Pimoroni Explorer board is a Raspberry Pi RP2350-based learning platform with 2.8-inch LCD, breadboard sensors and more

Pimoroni Explorer Starter Kit

The Pimoroni Explorer board is an electronic prototyping board built around the Raspberry Pi RP2350 chip with a 2.8-inch LCD screen, a speaker connector, and various I/Os, which makes it easy to build circuits, prototype projects, and even make small robots. It also features a mini breadboard, tactile buttons, and crocodile clip terminals, making it suitable for both beginners and experienced makers. The RP2350 MCU was recently released by Raspberry Pi Limited along with the $5 Raspberry Pi Pico 2 board. Since that initial release, we have seen many RP2350-based development boards like the Cytron MOTION 2350 Pro, the Bus Pirate 5XL and 6, and many other development boards released, feel free to check those out if you are looking for development boards built around the RP2350 MCU.   Pimoroni Explorer board specifications Microcontroller  – Raspberry Pi RP2350B MCU CPU Dual-core Arm Cortex-M33 @150MHz with Arm Trustzone for secure boot Dual-core 32-bit […]

Bus Pirate 5XL and 6 hardware debugging tools utilize Raspberry Pi RP2350A and RP2350B microcontrollers

Dangerous Prototypes Bus Pirate

The Bus Pirate 5XL and 6 are open-source hardware debugging tools respectively based on Raspberry Pi RP2350A and RP2350B and designed to simplify interaction with various bus protocols like 1-Wire, I2C, SPI, UART, several LEDs, and more. The idea is to send commands to a chip or sensor and get the response, without writing a single line of code making it ideal for hardware hacking and tinkering. The devices feature buffered I/O pins with voltage and current measurement, a programmable power supply with current limiting, an RGB LCD  for pin status and info, and an auxiliary header for connecting logic analyzers. All these features make this device useful for applications like debugging circuits, prototyping projects, and reverse engineering devices. The new devices are updates to the Bus Pirate 5 based on Raspberry Pi RP2040 MCU. You’ll find Bus Pirate specifications for the three models in the table below. The original […]

Akeana unveils 10 RISC-V cores suitable for microcontrollers up to data center chips

Chip Diagram Akeana 5000

Founded about three years ago, Akeana has just officially launched and announced three 32-bit and 64-bit RISC-V processor lines and SoC IP with the Akeana 100 series for 32-bit microcontrollers, the Akeana 1000 series for 64-bit processors with MMU, and the Akeana 5000 series with much higher single-thread performance and designed for laptops, data centers, and cloud infrastructure. The company also introduced Scalable Coherent Interconnect, Interrupt Controller, and IOMMU IP for building out compute subsystems based on the aforementioned RISC-V cores,  as well as AI-targeted Vector RISC-V Cores and Matrix Computation IP. The design team is said to have previously worked on Marvell’s ThunderX2 server chips. Akeana 100 Series The Akeana 100 Series is a line of highly configurable processors with 32-bit RISC-V cores that support applications from embedded microcontrollers to edge gateways, to personal computing devices. Four Akeana 100 RISC-V cores are available Akeana 110 for area- and power-constrained […]

Google Pigweed SDK now supports Raspberry Pi RP2350 microcontroller

Raspberry Pi Pico 2 (RP2350) with Enviro+ pack hat.

Google Pigweed, a collection of open-source libraries for embedded software development, now supports the Raspberry Pi RP2350 MCU and comes as a software development kit (Google Pigweed SDK). These libraries, also called modules, are building blocks that make embedded software development faster and more reliable. It targets tiny 32-bit microcontrollers such as STMicro STM32L452, Nordic Semi nRF52832, and the Raspberry Pi Pico line of microcontrollers. The library components have shipped in Google Pixels, Nest thermostats, robots, satellites, and drones. On August 8, the Pigweed project was released as a software development kit (SDK) in developer preview with official support for Raspberry Pi RP2350 and the associated Pico 2 development board. The new release uses the Bazel build system – a feature upstreamed into the Pico SDK by the Google Pigweed team – and a complete, open-source Clang/LLVM toolchain. The Google Pigweed SDK includes sample code, modules, and a comprehensive tutorial […]

Challenger+ RP2350 WiFi6/BLE5 board combines Raspberry Pi RP2350 MCU with ESP32-C6 WiFi 6 and Bluetooth 5.4 LE module

Raspberry Pi RP2350 board ESP32-C6 WiFi module

You don’t need to wait for the Raspberry Pi Pico 2 W to get a Raspberry Pi RP2350 board with WiFi and Bluetooth thanks to the Challenger+ RP2350 WiFi6/BLE5 board that combines an RP2350A microcontroller with an ESP32-C6 module offering 2.4 GHz WiFi 6 and Bluetooth 5.4 LE connectivity. The board follows the Adafruit Feather form factor with 28-pin through holes for I/Os making it compatible with FeatherWings add-on boards. It comes with a USB-C port for power and programming, and a JST connector plus a charging circuit for people wanting to connect a LiPo battery. Challenger+ RP2350 WiFi6/BLE5 specifications: Microcontroller – Raspberry Pi RP2350A MCU CPU Dual-core Arm Cortex-M33 processor @ 150MHz Dual-core 32-bit RISC-V processor @ 150MHz Only two cores can be used at a given time Memory – 520KB internal RAM 8KB OTP Storage Package – QFN-60; 7×7 mm Memory – 8MB PSRAM Storage – 8MB SPI […]

Solder Party’s “RP2350 Stamp” modules features Raspberry Pi RP2350A or RP2350B microcontroller

RP2350 Stamp RP2350 Stamp XL

Solder Party’s RP2350 Stamp is an update to the company’s tiny RP2040 Stamp module based on a Raspberry Pi RP2350A, and they also introduced the RP2350 Stamp XL module that makes use of the extra GPIO pins on the RP2350B, and a “RP2xxx Stamp Carrier XL” carrier board taking either module. RP2350 Stamp and RP2350 Stamp XL The RP2350 Stamp has exactly the same layout as the RP2040 Stamp and mostly benefits from the more powerful Cortex-M33 cores, additional memory, and security features, while the XL variant adds more GPIOs, footprint for a PSRAM chip, as well as UART and SWD connectors. Both come with a 16MB SPI flash for storage. RP2350 Stamp specifications: Microcontroller – Raspberry Pi RP2350A MCU CPU – Dual-core Arm Cortex-M33 processor @ 150MHz Memory – 520KB internal RAM 8KB OTP Storage Package – QFN-60; 7×7 mm Storage – 16MB flash I/Os – All 30x I/Os […]

$5 Raspberry Pi Pico 2 launched with Raspberry Pi RP2350 dual-core RISC-V or Arm Cortex-M33 microcontroller

Raspberry Pi Pico 2

The Raspberry Pi Pico 2 is an MCU development board based on the new Raspberry Pi RP2350 dual-core RISC-V or dual-core Cortex-M33 microcontroller with 520 KB on-chip SRAM, a 4MB flash, a micro USB port for power and programming and the same GPIO headers as the Raspberry Pi Pico board with an RP2040 dual-core Cortex-M0+ microcontroller with 264KB SRAM. The RP2350 embeds both an open-source Hazard3 RISC-V dual-core CPU and a dual-core Cortex-M33, but only one cluster can be used at a given time. Apart from the faster MCU cores and higher SRAM capacity, the RP2350 is about the same as the RP2040, albeit it also adds one extra PIO block bringing the total to three. One important new feature is built-in security when using Arm Cortex-M33 cores with Trustzone and other security features. Raspberry Pi RP2350 microcontroller Let’s have a closer look at the RP2350 microcontroller, before checking out […]

Femtosense introduces the AI-ADAM-100 system-in-package for affordable, efficient AI-based voice processing on the edge

Femtosense AI-ADAM-100

Femtosense’s newest release, the AI-ADAM-100, combines a low-power Arm Cortex M0+ microcontroller from ABOV Semiconductor with the Femtosense Sparse Processing Unit (SPU), an in-house neural processing unit. This combination powers AI voice processing and cleanup capabilities on edge devices. It leverages sparsity techniques to ensure that models can run on edge devices without intensive processing. Sparsity in AI refers to the presence of zeroes or non-zero values in the matrices and tensors used in machine learning models. No computation is required for these zero weights, heavily reducing processing requirements. The Femtosense AI-ADAM-100 aims to bring voice control to various devices such as home appliances, hearing aids, industrial headsets, and consumer earbuds. These appliances can implement voice user interfaces that allow users to talk naturally in their own words. On-device voice cleanup functionality would reduce infrastructure costs and improve the accuracy of the data sent to the cloud. The Femtosense SiP […]

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