It's expected that there will be 75 billion smart connected devices in our homes and offices by 2025, and many of them will have added capacity to sense, process and make decisions without first checking with the cloud -- or with us. If we're going to rely on them to take more active and responsible roles in our lives, we must be able to trust that they're not only ethical but that the AI and the machine learning that underpins them operate safely and securely. Already, the U.S., EU and other countries have started working on laws and regulations focused on the impact of AI on end users. A number of tech companies and other organizations (including the Vatican) are also collaborating to develop ethical codes of conduct for AI built upon the key principles, which include privacy, transparency and fairness. However, the process required to make ethical AI safe and secure requires more than the coding of virtuous machines.

Vivoka, a Lorraine-based company and French leader in speech recognition with the Voice Development Kit, announced in early January its participation in the partnership program of NXP Semiconductors, the world's tenth largest supplier of embedded controllers. The addition of NXP's technology to Vivoka's voice recognition artificial intelligence solution will benefit customers of both brands. Vivoka, a French company located in Metz, founded in 2015 by William Simonin, develops a solution that allows any company to add a voice interface to its products, very simply. This solution, called VDK (Voice Development Kit), is suitable for kiosks, robots, mobile applications, headsets… and has allowed it to become the French leader in voice recognition. Vivoka won the coveted Innovation Award in the sustainability and eco-design category at CES 2019.

NXP Semiconductors and Volkswagen shared on Tuesday early glimpses into Ultra-Wideband (UWB) technology and its future applications. In a Volkswagen concept car, the companies showed the capabilities of Ultra-Wideband for advancing security, safety and convenience in vehicles. Lars Reger, CTO of NXP Semiconductors, and Maik Rohde, head of body electronics and car access systems, Volkswagen, discussed the alliance as part of a broader, cross-industry push to leverage the capabilities of UWB: accurate localization and fine ranging at maximum security levels. In automotive alone, UWB will enable interesting new use cases such as automated trailer hitch activation, in-cabin passenger detection, automated valet parking, hands-free parking, lot access and drive-through payment, to name a few. Another application is walking pattern recognition for car access, which was demonstrated in the VW concept car.

NXP Semiconductors has launched an edge intelligence software environment for edge node developers to build machine learning applications in the cloud, along with turnkey solutions to make voice, vision, and anomaly detection application development accessible to customers without in-house ML expertise. The NXP eIQ toolkit provides developers with tools to structure and optimize cloud-trained ML models to run efficiently in the resource-constrained IoT and other edge devices, and supports neural network frameworks such as TensorFlow Lite and Cafe2, as well as non-neural ML algorithms. The company has also expanded its EdgeScale software infrastructure for NXP devices with secure device onboarding, provisioning, and container management. The turnkey solutions provide both the hardware and software to build applications, while allowing customers to add differentiation, and are modular, allowing, for example, voice recognition to be added to a product using NXP's vision recognition solution, according to the announcement. "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 for NXP.

NXP Semiconductors has launched a new machine learning toolkit. Called "eIQ", it's a software development platform that supports popular neural network frameworks including Caffe2 and TensorFlow Lite. The platform is aimed particularly at the development of machine learning software for edge devices with limited energy consumption and other resource constraints, with NXP Semiconductors highlighting automotive, industrial, and Internet of Things applications. In announcing the new platform, the company noted that eIQ and its other processor solutions can be used to support a range of machine learning applications including facial recognition, wake word and voice control systems, and computer vision technologies including traffic sign recognition and even food recognition. NXP Semiconductors announced the eIQ platform at this week's IoT World Congress in Barcelona, where the company is demoing examples of real-world applications of its machine learning technology.

Internet of Things Release 3 is published by oneM2M, the worldwide Internet of Things interoperability standards initiative. The third set of specifications deals with 3GPP interworking, especially as it relates to cellular IoT connectivity, among other features. The release is said to enable seamless interworking with narrowband IoT and LTE-M connectivity through the 3GPP Service Capability Exposure Function. More information is available here. FogHorn Systems says its Lightning Edge Industrial IoT platform received Industrial Software Competency status from Amazon Web Services, attesting that the software is capable of working in product design, production design, production, and operations.

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. 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. On artificial intelligence, NXP is perceived to lag competitors such as NVIDIA, the leading producer of AI-focused graphics processing units (GPU).

At CES recently, Qualcomm introduced its Drive Data Platform, which the company claims is designed to intelligently collect and analyze information from vehicle's sensors. In addition, the Drive Data Platform can assist smart cars in accurately detecting location, monitoring and learning driving patterns, perceiving surroundings, and capturing and sharing this data. Clearly, the Drive Data Platform should help Qualcomm to tap into connected and autonomous car market, which has a huge growth potential. According to a research by Boston Consulting Group, the autonomous car market could be a $42 billion market by 2025, which could be around 12-13% of the total auto market. As more and more customers look for improved digital experience in the car, in addition to other parameters, car companies are banking on technological advancements in their interiors to compete with each other.

Many industry experts consider Google to have made the most progress on the road towards fully autonomous driving, but at this year's CES, Microsoft is revealing its own plans for putting drivers in the passenger seat. The company, best-known for the Windows PC operating system, is partnering with five firms including insurance company Swiss Re on what it's billing as a "collective vision of safe and secure end-to-end mobility." And it's one where artificial intelligence takes a front seat. Specifically, AI bots will make real-time connections between traffic situations and pedestrian density via the current suite of sensing tools used in vehicles, from car-to-car (V2V) and car-to-infrastructure (V2I) communication, to radar, camera and LIDAR systems to optimise driver safety and engagement. What's more, the same tech will use information gathered from a driver's personal preferences and daily routine.

Qualcomm said Thursday that it had agreed to acquire NXP Semiconductors for about $38 billion, expanding its presence in the increasingly lucrative market for automotive sensors and chips. Qualcomm said it would pay $110 per share for NXP and expects the deal to close by the end of 2017. The deal gives the telecommunications giant a greater foothold in the burgeoning market for technology that will power self-driving cars -- which represents a growth space compared to the saturated market for smart phones and other mobile devices. NXP also has a desirable position in the market for technology powering the so-called Internet of Things as well as security products. The acquisition also marks the latest in a series of deals for the semiconductor business, accelerating the trend of consolidation.