Infineon showcases its PSoC Edge MCU family, a heterogeneous Arm Cortex-M55/M33 platform with Helium DSP, Arm Ethos-U55 NPU and Infineon’s NNLite accelerator, aimed at low-power edge machine learning for face ID, voice assistants and rich 2.5D graphics HMI on a compact evaluation kit platform https://www.infineon.com/promo/next-generation-mcu
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In the interview, Infineon engineer Alexi walks through the PSoC Edge evaluation kit that combines a high-density MCU module, display and an extension board with extra peripherals to prototype human–machine interfaces, smart home nodes and industrial control devices on the same hardware. Shot during Embedded World North America 2025 in San Diego, the demo highlights how the graphics engine, memory subsystem and sensor interfaces are tuned for responsive yet energy-efficient interaction on battery-powered hardware
The conversation focuses on deploying machine learning models directly into the microcontroller, with examples like on-device face recognition on the Cortex-M55 plus Ethos-U55 path and keyword-spotting voice assistance running in the low-power domain. Infineon’s toolchain combines ModusToolbox, DEEPCRAFT AI Suite and support for NVIDIA TAO-generated models so developers can train, quantize and map neural networks efficiently onto the PSoC Edge accelerators while staying within tight memory and power envelopes
For embedded developers, this video offers a concise look at how PSoC Edge turns Arm-based microcontrollers into practical TinyML platforms for wearables, smart locks, appliances, domestic robots, industrial robots and other HMI-centric designs. With always-on acoustic activity detection, on-chip non-volatile RRAM, up to several megabytes of SRAM and open demo projects available online, the PSoC Edge family provides a realistic path from proof-of-concept boards to production-grade edge AI products in the broader Infineon ecosystem
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