Infineon Technologies has launched an edge AI tool for microcontrollers from its acquisition of Cypress Semiconductor.
The Machine Learning (ML) add on to the ModusToolbox tool works with the PSoC microcontrollers developed by Cypress around the ARM Cortex-M core. This provides middleware, software libraries and special tools for designers to evaluate and deploy deep learning-based ML models. This feature allows seamless integration with existing frameworks available in ModusToolbox so that ML workloads can be easily integrated into secured IoT systems
This allows developers to use their preferred deep learning framework, such as TensorFlow, to be deployed directly to PSoC MCUs but also optimize the model for embedded platforms to reduce size and complexity, as well as validate performance against test data.
Infineon sees this capability as key for the combination of AI and IoT (AIoT) to provide machine learning in connected devices at the edge of the network. “As the IoT scales, massive amounts of data are being generated at the edge. Enabled by TinyML, AIoT is a natural evolution, where acting on data locally helps manage data privacy, latency and overall system reliability,” said Steve Tateosian, Vice President of IoT Compute and Wireless at Infineon.
“ModusToolbox bridges a critical gap between machine learning and embedded systems design by providing flexible tools and modular libraries to easily optimize, validate and deploy deep learning models from popular training frameworks on Infineon’s ultra-low power microcontrollers,” he said.
The AIoT market is expected to increase from US$5.1 billion in 2019 to US$16.2 billion by 2024, growing at a CAGR of 26 percent, according to researchers Markets and Markets.
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