Alif Semiconductor unveiled the Ensemble E4, E6, and E8 dual-core Cortex-M55 Edge AI microcontrollers and fusion processors, all equipped with Arm Ethos-U85 with the ability to run small language models (SLM) on-device while consuming just 36mW of power on the E4 SKU. Besides the ability to handle generative AI workloads, the new microcontrollers also integrate two power-efficient Ethos-U55 NPUs for AI vision. They can perform power-efficient object detection in less than 2ms and image classification in less than 8ms. Other highlights include support for up to two MIPI CSI image sensors, a fully hardware-accelerated image signal processor (ISP) pipeline operating at up to 60 FPS at 2MP resolution, and a new wide memory subsystem to enable an inferencing speed of well under a millisecond. Alif Ensemble E4 Ensemble E4 specifications: CPU High-Performance Arm Cortex-M55 core @ up to 400 MHz High-Efficiency Arm Cortex-M55 core @ up to 160 MHz GPU […]
MicroPython-programmable OpenMV N6 and AE3 AI camera boards run on battery for years (Crowdfunding)
OpenMV has launched two new edge AI camera boards programmable with MicroPython: the OpenMV AE3 powered by an Alif Ensemble E3 dual Cortex-M55, dual Ethos-U55 micro NPU SoC, and the larger OpenMV N6 board based on an STMicro STM32N6 Cortex-M55 microcontroller with a 1 GHz Neural-ART AI/ML accelerator. Both can run machine vision workloads for several years on a single battery charge. The OpenMV team has made several MCU-based camera boards and corresponding OpenMV firmware for computer vision, and we first noticed the company when they launched the STM32F427-based OpenMV Cam back in 2015. A lot of progress has been made over the years in terms of hardware, firmware, and software, but the inclusion of AI accelerators inside microcontrollers provides a leap in performance, and the new OpenMV N6 and AE3 are more than 100x faster than previous OpenMV Cams for AI workloads. For example, users can now run object […]


