Nuvoton has announced its latest Endpoint AI Platform, designed to expedite the creation of comprehensive microcontroller (MCU) AI products. The platform uses Nuvoton’s advanced MCU and MPU silicon, such as the NuMicro M55M1 featuring Ethos U55 NPU, NuMicro MA35D1, and NuMicro M467 series. These MCUs serve as valuable additions to the contemporary AI-focused computing toolkit, showcasing Nuvoton’s ongoing collaboration with Arm and other industry leaders to develop a user-friendly and all-encompassing Endpoint AI Ecosystem.
Development on these platforms is made easy by Nuvoton’s NuEdgeWise, a tool for machine learning (ML) development, which is nonetheless suitable for cutting-edge tasks.
These new single-chip-based platforms are ideal for applications including smart home appliances and security, smart city services, industry, agriculture, entertainment, environmental protection, education, highly accurate voice-control tasks, sports, health, and fitness.
New ML-focused hardware with NPU: NuMicro M55M1
The NuMicro M55M1 series microcontroller is targeted at machine learning applications, aided by its Ethos-U55 NPU (neural processing unit) and on-device AI features suitable for embedded applications. This MCU lets the system watch for events – based on image sensor, microphone and sensors – while in low-power mode, without waking up the central processor.
The M55M1 MCU includes an ML model protection mechanism that enhances security by safeguarding ML intellectual property against potential malicious hacking attempts. These are some of the first processors to support Arm Helium technology, which provides a significant performance boost for ML and digital signal processing (DSP) applications in small, low-power embedded systems.
Edge IIoT gateway solution: NuMicro MA35D1
The MA35D1 series is a heterogeneous multi-core microprocessor for high-end Edge IIoT Gateway, based on a dual-core 64-bit Arm Cortex-A35 core at 800 MHz and a 180 MHz Arm Cortex-M4. These high-performance cores facilitate Tiny AI/ML edge computing.
The versatile M467, with IoT applications and great connectivity
The M467 series is a 32-bit microcontroller based on the Arm Cortex-M4F core with a built-in DSP instruction set and single precision floating point unit (FPU). It is ideal for various applications, including smart home appliances, IoT gateways, industrial control, telecommunications, and data centres.
The M467 microcontroller offers a range of connectivity, I/O, and security peripherals deployed for IoT tasks. These include Ethernet 10/100 MAC for network connectivity, hardware encryption, decryption, and key storage for enhanced security. The M467 also provides extensive built-in I/O support, allowing users to select the specific hardware extensions required for their applications.
Additionally, the M467 supports HyperRAM, which offers 64MB of memory for AI/ML applications. This memory flexibility enables the handling of various ML models with different memory sizes or density requirements. HyperRAM also provides power-saving features, compatibility with available bandwidth, ease of use, and expandable memory options.
Strong development support
Fully-featured development boards are available for all of the above hardware applications. These are supported by Nuvoton’s deep development tools, development environment, and enthusiastic support. For example, the NuMaker MA35D1 facilitates the development of AI applications, allowing for efficient ML projects like image classification. Additionally, it offers an intuitive Human Machine Interface (HMI) that presents analysis to the user in a user-friendly manner. On the other hand, the NuMaker-IoT-M467 development board is designed for IoT applications utilising the M467 MCU.
NuEdgeWise ML IDE makes TinyML development simple
Nuvoton’s NuEdgeWise integrated development environment (IDE) is a machine-learning tool designed for TinyML development. The IDE supports the four key stages of ML application development: labelling, training, validation, and testing. NuEdgeWise uses the popular Jupyter Notebook platform, allowing developers to train and deploy models on Nuvoton chips using TensorFlow Lite. This makes TinyML applications more accessible and easier to implement.
Nuvoton provides information including details on its applications for Nuvoton machine learning solutions at www.nuvoton.com/ai.
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- Source: https://www.iot-now.com/2024/01/08/141667-nuvoton-unveils-endpoint-ai-platform-for-mcu-ai-products/
