Yokogawa has released the DLM5000, a new generation mixed-signal oscilloscope with options for four or eight analog inputs.

The new oscilloscope succeeds the previous eight-channel DLM4000 model. With redesigned hardware, the device provides major improvements in both performance and operability, incorporating a sampling rate double that of the previous model.

Created to be extremely adaptable and flexible, the device satisfies the precise demands of companies in industries such as automotive, aerospace, mechatronics, power electronics, railway and consumer electronics.

The device is excellent for developing high-performance and intelligent power-semiconductor technologies and mechatronics applied in modern electric vehicles, motor controls and energy-efficient electronic designs.

Terry Marrinan, VP sales and marketing Yokogawa Europe and South-East Asia, says: “With its eight analog channels and the ability to link up with other units, the DLM5000 sets a new standard in measurement flexibility. The large number of data points needed in the analysis of inverters, motors and mechatronic systems means that more channels are needed to capture that data. The Yokogawa DLM5000 meets the demands of today’s development engineers, giving them the features they need to analyse thousands of captured waveforms.”

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TEMPE, Ariz., June 29, 2020 — Intel is partnering with Maricopa County Community College District (MCCCD) to launch the first Intel-designed artificial intelligence (AI) associate degree program in the United States. The Arizona Commerce Authority will also provide a workforce grant of $100,000 to support the program. It will enable tens of thousands of students to land careers in high-tech, healthcare, automotive, industrial and aerospace fields.

“We strongly believe AI technology should be shaped by many voices representing different experiences and backgrounds. Community colleges offer the opportunity to expand and diversify AI since they attract a diverse array of students with a variety of backgrounds and expertise. Intel is committed to partnering with educational institutions to expand access to technology skills needed for current and future jobs,” said Gregory Bryant, Intel executive vice president and general manager of the Client Computing Group.

Based in Tempe, Arizona, MCCCD is the largest community college district in the U.S. with an estimated enrollment of more than 100,000 students across 10 campuses and 10,000 faculty and staff members.

The AI program consists of courses that have been developed by MCCCD’s faculty and Intel leaders based on Intel software and tools such as the Intel Distribution of OpenVINO Toolkit and Intel Python. Intel will also contribute technical advice, faculty training, summer internships and Intel mentors for both students and faculty members. Students will learn fundamental skills such as data collection, AI model training, coding and exploration of AI technology’s societal impact. The program includes a social impact AI project that is developed with guidance from teachers and Intel mentors. Upon completion, MCCCD will offer an associate degree in artificial intelligence that can be transferred to a four-year college.

AI technology is rapidly accelerating with new tools, technology and applications requiring workers to learn new skills. Recent studies show the demand for artificial intelligence skills is expected to grow exponentially. A 2020 LinkedIn report notes that AI skills are one of the top five most in-demand hard skills. Research by MCCCD Workforce and Economic Development Office estimates an increase of 22.4 percent for these roles by 2029.

As of early June 2020, more than 43 million Americans have filed for unemployment benefits. Furthermore, a recent McKinsey study estimates that over 57 million jobs are vulnerable, meaning they are subject to furloughs, layoffs or being rendered unproductive. It is critical for educational institutions and corporations to collaborate to prepare for future workforce demands.

The program’s first phase will be piloted online at Estrella Mountain Community College and Chandler Gilbert Community College in fall 2020. As physical distancing requirements are lifted and the concerns of the COVID-19 pandemic decrease, classes will begin in-person at both campuses.

This expands on the Intel AI for Youth program, which provides AI curriculum and resources to over 100,000 high school and vocational students in nine countries and will continue to scale globally. (Read, “AI for Youth Uses Intel Technology to Solve Real-World Problems.”) Additionally, Intel recently collaborated with Udacity to create the Intel Edge AI for IoT Developers Nanodegree Program aimed at training 1 million developers. Intel has a commitment to expand digital readiness to reach 30 million people in 30,000 institutions in 30 countries. This builds on the company’s recently announced 2030 goals and Global Impact Challenges that reinforce its commitment to making technology fully inclusive and expand digital readiness.

Intel’s corporate responsibility and positive global impact work is embedded in its purpose to create world-changing technology that enriches the lives of every person on Earth. By leveraging its position in the technology ecosystem, Intel can help customers and partners achieve their own aspirations and accelerate progress on key topics across the technology industry.

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While Internet of Things (IoT) will be integral to the long-term recovery plans of the post-COVID-19 economy worldwide, ABI Research said some facets of the IoT itself will be negatively impacted in the short term.

In its latest report “Assessing the Impact of COVID-19 on the IoT Market”, the technology research firm predicts an 18% drop in the net addition of IoT devices in 2020 as a result of manufacturing shut-downs, supply chain interruptions, and changes in connected product availability and demand.

This equates to the loss of 66 million potential Wide Area Network (WAN) connections over previous forecasts. Proportionally, the most heavily impacted markets will be fleet and other heavy vehicles/equipment. These are expensive assets that enterprises are buying less of in the interests of cost control. Fixed assets, digital signage, and kiosks also face huge impacts, as they are driven by a entertainment and retail sector that has been effectively put on hold by the massive reduction in personal mobility and footfall, and increased emphasis on online shopping.

“COVID-19’s impact on the IoT is three-fold. Some applications will experience a decline in shipments during 2020, ergo a reduction in the expected growth rate to their installed base. Yet, with no intrinsic change to their desirability and utility, they will return to expected growth in subsequent years,” said Jamie Moss, research director for M2M, IoT and IOE at ABI Research.

He added:  “Some will experience a temporary stall in 2020 that will be compensated  by increased activity immediately after, to bring things installed base expectations back into line. While others will experience fundamental shifts in demand, both positive and negative, for years to come as consumer and enterprise priorities shift in the light of COVID-19.”

In the consumer space, passenger vehicle and connected car markets are suffering considerably as people stay in place. Yet, by spending more time at home, improving the function and comfort of that environment is expected to boost smart home revenues. For enterprise, while utility metering initiatives face delays as home visits are temporarily prohibited, they are expected to bounce back fast. At the same time,  asset tracking, inventory management, and condition-based monitoring are all set for greater long-term investment to build better businesses that allow people to do more with less and to reliably run things remotely.

Moss noted the diversity of the IoT and the pragmatic nature of its utility.

“At ABI Research, we analyse 32 IoT applications, that’s 32 different types of connected device embedded in the fabric of the world around us. Each provides information on where things are, what their status is, and what actions we must take. To be forewarned is to be forearmed and the mass use of Microcontroller Unit (MCU)-based Low Power Wide Area (LPWA) sensors can help us make a safer world, where we can quickly respond to threats. The IoT is a market that grows naturally as and when it right for it to do so, to deliver planned results. And the need for guaranteed outcomes has never been more acute than now.”

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To help engineers develop AI systems, MathWorks has added deep learning capabilities to its latest update of MATLAB and Simulink. The update, called R2020A, includes a “Deep Network Designer” app, which is said to help engineers train neural networks. Designers can also manage several deep learning experiments at a time in another app, Experiment Manager.

Users will have more network options when creating deep learning code. 

What else is included in this update and how will it benefit engineers in various fields?

Core Updates for AI Development

The latest update from MathWorks includes a range of updates for AI systems, including code conversions, deployable web apps, and managers. Many of these are included in an updated Deep Learning Toolbox.

As mentioned, the two major updates of R2020A is the Deep Network Designer app, which allows users to train neural networks, and the Experiment Manager, which allows users to organize multiple experiments. The Experiment Manager also allows users to track experimental data, like core variables and results, providing a comprehensive view of a deep learning project.

Deep learning tools have also dramatically improved over a range of applications to help engineers with common AI tasks. AI involved with video and image data now includes features such as a signal labeler, pixel label datastore, audio datastore, and image datastore. In the network realm, MathWorks now allows users to build advanced network architectures, such as GANs, Siamese networks, attention networks, and variational auto-encoders.

Deep Learning Frameworks

MathWorks Deep Learning now supports a new range of other deep learning frameworks such as MobileNet-v2, ResNet-101, Inception-v3, SqueezeNet, NASNet-Large, and Xception. When it comes to the deployment of AI systems MathWorks now supports Arm Mali GPUs and includes a GPU Coder. The update is said to enable automatic deployment to Jetson AGX Xavier and Jetson Nano Platforms.

MathWorks can also generate code for networks such as YOLO V2 object detector, DeepLab-v3+, MobileNet-v2, Xception, DenseNet-201, and recurrent networks. AI algorithms for reinforcement learning are now included for systems for walking and driving. Other generic robotics use algorithms including DQN, DDPG, A2C, and PPO.

Classes and Interface Upgrades

The R2020A update does not just affect deep learning applications; it also includes features that can help designers interface their designs with other systems and improve organization. For example, MathWorks now offers C++ classes from MATLAB classes. It also offers new messaging protocols.

The R2020A update allows MathWorks users to work with UTF-8 characters and includes new graphic options for graphs. Users can also access a live editor tool, which allows them to view tasks currently being executed. 

Three new products included in the R2020A update include the Motor Control Blockset, Simulink Compiler, and MatLab Web App Server.

To help designers generate compact code, the Motor Control Blockset offers a library of motor control algorithms. It also provides “out-of-the-box support” for a number of motor control hardware kits.

With the Simulink Compiler, designers can use Simulink models to create software, web apps, and standalone applications that will run simulations without actually installing Simulink. 

Finally, the last major product—MATLAB Web App server—gives engineers organizational control over MATLAB web apps across one’s organization from a web browser.

A Deeper Understanding of Designs

MathWorks says the tools included with R2020A will not only help engineers continue to develop AI systems but also help them to better understand their designs. For example, because users can now label signals in video applications, they can visualize stimuli; likewise, datastores allows them to manage audio and visual data.

By targeting more AI frameworks, MathWorks extends its reach and therefore widens the deployment possibilities of a trained system. The new debugging features will allow designers to better understand why their AI systems produce the results they do (i.e. explain their decisions), while the inclusion of reinforcement algorithms allows for engineers to explore new methods for training systems.

A Useful Asset for Automotive and Wireless Designers

MathWorks asserts that the automotive tools included with R2020A will dramatically improve the automotive sector, with tools like the HD map to road data converter. These features are said to decrease the time needed to set up a traffic simulation environment and define road lengths and intersections. 

The update allows automotive designers to read high-definition road maps to create road data for use in traffic simulations. Optimized shift schedules can then be used with fuel economy and emissions analysis.

The update may also give designers in wireless communication a leg up with better support for wireless and 5G signal analysis, including waveform generation and cell detection.

A “Comprehensive” AI Platform

David Rich, MATLAB’s marketing director, says that this R2020A update gives designers a comprehensive platform for building an AI-focused system. He explains, “We’ve taken three decades of product, consulting and support experiences and applied it to an AI workflow that empowers engineers and scientists to clean data, build models and deploy them in production IT or embedded systems.”

Have you seen deep learning become a more central part of your workplace? If so, how? Share your experiences in the comment below.

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LG Powers Automotive Infotainment and Building Management Systems with Microsoft Azure Cloud and AI Technologies

LG Electronics (LG) is working with Microsoft to build its automotive infotainment systems, building management systems and other business-to-business collaborations. As announced at CES 2020, LG will leverage Microsoft Azure and AI services to accelerate the digital transformation of LG’s B2B business growth engines.

A year ago, LG started its collaboration with Microsoft to enhance and further grow LG’s autonomous vehicle and infotainment system business. LG will expand the scope of new projects beyond the automotive sector and further into the commercial space.

LG plans to enhance its management systems to enable its Building Energy Control (BECON) system to manage and control HVAC (heating, ventilation, and air conditioning) systems more efficiently using Azure. While extending its BECON system around the world with Microsoft’s support, the company will develop the next version of BECON with Azure data and hybrid cloud + AI services.

The integration with Azure will further enhance LG’s in-vehicle infotainment solution. This builds on the powerful combination of LG’s webOS Auto and the Microsoft Connected Vehicle Platform for the next generation of connected vehicles. For the next version of webOS Auto, LG will provide various additional HMI (human machine interface) experiences, especially in the in-vehicle entertainment and work efficiency areas.

LG’s infotainment systems will integrate virtual personal assistant technologies from LG with the Microsoft virtual assistant solution accelerator and automakers’ own personal assistants to enhance their brand experiences and provide various connected services to end users. This innovative HMI software platform is designed to advance the monetization of new digital services.

“Microsoft brings complementary technologies and synergy to advance LG’s B2B solutions,” said Dr. Lee Sang-yong, senior vice president and head of Automotive & Business Solutions Center at LG Electronics. “Our work with Microsoft will help drive competitiveness and the digital transformation for LG’s B2B areas, which represent the growth engine for the future.”

“Microsoft empowers mobility companies to digitally transform and identify new business opportunities,” said Sanjay Ravi, general manager of Automotive Industry at Microsoft Corp. “LG is fostering innovation and providing their customers with new value-added services by building its own digital capabilities and data-driven culture.”

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Everybody in the automotive industry is hustling to progress autonomous driving technologies and deploy driverless cars. This year, we’ve seen huge steps on account of rising technologies, for example, augmented reality and artificial intelligence. In light of current circumstances, Tesla CEO Elon Musk may really have the option to make a completely autonomous vehicle before the end of 2020.

Augmented reality highlights are as of now deployed by a few automobile manufacturers and choices for aftermarket augmented reality products is developing. Because of the administrative issues of completely autonomous driving and different limitations that still should be worked through before autonomous driving innovation is widely adopted, it’s a decent bet that augmented reality will be the next automotive innovation to be seen on the roadways.

There’s a marketing challenge with autonomous driving. The general population and a significant part of the press still don’t see how it functions. What’s more, if they don’t see how it functions, they’re not liable to purchase in.

Civil Maps, a startup whose mission is to crowdsource maps for self-driving vehicles, thought of an extraordinary solution. They made sense of how to give individuals access to the mind of a self-driving machine. The innovation utilizes augmented reality to show a “vehicle’s eye view” while driving. During a ride in one of the specially-equipped cars, a screen gives the rider a visual representation of sensor information as the vehicle processes it.

The designs are unrefined, comprised of essential hues and wireframes. It would appear that a 90s form of Google Street View. However, it’s rapidly apparent exactly what amount is truly going on. With a couple of hues and some floating boxes, the demo shows how the vehicle sees the state of the street, road signs, navigational milestones, and different vehicles. It can even tell if a traffic light is red, green, or yellow. It’s an unbelievably accessible look into an extremely mind-boggling innovation.

By overlaying essential data for the driver inside their line of sight, augmented reality can improve security. Rather than a driver expecting to look down at the dash or to their phone to get driving information or data, the guarantee of augmented reality would have the information accessible on a heads-up show, the windshield or projected on the road in the driver’s line of sight. Notwithstanding assisting with route and information from gauges, augmented reality can make the driver mindful of risks and other emergency notices. Through Nissan’s Invisible-to-Visible innovation, vehicle drivers later on could pick to have augmented reality travelers in the vehicle who can cooperate with them, perform co-pilot duties, and much more.

Augmented reality’s ability to incorporate a virtual domain into this present reality makes it perfect for testing driverless cars. It gives a quicker way to deal with testing as well as an increasingly affordable one.

The University of Michigan utilizes AR and other virtual technologies to make a protected space for testing self-driving vehicles in their Mcity Test Facility. It has 32 acres of land of fake street and infrastructure. From that point, genuine vehicles can connect with computer produced autos in real-time. In this reenactment, specialists have set up various conditions and situations that mirror true challenges. This empowers them to survey the security of driverless vehicles.

Scientists likewise utilized this AR simulation to test a patent-pending programming that empowers real and virtual cars to communicate. By trading data out and about, self-driving vehicles can settle on better choices. Hence, they can explore any environment securely without imperiling the lives of their travelers. At Mcity, analysts are additionally leading tests to improve self-driving experience. Their simulations assess how drivers react to unexpected stops and different difficulties when the vehicle is accountable for the driving. In doing such, they try to improve the quality of the ride.

In comparison, a large group of smaller start-up self-driving organizations have been discreetly creating and working constrained local driverless taxi benefits in a few areas. Drive.ai, for instance, started working a self-driving shuttle service in Arlington, TX and Fresco, TX, in the territories of the city involved principally of entertainment, commercial and retail foundations. Every one of the organization’s vans is furnished with self-driving tech and can be brought utilizing an application. The project is still, in fact, a pilot, with obligatory safety drivers, yet if they keep on observing achievement it’s anything but difficult to accept that Drive.ai, or one of their rivals, could present the first wide-scale commercialized service.

Other start-up efforts incorporate a deal between Kroger markets and start-up Nuro to deliver groceries utilizing a completely autonomous vehicle called the R1, or the organization Voyage offering self-driving taxi service at a Florida retirement network called the Villages.

There’s a tremendous amount of investment in research and development of autonomous driving advancements. In any case, not many products have hit the market. Starting now, everything we can do is wait. Obviously, completely autonomous vehicles will change our everyday lives. They will disrupt enterprises as much as or maybe considerably more than augmented reality as of now has.

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