Infineon buys Imagimob for TinyML edge AI boost
Infineon Technologies has bought Swedish startup Imagimob to boost its TinyML edge AI capabilities on its microcontrollers and sensors.
Imagimob in Stockholm has developed an end-to-end machine learning toolchain that is highly flexible and easy to use with a strong focus on delivering production-grade ML-models. Infineon is acquiring 100% of the company’s shares. Both parties have agreed not to disclose the amount of the transaction, but Imagimob is mostly self-funded, having raised just $3.9m in funding.
Imagimob’s platform enables a wide range of use cases in embedded designs, from audio event detection, voice control, predictive maintenance, gesture recognition and signal classification to material detection.
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The deal will extend Infineon’s hardware/software ecosystem even further, with making TinyML more available to developers using the PSoC microcontrollers it acquired from Cypress and Infineon’s sensor range. But could also potentially be used internally on the firmware for wireless AIROC chips to boost the performance and reduce power consumption by using TinyML to optimise the signal chain.
“Artificial Intelligence and Machine Learning respectively are about to largely enter every embedded application and thus enable new functionalities. With Imagimob’s outstanding platform and its expertise in developing robust machine learning solutions for edge devices, we further strengthen our ability to enable new levels of control and energy efficiency on our products while preserving privacy,” said Thomas Rosteck, President of Infineon’s Connected Secure Systems division.
”With Infineon we can accelerate our customer’s developments, enable new applications and help them to differentiate in their markets,” said Anders Hardebring, Co-Founder and CEO of Imagimob. “Becoming an integral part of the Infineon ecosystem with their profound application expertise and an extensive product portfolio allows us energy efficient and secure implementation of advanced sensing and control in IoT contexts.”
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www.imagimob.com; www.infineon.com
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