Shivay Lamba (@HowDevelop)

AI Engineer Melbourne 행사에서 엣지 환경을 위해 AI 모델을 distill 및 quantize하는 방법을 발표한다는 소식입니다. 경량화 모델과 온디바이스/엣지 배포에 관심 있는 개발자에게 유용한 내용입니다.

https://x.com/HowDevelop/status/2051893884767363475

#aiengineering #distillation #quantization #edgeai #models

Shivay Lamba (@HowDevelop) on X

Super stoked to speak at @aiDotEngineer (AI Engineer) Melbourne next month on how to distill and quantize AI models for the edge!

X (formerly Twitter)
Toradex Zinnia Linux IoT Gateway offers dual GbE, WiFi 5, 4G LTE, I/Os, and simplified software deployment

Toradex Zinnia is an industrial IoT gateway based on the company's Verdin system-on-module, powered by a choice of NXP or Texas Instruments SoC, with dual Gigabit Ethernet, WiFi 5, Bluetooth 5, optional 4G LTE or 5G connectivity, a few USB ports, an I/O connectors, and a wide 9-36V power supply range. The first model is based on an NXP i.M 8M Plus SoM with 4GB LPDDR5 and 32GB eMMC flash preloaded with the company's Torizon OS Linux distribution. Other SoM available are based on TI AM62/AM62P, NXP i.MX 8M Mini, or NXP iMX 95. The gateway targets edge AI and industrial automation, smart cities, and energy infrastructure. Toradex Zinnia specifications: SoC – NXP i.MX 8M Plus CPU – Quad-core Cortex-A53 processor @ 1.6/1.8 GHz, Arm Cortex-M7 real-time core @ 800 MHz GPU – Vivante GC7000UL OpenGL ES 1.1, 2.0, 3.0, OpenCL 1.2, Vulkan support AI accelerator – 2.3 TOPS NPU

CNX Software - Embedded Systems News

🧩 24 Ideas. 1 Future | @O_CEI_Horizon Open Call Winners

Indigma AI is revolutionizing EV fleet management with privacy-first intelligence.

Through ARIEL, they use federated learning to train AI models directly at charging stations. This ensures operational data stays local and secure while enabling smart demand prediction and battery monitoring for a sustainable transport future.

📰 Winner: https://o-cei.eu/indigma/
🔎 Pilot 3: https://o-cei.eu/use-cases-pilot-3/

#Privacy #EV #EdgeAI #Innovation #EUHorizon

@kuketzblog Ich empfehle Vosk 🗣️✅ — Offline-Spracherkennung, die zuverlässig auf dem Raspberry Pi 🥧 läuft. Einfache Installation & Python-Integration 🐍🔧. Ressourcenschonend, leicht und datenschutzfreundlich 🔒⚡. Perfekt für lokale Sprachassistenten—so behältst du die Kontrolle über deine Daten.
https://alphacephei.com/vosk/
#Vosk #RaspberryPi #OfflineASR #Python #OpenSource #Datenschutz #EdgeAI
VOSK Offline Speech Recognition API

Accurate speech recognition for Android, iOS, Raspberry Pi and servers with Python, Java, C#, Swift and Node.

VOSK Offline Speech Recognition API

Omar Sanseviero (@osanseviero)

Gemma 4 Multi-Token Prediction Drafters가 공개되었습니다. 최대 3배의 추론 속도 향상과 동일한 품질 보장을 내세우며, 익숙한 오픈소스 도구에서 바로 사용할 수 있다고 합니다. 온디바이스·엣지 환경의 빠른 추론을 원하는 개발자에게 매우 중요한 모델/기술 발표입니다.

https://x.com/osanseviero/status/2051695861801820475

#gemma #multitokenprediction #inference #opensource #edgeai

Omar Sanseviero (@osanseviero) on X

Excited to introduce Gemma 4 Multi-Token Prediction Drafters⚡️Accelerated inference right in your pockets - Up to a 3x speedup - Same quality guarantees - Available in your favorite open-source tools

X (formerly Twitter)
Renesas RZ/V2H Robotics Development Kit handles AI vision, motor control, and power management with a single board

Renesas WS125-V2HRDKREFZ is a Robotics Development Kit (RDK) powered by Renesas RZ/V2H Arm Cortex-A55/R8/M33 microprocessor and designed for high‑performance AI vision applications leveraging the MPU's built-in 80 TOPS (sparse) AI accelerator. The kit ships with 16GB LPDDR4, 64MB QSPI flash, a 64GB microSD card, and appears to be partially inspired by the Raspberry Pi 5 with a 40-pin Raspberry Pi GPIO header, a 16-pin PCIe Gen3 FFC connector, two MIPI CSI connectors, and a micro HDMI port. Other features include a Gigabit Ethernet port, two USB 3.2 ports, two CAN-FD interfaces, and a 12-24V DC input voltage range. Renesas WS125-V2HRDKREFZ specifications: SoC – Renesas RZ/V2H CPU/MCU cores 4x Arm Cortex-A55 cores up to 1.8 GHz 2x Cortex-R8 real-time cores up to 800 MHz Arm Cortex-M33 microcontroller core up to 200 MHz for system management GPU – Arm Mali-G31 GPU NPU - DRP-AI3 dynamically reconfigurable processor delivering up to 8 TOPS (INT8) or

CNX Software - Embedded Systems News
Congatec conga-TC300 COM Express module features up to Intel Core 7 350 Wildcat Lake processor

congatec conga-TC300 is an entry-level edge AI COM Express Type-6 Compact module powered by 15W Intel Core Series 3 "Wildcat Lake" SoCs up to the Core 7 350 hexa-core processor. The module supports up to 64GB DDR5 SO-DIMM memory and features optional on-board UFS 3.1 storage, an Intel i226 2.5GbE controller, and two standard 220-pin board-to-board connectors exposing I/Os such as SATA, DDI and LVDS or eDP display interfaces, USB4, USB 3.2, USB 2.0, PCIe Gen4/Gen3, and more. congatec conga-TC300 specifications: Wildcat Lake SoC (one or the other) Intel Core 3 305 6-core CPU - 2x P-cores @ 1.5/4.3 GHz (Turbo) + 4x LPE-cores @  1.4/3.3 GHz (Turbo) GPU - 1-core Intel Xe3 Graphics @ 2.3 GHz (9 TOPS) NPU - N/A Intel Core 5 320 6-core CPU - 2x P-cores @ 1.5/4.6 GHz (Turbo) + 4x LPE-cores @ 1.4/3.4 GHz (Turbo) GPU - 2-core Intel Xe3 Graphics @ 2.5

CNX Software - Embedded Systems News

🧩 24 Ideas. 1 Future | @O_CEI_Horizon Open Call Winners

Spotlight on Pilot 3: InfAI is bringing advanced data intelligence to #EV fleet management! 🚗⚡️

Through the INFINITY project, they use a Cloud-Edge-IoT approach to enable real-time monitoring and smart scheduling. This "digital backbone" for software-defined vehicles ensures efficient operations without grid overload.

📰 Winner: https://o-cei.eu/infai-infinity/
🔎 Pilot 3: https://o-cei.eu/use-cases-pilot-3/

#SmartGrid #IoT #Innovation #GreenMobility #EdgeAI

Banana Pi BPI-OM7 AI 3D camera pairs BPI-M7 RK3588 SBC with ORBBEC Gemini 2 depth camera

Banana Pi BPI-OM7 is an AI 3D depth camera that combines Banana Pi BPI-M7 low-profile Rockchip RK3588 SBC with an ORBBEC Gemini 2 depth camera, targeting applications in 3D vision, robotics, edge AI, and spatial perception. The solution ships with 8GB of RAM and a 64GB eMMC flash by default, offers HDMI and USB-C video outputs, dual 2.5GbE networking, and a few USB ports. It's mounted on a tripod for convenience. Banana Pi BPI-OM7 specifications: SoC – Rockchip RK3588 octa-core processor with CPU – 4x Cortex‑A76  cores @ up to 2.4 GHz, 4x Cortex‑A55 core @ 1.8 GHz GPU – Arm Mali-G610 MP4 GPU Video decoder – 8Kp60 H.265, VP9, AVS2, 8Kp30 H.264 AVC/MVC, 4Kp60 AV1, 1080p60 MPEG-2/-1, VC-1, VP8 Video encoder – 8Kp30 H.265/H.264 video encoder AI accelerator – 6 TOPS NPU System Memory – 8GB (default), 16GB, or 32GB LPDDR4x Storage 32GB, 64GB (default), or 128GB eMMC flash

CNX Software - Embedded Systems News