Edge Impulse and Infineon Technologies have teamed to improve the Tiny Machine Learning-based AI development tools for the PSoCTM 63 Bluetooth® LE microcontroller (MCU). The collaboration aims to provide developers of AI-enabled IoT applications with expanded capabilities to build and deploy Edge Machine Learning (ML) applications on high-performance, low-power PSoC 63 Bluetooth LE MCUs.
Enabling AI-driven IoT solutions for Edge AI applications
Infineon Technologies, a global leader in semiconductor solutions, has announced a strategic collaboration with Edge Impulse, an innovative provider of development tools for Edge AI applications. The partnership seeks to extend the capabilities of Infineon’s Tiny Machine Learning-based AI development tools for the PSoC 63 Bluetooth LE microcontroller (MCU), empowering developers to create advanced ML applications for IoT systems.
The collaboration enables developers to leverage the Edge Impulse Studio environment, a comprehensive platform for building and deploying ML applications specifically tailored for deployment on high-performance, low-power PSoC 63 Bluetooth LE MCUs. This joint effort provides customers with increased flexibility and choice in developing and configuring ML applications for PSoC 63 Bluetooth LE MCU devices.
Infineon’s PSoC 63 Bluetooth LE MCU devices offer exceptional performance and power efficiency, making them well-suited for edge IoT applications that require advanced ML capabilities. With a dual-core Arm Cortex-M4F and Arm Cortex-M0+ chip architecture, Bluetooth LE 5.2, configurable voltage and frequency settings, and built-in hardware-based security, these MCUs provide a powerful combination of processing power, connectivity, and programmability.
Zach Shelby, CEO and co-founder of Edge Impulse, shared his excitement regarding the collaboration, highlighting the advantageous features of the PSoC 63 Bluetooth LE MCU. He emphasized how its advanced processing capabilities and low power consumption make it an excellent choice for the next generation of edge devices, ranging from wearables to industrial monitoring. According to Shelby, when combined with the Edge Impulse platform, embedde systems developers can expedite developing and deploying robust solutions for various edge ML applications.
Accelerating time-to-market for embedded AI/ML use cases
Developers can accelerate the entire process of gathering and organizing data sets, building algorithms, validating models, and releasing production-ready results to edge targets, like the PSoC 63 Bluetooth LE MCU, by integrating Edge Impulse’s full ML development tools. This collaboration empowers developers to accelerate their development cycles and quickly bring AI-driven solutions to market.
Shantanu Bhalerao, Vice President of the Bluetooth Product Line at Infineon, emphasized the advantages of the collaboration, explicitly noting how it enables Infineon customers to expedite the introduction of their solutions for embedded AI/ML use cases. Bhalerao highlighted Infineon’s dedication to empowering customers to develop their own AI/ML models or leverage a collection of predefined models provided by Infineon and its esteemed partners. According to Bhalerao, this collaboration reflects Infineon’s commitment to supporting customers in swiftly bringing their solutions to market.
Infineon is dedicated to expanding its partner network and welcomes Edge Impulse as a valuable addition. The company will continue collaborating with a diverse group of AI/ML partners to complement its existing offerings and deliver comprehensive solutions to its customers.
The collaboration between Infineon Technologies and Edge Impulse marks an important step forward in strengthening edge AI offerings for developers. Developers can unlock new possibilities in AI-enabled IoT applications by combining Infineon’s powerful PSoC 63 Bluetooth LE MCU devices with Edge Impulse’s ML development tools. This partnership enables faster development cycles, streamlined processes, and accelerated time-to-market for embedded AI/ML use cases, ultimately driving innovation in the edge computing landscape.
