Arduino Nicla Voice enables always-on speech recognition with Syntiant NDP120 “Neural Decision Processor”

Arduino PRO Nicla Voice with LiPo battery

Nicla Voice is the latest board from the Arduino PRO family with support for always-on speech recognition thanks to the Syntiant NDP120 “Neural Decision Processor” with a neural network accelerator, a HiFi 3 audio DSP, and a Cortex-M0+ microcontroller core, and the board also includes a Nordic Semi nRF52832 MCU for Bluetooth LE connectivity. Arduino previously launched the Nicla Sense with Bosch SensorTech’s motion and environmental sensors, followed by the Nicla Vision for machine vision applications, and now the company is adding audio and voice support for TinyML and IoT applications with the Nicla Voice. Nicla Voice specifications: Microprocessor – Syntiant NDP120 Neural Decision Processor (NDP) with one Syntiant Core 2 ultra-low-power deep neural network inference engine, 1x HiFi 3 Audio DSP, 1x Arm Cortex-M0 core up to 48 MHz, 48KB SRAM Wireless MCU – Nordic Semiconductor nRF52832 Arm Cortex-M4 microcontroller @ 64 MHz with 512KB Flash, 64KB RAM, Bluetooth […]

VAR-SOM-MX93 SO-DIMM NXP i.MX 93 SoM features WiFi, Bluetooth, Audio codec

NXP i.MX 93 development board

Variscite VAR-SOM-MX93 is a 200-pin SO-DIMM system-on-module based on NXP i.MX 93 dual-core Cortex-A55/M33 AI processor with up to 2 GB LPDDR4 RAM, 64GB eMMC flash, and onboard WiFi & Bluetooth module and audio driver. The Variscite module follows the announcement of two other NXP i.MX 93 system-on-modules, namely the Forlinx FET-MX9352-C with board-to-board connectors and the iWave Systems iW-RainboW-G50M LGA module compliant with OSM Size L form factor to be soldered directly on the carrier board. VAR-SOM-MX93 specifications: SoC – NXP i.MX 93 with up to 2x Cortex-A55 cores @ 1.7GHz, 1x Cortex-M33 real-time co-processor @ 250 MHz, 0.5 TOPS NPU, 2D PxP graphics engine System Memory – 512MB to 2GB LPDDR4 Storage – 8 to 64GB eMMC flash, 4KB EEPROM Ethernet – ADIN1300 Gigabit Ethernet PHY Wireless module Single-band 802.11 b/g/n WiFi 4 or dual-band 802.11 ac/a/b/g/n WiFi 5 Bluetooth 5.2 classic + LE Audio – Unnamed Audio […]

Maker Feather AIoT S3 – An ESP32-S3 board programmable with CircuitPython or Arduino

Maker Feather AIOT S3

Cytron Maker Feather AIoT S3 is an ESP32-S3 board compatible with the Adafruit Feather form factor and suitable for makers and STEM education with features like LEDs for GPIOs, a buzzer, expansion headers and connectors, and support for CircuitPython & Arduino. The WiFi and Bluetooth LE IoT board also supports LiPo and Li-Ion batteries, includes a USB Type-C port for power/charging and programming, and a few buttons. It’s suitable for machine learning thanks to the vector extensions found in the ESP32-S3 microcontroller. Maker Feather AIoT S3 specifications: Wireless module – Espressif ESP32-S3-WROOM-1-N8R8 module with ESP32-S3 dual-core LX7 microprocessor @ up to 240 MHz with Vector extension for machine learning, 8MB FLASH, 8MB PSRAM, WiFi 4 and Bluetooth 5 LE/Mesh USB – 1x USB Type-C port power and programming Expansion 2x GPIO headers compatible with Adafruit Feather form factor and FeatherWing add-on boards 3x Maker Ports compatible with Qwiic, STEMMA QT, […]

MistySoM Renesas RZ/G2L or RZ/V2L SoM and devkit goes for $112 and up

MistySOM devkit Renesas RZ/G2L or RZ/V2L

We’ve previously written about several system-on-modules and SBCs based on Renesas RZ/G2L or RZ/V2L Cortex-A55/M33 processors such as Geniatech “AHAURA” RS-G2L100 and “AKITIO” RS-V2L100 single board computers, Forlinx FET-G2LD-C system-on-module, and SolidRun RZ/G2LC SOM and devkit. But most of those are hard to buy, and you need to contact the company, discuss your project, etc… before purchase, except for the SolidRun Renesas RZ/G2LC Evaluation Kit going for $249. Another option is the MistyWest MistySOM module offered for $112 and up on GroupGets with either Renesas RZ/G2L or RZ/V2L processor, as well as an optional carrier board. MistySOM system-on-module MistySOM-G2L (aka MW-G2L) and MistySOM-V2L (aka MW-V2L) specifications: SoC – Renesas RZ/G2L or RZ/V2L with dual-core Cortex-A55 processor @ 1.2 GHz, Arm Cortex-M33 core @ up to 200 MHz, Arm Mali-G31 GPU, and DRP-AI vision accelerator (RZ/V2L only) System Memory – 2GB LPDDR4/DDR4 Storage – 32GB eMMC flash 2x 120-pin high-speed mezzanine […]

NXP i.MX 95 processor features Cortex-A55, Cortex-M33, and Cortex-M7 cores, eIQ Neutron NPU

NXP i.MX 95 CPU

NXP i.MX 95 is an upcoming Arm processor family for automotive, industrial, and IoT applications with up to six Cortex-A55 application cores, a Cortex-M33 safety core, a Cortex-M7 real-time core, and NXP eIQ Neutron Neural Network Accelerator (NPU). We’re just only starting to see NXP i.MX 93 modules from companies like iWave Systems and Forlinx, but NXP is already working on its second i.MX 9 processor family with the i.MX 95 application processor family equipped with a higher number of Cortex-A55 cores, an Arm Mali 3D GPU, NXP SafeAssure functional safety, 10GbE, support for TSN, and the company’s eIQ Neutron Neural Processing Unit (NPU) to enable machine learning applications. NXP i.MX 95 specifications: CPU Up to 6x Arm Cortex-A55 cores with 32KB I-cache, 32KB D-cache, 64KB L2 cache, 512KB L3 cache with ECC 1x Arm Corex-M7 real-time core with 32KB I-cache, 32KB D-cache, 512KB TCM with ECC 1x Arm Cortex-M33 […]

Forlinx FET-MX9352-C – An NXP i.MX 9352 system-on-module for industrial AIoT applications

Forlinx FET-MX9352-C System-on-Module

Forlinx FET-MX9352-C is a system-on-module based on NXP i.MX 9352 dual Cortex-A55 processor with Cortex-M33 real-time core and a 0.5 TOPS AI accelerator that can be used for industrial control, IoT gateways, medical equipment, and various applications requiring machine learning acceleration. The FET-MX9352-C follows last week’s announcement of the iWave Systems iW-RainboW-G50M OSM module and SBC with a choice of NXP i.MX 93 processors. The Forlinx module comes with two board-to-board connectors instead of solderable pads and can be found in the OK-MX9352-C single board computer with dual GbE, various display and camera interfaces, RS485 and CAN Bus, etc… FET-MX9352-C i.MX 9352 system-on-module Specifications: SoC – NXP i.MX 9352 with 2x Arm Cortex-A55 cores @ up to 1.7GHz (commercial) or 1.5 GHz (industrial), Cortex-M33 real-time core @ 250 MHz, 0.5 TOPS Arm Ethos U65 microNPU System Memory – 1GB/2GB LPDDR4 RAM Storage – 8GB eMMC flash 2x high-density 100-pin board-to-board […]

Pico-ITX SBC features NXP i.MX 93 LGA system-on-module

NXP i.MX 93 SBC

iWave Sytems iW-RainboW-G50M is an NXP i.MX 93 OSM-L compliant LGA module with up to 2GB RAM, WiFi 5 and Bluetooth 5.2 module that is found in the company’s iW-RainboW-G50S Pico-ITX SBC designed for industrial applications. The NXP i.MX 93 single and dual-core Cortex-A55 processor with an Ethos U65 microNPU was announced in November 2021, but we had yet to see any hardware based on the new NXP i.MX 9 processor family. The iW-RainboW-G50M and iW-RainboW-G50S change that with a system-on-module and single board computer. iW-RainboW-G50M NXP i.MX 93 system-on-module Specifications: SoC (one or the other) NXP i.MX 9352 dual-core Cortex-A55 processor @ up to 1.7 GHz with Arm Cortex-M33 @ 250 MHz,  0.5 TOPS NPU NXP i.MX 9351 single-core Cortex-A55 processor @ up to 1.7 GHz with Arm Cortex-M33 @ 250 MHz, 0.5 TOPS NPU NXP i.MX 9332 dual-core Cortex-A55 processor @ up to 1.7 GHz Arm Cortex-M33 @ […]

Achronix Speedster7t AC7t1500 FPGA is now available for high-bandwidth applications

Speedster7t 7t1500 VectorPath Accelerator Card

Achronix Semiconductor has recently announced the general availability of the Speedster7t AC7t1500 FPGA designed for networking, storage, and compute (AI/ML) acceleration applications. The 7nm Speedster7t FPGA family offers PCIe Gen5 ports and GDRR6 and DDR5/DDR4 memory interfaces, delivers up to 400 Gbps on the Ethernet ports, and includes a 2D network on chip (2D NoC) that can handle 20 Tbps of total bandwidth. Achronix Speedster7t highlights: Two-dimensional network on chip (2D NoC) enabling high bandwidth data flow throughout and between the FPGA fabric and hard I/O and memory controllers and interfaces MLP (Machine Learning Processors) blocks with arrays of multipliers, adder trees, accumulators, and support for both fixed and floating-point operations, including direct support for Tensorflow’s bfloat16 format and block floating-point (BFP) format. Multiple PCIe Gen5 ports High-speed SerDes transceivers, supporting 112 Gbps PAM4 and 56 Gbps PAM4/NRZ modulation, as well as lower data rates Hard Ethernet MACs that support […]