NXP is using Electra Vehicles' EVE-Ai 360 Adaptive Controls technology to use digital twin models in the cloud to predict and control the physical BMS in real time, to improve battery performance, battery state of health of up to 12% and enable multiple new applications, such as EV fleet management. Batteries remain the costliest element in an electric vehicle (EV), and AI-powered digital twin cloud services have the potential to improve estimations of the battery's state of health (SOH) and state of charge (SOC) to deliver improved efficiency, lifetime and cost. Battery digital twins adapt to ongoing changes in battery health due to operating conditions and provide updated figures back to the BMS for continuously improving control decisions. Carmakers can use the technology to provide driver insights, such as range and speed recommendations. In addition, adaptive battery control can improve the battery's performance and safely extend its lifespan, reducing warranty costs for the carmaker.

Israeli edge-computing outfit SolidRun has launched a new lineup of Raspberry Pi-like computers based on NXP's new i.MX 8M Plus application processor. SolidRun makes edge computing kit containing Arm-based and Intel chips. Earlier this year, it teamed up with application-specific integrated circuit (ASIC) chip manufacturer Gyrfalcon Technology to build the Arm-based, Linux Janux GS31 AI inference server. Now the company has launched three new single-board computers powered by NXP's i.MX 8M Plus application processors. They're aimed at the same industrial market Raspberry Pi is targeting beyond its traditional education purposes – and which Google is also targeting with its line of Coral-branded single-board computers.

NXP Semiconductors N.V. announced that it is enhancing its machine learning development environment and product portfolio. Through an investment, NXP has established an exclusive, strategic partnership with Canada-based Au-Zone Technologies to expand NXP's eIQ Machine Learning (ML) software development environment with easy-to-use ML tools and expand its offering of silicon-optimized inference engines for Edge ML. Additionally, NXP announced that it has been working with Arm as the lead technology partner in evolving Arm Ethos-U microNPU (Neural Processing Unit) architecture to support applications processors. NXP will integrate the Ethos-U65 microNPU into its next generation of i.MX applications processors to deliver energy-efficient, cost-effective ML solutions for the fast-growing Industrial and IoT Edge. "NXP's scalable applications processors deliver an efficient product platform and a broad ecosystem for our customers to quickly deliver innovative systems," said Ron Martino, Senior Vice President and General Manager of Edge Processing at NXP Semiconductors.

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NXP claims that this support provides the industry's first compiler implementation of the Glow neural network for higher performance with low memory footprint on its i.MX RT crossover MCUs. Originally developed by Facebook, Glow is able to integrate target-specific optimizations. NXP took advantage of this ability using Glow neural network libraries for Arm Cortex-M cores and the Cadence Tensilica HiFi 4 DSP. The capability is also integrated into NXP's eIQ Machine Learning Software Development Environment, which is freely available within NXP's MCUXpresso SDK. As an NN compiler, Glow takes in an unoptimized neural network and generates highly optimized code.

NXP Semiconductors 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, we are driving innovation in the secure connected vehicle, end-to-end security & privacy and smart connected solutions markets. NXP's Automotive business unit offers sensor and processing technology that drives all aspects of the secure connected cars of today and the autonomous cars of tomorrow. Job Summary: A 2017 summer internship Projects include: Detecting defective product outliers by applying statistical methods and machine learning algorithms to evaluate test data Analyze customer product returns through statistical methods and algorithms to determine preventive actions Develop a compilation of self-checking microcontroller flash tests that can be automated to run in its entirety or individually for bench evaluation board applications Job Qualifications: Working on a BS or MS in Electrical Engineering or Computer Science/Engineering Software: Python and C Solid understanding of Statistics and Machine learning Other skills will be supported through on the job training NXP is an Equal Opportunity/Affirmative Action Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, NXP will provide reasonable accommodations for otherwise qualified disabled individuals.

Chip giants such as Nvidia, Intel and Qualcomm rarely miss an opportunity to tout their achievements and technology prowess in artificial intelligence. The message on AI from NXP Semiconductors, however, is neither so loud nor so clear. NXP's AI strategy has been a mystery ever since CEO Richard Clemmer revealed the company has had "no internal technology development going on" in machine learning. That declaration, in October 2016, came as a shock. How in the world, was NXP -- a leading automotive chip supplier -- planning to lead the market in the era of ADAS and AV with "no internal development of machine learning?"

NXP Semiconductors N.V. announced the i.MX RT1170 family of crossover MCUs that combines unprecedented performance, reliability, and high levels of integration to propel industrial, IoT and automotive applications. The NXP i.MX RT1170 family reinforces the Company's commitment to advance edge computing with its EdgeVerse portfolio of solutions and marks a technology breakthrough with MCUs that run up to 1GHz while maintaining low-power efficiency. Additionally, to achieve an optimal balance of power, performance, and cost-effective integration, the solution uses advanced 28nm FD-SOI technology, making NXP the first company to build MCUs in this advanced technology node. The i.MX RT1170 MCU features include: a dual-core architecture with the Arm Cortex -M7 core running up to 1GHz and Cortex-M4 running up to 400MHz, 2D vector graphics core, NXP's pixel processing pipeline (PxP) 2D graphics accelerator, and EdgeLock 400A, the Company's advanced embedded security technology. Moreover, it is architected to deliver a record-setting 12ns interrupt response time, 6468 CoreMark score and 2974 DMIPS while executing from on-chip memory.

SAN JOSE, Calif. and BARCELONA, Spain, 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 microcontrollers.

Companies like Nvidia and Intel are battling to build processors that act like the brains of autonomous cars, making decisions based on their surroundings to enable advanced driver assistance systems like automatic braking or adaptive cruise control and eventually to safely navigate city streets as well as highways. NXP Semiconductors is trying to turn those thoughts into action. On Monday, the Eindhoven, Netherlands-based company announced a new microcontroller to manage the systems that accelerate, steer and brake vehicles safely. The hardware, called S32S, can act on commands not only from a driver's turn of the steering wheel and foot pressing on the brake pedal but also from a car's central computer. It will compete with rival chips from the likes of Renesas and Infineon. The announcement reflects the understated role the world's largest maker of automotive chips is playing in the driverless car industry.