Launches NXP edge intelligence environment (eIQ®), a comprehensive machine learning (ML) toolkit
with support for TensorFlow Lite, Caffe2, and other neural network frameworks, plus non-neural
Introduces turnkey integrated ML solutions for voice, vision and anomaly detection applications,
including data acquisition, trained models, with user feature customization
Expanding NXP EdgeScale with secure device on-boarding, provisioning, and container management
of ML applications targeting i.MX and Layerscape applications processors
SAN JOSE, Calif. and
Oct. 16, 2018 (GLOBE NEWSWIRE) --
(ARMTECHCON and IoT World Congress Barcelona) – Mathematical advances that are
driving the historic growth of machine learning (ML) in the cloud are now within reach of edge
node developers with NXP's eIQ edge intelligence software environment and customizable,
system-level solutions for focused applications.
The eIQ software environment includes the tools necessary to structure and optimize cloud-trained
ML models to efficiently run in resource-constrained edge devices for a broad range of industrial,
Internet-of-Things (IoT), and automotive applications. The turnkey, production-ready
solutions are specifically targeted for voice, vision, and anomaly detection applications. By
removing the heavy investment necessary to become ML experts, NXP enables tens of thousands of
customers whose products need machine learning capability.
"Having long recognized that processing at the edge node is really the driver for customer
adoption of machine learning, we created scalable ML solutions and eIQ tools, to make transferring
artificial intelligence capabilities from the cloud-to-the-edge even more accessible and easy to
use," said Geoff Lees, senior vice president and general manager of
With support for NXP's full microcontroller (MCU) and applications processor product line, eIQ
provides the building blocks that developers need to implement ML in edge devices. Keeping pace
with ML's changing landscape, NXP eIQ is continuously expanding to include: data acquisition and
curation tools; model conversion for a wide range of neural net (NN) frameworks and inference
engines, such as, TensorFlow Lite, Caffe2, CNTK, and Arm® NN; support for emerging NN compilers
like GLOW and XLA; classical ML algorithms (e.g. support vector machine and random forest); and
tools to deploy the models for heterogeneous processing on NXP embedded processors.
NXP also recently introduced a software infrastructure called EdgeScale to unify how data is
collected, curated, and processed at the edge, with focus on enabling ML applications. EdgeScale
enables seamless integration to cloud-based artificial intelligence (AI) / ML services and
deployment of cloud-trained models and inferencing engines on all NXP devices, from low-cost MCUs
to high-performance i.MX and Layerscape applications processors.
Building on the eIQ environment, the company introduced turnkey solutions for edge-based learning
and local execution of vision, voice, and anomaly detection models. These system-level solutions
provide the hardware and software necessary for building fully functional applications, while
allowing customers to add their own differentiation. The solutions are modular, making it easy for
customers to expand functionality of their products with a simple plug-in. For example, a voice
recognition module can be easily added to a product that has NXP's vision recognition solution.
This week at
IoT World Congress in
Barcelona, NXP is demonstrating real-world applications incorporating these capabilities – attendees will
experience a simulated factory floor that uses drones and includes sub-systems for facial
recognition for operator access, object recognition for operator safety, local voice control
commands, and anomaly detection for predicting failures in drone operation. The demonstrations
will take place in the NXP Booth #261 located in the Gran Via – Hall 2, Street B, Level 0.
NXP at ArmTechCon
NXP will demonstrate its
latest edge compute offerings at ArmTechCon
this week. The versatility of eIQ tools and ML applications applied to NXP's breadth of embedded
processing portfolio will be highlighted in Booth #620 and the automotive pavilion.
Cascaded Learning: facial recognition training on high-performance i.MX 8QM and deployment of
extracted inference engines on mid-range i.MX 8QXP and i.MX 8M applications processors using
secure docker containers.
MCU-level Industry 4.0 ML applications: CMSIS-NN performance benchmarking using CIFAR-10 on
and anomaly detection with classical machine learning techniques using Cortex-M4F based Kinetis
Localized voice and vision ML applications, featuring:
i.MX RT600 crossover processor
leveraging its integrated DSP, security and ultra-low power operation
Voice-enabled solution for localized wake word and end-user programmable voice control
experience also using i.MX RT1050 crossover processor
Vision solutions enabled by
Au-Zone DeepView ML
Kit: food-recognition using i.MX 8QM implemented in a microwave oven and traffic sign
recognition using low-cost i.MX RT 1050 crossover processor.
About NXP Semiconductors
NXP Semiconductors N.V. (NASDAQ:NXPI) enables
secure connections and infrastructure for a smarter world, advancing solutions that make lives
easier, better and safer. As the world leader in secure connectivity solutions for embedded
applications, NXP is driving innovation in the secure connected vehicle, end-to-end security &
privacy and smart connected solutions markets. Built on more than 60 years of combined experience
and expertise, the company has over 30,000 employees in more than 30 countries and posted revenue
of $9.26 billion in 2017. Find out more at
NXP, the NXP logo, Layerscape, EdgeScale and eIQ are trademarks of NXP B.V. All other
product or service names are the property of their respective owners. All rights reserved. © 2018
For more information, please contact:
||Greater China / Asia
||Martijn van der Linden
|Tel: +1 408-802-0602
||Tel: +31 6 10914896
||Tel: +886 2 8170 9990
NXP USA, Inc.