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Google’s TensorFlow Lite for Microcontrollers and SensiML – More Powerful Together

Today we issued a press release announcing the integration of SensiML’s Analytics Toolkit with Google’s open source machine learning framework, called TensorFlow Lite for Microcontrollers. Together, SensiML and TensorFlow Lite for Microcontrollers complement each other by offering powerful neural network algorithm execution along with an established AI tool. As I mentioned in our Q2 earnings conference call, SensiML has been diligently working on this and we are excited to enable a seamless, fast, and productive workflow for developers creating and deploying edge AI sensor algorithms for IoT devices.

TensorFlow Lite for Microcontrollers is a part of Google’s popular open-source TensorFlow machine learning framework tailored to the unique power, compute, and memory limitations of extreme IoT edge nodes. The SensiML Analytics Toolkit has been designed to deliver the easiest and most transparent set of developer tools for the creation and deployment of machine learning at the edge for developers of all levels of AI expertise.

Developers working with Google’s TensorFlow Lite for Microcontrollers open source neural network inference engine now have the option to leverage SensiML’s powerful automated data labeling and preprocessing capabilities to reduce dataset errors, build more efficient edge models, and do so more quickly. Through this tightly coupled integration of SensiML and Google’s TensorFlow Lite for Microcontrollers, developers reap the benefit of best-in-class solutions for building efficient, intelligent sensor AI algorithms capable of running autonomously on IoT edge devices.

The openness, flexibility, and performance enabled by this effort is important and valued by our MCU partners and IoT device customers and will be a key enabler for our SaaS-related revenue growth in the coming quarters.

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