🍓 Raspberry Pi M.2 HAT+ Review

The Raspberry Pi M.2 HAT+ is a new addition to the Raspberry Pi accessory lineup, designed to offer high-speed NVMe storage at an affordable price. Priced at just $12, this board aims to deliver PCIe Gen 3 speeds, providing a significant performance boost for Raspberry Pi 5 users.

Features of the expansion board:
➡️One of the cheapest options for adding NVMe storage to Raspberry Pi.
➡️The board comes with pre-connected PCIe cable and plastic standoffs for straightforward installation.
➡️Designed to fit within the Raspberry Pi 5's form factor, making it compact and compatible.
➡️Offers faster boot times and better overall system responsiveness compared to microSD cards.
➡️Works seamlessly with the latest Raspberry Pi firmware, ensuring easy setup.

The M.2 HAT+ also maintains efficient cooling, only slightly increasing idle temperatures. Additionally, it supports M.2 2230 and 2242 drives, which are widely available and affordable.

Overall, the Raspberry Pi M.2 HAT+ is an excellent low-cost option for adding high-speed NVMe storage to your Raspberry Pi 5, despite some minor inconveniences with GPIO access.

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🍓 Raspberry foundation has released an affordable AI Kit

The Raspberry Pi Foundation has launched the Raspberry Pi AI Kit, priced at $70, in collaboration with Hailo. This kit, featuring an M.2 HAT+ board preassembled with a Hailo-8L AI accelerator module, is designed to enhance the Raspberry Pi 5's capabilities in neural networks (NN), artificial intelligence (AI), and machine learning.

Key features of the kit:
➡️13 tera-operations per second (TOPS)
➡️Single-lane PCIe 3.0 connection running at 8Gbps
➡️Full integration with Raspberry Pi's software ecosystem
➡️Support for multiple cameras and NN configurations

The kit supports a range of AI applications, such as object detection and pose estimation, by running complex AI models on the Hailo-8L co-processor, thus freeing up the Raspberry Pi's CPU for other tasks.

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🍓 Introducing Raspberry Pi Pico 2

The Raspberry Pi Pico 2 is a newly launched development board featuring the RP2350 microcontroller, which offers dual-core processing options: Arm Cortex-M33 or RISC-V Hazard3. It provides enhanced performance and memory, making it suitable for a wide range of applications.

Key Features of Raspberry Pi Pico 2:
➡️Dual-core Arm Cortex-M33 @ 150 MHz or dual-core RISC-V Hazard3 @ 150 MHz
➡️520 KB on-chip SRAM and up to 16 MB external QSPI flash storage
➡️Comprehensive peripheral support including GPIOs, ADCs, PWM channels, UARTs, SPI, and I2C controllers
➡️Enhanced security features with Trustzone, SHA-256 acceleration, and secure boot options
➡️Low-power modes with optional SRAM retention for energy efficiency
➡️Micro USB port for power and programming

Overall, the Raspberry Pi Pico 2 is ideal for developers and hobbyists looking for a versatile, powerful microcontroller that balances cost and functionality, making it suitable for a variety of projects.

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💻 Expanding RP2040 Memory: Using QSPI RAM with RP2040's SSI in read-write mode

The article discusses a useful lifehack for expanding the memory of the 🍓 RP2040 microcontroller. The RP2040 typically supports flash XIP (eXecute In Place), which allows for executing code directly from external flash memory, but it only supports read and execute operations, not writes.

The author overcomes this limitation by employing a combination of hardware (OR and NOT gates) and software (a custom HardFault handler) to copy code from flash to RAM during boot, then switch the RP2040 to execute from RAM, effectively making it behave like real memory.

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👩‍💻 PI-CI: Dockerized Raspberry Pi Emulator

PI-CI is a Docker-based Raspberry Pi emulator designed to streamline the setup, configuration, and flashing of Raspberry Pi virtual machines (VMs).

Features of the project:
➡️Supports Raspberry Pi 3, 4, and 5 models.
➡️Includes 64-bit Raspberry Pi OS (24.04, Bookworm).
➡️Operates without requiring root privileges, ensuring safety and reproducibility.
➡️Offers commands like init, start, resize, flash, and export for VM management and image handling.

PI-CI is ideal for developers and sysadmins aiming to automate the setup and deployment of Raspberry Pi configurations. It facilitates tasks such as preconfiguring servers, testing ARM applications in a virtualized environment, and integrating with CI pipelines for continuous deployment.

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📺 Raspberry Pi Pico RP2350 - Massive Performance Boost Trick

This video explores the performance differences between Cortex-M33 and RISC-V Hazard 3 cores on the 🍓 RP 2350 microcontroller. Initially, the RISC-V cores were surprisingly slower than expected due to using suboptimal compiler setups on Windows with 👩‍💻 Visual Studio Code. Feedback from the core designer revealed that the default toolchains lacked important optimizations, especially for floating-point operations.

By switching to 👩‍💻 Linux and manually configuring the toolchain and compilers, significant performance improvements were achieved. The optimized setup showed the RISC-V cores outperforming Cortex-M0 cores and, in some cases, even matching or exceeding the Cortex-M33. The video concludes that to fully unlock the RP 2350's potential, developers should use the right compiler and setup, ideally on Linux, for the best performance.

⛓ https://youtu.be/_O3Aeyv2ILM

#video #raspberry #pico2

🎹 Enhanced Connectivity with Pimoroni Pico Plus 2 W

This microcontroller is an enhanced version of the popular Raspberry Pi Pico 2 microcontroller, featuring integrated Wi-Fi capabilities. Developed by Pimoroni, this board builds upon the Pico 2 platform by incorporating the "Raspberry Pi RM2" module for wireless connectivity, marking a significant upgrade for IoT and embedded projects.

Features of the microcontroller:
➡️Integrated Wi-Fi functionality with the Raspberry Pi RM2 module.
➡️Powered by the RP2350B with 8MB of PSRAM and 16MB of QSPI flash storage.
➡️Compatible pinout with the Raspberry Pi Pico series.
➡️Includes Qw/St connector (Stemma QT) and SWD debug port.
➡️USB Type-C port for data and power.

With ample memory and a robust set of connectivity options, it's well-suited for IoT applications, data logging, and remote monitoring projects. The addition of the Clipper LTE 4G breakout board expands its utility further, offering cellular connectivity for applications that require reliable data transmission in areas without Wi-Fi coverage.

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🎹 FlexiPi: A Bendable, Versatile Raspberry Pi Clone (Kickstarter)

FlexiPi is a unique, bendable microcontroller board based on the 🍓 Raspberry Pi RP2040. Designed by TOP Gadgets, this innovative take on the Raspberry Pi Pico integrates a flexible PCB and USB-C connectivity, offering the same power as the original but with added versatility for compact or irregular enclosures.

Features of the microcontroller:
➡️Ideal for tight spaces and curved surfaces.
➡️Built on the dual-core Cortex-M0+ RP2040, overclockable to 133 MHz.
➡️Features a USB-C port for modern compatibility.
➡️26 GPIOs, including ADC, UART, I2C, SPI, and PWM.
➡️Includes RGB LED, temperature sensor, and RTC.
➡️Supports Raspberry Pi Pico SDKs (C/C++, MicroPython, CircuitPython) and Arduino IDE.

The project is ongoing on Kickstarter and it is interesting to see how people are trying to commercialize this technology. Overall it is a useful project for engineers looking to integrate powerful microcontroller functionality into constrained or curved spaces.

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👩‍💻 Kickstart Your Raspberry Pi Pico with VS Code

Setting up a development environment for the 🍓 Raspberry Pi Pico can be daunting, especially with the variety of languages and tools available. While MicroPython and CircuitPython simplify things for beginners, using C/C++ offers greater control and flexibility—at the cost of a more complex setup process.

Fortunately, Raspberry Pi's official extension for Microsoft Visual Studio Code is a game-changer, making it easier than ever to get started with C/C++ on the Pico. This guide will give you a quick walk though the steps needed to start embedded development with Pico on Windows environment.

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🖥 Open-Source Cardiography Signal Measuring Device

This open-source project is designed to build a fully-functional device for recording, analyzing, and visualizing a range of cardiography signals. Powered by a 🍓 Raspberry Pi Pico W microcontroller, the device captures physiological signals, then amplifies and transmits them to a PC for real-time display and in-depth analysis.

Features of the device:
➡️Isolated USB communication for data transfer.
➡️Power regulation features for stable performance.
➡️Signal conditioning for accurate stethoscope and ECG data collection.
➡️Firmware in C++ for device control and data acquisition.
➡️Python-based graphical interface for real-time data display and recording.
➡️Data analysis scripts in Python for post-collection analysis.

This project offers valuable insights into signal processing and data analysis methods, making it a practical resource for hands-on learning and experimentation with cardiographic measurement.

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💻 Mastering Asynchronous Programming with MicroPython on Raspberry Pi Pico

This short guide will walk you through the asynchronous programming on the 🍓 Raspberry Pi Pico using 🐍 MicroPython and the asyncio module. You’ll learn the difference between asynchronous (non-blocking, concurrent tasks) and synchronous (blocking, sequential tasks) programming.

It covers key concepts like event loops, coroutines, tasks, and the await keyword, along with setting up MicroPython firmware and using 👷‍♂️ Thonny IDE or 👩‍💻 VS Code to write and upload code. By following the tutorial, you'll master running multiple tasks concurrently, ideal for applications like networking, sensor data handling, and user interactions.

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🍓 What’s New on the Raspberry Pi CM5

The Raspberry Pi Compute Module 5 (CM5) brings the power of 🇳🇱 Raspberry Pi 5 to a compact, CM4-compatible form, ideal for industrial and maker applications. It offers significant performance upgrades while maintaining broad accessory compatibility.

Key features of the board:
➡️Faster CPU, GPU, and storage speeds, with eMMC storage nearing PCIe Gen 2 performance.
➡️Support for optional NVMe SSDs for high-speed operations.
➡️Enables dual camera or display configurations with flexible setups.
➡️Multiple variants (2GB–8GB RAM, eMMC, Wi-Fi) to match project needs.
➡️Broad GPIO support with most CM4-compatible accessories.

Cooling can be a challenge—passive solutions suffice for standard tasks, but overclocking requires better thermal management than the current active cooling setup offers.

Designed for embedded projects, the CM5 starts at $45 and is a powerful tool for makers and professionals seeking scalable, customizable solutions. Those with simpler needs may prefer the standard Raspberry Pi 5.

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🐟 How to Run DeepSeek R1 on Raspberry Pi 5

DeepSeek R1 can run on the 🍓 Raspberry Pi 5, enabling local AI experimentation without cloud reliance. Setting it up is simple, making it accessible even for beginners. However, running the model on the Pi 5 comes with limitations, requiring creative workarounds for better performance.

Features of this approach:
➡️Optimized distilled LLM for Raspberry Pi 5’s 8GB RAM.
➡️No AI acceleration; external GPU possible via PCIe.
➡️Simple setup using ollama’s installation script.
➡️Much slower than desktop GPUs, with noticeable latency.

This guide is perfect for AI enthusiasts and developers exploring LLMs on low-cost hardware. While the Pi 5 can handle basic tasks, serious AI work requires more powerful setups. Still, it’s an interesting experiment for those curious about running AI on compact devices.

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👩‍💻 Free YouTube Course: Developing a Linux Driver

This tutorial series is a practical guide to writing Linux kernel modules and drivers, with a focus on hardware access. It starts with an introduction to the Linux kernel, explaining its role as a hardware abstraction layer and its monolithic nature.

The series emphasizes Loadable Kernel Modules (LKMs), which allow dynamic driver loading to keep the kernel lightweight and flexible.

Key topics covered include:
➡️Kernel basics – Process management, resource allocation, and system calls.
➡️LKMs – How to write and load kernel modules dynamically.
➡️Essential mechanisms – Linked lists, mutexes, memory management, and logging.
➡️User-space interfaces – Working with /proc, /sys, and device files.
➡️Hardware interfacing – GPIOs, I²C, SPI, timers, and more.
➡️Device Tree – Adding and probing devices dynamically.

The tutorials use 🍓 Raspberry Pi for hands-on development due to its affordability, GPIO support, and ease of configuration. The series is continuously updated to reflect kernel API changes, making it a valuable resource for anyone looking to master Linux driver development.

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📠 ClockworkPi PicoCalc - Modular Open-Source Calculator

ClockworkPi PicoCalc is an open-source, modular device that resembles a scientific calculator but functions as a powerful microcontroller development platform. It features a QWERTY keyboard and a 🍓 Raspberry Pi Pico carrier board, making it ideal for customization.

Features of the project:
➡️Compatible with multiple Raspberry Pi Pico models.
➡️4-inch IPS screen, SD card slot, speakers, and 8MB PSRAM.
➡️Runs on two 18650 batteries with USB-C charging.
➡️Open-source firmware and hardware for easy modifications.
➡️QWERTY layout with backlight, connected via I2C.

By digging into PicoCalc, users can explore hardware design, firmware development, and embedded programming. The open-source nature provides an excellent opportunity to study schematics, experiment with software, and even create custom enclosures using 3D printing or CNC machining.

This project is perfect for electronics enthusiasts, programmers, and makers who enjoy building and customizing their own devices. Whether for learning, prototyping, or developing unique applications, PicoCalc offers a hands-on experience in open-source hardware and embedded systems.

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