How NXP Semiconductors Is Moving Into Artificial Intelligence

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What is "Industry 4.0?"

To NXP Semiconductors (NASDAQ: NXPI), a leading provider of embedded chips (electronics found in things like automobiles and factories), Industry 4.0 centers around four technologies: fast networking, fast processing (with artificial intelligence), human-machine interfaces, and cybersecurity.

White animations against a gray bacground of shapes signifying edge devices of the Internet of Things.
White animations against a gray bacground of shapes signifying edge devices of the Internet of Things.

Image source: Getty Images.

The confluence of these four technologies has the potential to more fully automate factories, automobiles, and wearable devices. According to IHS, there will be over 70 billion internet-connected devices by 2025.

But while the NXP conversation largely centers around its impending acquisition by Qualcomm (NASDAQ: QCOM) (which may or may not happen), investors may be missing out on some exciting recent news on NXP products geared toward Industry 4.0.

Man smart, chips smarter

On artificial intelligence, NXP is perceived to lag competitors such as NVIDIA, the leading producer of AI-focused graphics processing units (GPU). But NXP has recently found ways to make its embedded processors and microcontrollers more "intelligent." Last month, the company unveiled a new software tool for its EdgeScale platform-as-a-service offering (which was only unveiled in February). The software allows customers to more easily load machine learning algorithms from other sources into NXP's embedded chips and systems-on-chips (SOCs). Here's why the new offering could be important to NXP's customers and investors.

Pushing to the edge

The Internet of Things is an architecture whereby "edge" devices will be able to send and receive information from a cloud-based server over an internet connection. This has a lot of benefits but also some complications. Companies that use cloud-based infrastructure-as-a-service need to pay for processing power and networking. Also, the time it takes for data to get from the cloud to the "edge" can mar efficiency, especially if a sensor is supposed to react to stimuli in real-time.

Companies are therefore racing to develop products that facilitate "edge" computing. For instance, Amazon released its FreeRTOS operating system for AWS late last year at its November Re: Invent conference, then announced a partnership with NXP competitor Texas Instruments to integrate the latter's SimpleLink MCU microcontroller hardware platform with FreeRTOS.

Responding in kind, NXP came out with its EdgeScale platform-as-a-service offering in February. EdgeScale is designed to securely work with NXP's Layerscape embedded chip platform, a line of ARM-based microprocessors that are more computing-intensive than low-power microcontrollers. Thus, it appears EdgeScale is a more advanced or specialty edge-computing platform.