CHIPSEA CST85F01 480 MHz Cortex-M4 MCU supports dual-band WiFi 6 and Bluetooth 5.0 LE

Dual-band WiFi 6 IoT module

CHIPSEA CST85F01 is an Arm Cortex-M4F microcontroller clocked at up to 480 MHz and designed for IoT applications with dual-band (2.4/5.0 GHz) WiFi 6 with TWT (Target Wake Time) support, Bluetooth 5.0 LE, and a range of I/Os. Following the recent availability of 2.4 GHz WiFi 6 IoT chips such as Espressif Systems ESP32-C6 and Bouffalo Lab BL616, CHIPSEA CST85F01 offers an alternative with dual-band WiFi 6 connectivity while we are waiting for the launch of the ESP32-C5 RISC-V microcontroller. CST85F01 specifications: CPU core – Arm Cortex-M4F CPU with MPU and FPU @ up to 480 MHz Memory – 992 KB SRAM, SDR/DDR PSRAM interfaces Storage – 752 KB ROM, 8 Mbit to 128 Mbit flash WiFi features 2.4GHz/5GHz Wi-Fi 6 Data rates up to 286.8 Mbps (Tx) and 229.4 Mbps (Rx) with 20/40 MHz bandwidth Rx sensitivity – -98dBm in 11b mode, -93.5dBm in MCS0 HT20 mode Tx power […]

Panthronics PTX30W is a 1W NFC wireless charging listener IC

Panthronics PTX30W is an NFC wireless charging listener chip that can receive up to 1W as per the NFC Wireless Charging (WLC) specification unveiled in 2020 and integrates a power management unit and a Li-Ion battery charger. Offered in a compact 3.2mm2 (1.78 x 1.78 mm) WL-CSP package, the PTX30W will enable small battery-powered products, such as smartwatches and other wearables, to be charged over NFC. The chip can operate in standalone mode or connected to a host microcontroller, and the company claims it is around four times smaller than existing designs based on multiple discrete components. PTX30W features and specifications: Integrated NFC Wireless Charging Listener device Efficient Active Rectifier RF interface according to Forum Type 2 Tag Li-Ion battery charger with charging current from 5mA to 250mA MCU LDO with 1.8V or 3.3V output, up to 50mA Embedded power negotiation logic High-efficiency NFC wireless charging listener IC with up […]

$150 Axelera M.2 AI accelerator module claims to deliver up to 214 TOPS

Axelera M.2 AI accelerator module is said to deliver up to 214 TOPS of AI inference and up to 3200 FPS with ResNet -50 in a compact M.2 2280 form factor. Few details are available at this time, but the module is based on the company’s Metis AIPU (AI Processing Unit) using in-memory computing based on arrays of SRAM memory devices used to “store a matrix and perform matrix-vector multiplications “in-place” without intermediate movement of data”. This technology is said to “radically” increase the number of operations per computer cycle with without suffering from issues such as noise or lower accuracy. The Metis AI platform delivers 50+ TOPS per core (RISC-V-controlled dataflow engine), offers FP32 equivalent accuracy, and has a 15 TOPS/W energy efficiency. The last point is impressive, but that means 214 TOPS won’t be reachable with the module shown above, since the M.2 form factor is designed to […]

Bouffalo Lab BL616/BL618 RISC-V MCU supports WiFi 6, Bluetooth 5.2, and Zigbee

Bouffalo Lab BL616/BL618 is a 32-bit RISC-V wireless microcontroller with support for 2.4 GHz WiFi 6, Bluetooth 5.2 dual-mode, and an 802.15.4 radio for Zigbee, Thread, and Matter designed for IoT applications. We first spotted the BL616 RISC-V IoT MCU during the BL602/BL606 announcement in November 2020, but we had virtually no additional information about it so far. It appears both BL616 and BL618 will be launched next month with the main difference between the two being that BL616 has 19 GPIOs and BL618 comes with 35 GPIOs. Bouffalo Lab BL616 and BL618 specifications: MCU core – 32-bit RISC-V CPU (RV32IMAFCP) @ up to 320 MHz with FPU and DSP, 32KB instruction cache & 16KB data cache VPU – MJPEG video encoder Memory – 480KB SRAM, 4KB HBN RAM, embedded 4 or 8MB pSRAM (optional) Storage – 128KB ROM, 4Kb eFuse, embedded 2, 4, or 8MB flash (optional), XIP QSPI […]

Aetina launches ASIC-based Edge AI system with a 16 TOPS Blaize P1600 embedded SoM

Aetina AIE-CP1A-A1 is a compact, ASIC-based Edge AI system powered by the Blaize Pathfinder P1600 embedded system-on-module (SoM) equipped with dual-core Cortex-A53 processor, the Blaize Graph Streaming Processor (GSP) architecture delivering up to 16 TOPS, and 4GB RAM. The Aetina AI inference system also comes with 8GB eMMC flash, HDMI video output, Gigabit Ethernet, two USB 3.2 ports, and a serial interface, with the small-sized embedded computer targetting computer vision applications such as object detection, human motion detection, and automated inspection. Aetina AIE-CP1A-A1 specifications System-on-Module – Blaize PathFinder P1600 SoM SoC – Blaize 1600 dual ArmCortex A53 processor with H.264/H.265 encode and decode, MIPI CSI/DSI camera interfaces, PCIe Gen 3.0, Blaize GSP 16 TOPS AI accelerator supporting  INT8, INT16, BF16, FP16, FP32, and FP64 data formats System Memory – 4GB LPDDR4 Storage – 64 MB Quad SPI NOR Flash Carrier board interface – 400-pin board-to-board connector Cooling – Thermal transfer […]

Sipeed M1s & M0sense – Low-cost BL808 & BL702 based AI modules (Crowdfunding)

Sipeed has launched the M1s and M0Sense AI modules. Designed for AIoT application, the Sipeed M1s is based on the Bouffalo Lab BL808 32-bit/64-bit RISC-V wireless SoC with WiFi, Bluetooth, and an 802.15.4 radio for Zigbee support, as well as the BLAI-100 (Bouffalo Lab AI engine) NPU for video/audio detection and/or recognition. The Sipeed M0Sense targets TinyML applications with the Bouffa Lab BL702 32-bit microcontroller also offering WiFi, BLE, and Zigbee connectivity. Sipeed M1s AIoT module The Sipeed M1S is an update to the Kendryte K210-powered Sipeed M1 introduced several years ago. Sipeed M1s module specifications: SoC – Bouffalo Lab BL808 with CPU Alibaba T-head C906 64-bit RISC-V (RV64GCV+) core @ 480MHz Alibaba T-head E907 32-bit RISC-V (RV32GCP+) core @ 320MHz 32-bit RISC-V (RV32EMC) core @ 160 MHz Memory – 768KB SRAM and 64MB embedded PSRAM AI accelerator – NPU BLAI-100 (Bouffalo Lab AI engine) for video/audio detection/recognition delivering up […]

Quadric Chimera GPNPU IP combines NPU, DSP, and real-time CPU into one single programmable core

A typical chip for AI or ML inference would include an NPU, a DSP, a real-time CPU, plus some memory, an application processor, an ISP, and a few more IP blocks. Quadric Chimera GPNPU (general purpose neural processor unit) IP combines the NPU, DSP, and real-time CPU into one single programmable core. According to Quadric, the main benefit of such design is simplifying system-on-chip (SoC) hardware design and subsequent software programming once the chip is available thanks to a unified architecture for machine learning inference as well as pre-and-post processing. Since the core is programmable it should also be future-proof. Three “QB series” Chimera GPNPU cores are available: Chimera QB1 – 1 TOPS machine learning, 64 GOPS DSP capability Chimera QB4 – 4 TOPS ML, 256 GOPS DSP Chimera QB16 – 16 TOPS ML, 1 TOPS DSP Quadric says the Chimera cores can be used with any (modern) manufacturing process […]

AI Thinker Ai-WB2 modules feature BL602 RISC-V MCU with WiFi and BLE connectivity

AI Thinker has just introduced a new family of wireless IoT modules with the Ai-WB2 equipped with Bouffalo Lab BL602 RISC-V microcontroller offering both 2.4 GHz WiFi 4 and Bluetooth 5.0 LE connectivity. There are ten different modules to choose from, probably to keep mechanical and electrical compatibility with ESP8266 and ESP32 modules, and the company expects customers to integrate those into Internet of Things (IoT) products, mobile devices, wearables, Smart Home appliances, and more. Ai-WB2 modules share the following specifications: Wireless MCU – Bouffalo Lab BL602 32-bit RISC-V microcontroller @ up to 192 MHz with 276KB SRAM, 2.4 GHz WiFi 4 and Bluetooth 5.0 LE connectivity Storage – 2MB or 4MB SPI flash WiFi range – Up to about 500 meters (typical) I/Os – SDIO, SPI, UART, I2C, IR receiver, PWM, ADC, DAC, and GPIO  (except Ai-WB2-01S with just UART/PWM/GPIO/ADC) Power Supply – 2.7V to 3.6V > 500mA Power […]