Top 10 Electronic-Enabled Tech Highlights From CES 2020

January 15, 2020 • Alternative Energy, Artificial Intelligence, Consumer Electronics, Cyber Security, Design Hardware & Software, Electronics & Test, Gadget Freak, IoT, Medical, Science, Sensors, Sustainability, Technology

Not all cool tech involved robots and autonomous cars. Here’s a list of the other electronic tech featured at the show.

This year’s Consumer Electronics Show (CES) 2020 featured a range of marvals enabled by electronic technologies covering application areas from smart cities, AI edge intelligence, body haptics, security systems, real-time accident reports, uncooled thermo cameras, wearables and more.

Here are the top 10 products and technologies that piqued the interest of the Design News editorial staff.
Smart Cities

Why do major Japanese car manufacturers like to build smart homes and now cities? Several years ago, Honda built a zero-net energy smart home in partnership with UC-Davis. At this year’s CES, Toyota announced it will build a smart city to test their AI, robots and self-driving cars. Toyota’s Woven City will be built at the foothills of Mt. Fuji in Japan. The city will be the world’s first urban incubator dedicated to the advancement of all aspects of mobility, claims Toyota.

The project is a collaboration between the Japanese carmaker and the Danish architecture firm Bjarke Ingels Group (BIG). Houses in Woven City will have in-home robotics to help with the more mundane tasks of daily life. The homes will have full-connectivity, which will be needed for the sensor-based AI to automate many household chores, like restocking the refrigerator and taking out the trash. Power storage units and water purification systems will be hidden beneath the ground.
Intelligence At The Edge

Blaize is a computing company that optimizes AI at scale wherever data is collected and processed from the edge. The company enables a range of existing and new AI use cases in the automotive, smart vision, and enterprise computing segments. The company claims that developers can create new classes of products to bring the benefits of AI and machine learning to broad markets.

The company has developed a fully programmable GSP architecture that utilizes task-level parallelism and streaming execution processing to take advantage of very low energy consumption, high performance and scalability. Blaize claims that, in comparison, existing GPUs and FPGAs exert a much higher energy price, while CPUs cost more and scale poorly, and all are subject to excessive latency due to their sequential execution processing architectures.
Full-Body Haptics Suit

Haptics are all about the sense of touch. Now you can immerse your entire body – or at least 70 tactile points mainly around your torso – into the world of artificial experiences. The BHaptics Tacksuit provides an audio-to-haptic feature that converts sound into haptic feedbacks that are felt real time around your torso. For example, when a bomb explodes or you hear footsteps during a PC/VR game, you’ll feel the experience from the right direction. You’ll even be able to feel Samurai cuts and friendly hugs.
Security Comes In Many Forms

There are many ways to protect your PC data and applications, from hardware encrypted portable storage devices, backup solutions, file repair software, and data recovery, to digital forensics services. SecureData provides both products and services in these areas. At CES, the company demonstrated a secure UBS drive which they claimed was the only hardware encrypted flash drive in the world with keypad and Bluetooth authentication.
Wireless Six-Degrees Of Freedom (6DOF)

Atraxa’s system tracks 6DOF motion without the need for optical cameras or infrared markers to be placed around the room, or mounted externally to the XR headset or controller. And no line of sight—or wires—are required between the headset and controllers. Unhindered by wires or line-of-sight constraints, users can move freely in large spaces. Even move from room to room without any room mapping, or controller orienting (or reorienting) is required. Tracking starts immediately and lasts without interruption.

The tech combines electromagnetic (EM) and inertial technologies into a single sensor-fusion tracking platform. The IMU (inertial measurement unit) returns acceleration and angular velocity data. The EM tracker delivers true position and orientation data; it also establishes the tracking volume and local coordinate system. Atraxa is comprised of two main components: a tracker module and receiver module. The tracker module houses the IMU and an EM transmitter coil that generates the magnetic field (i.e. the tracking volume). The tracker modules are embedded into the handheld controllers (or other peripherals).
Real-Time Accident Report

Sooner or later, all of us get into an automotive accident. When that occures, wouldn’t it be great to have a record of what happened? Through the use of embedded acceleration sensors, MDGo generates a real-time report in the case of a car crash, detailing each occupant’s injuries by body region. The company’s technology enables accurate delivery of needed services and support by providing optimal medical care in the case of an emergency and supporting the claim process.
Smart Factory

Could a factory think for itself or autonomously design a better car or aircraft? Can it eliminate waste? All of these questions fit into the realm of manufacturing intelligence. One company with experience in this area is Hexagon, claiming that their technologies are used to produce 85% of smartphones, 75% of cars and 90% of aircraft.

Their Smart Factory approach aims to have fewer inputs, zero waste and high quality. All this is achieved through sensor, software and autonomous solutions that incorporates data feedback to improve work to boost efficiency, productivity, and quality across industrial and manufacturing.
A Cool “Uncooled” Methane Gas Detector

The FLIR GF77 Gas Find IR is the company’s first uncooled thermal camera designed for detecting methane. This handheld camera offers inspection professionals the features they need to find potentially dangerous, invisible methane leaks at natural gas power plants, renewable energy production facilities, industrial plants, and other locations along a natural gas supply chain. The gas detector provides methane gas detection capability at roughly half the price of cooled gas inspection thermal cameras, to empower the oil and gas industry to reduce emissions and ensure a safer work environment.
IoT Arduino Adds LoRaWAN Connectivity

You can now connect your sensors and actuators over long distances via the LoRa wireless protocol or throughout LoRaWAN networks. The Arduino MKR WAN 1310 board provides a practical and cost effective solution to add LoRa connectivity to projects requiring low power. This open source board can be connected to: the Arduino IoT Cloud, your own LoRa network using the Arduino LoRa PRO Gateway, existing LoRaWAN infrastructure like The Things Network, or even other boards using the direct connectivity mode.
Wearables, Ingestibles, Invisibles

One of the keys to a healthy life is nutrition. But what exactly constitutes ‘healthy’ food for a specific person? To answer that question, you need to measure and analyze the processes inside the complex human digestive system. Imec is working on prototype technology that is up to that task. It’s called ingestible sensors.

The company also develops wearables for medical and consumer applications that enable reliable, continuous, comfortable, and long-term health monitoring & management. This includes high-accuracy & low-power biomedical sensing technologies sometimes embedded into fabrics.

John Blyler is a Design News senior editor, covering the electronics and advanced manufacturing spaces. With a BS in Engineering Physics and an MS in Electrical Engineering, he has years of hardware-software-network systems experience as an editor and engineer within the advanced manufacturing, IoT and semiconductor industries. John has co-authored books related to system engineering and electronics for IEEE, Wiley, and Elsevier.

Researchers Are Looking For Ways To Make VR Less Painful

January 15, 2020 • Consumer Electronics, Design Hardware & Software, Electronics & Test, Medical, Science, Sensors, Technology

Researchers are hoping to develop standards and guidelines for developers to reduce the risk of physical discomfort and injuries among VR users. (Image source: Oregon State University)

Can the physical risk of using VR be reduced or eliminated altogether?

Ask anyone who has used VR for a prolonged period of time and they’ll tell you a big issue with a lot of VR hardware is comfort level. Bulky headsets and controllers with no ergonomic design can turn a fun immersive experience into a literal pain in no time. This becomes a big concern, not only to developers who want their hardware and software to be used for extended periods, but for users themselves who risk long term injury and health complications ranging from musculoskeletal issues to more commonly reported issues such as eye strain, nausea, and motion sickness.

Hardware developers have put a premium on ensuring comfort with their latest generation headsets, using techniques ranging from better balancing of internal components to using lighter-weight materials. But while other industries have guidelines and standards to fall back on, nothing of the sort exists for virtual and augmented reality.

Researchers from Oregon State University (OSU) and Northern Illinois University have been examining how common movements done in VR are contributing to muscle strain and discomfort in users. Their goal is to establish baselines for optimal object placement and angles in virtual environments so that developers can design games and other applications that cause minimum discomfort in users.

The results of their work are published in a recent study in the journal Applied Ergonomics.

“In computer users, the relationship between awkward postures or repeated movements and musculoskeletal disorders is well known, researcher Jay Kim of OSU’s College of Public Health and Human Sciences, said in a press statement. “We wanted to see how the VR compares to conventional computer-human interactions…We wanted to evaluate the effects of the target distances, locations, and sizes so we can better design these interfaces to reduce the risk for potential musculoskeletal injuries.”

According to Kim it can take as little as three minutes for shoulder discomfort to occur as a result of having to extend your arm straight out, as in many VR applications. He said that prolonged use of VR can lead to a range of problems from gorilla arm syndrome, to rotator cuff injuries, to neck strain and cervical spine damage.

For their study, Kim and his team focused primarily on neck and shoulder movements. The researchers had participants wearing Oculus Rift headsets perform tasks that involved them pointing to specific dots around a circle, or coloring in a designated area with their fingers. The participants’ movements were monitored using motion capture cameras. They were also outfitted with sensors measure electrical activity in their muscles.

The tests were repeated with the visuals placed at eye level, 15 degrees above and below eye level, and 30 degrees below eye level.

Results showed performance at the color task worsened when participants had to tilt their heads down at either 15 or 30 degrees. At 15 degrees above eye level, researchers noted the greatest degree of muscle activation, with the most discomfort occurring during the pointing task at 15 degrees above eye level.

“This result indicates that excessive vertical target locations should be avoided to reduce musculoskeletal discomfort and injury risks during VR interactions,” the study reads. “Based on relatively lower biomechanical exposures and trade-off between neck and shoulder postures, vertical target location between eye height and 15-degrees below eye height could be recommended for VR use.”

“Based on this study, we recommend that objects that are being interacted with more often should be closer to the body,” Kim said. “And objects should be located at eye level, rather than up and down.”

Kim said research like this is going to become increasingly important as VR and AR technologies proliferate into more and more industries. While entertainment remains VR’s largest use case – and the biggest area of concern in terms of safety and discomfort – more and more enterprise deployments of VR in areas such as industrial and medical training as well as in intricate applications such as virtual prototyping and design mean that VR-related injuries could quickly transition into a workplace hazard.

Data released by Statista forecasts the number of active VR users worldwide to be around 171 million as of 2018.

Kim and his team hope their work can help avoid the same mistakes that occurred as personal computers became more mainstream in the 80s and 90s, where a lack of awareness lead to a variety of health issues such as carpal tunnel syndrome and vision issues. “ With VR, we’d like to learn now rather than later,” he said.

Chris Wiltz is a Senior Editor at Design News covering emerging technologies including AI, VR/AR, blockchain, and robotics

The 12 Best Innovations Of CES 2020

January 14, 2020 • 3D Printing, Alternative Energy, Artificial Intelligence, Automation & Motion Control, Battery/Energy Storage, Consumer Electronics, Design Hardware & Software, Electronics & Test, Gadget Freak, Government/Defense, IoT, Materials & Assembly, Medical, Science, Sensors, Sustainability, Technology

Forget new TVs and smartphones. These are the real game changers introduced at CES 2020.

Now that the smoke is cleared from CES 2020, we can take a step back and see which technologies were the real innovations of 2020. Let’s be honest, CES can be a black hole of vaporware, false promises, and concepts intended to be just that.

We’ve compiled a list of our favorite technologies introduced at CES 2020 – innovations that we’re sure will be having a lasting impact in 2020 and beyond.
AerNos AerSIP Gas Sensor

The AerSIP from AerNos is a 5 x 5-mm, mulit-gas sensing module that combines nanotechnology and machine learning algorithms to monitor indoor and outdoor air quality. The system-in-package (SIP) is an embedded plug-and-play solution that can be integrated into wearables, mobile devices, and other IoT devices and is capable of detecting hazardous gases and other dangers at parts per billion levels.

(Image source: AerNos/CES)
AMD Ryzen 4000 Series Mobile Processor

AMD’s Ryzen 4000 could be a literal game changer for high-end laptops users – particularly gamers and designers. AMD says its new Ryzen 4000 series is the world’s first 7-nanometer laptop processor. Designed for ultra-thin laptops, the Ryzen 4000 series features up to 8 cores and 16 threads and configurable 15W thermal design power. AMD pledges the Ryzen 4000 series offers up to four percent greater single-thread performance and up to 90 percent faster multithreaded performance than its competitors, as well as up to 18 percent faster graphics performance over competing chips.

(Image source: AMD)
Atmosic Technologies M3 Battery-Free Bluetooth 5 SoC

Atmosic says its M3 Battery-Free Bluetooth 5 SoC uses so little power that it can even eliminate the need for battery power entirely in devices such as wearables, keyboards, mice, asset trackers, beacons, and remotes. The M3 integrates Atmosic’s Lowest Power Radio, On-demand Wake-Up, and Managed Energy Harvesting technologies to deliver what the company says is 10 to 100 times lower power than other SoCs, while still complying with Bluetooth standards. The M3’s radio uses two “ears” – one for listening in a low-power state to perceive incoming commands, and another that only wakes when alerted. The SoC uses energy harvesting technology to gather power from radio frequency, photovoltaic, thermal, and motion.

(Image source: Atmosic)
Bot3 Zen-P VSLAM Deep Learning Module

Bot3‘s Zen-P VSLAM Deep Learning module integrates visual simultaneous localization and mapping (VSLAM) technology (a version of the same technology used in autonomous vehicles) into mobile robots ranging from industrial machines to smart home products. Bot3’s image processing algorithm, Pascal, allows for autonomous navigation without tracks as well as indoor mapping and positioning. (for instances such as warehouse applications).

(Image source: Bot3)
BrainCo BrainRobotics Prosthetic Hand

Many companies have been developing mind-controlled prosthetics for amputees and other disabled patients. What separates the prosthetic hand developed by BrainRobotics is the integration of AI technology. The BrainRobotics hand utilizes machine learning to allow the hand and its user to learn from each other over time – leading to more lifelike movements. The company is aiming to provide accurate and reliable prosthetics and at affordable price for all patients. BrainRobotics is a subsidiary of BrainCo, a software developer focused on brainwave measuring and monitoring.

(Image source: BrainCo/BrainRobotics)
Fluent.ai MultiWake Word and Voice Control Engine

Fluent.ai is a technology company focused on AI for voice interface and speech recognition. The company’s Multi-Wake Word and Voice Control Engine is an edge-based, noise robust, and multilingual speech technology that consumes minimal power and storage, allowing it to be embedded in small devices. The solution is Cortex M4-based and supports four separate wake words and 100 multilingual commands, according to Fluent.ai.

Fluent.ai has recently partnered with semiconductor designer Ambiq Micro to implement Fluent.ai’s software solutions into Ambiq’s ultra-small footprint, low-power microcontrollers. Ambiq’s MCU supports frequencies up to 96 MHz, and Fluent.ai’s solution requires only 16 MHz from the MCU. The new partnership means Fluent.ai and Ambiq will be releasing MCUs for OEMs looking for an easy way to add speech recognition and voice command functionality to their smart home devices and other products.

(Image source: Fluent.ai / CES
Intel Tiger Lake Chip

When Intel announces a new chip, the whole world takes notice. The chipmaking giant is launching its latest chip for consumers this year. Dubbed Tiger Lake, the new chip is said to be optimized for AI performance, graphics, and USB 3 throughput. Rather than desktops, the new chips will be focused on mobile devices such as ultra-thin laptops and tablets. The first products featuring Tiger Lake are expected to ship later in 2020.

(Image source: Intel)
Monster MultiLink Bluetooth Technology

Sometimes its the most straightforward ideas that can make the biggest difference. Most of us love our Bluetooth wireless headphones and earbuds. The problem is they don’t create a sharable experience. What if you want to show your friend the video you’re watching without disturbing the people around you? Monster has debuted a new technology called Music Share that uses MultiLink technology to allow devices to send Bluetooth audio to multiple devices in sync. The technology expands how Bluetooth headphones can be used and opens up new use cases ranging from air travel to fitness classes as well as new avenues for social interaction.

(Image source: Bluetooth SIG)
Murata Coral Accelerator Module

Working in partnership with Coral and Google, Murata Electronics has developed what it is calling the world’s smallest AI module. The Coral Accelerator Module packages Google’s Edge TPU ASIC into a miniaturized footprint to enable developers to embed edge-based AI into their products and devices. The new module forms an integral part of Coral’s integrated AI platform, which also includes a toolkit of software tools and pre-compiled AI models.

(Image source: Murata Electronics Americas)
Pollen Robotics Reachy Open-Source Robot

Reachy is a robot developed by Pollen Robotics, in collaboration with the INCIA Neuroscience Institute in France, that is fully open source. The robot, which can be programmed using Python, is modular – employing a variety of 3D-printed grippers – and comes with prepackaged AI algorithms to allow developers to customize it for a variety of applications ranging from customer service and assisting the elderly or disabled.

Read more about Reachy, and the rise of open-source robotics, here.

(Image source: Pollen Robotics)
VRgineers 8K XTAL Headset

VRgineers, a maker of premium VR headsets for enterprise applications in industries ranging from automotive to defense and military, has released a major upgrade to its flagship XTAL headset. The latest version of XTAL features 8K resolution (4K per eye), improved lenses with a 180-degree field-of-view, and a new add-on module for augmented reality and mixed reality functionality. The headset also still includes eye tracking as well as integrated Leap Motion sensors to enable controller-free navigation and interactions.

(Image source: VRgineers)
zGlue ChipBuilder

zGlue is a software company that develops tools for chipmakers and designers. Its latest offering, ChipBuilder 3.0 is a design tool to for building custom silicon chips and accelerating time to market. The software suite features an expansive library of chipsets and allows engineers to capture schematics, route and verify designs, and download netlists. The tool allows engineers to create realistic 3D models and code their own chips and even place orders for physical chips via zGlue’s Shuttle Program.

(Image source: zGlue / CES)

Chris Wiltz is a Senior Editor at Design News covering emerging technologies including AI, VR/AR, blockchain, and robotics

What Happened To Intel’s Early Facial Recognition Platform?

January 14, 2020 • Consumer Electronics, Consumer Products, Electronics & Test, Gadget Freak, Science, Sensors, Technology

Facial recognition technology is one of the big trends at CES 2020. That’s not surprising since facial recognition market is expected to grow from USD 5.07 billion in 2019 to USD 10.19 billion by 2025, according to Mordor Intelligence. The hardware market is segmented into 2D and 3D facial recognition systems with the latter expected to grow the most in the coming decade.

Image Source: Intel / SID

One of the early hardware platforms that would enable facial recognition was Intel’s Realsense. When the platform was first introduced in 2015, it was positioned as a way for PCs, mobile phones and robotic systems to see beyond two-dimensions or 2D. The smart-camera-based system was capable of sensing the third-dimension or depth perception to better understand objects in its environment. Since the first introduction in 2015, the camera-based system has gotten even smaller in size yet better in performance thanks to the scaling benefits of Moore’s Law.

One of the reasons for the early adoption and growth of the system was that software developers had free access to all of the Realsense APIs. These interfaces interacted with the camera to enable motion tracking, facial expressions – from smiles and frowns to winks – and more. Gesture tracking was also provided to create programs for those cases when users could not really touch the display screen, as while using a cooking recipe.

“Computers will begin to see the world as we do,” explained Intel’s then CEO Brian Krzanich at the 2015 Society for Information Display conference. “They will focus on key points of a human face instead of the rest of the background. When that happens, the face is no longer a square (2D shape) but part of the application.”

At the time, one of the early companies adopting the technology was JD.com, a Chinese online consumer distributor. JD.com had replaced its manual tape ruler measurements with container dimensions captured by the RealSense camera platform. This automation had saved almost 3 minutes per container in measurement time.

Image Source: Intel / SID

Back then, the big deal was to move from 2D to 3D computing, where the third dimension really meant adding depth perception. An example of this extra dimension was given by Ascending Technology, a Germany company that used the Intel platform to enable a fast-moving drone to move quickly through a forest including up and down motions. To accomplish this feat required the use of multiple cameras and an processor.

Now, fast forward to CES 2020, where Intel’s Realsense has further evolved into a platform that not only supports depth perception but also tracking and LiDAR applications. Tracking is accomplished with the addition of two fisheye lens sensors, an Inertial Measurement Unit (IMU) and a Intel Movidius Myriad 2 Visual Processing Units (VPU). The cameras scan the surrounding areas and the nearby environment. These scans are then used to construct a digital map that can be used detect surfaces and for real world simulations.

One application of depth perception and tracking at CES was for a robot that would follow its owner and carry things. Gita, the cargo robot from the makers of Vespa, not only followed it owner but also tracked their where-about on the CES exhibitor floor.

LiDAR (Light Detection and Ranging) was the newest addition to the Realsense platform. LiDAR cameras allow electronics and robots to “see” and “sense” the environment. Such remote sensing technology measures distance to a target by shining the target with a laser light and then measuring the reflected light. It is very accurate and is being used in the automotive industry to complement ultrasonic and regular cameras.

At CES 2020, one of the highlighted LiDAR applications was a full body, real-time, 3D scan of people. Another application of LiDAR was skeletal motion tracking with the Cubemos Skeletal tracking SDK, which boasted the capability to integrate 2D and 3D skeleton tracking into a program with a mere 20 lines of code. The SDK provided full skeleton body tracking of up to 5 people.

Image Source: Intel / Realsense LiDAR

Since its release over 5 years ago, there have been many competitors to Intel’s Realsense platform, including Google Scale, Forge, ThingWorx Industrial IoT, and several others. Such healthy competition attests to the market for compact, relatively inexpensive camera platforms that are capable of depth perception, tracking objects an using LiDAR for scanning of shapes.

Fiber Optic Sensor Moves Robot In Near Real-Time

January 14, 2020 • Consumer Electronics, Electronics & Test, Government/Defense, Science, Sensors, Technology

Although not as prominent at this year’s 2020 CES, fiber optics sensing technology has been a highlight of past shows. Fiber optic sensing measures changes in the backscattered light in a fiber cable, which can happen when the fiber undergoes a vibration or strain. When attached to an opto-electrical connection, the fiber optic sensing can be used as a hyper-sensitive measurement device for electronic systems.

NASA, among other R&D agencies, began developing Fiber Optic Sensing Systems (FOSS) technologies over 5 years ago. Innovators at NASA’s Armstrong Flight Research Center began using FOSS to monitor the safety of aircraft structures in flight, but quickly found other uses for the technology in civil structures, transportation, oil and gas, medical, and many more spaces.

Image Source: Fraunhofer / SPIE Photonics / John Blyler

Germany’s Fraunhofer, one of Europe’s largest application-oriented research organizations, has been exploring the use of a related technology, namely, fiber optical 3D Shape Sensing. One application they have been studying is the real-time shape and position sensing of the fiber anywhere along the length of the optical fiber. Such sensors provide highly accurate measurements as the fibers twist and bend at every point along the sensor.

A few years back, Fraunhofer showed the value of using fiber optic sensing to accurately control the movements of a robot. The video below provides a convincing demonstration of this technology.

Pico Interactive Is One Of The Best Kept Secrets In VR

January 13, 2020 • Consumer Electronics, Design Hardware & Software, Electronics & Test, Gadget Freak, Materials & Assembly, Science, Sensors, Technology

The Pico G2 4K (Image source: Design News)

Unless you’ve been deeply entrenched in the VR space for years you might be forgiven for not knowing about Pico Interactive. While big names in VR hardware like HTC and Oculus have only recently shifted their focus to creating standalone headsets (ones that do not need external sensors or a PC to operate), standalone has been Pico’s focus from the very beginning.

The San Francisco-based company, made a quiet, but significant, showing at the 2016 Electronic Entertainment Expo (E3) with a small, standalone headset called the Pico Neo. The Neo was an Android-based gaming headset that actually boasted some impressive specs for its size. It was based on the same Snapdragon 820 chipset behind the early Oculus Rift and HTC Vive headsets, offered a 90 Hz refresh rate, and a 110-degree field of view.

When we spoke to Pico in 2016, Ennin Huang, Pico’s VP of Design, said the company’s vision was pretty straightforward – “We really wanted to push VR and make it affordable for everyone without comprising the graphics and experience.”

The way to do that, Huang said, was by offering users a lightweight, untethered experience.

The Pico Neo didn’t make a big splash in the US. But it turned out Huang was right.

In recent years VR hardware makers have pivoted into offering headsets that are not only lighter and more powerful, but, most importantly, standalone. The latest hardware from Oculus, the Oculus Quest, is an all-in-one headset targeted at gaming with six degrees of freedom (6DoF) tracking. The Quest, the less robust Oculus Go, other standalone models such as the HTC Vive Focus, and the (fortunate) death of smartphone-based VR headsets point to one clear trend for future of VR hardware – wireless, standalone, and powerful.

But Pico Interactive hasn’t stood still. In recent years the company has pivoted into targeting its headsets specifically at engineers, designers, and other enterprise users – with the aim of providing a convenient and mobile experience for applications ranging from virtual prototyping and design, to education, and even medical applications.

Design News had a chance to go hands-on with one of Pico Interactive’s flagship enterprise headsets, the G2 4k, and found it to be one of the best overall user experiences to date. The G2 4K is very light (276 grams according to company specs) and very well-balanced. The 4K resolution, comes through crystal clear thanks to LCD displays and the use of fresnel lenses (which also help contribute to the unit’s light weight).

In terms of overall image quality, the G2 4k rivaled high-end PC-based enterprise headsets like HP’s Reverb, despite having a lower-resolution (3840 x 2160, or roughly 1920 x 1080 per eye).

“We conducted a lot of human-factors study for the G2 4K,” Huang told Design News in a recent interview. “There are two main strategies for tackling the overall weight issue: First, the material for the G2 4k is carefully selected to achieve the lightest weight possible while still keeping it affordable for everyone. Second is the weight distribution – we want to make sure the overall center of the mass is somewhere close to the center of the user’s head when the user is wearing the headset. To achieve that we have moved some of the components to the back of the head-padding while still keeping the form factor as compact as possible.”

The G2 4K’s fresnel lenses lend to its light weight and image quality, while its foam face cushion and adjustable Velcro staps support overall comfort. (Image source: Design News)

With a 101-degree field of view and a 75 Hz refresh rate, the G2 4K does fall below the specs of more entertainment-focused headsets. But then again, enterprise software apps don’t usually require the same high frame rates as, say, the latest action game.

The G2 4K is built on the Snapdragon 835, Qualcomm’s first chipset offering targeted at mobile VR and augmented reality. It’s the same chipset behind the highly-praised Oculus Quest.

Aside from the headset having its own online store (the Pico Store), the company also offers an SDK for the G2 4K that we found supports both Unreal and Unity engines. For those who might be put off by the thought of learning a new SDK or having to purchase apps within a proprietary store, the headset is also compatible with the Wave SDK for the HTC Vive line of headsets and also supports apps from HTC’s Viveport. We tried running a few enterprise apps from Viveport on the G2 4K and didn’t notice any difference in performance.

Where one might find disappointment with the G2 4K is that it is only offers three degrees of freedom (3DoF) tracking for both the controller and the headset, which can significantly limit user mobility depending on the application. Some enterprise users who prefer a more fixed design space won’t notice the difference at all, but someone like an automotive engineer or architect for example, who might prefer to be able to walk through a virtual space at room scale, might be frustrated at having to use point-and-click navigation to move around.

The G2 4K’s controller is compact and comfortable, but only offers 3DoF tracking. (Image source: Design News)

Asked about the decision to give such a visually powerful headset only 3DoF tracking, Huang said the decision came down to offering a product with the right specs for enterprise users but would also provide a comfortable barrier to entry for new users. “We think 3DoF and 6DoF both have their niche in enterprise solutions,” Huang said. “While 6DOF is great for a little more advanced users, the 3DoF VR training and tutorials experience is great for someone who has never had or had a very little VR experience. In fact, many users of our enterprise-customers have never used VR before.”

Very serious enterprise users will probably opt for a PC-based setup along the lines of the HP Reverb or HTC’s Vive Pro. But smaller organizations or those looking to get their feet wet in implementing VR into their workflow, and who hold high value in an untethered experience, could find the G2 4K a more economical option capable of still delivering in terms of image quality and overall performance.

The G2 4K features two external speakers, audio jack, a micro SD card slot, USB-C port, and a built-in microphone. (Image source: Design News)

Enter the Neo 2

At the time we spoke, Pico Interactive was shipping another headset, the Neo 1, which featured 6DoF head tracking and a 3DoF controller, in Japan, China, and parts of Europe. Huang teased that the company’s R&D team was working on prototypes for headsets that offers 6DoF head and controller tracking, but declined to provide any further details.

However at CES 2020, Pico made another announcement that should please users who demand a 6DoF experience with their VR.

The company’s latest headset, announced at CES 2020, is the Neo 2, a standalone enterprise headset with 4K resolution and 6DoF inside-out tracking. A second version, the Neo 2 Eye, features eye tracking and foveated rendering capabilities courtesy of Tobii, the go-to supplier of eye tracking sensors and analytics technologies for VR.

The Pico Neo 2 debuted at CES 2020. (Image source: Pico Interactive)

Based on the Qualcomm Snapdragon 845 platform, the Neo 2, is a bit heavier than the G2 4K (350 grams, according to specs), and features the same resolution, lenses, and refresh rate. Where the headset takes a step up from previous models in utilizing the 845’s integrated simultaneous localization and mapping (SLAM) technology for room-scale 6DoF tracking. Both models of the Neo 2 also feature two mono fisheye external cameras.

For its part, Tobii says the foveated rendering technology integrated into the Neo 2 allows it to increase framerates by up to 66 percent and reduces shading loads by up to 72 percent, which gives the headset improved visual performance without sacrificing performance or draining battery life.

The addition of eye tracking also gives Neo 2 users a novel control scheme (navigating apps and menus via eye movement) and can also be used to capture gaze data to assist with training applications as well as capturing user behavior insights.

It’s a pretty big leap for a company that started with mobile gaming, though Huang said Pico hasn’t left its roots behind. And while enterprises may be the first to take note of what Pico is offering, Huang said the company believes first in serving VR users in any application they desire.

“Mobile gaming and entertainment are still part of our focus, and in fact, we have been doing pretty well in Asia in places like Korea, Japan, and China. In addition to the consumer market, we also see great opportunities where Pico can provide enterprise solutions for many of our business partners,” Huang said.

“The motivation behind all the Pico products has always been the same since we’ve started back in 2016; it has always been user-first design.”

Chris Wiltz is a Senior Editor at Design News covering emerging technologies including AI, VR/AR, blockchain, and robotics

Don’t Forget About Standby Power

January 10, 2020 • Battery/Energy Storage, Consumer Electronics, Electronics & Test, IoT, Science, Sensors, Technology

Standby power refers to the electronic and electrical power consumed by systems when the primary operational functions are waiting to be activated. Standby power needs are often overlooked by systems designers but are crucial considerations to ensure power is available for the smart devices that make up the Internet of Things (IoT).

Consider the design of a smart home, a dwelling that consumes zero net energy. To maintain zero net power consumption, the smart home must be capable of monitoring and controlling the main energy consumers – e.g., HVAC and lighting – as well as interfacing with energy sources such as solar panels/batteries and the power grid. Adding control and monitoring intelligence to the home will itself require energy. The trick is to make sure that the controlling and monitoring electronics don’t consume more power than the devices themselves. One part of this trick is to make sure that the smart systems pay attention to stand-by loads, those mischievous power draining loads consumed by electronics and electrical appliances even when they are turned off (but still drawing power in standby mode).

In addition to – or often part of – controlling and monitoring electronics, connectivity transceivers like RF and wireless are another reason why standby power awareness are so important. Most of our modern appliances and control devices constantly consume a trickle of power to be ready to perform updates, connect to edge or cloud servers, listen for our voice commands, and the like.

Numerous studies attest to the amount of energy lost from devices not in use due to standby power consumption. According to a report from the Natural Resources Defense Council (NRDC), an international nonprofit environmental organization, always-on but inactive devices can cost Americans $19B annually. That comes to about $165 per U.S. households on average—and 50 large (500-megawatt) power plants’ worth of electricity.

Further, Berkeley Labs notes that standby power is roughly responsible for 1% of global CO2 emissions.

What are the best ways to reduce the impact of standby power? Let’s consider one approach that looked promising but so far has failed and another more integrated approach that has proven to be successful.

Image source: Natural Resources Defense Council (NRDC)

Hyper Automation, Multi Experience, And Securing AI (Or Baby Yoda)

January 7, 2020 • Artificial Intelligence, Automation, Automotive, Consumer Electronics, Cyber Security, Electronics & Test, IoT, Science, Technology

If you google “technology trends,” one of the companies that will appear in the top 10 hits will be Gartner. The research and advisory firm not only analyzes numerous markets in terms of technical innovations but also covers business aspects of technology for C-suite professionals.

For 2020, Gartner has produced a number of predictive reports, including those covering digital and strategic technologies. From those lists, I’ve selected three trends that appear vaguely familiar from the recent past, albeit with new names. Do you agree? Don’t hesitate to ping me with your take on these trends at: [email protected]

Trend: Hyper Automation

Gartner: “Automation uses technology to automate tasks that once required humans. Hyper automation deals with the application of advanced technologies, including artificial intelligence (AI) and machine learning (ML), to increasingly automate processes and augment humans. Hyper automation often results in the creation of a digital twin of the organization. As no single tool can replace humans, hyper automation today involves a combination of tools, including robotic process automation (RPA), intelligent business management software (iBPMS) and AI, with a goal of increasingly AI-driven decision making.

My Take: Do we really need yet another word or phrase to represent the ongoing digitization process that will eventually enable a complete digital twin? One might just as well say that the creation of a digital twin – from improved modeling, simulations, sensors, etc. – have accelerated the pace of automation thus creating a new hypeautomoation or superautomation reality.

It’s really a chicken and egg perspective. Which came first – the creation of hyper automation systems that eventually result in a digital twin? Or did the creation of a digital twin from a sensor-rich ecosystem lead to improved automation of tasks previously performed by humans?

Regardless of the answer, there seems to be little doubt about the movement toward a more complete digital twin within the next decade. Mordor Intelligence predicts that the digital twin market is anticipated to witness a CAGR of 35.0% over the forecast period 2019 – 2024. Growth in IoT and cloud-based platforms, the surge in adoption of 3D printing technology in the manufacturing industry, and the objective to reduce project cost are some of the major factors, driving the growth for the digital twin market. Mordor notes that IoT sensors have created a potential space for engineers to test and communicate with sensors integrated with the operating products, hence delivering real-time prescriptive of system functioning and timely maintenance.

Which came first: Hyper automation or the digital twin? It’s your call.

Deepfakes: The Looming Threat Of 2020

January 6, 2020 • Artificial Intelligence, Consumer Electronics, Design Hardware & Software, Electronics & Test, IoT, Science, Technology

I’m watching a clip from the movie The Shining. Shelly Duvall is hiding from her crazed husband as he chops down the door with an axe. Jim Carrey sticks his head through the opening and cackles the iconic line: “Here’s Johnny!”

…Jim Carrey is not in The Shining.

What you’re seeing is not a Hollywood special effect. It wasn’t done with After Effects, green screen, or with costuming and makeup. The video is a fake created by deep learning artificial intelligence – a deepfake. And anyone with a powerful computer and enough time can make one.

You might have heard of deepfakes before, or glimpsed headlines discussing the technology. You might even have laughed at various YouTube videos on channels such as Ctrl Shift Face that have swapped faces of celebrities in iconic roles to some humorous and sometimes unsettling results (once you’ve seen any of the bizarre deepfakes involving Nicolas Cage you can never un-see them.)

But deepfakes, once confined to darker corners of the internet, are becoming a serious threat. In the US, particularly as the 2020 election season rapidly approaches, AI experts are warning that deepfakes could become a powerful tool for spreading misinformation and manipulating the public. With enough effort a bad actor could create a video of any political candidate saying nearly anything. And in today’s climate of social media outrage and algorithm-driven content distribution, there’s no telling how far it could spread before someone caught it.

It’s time engineers, developers, and technologists all had a serious discussion about deepfakes.

(Image source: Adobe Stock)

The Origin Of Deepfakes

There’s no one particular person that has taken credit for originally developing deepfakes. Their existence owes to a confluence of technologies ranging from ever-more sophisticated computer vision algorithms and neural networks, to increasingly powerful GPU hardware.

The first deepfakes to emerge on the internet seem to have emerged in 2017, when an anonymous Reddit user called “Deepfakes” began distributing illicit, altered videos of celebrities online. Other Reddit users followed suit and it wasn’t long before a community had sprung up around distributing both deepfakes themselves as well as tutorials and software tools to create them.

In an interview with Vice, [NSFW link] one of the first outlets to take an extensive look at deepfakes, the Reddit user outlined how comparatively easy the process is:

“I just found a clever way to do face-swap. With hundreds of face images, I can easily generate millions of distorted images to train the network. After that if I feed the network someone else’s face, the network will think it’s just another distorted image and try to make it look like the training face.”

But it wasn’t all fun and games. Far from it. When they first appeared, deepfakes had one particularly popular and disturbing use case – pornography. Much of the early deepfake content available was pornographic films created using the faces of celebrities like Gal Gadot, Scarlett Johansson, and Taylor Swift without their consent.

As the videos proliferated, there was an crackdown with Reddit itself shutting down its deepfakes-related communities, pornographic websites removing the content, and sites like GitHub refusing to distribute deepfake software tools.

If private citizens weren’t that concerned yet it was probably because sites got somewhat ahead of the problem. Left unchecked it wouldn’t have been long before deepfake pornography spread from celebrities to every day people. Anyone with enough publically available photos or video of themselves on a platform like Facebook or Instagram could potentially become a victim of deepfake revenge porn.

In 2018, Rana Ayyub, and investigative journalist from India, fell victim to a deepfakes plot intended to discredit her as a journalist. Ayyub detailed her ordeal in an article for The Huffington Post:

“From the day the video was published, I have not been the same person. I used to be very opinionated, now I’m much more cautious about what I post online. I’ve self-censored quite a bit out of necessity.

“Now I don’t post anything on Facebook. I’m constantly thinking what if someone does something to me again. I’m someone who is very outspoken so to go from that to this person has been a big change.

“I always thought no one could harm me or intimidate me, but this incident really affected me in a way that I would never have anticipated…

“…[Deepfakes] is a very, very dangerous tool and I don’t know where we’re headed with it.”

How Deepfakes Work

On the surface the process of creating a deepfake is fairly straightforward. First, you need enough images (hundreds or more ideally) of your target – showing their face in as many orientations as possible (the more images you can get, the better the results – hence why celebrities and public figures are an easy target). If you think it might be difficult to get hundreds or thousands of images of someone remember that a single second of video could contain 60 frames of someone’s face.

Then you need a target video. The AI can’t change skin tone or structure so it helps to pick a target and source with similar features. Once a deep learning algorithm is trained on a person’s facial features, additional software can then superimpose that face onto another person’s in your target video. The results can be spotty at times, as many videos online will attest to, but done right, and with enough attention to detail, the results can be seamless.

In an interview with Digital Trends, the anonymous owner of the Ctrl Shift Face YouTube channel (the channel responsible for the Jim Carrey/The Shining videos, among others) discussed how simple, yet time-consuming the process is:

“I’m not a coder, just a user. I don’t know the details about exactly how the software works. The workflow works like this: You add source and destination videos, then one neural network will detect and extract faces. Some data cleanup and manual extraction is needed. Next, the software analyzes and learns these faces. This step can sometimes take a few days. The more the network learns, the more detailed the result will be. In the final step, you combine these two and the result is your deepfake. There’s sometimes a bit of post-process needed as well.”

On one hand, the relative ease at which this can be done with little to no coding experience is certainly disconcerting. On the other however, deepfakes are an impressive demonstration of the sophistication of AI today.

At the core of deepfakes is a neural network called an autoencoder. Put simply, an autoencoder is designed to learn the important features of a dataset so it can create a representation of it on its own. If you feed a face into an autoencoder its job is then to learn the distinguishing characteristics that make up a face and then construct a lower-dimensional representation of that face – in this case called a latent face.

Deepfakes work by having a single encoder train to create a generalized representation of a face and then have two decoders share that representation. If you have two decoders – one trained on Person A’s face, the other on Person B’s – then feed the encoder either face you can transpose Person A’s face onto Person B’s (or vice versa). If the encoder is trained well enough, and the representation is generalized enough, it can handle facial expressions and orientations in a very convincing way.

Since faces in general are very similar in their overall shape and structure, a latent face created by an encoder using Person A’s face, can be passed to a decoder trained on Person B’s face to good effect. The result at the other end is a video of Person B, but with Person A’s face.

As long as you have two subjects similar enough and a computer with enough processing power, the rest just takes time. Faceswap – one of the more readily available deepfakes apps – can run on a Windows 10, Linux, or MacOS computer and recommends a newer Nvidia GPU for processing. “Running this on your CPU means it can take weeks to train your model, compared to several hours on a GPU,” according to Faceswap’s documentation.

Top 10 Tech Failures From 2019 That Hint At 2020 Trends

January 3, 2020 • Aerospace, Artificial Intelligence, Automotive, Consumer Electronics, Consumer Products, Cyber Security, Electronics & Test, Gadget Freak, Science, Technology

As the last year of the last decade, 2019 had a lot to live up to. Within the span of 10 short years, service apps like Uber, Lyft, AirBnB and others on mobile phones became big business. Mobile phone companies introduced amazing personal features like voice assistance (e.g., Siri and Alexa), iCloud connections for fast video streaming, and very high-resolution HD cameras. Not to be outdone, the automobile was transformed with automation tech and electrification. A Tesla electric vehicle even made it into space.

Space technology flourished in the last decade with the commercialization of space rockets, the launch of hundreds upon hundreds of communication satellites and the increasing popularity of Cubesats. Back on earth, homes and buildings became smarter while alternative forms of energy continued to improve in efficiency. And the list goes on.

But there were several notable failures in the last decade, many seeming to culminate in 2019. Here is the short list of the 10 tech failures most worthy of mention, in no particular order.
#1 Glitchy Spacecraft Launch

Boeing suffered several major setbacks this year. The first one was an incomplete demonstration flight of its new astronaut capsule. The mission of Boeing’s CST-100 Starliner spacecraft began successfully but suffered technical problems that prevented it from reaching the International Space Station (ISS). Many observers believe that the Starliner capsule on top of an Atlas rocket simply burned too much fuel as it climbed into space, leaving an insufficient amount to reach the ISS. Some have suggested the failure was from a glitchy timer system that turned off the rocket thrusters too soon.

The demonstration test wasn’t a complete failure as the Starliner did land successfully in the deserts of New Mexico.
#2 Andromeda Strain revisited?

Remember the Andromeda Strain? It was a techno-thriller novel from 1969 written by Michael Crichton that centered around the efforts of a team of scientists investigating the outbreak of a deadly extraterrestrial microorganism in Arizona.

Fast forward to 2019. A company in Israel launched its first lunar lander that unfortunately crashed-landed on the moon. The small robotic spacecraft called Beresheet was created by the SpaceIL and Israel Aerospace Industries (IAI). It failed just moments before landing on the moon.

This was an unmanned operation, but not one devoid of life. A US-based nonprofit had added tardigrades, or water bears, to the capsule. These microscopic, eight-legged creatures could survive in a dormant state through harsh conditions, and maybe even on the moon.

In other words, earth-based lifeforms have now been introduced to the moon’s ecosystem. Without some water, the tardigrades aren’t likely to revive and spread. But this failure highlights the need for planetary protections – both on the moon and earth.

It should be noted that the goal of the Arch Mission Foundation was not to contaminate the moon but rather to, “create multiple redundant repositories of human knowledge around the Solar System.” The foundation tests out technologies for long-lasting archives, like securing information in DNA strands or encapsulating insects in artificial amber. In addition to water bears, the Arch’s payload included nickel sheets nanopatterned with thousands of pages of Wikipedia and other texts.

One of Arch’s first missions was launched by SpaceX on the Falcon Heavy rocket and is now entering an orbit around the Sun for millions of years. The first books in the Solar Library were Isaac Asimov’s Foundation Trilogy. Can you guess where they are located? The books containing Asimov’s Foundation Trilogy were placed in the glovebox of the Cherry Red Tesla Roadster that will soon be orbiting the Sun.
#3 Communication Failures (again)

Both Boeing and the FAA have been cited for oversight breakdowns that contributed to 737 Max failure. But the actual cause of the tragedy that resulted in the crash of two Boeing 737 Max aircrafts seems to be broad failures in the automated system that controls the new planes. The report by the Joint Authorities Technical Review panel said that assumptions about critical aspects of the plane’s design were “not adequately reviewed, updated, or validated.”

This lack of communication and incorporation of warnings from the engineering teams is a common problem with very complex, modern systems, e.g., the Challenger Space Shuttle and others.
#4 Disappearing Bitcoin Miners

While 2019 was overall a profitable year for the semiconductor chip development market, there were a few noticeable declines. One was the system-on-chip (SoC) devices made specifically for bitcoin mining. The cost of mining for bitcoins dramatically increased in 2019, leading to a drop in the need for hardware SoC-based equipment.

In essence, it took much more effort for bitcoin miners to solve the equations required to validate transactions on the Bitcoin network. This increase in mining difficulty reflects the increased competition.

Another slowdown was in the market for automotive chips and electronics, as companies and drivers realized that autonomous car technology won’t really be ready for several more years. This corresponds well to Gartner’s famous “trough of disappointment” portion in its hype cycle for emerging technologies.
#5 Cloud Buckets

A new type of cybersecurity issue has emerged in which millions of people have had their personal information exposed through file storage systems known as cloud buckets. Such storage areas typically consist of public resources that are easily accessed by a variety of web service applications. Cloud buckets are like public file folders which contain user information.

Placing sensitive user data information in the cloud offers companies the capability to offload their security to big firms like Google, Apple, Amazon or Microsoft. The problem is that the buckets are not configured by these firms but rather by the companies who use their cloud networks.

Not all of these companies are storing their customer information properly. This lack of security is easy pickings for identity thieves. It is an example of readily available information that doesn’t require any hacking.
#6 Hacks of the Year

Speaking of hacks, this year experienced even more cybersecurity breaches. In 2018, there were 500 million personal records stolen, according to the Identity Theft Resource Center. But that number was miniscule compared to the 7.9 billion records exposed in 2019 by over 5,000 breaches, as reported by Risk-Based Security. Compared to the 2018 Q3 report, the total number of 2019 breaches was up 33.3 percent and the total number of records exposed more than doubled, up 112 percent. Here’s just a small sampling of the more infamous breaches (more details here):

> ElasticSearch Server Breach

> Canva Data Breach

> Facebook App Data Exposure

> Orvibo Leaked Database

> Social Media Profiles Data Leak

Sadly, the common theme in many of these data exposures is that data aggregators obtained and used personal information in a way the owners never imaged or gave their consented. This is a legal problem as much as a technical one.
#7 Google Glass

In 2019, Google announced a new $999 Glass augmented reality headset that looked suspicious like the failed Google Glass from the past.

Early in 2012, Google co-founder Sergey Brin debuted Google Glass. A year later, the founder and head of the Google Glass Project, Babak Parviz, delivered a keynote about the technology at the IEEE Hot Chips event at Stanford.

One of the ongoing leading smart phone trends is the ever-improving screen resolution and larger screen size. During his keynote, Parviz argued that there was a physical limit to this trend, but glass offered the next display form factor evolution, i.e., immersion with one’s surroundings. This will be especially important in augmented reality applications.

Originally, Google Glass was a standalone unit (not yet cloud-based) that included internet access, voice controls, and a camera for pictures and videos. It accomplished all of this with dual core processors running at more than 1 GHz. Five MEMS sensors capture all the environmental data. It had a two-dimensional touch panel on side of glass.

Why was this technology a failure? It wasn’t because of the technology, but rather because it wasn’t clear to the customer what problem it solved or why they needed it. Additionally, many felt it was intrusive as a user of the device could take pictures and short film snippets of people without their knowledge.

In January 2015, Google announced that they would no longer be developing Google Glass. But that wasn’t the end of the project. Instead, Google pivoted to the business sector by launching Glass Enterprise Edition for workplaces like factories in 2017. This year, Google announced the Glass augmented reality headset.
#8 Folding Phone

Samsung’s Galaxy folding phone was billed as a new dawn in display technology. The phone levered open into a 7.3-inch dynamic AMOLED display.

Unfortunately, the company had to postpone the launched of the folding phone after early review models broke, delaminated, and got filled with gunk. The problem seemed to be potential defects with a weak hinge as well as substances found inside the device.

As with many new technologies, the price tag also presented a barrier to anyone but early adopters. A reengineered and improved version is now on sale for near $2,000.
#9 Machine-Bias or Garbage-in, Garbage-out

The challenge of machine-bias came clearly into focus in 2019. Similar to human-bias, machine-bias occurs when the learning process for a Silicon-based machine makes erroneous assumptions due to the limitations of a data set and pre-programming criteria. One example of machine-bias was recently revealed in Apple’s new credit card, which contained an algorithm to decide how much trustworthy (or risky) a user might be. This evaluation used to be done by trained humans but now is often performed by AI based algorithms.

Apple’s credit card was shown to have a gender bias. Males are more likely to get a higher credit line limit than females. This bias was highlighted when a male entrepreneur was assigned a spending limit 10 times higher than that of his wife, even though they have a common account.

How does a machine get a bias? A report from IBM Research outlines two main ways AI systems could inherit biases. First, the AI software might contain errors and dependencies. Second, the data set from which AI learns its task may have flaws and bias. These data points come from the real world which contains many biases, e.g., favoring white men to the exclusion of women and minorities. Algorithms are only as smart as the data you feed them. This is a modern update of the old computer data expression, “garbage-in, garbage-out.”
#10 Software App Failures

No list of tech failures would be complete without mention of the apps that didn’t make it. The range of the applications that failed is wide.

Consider first British Airways (BA) glitch, whose computer system completely wend down during a peak travel season. Over a hundred flights of BA were cancelled and near to 300 delayed. Thousands of passengers were affected. Sadly, this wasn’t the first time the system had failed, which suggests a systemic problem that has not been properly addressed by management.

Or how about the Facebook 2019 failure that prevented users from viewing or loading images form the newsfeed? Several other social media apps had a similar problem, including Instagram, WhatsApp and Messenger. In each case, users were prevented from sending messages, media files and the like. Facebook claimed their problem was the result of an accident during routine maintenance.

Several app failures or hacks from 2019 include Apple’s Facetime bug and the Ring security camera intrusions. The later may have been more of a customer problem as Ring notes that the system invasion was likely the result of the hacker gaining access to the family’s account through weak or stolen login credentials.