for Elderly

Elderly care system on RDK X3 integrating IoT, Avahi, and a ROS1 bridge for voice and gesture robot control, cloud-synced Vue 3 frontend, and fall detection.

6G Sub-THz Communication Test Solutions

Summary of terahertz sub-THz testing for 6G: spectrum use, RF front-end modules, signal generation, and channel measurement tools for terahertz communications research.

Voice Chips: Bluetooth Features and Use Cases

Overview of voice recognition chips and Bluetooth features, comparing WTK6900HA8 and WTK6900HC with power, BLE/audio modes and application guidance.

PCB Design for WT3000A-M6 Voice Module in Smart Toys

PCB implementation guide for smart toy hardware with WT3000A-M6 voice module: system architecture, audio capture, RF matching, power management, layout and safety.

RZ/A2M Microprocessor Datasheet for Embedded AI Imaging

RZ/A2M MPU for high-speed embedded AI image processing: hybrid DRP preprocessing tightly coupled with a Cortex-A9 CPU, up to 4MB SRAM and multiple PWM outputs.

Ferroelectric Memory SF25C20/SF25C512 for AI Edge Computing

Ferroelectric memory SF25C20/SF25C512: nonvolatile, low-power, high-endurance storage for AI model parameters in edge devices.

RDK-Powered Navigation Glasses for the Visually Impaired

Intelligent Tongxing navigation glasses use YOLOv8 for real-time object detection and ROS2-based communication to deliver low-latency spoken navigation for visually impaired users.

RZ/V2M Vision-AI Microprocessor Datasheet

RZ/V2M SoC with DRP-AI (≈1.0 TOPS/W), multi?stream ISP and face/human detection engine, dual Cortex?A53, H.265 codec and USB/PCIe/GigE I/O for low?power vision AI.

RZ/V2MA Vision AI Microprocessor Datasheet

RZ/V2MA microprocessor with DRP-AI accelerator: low-power, real-time vision AI and OpenCV preprocessing on-chip, with CPU, DDR, PCIe, USB3, GigE and high-speed I/Os.

High-Flexibility, High-Precision Bionic Robotic Hand

Technical overview of a modular, safety-focused bionic robotic hand integrating ROS, cable-driven mechanics, multi-modal sensing and AI-based control for adaptive manipulation.

What Is an AI Agent

Technical overview of AI agents: how they use machine learning and multimodal data to perform tasks, make decisions, and enable applications in healthcare and autonomy.

VLM Lets RDK X5 Follow 'Walk' and Avoid Obstacles

Hierarchical reinforcement learning framework where a vision-language model outputs intermediate instructions and low-level RL maps them to morphology-specific robot actions.

Passive Component Challenges and Solutions in AI

Overview of passive components for AI systems: material, architectural and process innovations for high-current power inductors and low-ESR polymer tantalum capacitors.

MAX78000 Low-Power CNN AI Microcontroller

MAX78000 AI microcontroller with low-power CNN accelerator, Arm Cortex?M4 with FPU, 442 KB weight SRAM and 512 KB flash, optimized for edge inference.

Embodied AI Simulation Generation System

LLM-driven system automates embodied intelligence skill generation for robotic arms, converting natural-language tasks into MuJoCo scenes, actions, and reward code.

12 Practical GPU Optimization Tips for AI Training

12 strategies to improve GPU utilization and compute efficiency in AI/ML workloads, covering mixed precision, data pipelines, profiling and distributed training.

RDK X3 Chess Robot Development Diary

Autonomous chess robot integrating board recognition, manipulator control, voice interaction, and navigation on RDK X3 with TROS-based node architecture.

Building a Sustainable AI Ecosystem with Smaller LLMs

Analysis of LLM model scale, hardware and cost trade-offs, showing how smaller models and cloud-native CPUs improve inference efficiency and sustainability.