PORTLAND, Ore., Sept. 16, 2020 /PRNewswire/ -- SensiML™
Corporation, a leading developer of
AI tools for building intelligent IoT endpoints, today announced
that its SensiML Analytics Toolkit now seamlessly integrates with
Google's TensorFlow Lite for Microcontrollers. 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.
Following the standardized workflow within the SensiML model
building pipeline, developers can collect and label data using the
SensiML Data Capture Lab, create data pre-processing and feature
engineering pipelines using the SensiML Analytics Studio, and
perform classification using TensorFlow Lite for Microcontrollers.
The net result is a state-of-the-art toolkit for developing
smart sensor algorithms capable of running on low power IoT
endpoint devices.
TensorFlow Lite for Microcontrollers is a version of TensorFlow
Lite from Google, which has been specifically designed to implement
machine learning models on microcontrollers and other
memory-limited devices. SensiML, via its SensiML Analytics Toolkit,
delivers the easiest and most transparent set of developer tools
for the creation and deployment of edge AI sensor algorithms for
IoT devices. Through this tightly coupled integration of SensiML
and Google's TensorFlow, developers reap the benefit of
best-in-class solutions for building intelligent sensor AI
algorithms capable of running autonomously on IoT edge
devices.
"Without high-quality datasets, it is difficult to train models
that can perform reliably in production. We talk a lot about how
critical datasets are to building sensor-based edge AI
applications, but currently don't have a good solution for creating
them," said Pete Warden technical
lead of Google's TensorFlow Mobile Team. "SensiML's Data Capture
Lab fills this gap in the industry by providing tools to quickly
collect and annotate high-quality sensor
datasets."
"The integration with SensiML Analytics Studio and Google's
TensorFlow Lite for Microcontrollers provides a nice end-to-end
workflow for creating IoT edge models on embedded devices," said
Ian Nappier, TensorFlow Lite for
Microcontrollers product manager at Google.
"TensorFlow Lite for Microcontrollers is an industry-leading
framework for running neural network models on embedded devices,"
said Chris Rogers, chief executive
officer of SensiML. "SensiML's end-to-end workflow automates
the tedious and error-prone data cleansing and labeling process as
well as preprocessing and feature extraction providing a powerful
new capability for TensorFlow Lite for Microcontrollers users to
improve performance and productivity for their edge AI
projects."
Availability
The SensiML Analytics Toolkit with
support for TensorFlow Lite for Microcontrollers is available now
from SensiML. For more information, visit
https://sensiml.com/tensorflow-lite.
About SensiML
SensiML, a subsidiary of QuickLogic
(NASDAQ: QUIK), offers cutting-edge software that enables ultra-low
power IoT endpoints that implement AI to transform raw sensor data
into meaningful insight at the device itself. The company's
flagship solution, the SensiML Analytics Toolkit, provides an
end-to-end development platform spanning data collection, labeling,
algorithm and firmware auto generation, and testing. The SensiML
Toolkit supports Arm® Cortex®-M class and higher microcontroller
cores, Intel® x86 instruction set processors, and heterogeneous
core QuickLogic SoCs and QuickAI platforms with FPGA optimizations.
For more information, visit www.sensiml.com.
SensiML and the SensiML logo are trademarks of SensiML. All
other trademarks are the property of their respective holders and
should be treated as such.
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SOURCE SensiML Corporation