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SensiML integrates Google’s TensorFlow Lite for microcontrollers :: QuickLogic Corporation (QUIK)



Portland, Oregon, September 16, 2020 / PRNewswire /-SensiML Corporation, a leading developer of AI tools for building intelligent IoT endpoints, today announced that the SensiML Analytics Toolkit is seamless with Google’s TensorFlow Lite for Microcontrollers. Announced to integrate into. Developers using Google’s TensorFlow Lite for Microcontrollers open source neural network inference engine take advantage of SensiML’s powerful automatic data labeling and preprocessing capabilities to reduce dataset errors and build more efficient edge models. And you have the option to run faster.

Developers use the SensiML Data Capture Lab to collect and label data and use SensiML Analytics Studio to create data preprocessing and functional engineering pipelines according to standardized workflows within the SensiML model building pipeline. You can then use TensorFlow Lite for Microcontrollers to perform the classification. The end result is a state-of-the-art toolkit for developing smart sensor algorithms that can be run on low-power IoT endpoint devices.

TensorFlow Lite for Microcontrollers is a version of Google’s TensorFlow Lite, specifically designed to implement machine learning models on microcontrollers and other memory-limited devices. SensiML provides the simplest and most transparent developer toolset for creating and deploying edge AI sensor algorithms for IoT devices through the SensiML Analytics Toolkit. The tightly integrated integration of SensiML and Google’s TensorFlow allows developers to benefit from best-in-class solutions for building intelligent sensor AI algorithms that can run autonomously on IoT edge devices.

“Without high-quality datasets, it’s difficult to train a model that can run reliably in production. We often talk about the importance of datasets in building sensor-based edge AI applications, There is currently no suitable solution to create them, “said Pete Warden, technical leader of Google’s TensorFlow mobile team. “SensiML’s data capture lab fills the industry gap by providing tools to quickly collect and annotate high-quality sensor datasets.”

“Integrating SensiML Analytics Studio with Google’s TensorFlow Lite for Microcontrollers provides a great end-to-end workflow for creating IoT edge models in embedded devices,” said Ian, Google’s TensorFlow Lite for Microcontrollers Product Manager. Nappier says.

“TensorFlow Lite for Microcontrollers is the industry-leading framework for running neural network models in embedded devices,” said SensiML CEO Chris Rogers. “SensiML’s end-to-end workflow automates tedious and error-prone data cleansing and labeling processes, as well as pre-processing and feature extraction, providing powerful new features for TensorFlow Lite for microcontroller users. , Improve the performance and productivity of edge AI projects. “

Availability The SensiML Analytics Toolkit, which supports TensorFlow Lite for Microcontrollers, is available from SensiML. For more information, please visit

SensiML, a subsidiary of QUIK (NASDAQ), SensiML is state-of-the-art software that enables ultra-low power IoT endpoints that implement AI to transform raw sensor data into meaningful insights into the device itself. To provide. The company’s flagship solution, the SensiML Analytics Toolkit, provides an end-to-end development platform that covers data collection, labeling, automatic algorithm and firmware generation, and testing. The SensiML toolkit supports heterogeneous core QuickLogic SoC and QuickAI platforms with Arm Cortex-M class and above microcontroller cores, Intel x86 instruction set processors, and FPGA optimization. For more information, please visit

SensiML and the SensiML logo are trademarks of SensiML. All other trademarks are the property of their respective owners and should be treated as such.

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