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Infineon Accelerates ML Application Development with New EdgeAI Evaluation Kit

Google 우선 소스Published2024.07.30 11:34


PSoC™ 6 AI Evaluation Kit Provides All the Tools Needed to Build Smart Home and IoT Applications
Cloud-centric solution architecture with improved real-time performance, power efficiency, and other benefits
Infineon Technologies AG (hereafter Infineon) announced on the 30th that it is launching a comprehensive evaluation kit for embedded, edge AI and machine learning (ML) system design.

The new PSoC™ 6 AI Evaluation Kit provides all the tools needed to build smart home and IoT applications.

The solution runs inference next to the sensor data source, providing improved real-time performance and power efficiency compared to cloud-centric solution architectures.

With its small form factor of 35 mm x 45 mm, reasonable price, and integration of various sensors and connectivity, it is ideal for field data collection, rapid prototyping, model evaluation, and solution development.

The PSoC 6 AI evaluation kit is supported by Infineon’s advanced MCU, sensor and connectivity portfolio and a powerful software development environment including Infineon’s ModusToolbox™, Imagimob Studio for custom ML models and Ready Models, off-the-shelf software.

The new AI evaluation kit includes hardware suitable for edge AI models andIt features AI models and tools that support a variety of applications.

The evaluation kit based on the Infineon PSoC 6 MCU supports development with the comprehensive XENSIV™ portfolio of connectivity products for automotive, industrial and consumer applications, including Wi-Fi, Bluetooth and Bluetooth low energy (BLE) solutions.

Imagimob Studio also allows developers to quickly transition to production. The platform is free to use (users only pay for new models after they launch a product) and makes it easy to build high-quality AI models from scratch or optimize existing ones.

Imagimob Ready Models enable businesses to access AI models even if they don’t have the time, money, or machine learning know-how required to develop custom models.
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