View On Astronomy: Perseids meteor shower an annual attraction – The Independent

Posted on August 10, 2020 by Danzig

By David A. Huestis

Special to the Independent

After more than 45 years of enjoying the splendor of the heavens, I still look forward to a simple yet rewarding observing experience watching burning rocks falling from the sky. Im referring to a meteor shower. There are about a dozen major meteor showers and hundreds of minor ones. During August we are fortunate to encounter the second most productive (the December Geminids are better) meteor display of the year the Perseids. These meteors are a stream of particles stripped off Comet 109P/Swift-Tuttles surface by the solar wind and left in orbit around the Sun. Annually the Earth passes through this stream and we experience a display of shooting stars.

For 2020 the Perseids peak on the night of Aug. 11-12, with the best time to observe as many meteors as possible between midnight and dawn. This shooting star display is the northern hemispheres most widely observed meteor shower because people spend more time with outdoor activities during late summer. Unfortunately, a last quarter Moon rises around midnight not far from the radiant point in the constellation Perseus from where the meteors appear to emanate. The Moons brightness will somewhat reduce the number of meteors to be seen. While the Perseid shower can produce between 60 and 90 meteors per hour, around southern New England we can usually expect to see no more than 60 shooting stars per hour. Moonlight will further reduce that number this year.

The Perseids, no larger than a thumbnail, blaze across the heavens at 134,222 miles per hour and completely disintegrate as they plunge through our atmosphere. In fact, J. Kelly Beatty, senior editor of Sky and Telescope Magazine, makes this analogy. The little nuggets in Grape-Nuts cereal (see accompanying photo) are a close match to the size of particles that typically create meteors in our atmosphere

The Perseids are usually green, red or orange in color. And some members of this shower are bright and often produce exploding fireballs. Also, fireballs may be more prevalent as we approach morning twilight. Why? At that time, we are hitting the meteor stream head-on! Maximize your viewing opportunity by finding a dark sky location well away any from light pollution.

The best way to observe any meteor shower is to get comfortable on a chaise lounge or blanket. During the Perseids you must protect yourself from the hungry mosquitoes. (Last summer the EEE virus prevented many of us from observing the Perseids. I prefer the cold December Geminids any day!) Perseus is well up in the northeast sky after midnight. Use the accompanying sky map to locate this star pattern above the northeast horizon. If you can identify the constellation of Cassiopeia, which looks like an M or W tipped sideways, then youre close enough. As Perseus rises higher the number of meteors will increase. Dont simply concentrate your gaze in that direction. The meteors can appear anywhere in the sky, so constantly scan as much of the heavens as possible without straining your neck. If the weather cooperates and you have the time, continue your observing session until dawns early light overwhelms the stars.

If the weather does not cooperate or you are unable to observe on peak night, try your luck on the nights before and after. You wont see 60 meteors per hour, but you may catch a couple of dozen or so. And if you happen to see a stationary meteor (think about itits headed directly at you), dont forget to duck!

And finally, while you are out there under the stars please take notice of Jupiter and Saturn. They will be located to the east (left) of the teapot asterism that is the constellation Sagittarius. Next month I will provide a brief observers guide to these beautiful distant worlds.

Keep your eyes to the skies.

The author has been involved in the field of observational astronomy in Rhode Island for more than 35 years. He serves as historian of Skyscrapers Inc., the second oldest continuously operating amateur astronomical society in the United States.

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View On Astronomy: Perseids meteor shower an annual attraction - The Independent

A Globular Cluster was Completely Dismantled and Turned Into a Ring Around the Milky Way – Universe Today

Posted on August 10, 2020 by Danzig

According to predominant theories of galaxy formation, the earliest galaxies in the Universe were born from the merger of globular clusters, which were in turn created by the first stars coming together. Today, these spherical clusters of stars are found orbiting around the a galactic core of every observable galaxy and are a boon for astronomers seeking to study galaxy formation and some of the oldest stars in the Universe.

Interestingly enough, it appears that some of these globular clusters may not have survived the merger process. According to a new study by an international team of astronomers, a cluster was torn apart by our very own galaxy about two billion years ago. This is evidenced by the presence of a metal-poor debris ring that they observed wrapped around the entire Milky Way, a remnant from this ancient collision.

The study, which recently appeared in the journal Nature, was led by Zhen Wan and Geraint Lewis (a Ph.D. astrophysics student and his professor at the University of Sydney, respectively) and included members from the Macquarie University Research Centre for Astronomy, the Observatories of the Carnegie Institution for Science, the ASTRO 3D center, the McWilliams Center for Cosmology, and multiple universities.

Their study was part of the Southern Stellar Stream Spectroscopic Survey (S5), an international collaboration dedicated to observing stellar streams in the Milky Way. Using the Anglo-Australian Telescope at the Siding Spring Observatory in New South Wales, Australia, the collaboration measured the speeds of the Phoenix Stream (a stream of stars in the Phoenix constellation) that appeared to be the remnants of a globular cluster.

Once we knew which stars belonged to the stream, we measured their abundance of elements heavier than hydrogen and helium; something astronomers refer to as metallicity, explained Wan in a recent Lowell Observatory press release.

To break it down, the oldest stars in the Universe are metal-poor because heavier elements like calcium, oxygen, phosphorous, iron, etc did not exist in abundance. Unlike hydrogen and helium (which were extremely plentiful in the early Universe) these elements formed in the interiors of stars sand were dispersed only after the earliest generation of stars collapsed and dispersed these elements when they exploded in supernovae.

In this respect, astronomers are able to discern the age of stars based on how metal-rich they are. Previous observations of globular clusters have found that their stars are enriched with heavier elements, which they obtained from previous generations of stars. As a result, astronomers have established a metallicity floor for globular clusters, a value that none of them can theoretically fall below.

However, the S5 collaboration noted that the metallicity of the Phoenix Stream (specifically, its iron-to-hydrogen content) sits well below this floor. In short, the Phoenix Stream represents the debris of the most metal-poor globular clusters discovered to date, making it distinct from the roughly 150 globular clusters that form a tenuous halo envelop the Milky Way today.

As Lowell Observatory astronomer Kyler Kuehn, one of the founders of the S5 collaboration and a co-author of the article, remarked:

We can trace the lineage of stars by measuring the different types of chemical elements we detect in them, much like we can trace a persons connection to their ancestors through their DNA. The most interesting thing about the remains of this cluster is that its stars have much lower abundance of these elements than any others we have seen. Its almost like finding someone with DNA that doesnt match any other person, living or dead. That leads to some very interesting questions about the clusters history that were missing.

We were really surprised to find that the Phoenix Stream is distinctly different to all of the other globular clusters in the Milky Way, added Wan. Even though the cluster was destroyed billions of years ago, we can still tell it formed in the early universe.

In short, the Phoenix Streams very existence indicates the existence of globular clusters that were below the metallicity floor. As to why none have been discovered so far, the answer may lie in the debris disk itself: they were destroyed in the early Universe as they were still merging with galaxies and galaxies merged with each other.

Of course, this is not yet a conclusive explanation for the origins of the Phoenix Streams progenitor cluster or where it sits in the evolutionary timeline of galaxies. Whats needed at this point is more observations and more evidence gathering to see if other progenitor clusters show the same levels of low metallicity.

There is plenty of theoretical work left to do, said co-author Geraint Lewis of the University of Sydney (and a co-author on the study). There are now many new questions for us to explore about how galaxies and globular clusters form, which is incredibly exciting.

Further Reading: Lowell Observatory, Nature

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Could JWST Discover the Largest Object in the Universe? Now. Powered by – Now. Powered by Northrop Grumman.

Posted on August 10, 2020 by Danzig

Soon, the James Webb Space Telescope (also known as JWST or Webb) will expand our views of the sky. Astronomers will use the new telescope to observe previously unseen regions of space, ranging from the galaxies that formed right after the Big Bang to the youngest star systems that are forming today.

Earth is minuscule in the scale of the universe. So far, astronomers have discovered giant planets, supermassive black holes, hypergiant stars, superclusters of galaxies and other large objects in between. And thats while observing just a small sliver of the universe with the Hubble Space Telescope. It is hard to predict what Webb will ultimately discover.

Its a new instrument, the largest telescope ever built for space, says Jon Arenberg, chief engineer for Space Science Missions at Northrop Grumman. Well be able to collect data that we have not gotten our hands on before, including observing the early universe, in particular.

Astronomers have already discovered some humongous objects, and JWST could soon uncover even more giants in space.

By having this new instrument that that can observe even more galaxies than weve seen before, we will be able to look for structures and groups of these galaxies in places weve never looked, Arenberg explains.

Contemplating the size of objects in space compared to our tiny home on Earth could make your head spin, but Arenberg finds comfort and pride in JWSTs mission of discovery.

I feel empowered, enlightened, illuminated not tiny, Arenberg says. He adds, The scale of the universe is huge. But so is our planet compared to me, and I dont feel small or insignificant here on Earth.

Its a straightforward question with a nebulous answer. First, it depends on how you define size by mass or volume. A giant cloud of gas, for example, is enormous in volume but relatively small in mass (it doesnt contain much matter). Black holes, on the other hand, are defined by infinitely small volume with infinite density, according to Sky and Telescope.

Secondly, well have to consider what counts as an object. If a group of particles is an object, what about a group of galaxies?

One thing is certain, the largest objects in space are much, much larger than Earth. They just appear small because they are so far away from us. Here are some of the largest known objects in the universe.

Jupiter is the largest planet in our solar system. Its a giant ball of gas that could fit all the other planets in the solar system inside it. According to NASA, more than 1,300 Earths would fit inside Jupiter.

But Jupiter is tiny compared to HAT-P-67 b, an exoplanet (orbiting a different star than our sun) that astronomers first observed in 2017. Astronomy.com reported that this newly discovered planet is 2.08 times the size of Jupiter, although it isnt as dense, weighing in at 60% less than Jupiters mass. Its the biggest, fluffiest planet we know of so far.

According to NASA, our sun is a million times the size of the Earth. But to put this in context, if our entire solar system was the size of a quarter, the sun would be a microscopic speck of dust on that quarter.

As big as a million times Earth sounds, Space.com points out that our sun is only an average-sized star. Scientists have discovered hypergiant stars such as UY Scuti, which could fit more than 1,700 of our suns in its radius.

Unlike stars, black holes dont take up space, but they are dense. The largest black hole in our neighborhood, Sagittarius A*, is 4 million times more massive than the sun, according to MIT Technology Review. Meanwhile, 700 million light-years away from Earth, a galaxy called Holm 15A contains the largest known black hole in the observable universe. Astronomers used data gathered by the Very Large Telescope in Chiles Atacama Desert to run simulations that map out this distant galaxy. Their models suggest that Holm 15A has a supermassive black hole that is at least 40 billion times more massive than the sun.

Although structures might not technically count as objects according to astrophysics terminology, from a logical perspective, a structure is the largest object in the universe.

Gravity can make galaxies clump together in space. Multiple galaxies form clusters, which can form superclusters, and even long lines of galaxies called walls, according to New Scientist. The largest known structure is the Baryon Oscillation Spectroscopic Survey Great Wall. This superstructure is made of 830 galaxies bound by gravity that swirl together in a wall that is a billion light-years across.

JWST could help astronomers discover even larger superstructures.

We will be able to collect images and spectra from hundreds or tens of thousands of galaxies. This will help astronomers identify groups of galaxies, says Arenberg.

Great societies have always pursued the unknown, explains Arenberg. He says, Increasing our scientific knowledge is not only good in and of itself, but its the basis of our economy and our security.

All these records for the largest objects in space could soon be broken as new, powerful telescopes reveal hidden spots in the universe.

Peering into deep space with JWST is the next step in a long legacy of exploration.

Arenberg says, Americans have always prided themselves on discovery and the frontier since the beginning of the country. And this is just carrying on that legacy from our ancestors. We should dare to do these amazing things and inspire ourselves and inspire the next generation.

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Could JWST Discover the Largest Object in the Universe? Now. Powered by - Now. Powered by Northrop Grumman.

Here’s How Exploding Stars Forged The Calcium in Your Teeth And Bones – ScienceAlert

Posted on August 10, 2020 by Danzig

Up to half the calcium in the Universe and that includes our bones and teeth is thought to come from exploding supernova stars, and researchers have now been able to get unprecedented insight at how these ultra-rare, calcium-rich supernovae reach the end of their lives.

The never-before-seen look at how these stellar explosions throw out so much calcium was carried out using deep space X-ray and infrared imaging, and fills in quite a few of the gaps in our scientific knowledge about the process.

Drawing together contributions from 67 authors across 15 countries, the resulting study suggests that the calcium-rich supernovae start off as compact stars that quickly lose mass at the end of their lives, giving off an outer layer of gas that exploding materials then collide with.

(Aaron M. Geller, Northwestern University)

"These events are so few in number that we have never known what produced calcium-rich supernovae," says astrophysicist Wynn Jacobson-Galan, from Northwestern University.

"By observing what this star did in its final month before it reached its critical, tumultuous end, we peered into a place previously unexplored, opening new avenues of study within transient science."

The supernova in question, SN 2019ehk, was first spotted by amateur astronomer Joel Shepherd in the Messier 100 (M100) spiral galaxy about 55 million light-years away from Earth. Very soon after the discovery was made, most of Earth's major telescopes were following it with transient events like this, speed is crucial.

What astronomers weren't expecting was the luminosity of the X-ray light that SN 2019ehk was giving off. Scientists quickly realised they were looking at a flood of high-energy X-rays flowing from the star and hitting the outer shell of gas, providing key clues to the materials that it was shedding and how much of the material there was.

The readings from the dying star helped scientists to work out what was happening: the reactions between the expelled materials and the outer gas ring were producing intensely hot temperatures and high pressures, leading to a calcium-producing nuclear reaction as the star tries to shed its heat and energy as quickly as possible.

"Most massive stars create small amounts of calcium during their lifetimes, but events like SN 2019ehk appear to be responsible for producing vast quantities of calcium and in the process of exploding disperse it through interstellar space within galaxies," says astronomer Rgis Cartier, from the National Optical-Infrared Astronomy Research Laboratory (NOIRLab) in the US.

"Ultimately this calcium makes its way into forming planetary systems, and into our bodies in the case of our Earth!"

It's because these stars are so important in calcium production that scientists have been so keen to take a look at them something that has proved difficult (even Hubble missed SN 2019ehk). The explosion at the centre of the new study is responsible for the most calcium ever seen emitted in a singular observed astrophysical event.

Being able to see the inner workings of this type of supernova will open up new areas of research and give us a better idea of how the calcium in our bones and teeth and everywhere else in the Universe came to be.

It's also a great example of the international scientific community working together to capture and record something of great importance. Just 10 hours after the initial bright burst was spotted in the sky by Joel Shepherd, some of the best telescopes we have were ready to record what happened next.

"Before this event, we had indirect information about what calcium-rich supernovae might or might not be," says astrophysicist Raffaella Margutti, from Northwestern University. "Now, we can confidently rule out several possibilities."

The research has been published in The Astrophysical Journal.

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Here's How Exploding Stars Forged The Calcium in Your Teeth And Bones - ScienceAlert

Astronomers find the largest impact crater in the solar system – FREE NEWS

Posted on August 10, 2020 by Danzig

The researchers said they had found the largest crater in the solar system. It was formed due to the impact of a huge asteroid, which was moving at a speed of 20 km/s.

Scientists have discovered the largest impact crater in the entire solar system. Astronomers found it on Jupiters largest moon, Ganymede. Most of the celestial body is covered with scars from impacts, so it was difficult for researchers to find this crater.

Astronomers have relied on observational data from many past NASA missions. They studied the massive Moon, which is larger than Mercury, the smallest planet. In particular, they concentrated on the grooves that appear on the surface of celestial bodies.

Researchers have learned that these grooves indicate powerful blows from all sides of Ganymede. But upon re-examining the structures, the scientists behind the new research suggested that the structure was an impact crater.

The researchers also carried out complex simulations on a very powerful computer at the National Astronomical Observatory of Japan. These data indicate that, most likely, a celestial body collided with a huge asteroid. Its diameter is about 15 km., It moved at a speed of 20 kilometers per second. The researchers suggest that particles of a celestial body can be found in the crater.

They want to confirm this theory scientists can do it when the European Space Agencys JUICE probe reaches the moon in 2029. Its launch is scheduled for 2022.

Stryker’s Neuroform Atlas Stent System granted an expanded indication – DOTmed HealthCare Business News

Posted on August 9, 2020 by Danzig

KALAMAZOO, Michigan, USA, Aug. 3, 2020 /PRNewswire/ -- Stryker announced today that it has received U.S. Food and Drug Administration (FDA) approval for an expanded indication of its Neuroform Atlas Stent System, becoming the first and only adjunctive stent approved for use in the posterior (back of the brain) circulation. Aneurysms in the posterior circulation rupture more frequently and are generally more difficult to treat. With the approval of the Neuroform Atlas adjunctive stent for the posterior circulation, long term treatment is more feasible.

Strykers Neuroform Atlas Stent System, which was granted an expanded indication, providing a new option for patients with aneurysms in the back of the brain.Already approved for use in the anterior circulation, the expanded indication was granted based on robust clinical trial evidence proving the safety and efficacy of the device. The combined patients from both the anterior and posterior cohorts totaled 298 patients, making it the largest study of its kind.

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An estimated 6.5 million people in the United States have unruptured brain aneurysms with an average rupture rate of 1 every 18 minutes. Ruptured brain aneurysms are fatal in roughly 50% of cases.1

"Complete occlusion, or complete blocking of blood flow, is the gold standard in determining long term aneurysm healing," said Dr Brian Jankowitz, Director, Cerebrovascular Surgery at the Cooper Neurological Institute in Camden, New Jersey. "With the additional challenges that come with treating posterior circulation aneurysms, we never would have anticipated reaching occlusion rates that rival those found in the anterior circulation. Now with Neuroform Atlas, those same high rates are achievable."

"The results from the Atlas Posterior PMA trial demonstrate that physicians can now address the more difficult posterior circulation aneurysms, offering hope for better outcomes in that patient population," said Mark Paul, president of Stryker's Neurovascular division. "This expanded indication of Neuroform Atlas, as the first and only adjunctive stent for use in the posterior circulation, reflects our ongoing commitment to advancing stroke care for patients with cerebrovascular disease."

About Neuroform Atlas Stent SystemStryker's Neuroform Atlas Stent System is a self-expanding nitinol stent used in conjunction with metal coils to pack weakened blood vessel sacs called aneurysms within the brain. The stent is positioned across the aneurysm neck to hold metal coils in place and occlude the aneurysm.

The Neuroform Atlas Stent System is indicated for use with neurovascular embolization coils in the anterior and posterior circulation of the neurovasculature for the endovascular treatment of patients 18 years of age with saccular wide-necked (neck width 4 mm or a dome-to-neck ratio of < 2) intracranial aneurysms arising from a parent vessel with a diameter of 2.0 mm and 4.5 mm.

About StrykerStryker is one of the world's leading medical technology companies and, together with its customers, is driven to make healthcare better. The company offers innovative products and services in Orthopaedics, Medical and Surgical, and Neurotechnology and Spine that help improve patient and hospital outcomes.

SOURCE Stryker

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Stryker's Neuroform Atlas Stent System granted an expanded indication - DOTmed HealthCare Business News

AI Experts Rank Deepfakes and 19 Other AI-Based Crimes By Danger Level – Unite.AI

Posted on August 9, 2020 by Danzig

Sarah Tatsis, is the Vice President of Advanced Technology Development Labs at BlackBerry.

BlackBerry already secures more than 500M endpoints including 150M cars on the road. BlackBerry is leading the way with a single platform for securing, managing and optimizing how intelligent endpoints are deployed in the enterprise, enabling customers to stay ahead of the technology curve that will reshape every industry.

BlackBerry launched the Advanced Technology Development Lab (Blackberry Labs) in late 2019. What was the strategic importance of creating an entire new business division for BlackBerry?

As an innovation accelerator, BlackBerry Advanced Technology Development Labs is an intentional investment of 120 team members into the future of the company. The rise of the Internet of Things (IoT) alongside a dynamic threat landscape has fostered a climate where organizations have to guard against new threats and breaches at all times. Weve handpicked the team to include experts in the embedded IoT space with diverse capabilities, including strong data science expertise, whose innovation funnel investigates, incubates and develops technologies to keep BlackBerry at the forefront of security innovation. ATD Labs works in strong partnership with the other BlackBerry business units, such as QNX, to further the companys commitment to safety, security and data privacy for its customers. BlackBerry Labs is also partnering with universities on active research and development. Were quite proud of these initiatives and think they will greatly benefit our future roadmap.

Last year, BlackBerry Labs successfully integrated Cylances machine learning technology into BlackBerrys product pipeline. BlackBerry Labs is currently focused on incubating and developing new concepts to accelerate the innovation roadmaps for our Spark and IoT business units. My role is primarily helping to drive the innovation funnel and partner with our business units to deliver valuable solutions for our customers.

What type of products are being developed at BlackBerry Labs?

BlackBerry Labs is facilitating applied research and using insights gained to innovate in the lines of business where were already developing market-leading solutions. For instance, were applying machine learning and data science to our existing areas of application, including automotive, mobile security, etc. This is possible in large part due to the influx of BlackBerry Cylance technology and expertise, which allows us to combine our ML pipeline and market knowledge to create solutions that are securing information and devices in a really comprehensive way. As new technologies and threats emerge, BlackBerry Labs will allow us to take a proactive approach to cybersecurity, not only updating our existing solutions, but evaluating how we can branch out and provide a more comprehensive, data-based, and diverse portfolio to secure the Internet of Things.

At CES, for instance, we unveiled an AI-based transportation solution geared towards OEMs and commercial fleets. This solution provides a holistic view of the security and health of a vehicle and provides control over that security for a manufacturer or fleet manager. It also uses machine learning based continuous authentication to identify a driver of a vehicle based on past driving behavior. Born in BlackBerry Labs, this concept marked the first time BlackBerry Cylances AI and ML technologies have been integrated with BlackBerry QNX solutions, which are currently powering upwards of 150 million vehicles on the road today.

For additional insights into how we envision AI and ML shaping the world of mobility in the years to come, I would encourage you to read Security Confidence Through Artificial Intelligence and Machine Learning for Smart Mobility from our recently released Road to Mobility guide. Also released at this years CES, The Road to Mobility: The 2020 Guide to Trends and Technology for Smart Cities and Transportation, is a comprehensive resource that government regulators, automotive executives and technology innovators can turn to for forward-thinking considerations for making safe and secure autonomous and connected vehicles a reality, delivering a transportation future that drivers, passengers and pedestrians alike can trust.

Featuring a mix of insights from both our own internal experts and recognized voices from across the transportation industry, the guide provides practical strategies for anyone whos interested in playing a vital role in shaping what the vehicles and infrastructure of our shared autonomous future will look like.

How important is artificial intelligence to the future of BlackBerry?

As both IoT and cybersecurity risk explodes, traditional methods of keeping organizations, things, and people safe and secure are becoming unscalable and ineffective. Preventing, detecting, and responding to potential threats needs to account for large amounts of data and intelligent automation of appropriate responses. AI and data science include tools that address these challenges and are therefore critical to the roadmap of BlackBerry. These tools allow BlackBerry to provide even greater value to our customers by reducing risk in efficient ways. BlackBerry leverages AI to deliver innovative solutions in the areas of cybersecurity, safety and data privacy as part of our strategy to connect, secure, and manage every endpoint in the Internet of Things.

For instance, BlackBerry trains our end point protection AI model against billions of files, good and bad, so that it learns to autonomously convict, or not convict files, pre-execution. The result of this massive, ongoing training effort is a proven track record of blocking payloads attempting to exploit zero-days for up to two years into the future.

The ability to protect organizations from zero-day payloads, well before they are developed and deployed, means that when other IT teams are scrambling to recover from the next major outbreak, it will be business as usual for BlackBerry customers. For example, WannaCry, which rendered millions of computers across the globe useless, was prevented by a BlackBerry (Cylance) machine learning model developed, trained, and deployed 24 months before the malware was first reported.

BlackBerrys QNX software is embedded in more than 150 million cars. Can you discuss what this software does?

Our software provides the safe and secure software foundation for many of the systems within the vehicle. We have a broad portfolio of functional safety-certified software including our QNX operating system, development tools and middleware for autonomous and connected vehicles. In the automotive segment, the companys software is deployed across the vehicle in systems such as ADAS and Safety Systems, Digital Cockpits, Digital Instrument Clusters, Infotainment, Telematics, Gateways, V2X and increasingly is being selected for chassis control and battery management systems that are advancing in complexity.

QNX software includes cybersecurity which protects autonomous vehicles from various cyber-attacks. Can you discuss some of the potential vulnerabilities that autonomous vehicles have to cyberattacks?

I think there is still a misconception out there that when you get into your car to drive home from work later today you might fall prey to a massive and coordinated vehicle cyberattack in which a rogue state threatens to hold you and your vehicle ransom unless you meet their demands. Hollywood movies are good at exaggerating what is possible, for example, instant and entire compromise of fleets that undermines all safety systems in cars. Whilst there are and always will be vulnerabilities within any system, to exploit a vulnerability and on scale with unprecedented reliability presents all kinds of hurdles that must be overcome, and would also require a significant investment of time, energy and resources. I think the general public needs to be reminded of this and the fact that hacking, if and when they do occur, are undesirable but not as movies would have you believe.

With a modern connected vehicle now containing well over 100 million lines of code and some of the most complex software ever deployed by automakers, the need for robust security has never been more important. As the software in a car grows so does the attack surface, which makes it more vulnerable to cyberattacks. Each poorly constructed piece of software represents a potential vulnerability that can be exploited by attackers.

BlackBerry is perfectly positioned to address these challenges as we have the solutions, the expertise and pedigree to be the safety certified and secure foundational software for autonomous and connected vehicles.

How does QNX software protect vehicles from these potential cyberattacks?

BlackBerry has a broad portfolio of products and services to protect vehicles against cybersecurity attacks. Our software has been deployed in critical embedded systems for over three decades and its worth pointing out, has also been certified to the highest level of automotive certification for functional safety with ISO 26262 ASIL D. As a company, we are investing significantly to broaden our safety and security product and services portfolio. Simply put, this is what our customers demand and rely on from us a safe, secure and reliable software platform.

As it pertains to security, we firmly believe that security cannot be an afterthought. For automakers and the entire automotive supply chain, security should be inherent in the entire product lifecycle. As part of our ongoing commitment to security, we published a 7-Pillar Cybersecurity Recommendation to share our insight and expertise on this topic. In addition to our safety-certified and secure operating system and hypervisor, BlackBerry provides a host of security products such as managed PKI, FIPS 140-2 certified toolkits, key inject tools, binary code static analysis tools, security credential management systems (SCMS), and secure Over-The-Air (OTA) software update technology. The worlds leading automakers, tier ones, and chip manufacturers continue to seek out BlackBerrys safety-certified and highly-secure software for their next-generation vehicles. Together with our customers we will help to ensure that the future of mobility is safe, secure and built on trust.

Can you elaborate on what is the QNX Hypervisor?

The QNX Hypervisor enables developers to partition, separate, and isolate safety-critical environments from non-safety critical environments reliably and securely; and to do so with the precision needed in an embedded production system. The QNX Hypervisor is also the worlds first ASIL D safety-certified commercial hypervisor.

What are some of the auto manufacturers using QNX software?

BlackBerrys pedigree in safety, security, and continued innovation has led to its QNX technology being embedded in more than 150 million vehicles on the road today. It is used by the top seven automotive Tier 1s, and by 45+ OEMs including Audi, BMW, Ford, GM, Honda, Hyundai, Jaguar Land Rover, KIA, Maserati, Mercedes-Benz, Porsche, Toyota, and Volkswagen.

Is there anything else that you would like to share about Blackberry Labs?

BlackBerry is committed to constant and consistent innovation its at the forefront of everything we do but we also have a unique legacy of being one of the pioneers of mobile based security, and further the idea of a truly secure devices, endpoints, and communications. The lessons we learned over the past decades, as well as the technology we developed, will be instrumental for helping us to create a new standard for privacy and security as the tsunami of connected devices enter the IoT. Much of what BlackBerry has done in the past is re-emerging in front of us, and were one of the only companies prioritizing a fundamental belief that all users deserve solutions that allow them to own their data and secure communications its baked into our entire development pipeline and is one of our key differentiators. BlackBerry Labs is combining this history with new technology innovations to address the rapidly expanding landscape of mobile and connected endpoints, including vehicles, and increased security threats. Through our strong partnerships with BlackBerry business units we are creating new features, products, and services to deliver value to both new and existing customers.

Thank you for the wonderful interview and for your extensive responses. Its clear to me that Blackberry is at the forefront of technology and its best days are still ahead. Readers who wish to learn more should visit the Blackberry website.

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AI Experts Rank Deepfakes and 19 Other AI-Based Crimes By Danger Level - Unite.AI

Google’s AI thinks women wearing masks have mouths covered with duct tape – ZDNet

Posted on August 9, 2020 by Danzig

AI may not know what's going on here.

Artificial intelligence is a work in progress.

Or, as some critics might say , a work in abject regress that will wreck humanity's remaining faith in itself.

Even some tech companies seem a touch unsure about their own AI systems. Why, not too long ago IBM announced it was withdrawing from the facial recognition business altogether.

We'll come back to IBM in a moment. You see, I've just been handed the results of a study that leaves a lot to consider.

Performed by marketing company Wunderman Thompson's Data group, the study examined whether well-known visual AI systems look at men wearing PPE masks in the same way as they do women.

The researchers took 256 images of each gender -- of varying qualities and taken in varying locations -- and then used generic models trained by some of the larger names in tech: Google Cloud Vision, Microsoft Azure's Cognitive Services Computer Vision, and IBM's Watson Visual Recognition.

The results were a little chilling.

Though none of the systems were particularly stellar at spotting masks, they were twice as likely to identify male mask-wearers as female mask-wearers.

So what did they think the women were wearing? Well, Google's AI identified 28% of the images as being women with their mouths covered by duct tape. In 8% of cases, the AI thought these were women with facial hair. Quite a lot of facial hair, it seems.

IBM's Watson took things a little further. In 23% of cases, it saw a woman wearing a gag. In another 23% of cases, it was sure this was a woman wearing a restraint or chains.

Microsoft's Computer Vision may need a little more accurate coding too. It suggested that 40% of the women were wearing a fashion accessory, while 14% were wearing lipstick.

Such results may make many wonder where these AIs get their ideas from. A simple answer might be "men."

The researchers, however, suggested the machines were looking for inspiration in "a darker corner of the web where women are perceived as victims of violence or silenced."

It's hard not to imagine that's true and it's something that potentially has awful consequences as we disappear ever more readily into AI's odiferous armpit.

The researchers say they're not trying to demonize AI. (AI is quite good at doing that for itself.)

Instead, as Wunderman Thompson's director of data science Ilinca Barsan put it: "If we want our machines to do work that accurately and responsibly reflects society, we need to help them understand the social dynamics that we live in to stop them from reinforcing existing inequalities through automation and put them to work for good instead."

See also:2084: What happens when artificial intelligence meets Big Brother |No matter how sophisticated, AI systems still need human oversight |AI's big problem: Lazy humans just trust the algorithms too much |What is AI? Everything you need to know about Artificial Intelligence

Still, when I asked the researchers what they thought about IBM withdrawing from the facial recognition business, they replied: "Our research focused on visual label recognition rather than facial recognition, but if it's this easy for an (admittedly general) AI model to confuse someone wearing a mask with someone being gagged or restrained, then withdrawing from a business that is so prone to misuse, privacy violation, and training bias seems to be the right (and smart) thing to do for IBM."

Humanity hasn't done too good a job of helping machines understand vital elements. Humanity itself, for example. Partly because machines just don't have that instinct. And partly because humans struggle to understand themselves.

How often have you been driven toward head-butting walls during even the briefest encounter with customer service AI?

I fear, though, that too many AI systems have already been dragged into a painfully biased view of the world, one from which they may never entirely return.

How much more darkness does that risk propagating?

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Google's AI thinks women wearing masks have mouths covered with duct tape - ZDNet

How the Army Is Really Using AI – AI Daily

Posted on August 9, 2020 by Danzig

It has always been controversial for the army to implement artificial Intelligence within their task force (particularly with the use of drones) because ethics of it, however artificial intelligence is being implemented within the army in other less controversial ways forget the movie Terminator, artificial intelligence is performing many tedious and manual tasks that would use a lot of time and resources and providing assistance to recognition and conversation systems to predictive analytics pattern matching and autonomous systems.

The army leverage artificial intelligence by (for a more detail example) predicting when vehicle parts may need to be replaced which saves a lot of time, money and increase operational safety. Some programs that leverage data using machine learning include Project Maven that retrieves data from drones and aids to automate some of the work that analysts do again saving time and money. As you can see artificial intelligence is being used to improve the armys efficiency.

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How the Army Is Really Using AI - AI Daily

Why human-like is a low bar for most AI projects – The Next Web

Posted on August 9, 2020 by Danzig

Show me a human-like machine and Ill show you a faulty piece of tech. The AI market is expected to eclipse $300 billion by 2025. And the vast majority of the companies trying to cash in on that bonanza are marketing some form of human-like AI. Maybe its time to reconsider that approach.

The big idea is that human-like AI is an upgrade. Computers compute, but AI can learn. Unfortunately, humans arent very good at the kinds of tasks a computer makes sense for and AI isnt very good at the kinds of tasks that humans are. Thats why researchers are moving away from development paradigms that focus on imitating human cognition.

A pair of NYU researchers recently took a deep dive into how humans and AI process words and word meaning. Through the study of psychological semantics, the duo hoped to explain the shortcomings held by machine learning systems in the natural language processing (NLP) domain. According to a study they published to arXiv:

Many AI researchers do not dwell on whether their models are human-like. If someone could develop a highly accurate machine translation system, few would complain that it doesnt do things the way human translators do.

In the field of translation, humans have various techniques for keeping multiple languages in their heads and fluidly interfacing between them. Machines, on the other hand, dont need to understand what a word means in order assign the appropriate translation to it.

This gets tricky when you get closer to human-level accuracy. Translating one, two, and three into Spanish is relatively simple. The machine learns that they are exactly equivalent to uno, dos, and tres, and is likely to get those right 100 percent of the time. But when you add complex concepts, words with more than one meaning, and slang or colloquial speech things can get complex.

We start getting into AIs uncanny valley when developers try to create translation algorithms that can handle anything and everything. Much like taking a few Spanish classes wont teach a human all the slang they might encounter in Mexico City, AI struggles to keep up with an ever-changing human lexicon.

NLP simply isnt capable of human-like cognition yet and making it exhibit human-like behavior would be ludicrous imagine if Google Translate balked at a request because it found the word moist distasteful, for example.

This line of thinking isnt just reserved for NLP. Making AI appear more human-like is merely a design decision for most machine learning projects. As the NYU researchers put it in their study:

One way to think about such progress is merely in terms of engineering: There is a job to be done, and if the system does it well enough, it is successful. Engineering is important, and it can result in better and faster performance and relieve humans of dull labor such as keying in answers or making airline itineraries or buying socks.

From a pure engineering point of view, most human jobs can be broken down into individual tasks that would be better suited for automation than AI, and in cases where neural networks would be necessary directing traffic in a shipping port, for example its hard to imagine a use-case where a general AI would outperform several narrow, task-specific systems.

Consider self-driving cars. It makes more sense to build a vehicle made up of several systems that work together instead of designing a humanoid robot that can walk up to, unlock, enter, start, and drive a traditional automobile.

Most of the time, when developers claim theyve created a human-like AI, what they mean is that theyve automated a task that humans are often employed for. Facial recognition software, for example, can replace a human gate guard but it cannot tell you how good the pizza is at the local restaurant down the road.

That means the bar is pretty low for AI when it comes to being human-like. Alexa and Siri do a fairly good human imitation. They have names and voices and have been programmed to seem helpful, funny, friendly, and polite.

But theres no function a smart speaker performs than couldnt be better handled by a button. If you had infinite space and an infinite attention span, you could use buttons for anything and everything a smart speaker could do. One might say Play Mariah Carey, while another says Tell me a joke. The point is, Alexas about as human-like as a giant remote control.

AI isnt like humans. We may be decades or more away from a general AI that can intuit and function at human-level in any domain. Robot butlers are a long way off. For now, the best AI developers can do is imitate human effort, and thats seldom as useful as simplifying a process to something easily automated.

Published August 6, 2020 22:35 UTC

Why human-like is a low bar for most AI projects - The Next Web

Viewpoint: Using AI to Identify Work Comp Fraud Related to COVID-19 – Claims Journal

Posted on August 9, 2020 by Danzig

As employees return to work after the COVID-19 crisis has subsided, insurers and employers will likely experience a surge in claims related to the virus. Analysts expect coverages for workers compensation, employer liability, and business interruption to be especially hard hit.[i] The California Workers Compensation Insurance Rating Bureau estimates annual losses in its state will be $1.2 billion.[ii] Extrapolating nationally, losses would be approximately $5 billion.

Most states have enacted legislation or executive orders to designate critical occupations in the wake of the virus. For workers compensation, certain front-line occupations (such as health care and first responders) will be presumptively covered in most states. According to data scientists at CLARA analytics, health care workers experienced a fourfold increase in virus-related claims since February 2020. This presumption may extend beyond the front line to include all employees in all occupations working outside the home regardless of direct risk.[iii]

The new COVID-19 laws and executive orders are sometimes ambiguous and could lead to disputes. Many questions will arise: Where and when did exposure to the virus occur? Did multiple employees at the same location suffer from the virus? Job classifications will be important: Do medical intake workers have the same level of exposure as nurses employed at the same hospital?

Also, medical treatment may raise additional questions: Was the COVID-19 test administered in a timely fashion? Are these tests carried out at a nationally recognized testing lab (NRTL)? Do the tests generate a high rate of false negatives?

In addition, given the current massive level of unemployment, we may see a surge in post-termination cumulative trauma claims. If a terminated worker tests positive, attorneys may allege he or she was exposed to the virus at his or her prior workplace (even if a test was not conducted during the period of employment). Moreover, if the worker suffers from any other medical condition, a COVID-19 diagnosis may be added as an aggravating factor.

Beyond workers compensation, health insurers forecast increases in fraud.[iv] Medicare has already experienced a rise in provider fraud due to COVID-19.[v]

Workers compensation claims fraud is supplier driven. A small segment of attorneys and medical providers exploit the system to file fraudulent claims. The pandemic offers these fraudsters an opportunity to revive practices that have been proven successful in the past. For example, the massive layoffs caused by dislocations resulting from COVID -19 may provoke some fraudsters to retain cappers. These intermediaries recruit laid-off employees in order to file workers compensation claims. The employees will be sent to networks which may include chiropractors, pharmacists, diagnostic facilities, medical equipment suppliers, and interpreters. In the wake of COVID- 19, pulmonologists, testing labs, and respiratory therapists may be recruited.

Attorney Data

Attorneys are the claims quarterbacks handing off workers to an entire array of vendors starting with medical providers. Attorneys are paid at settlement and, unlike medical providers, are not recorded in bill review systems. As a result, attorney data has been difficult to isolate. However, new AI tools can reliably identify attorney behavior over the course of many claims.

To detect attorney involvement in fraudulent claims, analysts start with a list of medical providers who have been publicly identified as fraudulent. They then work backward via longitudinal analysis to identify attorneys who originally refer to these providers. Attorney data is gleaned from claims notes and utilization review appeals. Accounts payable systems reveal final settlement information. This information can be used to identify attorneys and their firms.

Medical Provider Data

Using a multiyear, multipayer database, data scientists can identify a reliable picture of medical provider practice patterns. By tapping into bill review information, analysts can detect billing patterns, diagnoses, procedure codes, drug prescribing, and referrals. Excessive or inaccurate billing are common indicators of fraud. Given that many bills are disallowed, these providers usually display large gaps between billed and paid amounts.

Fraud Network Data

These complex networks consisting of multiple coordinated vendors are key drivers of fraud. AI can detect usually hidden connections between attorneys, medical providers, and other vendors, enabling data scientists to track their progression over time. These analysts can employ clustering techniques to graphically show cross-referrals. The analysis starts with the first provider as the node and includes other central and peripheral providers.

Putting Data into Action

To combat fraudulent COVID-19 claims, payers can now employ artificial intelligence tools to mine a multiyear, cross-payer claims database. Data scientists can track both attorneys and medical providers and the progression of fraud networks. CLARA analytics has created claims alerts to notify examiners when a claim deviates from expected patterns. Fraudsters are sometimes a major source of such deviations. Using these alerts, payers can intervene early to curb cost escalation or to shut down the claim entirely.

Tapping into aggregate attorney, medical provider, and network data will improve the efficiency and focus of specialized investigative units. At present, most of these units rely on one-off referrals from their own companies. By using a multipayer, multiyear database, payers can harvest a list of suspicious attorneys and providers. Claims examiners can intervene early to forestall a costly chain of referrals. Depending on the rules of each state, payers may be able to redirect the claims to their own preferred provider networks.

In sum, COVID-19 will account for a surge in workers compensation claims. The billions of dollars in additional costs may exceed those of the recession of 2008. In order to effectively handle the valid claims, payers must quickly and accurately eliminate the few fraudulent ones. Artificial intelligence tools can be deployed to identify fraud. Payers can then focus attention on helping patients who are the real victims of COVID-19.

[i] Gabriel Olano, Figuring out the new world post-coronavirus, Corporate Risk and Insurance, May 21, 2020.

[ii] WCIRB Wire, WCIRB Evaluates Governors COVID-19 Executive Order Impact on Workers Compensation Costs, May 22, 2020.

[iii] Alex Swedlow, Rena David and Mark Webb, Integrating COVID-19 Presumptions into the California Workers Compensation System, CWCI, May 2020.

[iv] Michael Adelberg and Melissa Garrido, The COVID-19 Epidemic As A Catalyst For Health Care Fraud, Health Affairs, May 7, 2020.

[v] Federal News Network, Combating health care fraud as CMS loosens rules to respond to coronavirus, May 18, 2020.

About Gregory Johnson Johnson is a health care consultant with 30 years experience in health care and insurance. He was previously a partner at Ernst & Young and PricewaterhouseCoopers, as well as director of medical analytics at the California Workers' Compensation Insurance Rating Bureau. He holds a Bachelor of Arts from University of Oregon and a Ph.D. from Harvard University.

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Viewpoint: Using AI to Identify Work Comp Fraud Related to COVID-19 - Claims Journal

Cloak your photos with this AI privacy tool to fool facial recognition – The Verge

Posted on August 9, 2020 by Danzig

Ubiquitous facial recognition is a serious threat to privacy. The idea that the photos we share are being collected by companies to train algorithms that are sold commercially is worrying. Anyone can buy these tools, snap a photo of a stranger, and find out who they are in seconds. But researchers have come up with a clever way to help combat this problem.

The solution is a tool named Fawkes, and was created by scientists at the University of Chicagos Sand Lab. Named after the Guy Fawkes masks donned by revolutionaries in the V for Vendetta comic book and film, Fawkes uses artificial intelligence to subtly and almost imperceptibly alter your photos in order to trick facial recognition systems.

The way the software works is a little complex. Running your photos through Fawkes doesnt make you invisible to facial recognition exactly. Instead, the software makes subtle changes to your photos so that any algorithm scanning those images in future sees you as a different person altogether. Essentially, running Fawkes on your photos is like adding an invisible mask to your selfies.

Scientists call this process cloaking and its intended to corrupt the resource facial recognition systems need to function: databases of faces scraped from social media. Facial recognition firm Clearview AI, for example, claims to have collected some three billion images of faces from sites like Facebook, YouTube, and Venmo, which it uses to identify strangers. But if the photos you share online have been run through Fawkes, say the researchers, then the face the algorithms know wont actually be your own.

According to the team from the University of Chicago, Fawkes is 100 percent successful against state-of-the-art facial recognition services from Microsoft (Azure Face), Amazon (Rekognition), and Face++ by Chinese tech giant Megvii.

What we are doing is using the cloaked photo in essence like a Trojan Horse, to corrupt unauthorized models to learn the wrong thing about what makes you look like you and not someone else, Ben Zhao, a professor of computer science at the University of Chicago who helped create the Fawkes software, told The Verge. Once the corruption happens, you are continuously protected no matter where you go or are seen.

The group behind the work Shawn Shan, Emily Wenger, Jiayun Zhang, Huiying Li, Haitao Zheng, and Ben Y. Zhao published a paper on the algorithm earlier this year. But late last month they also released Fawkes as free software for Windows and Macs that anyone can download and use. To date they say its been downloaded more than 100,000 times.

In our own tests we found that Fawkes is sparse in its design but easy enough to apply. It takes a couple of minutes to process each image, and the changes it makes are mostly imperceptible. Earlier this week, The New York Times published a story on Fawkes in which it noted that the cloaking effect was quite obvious, often making gendered changes to images like giving women mustaches. But the Fawkes team says the updated algorithm is much more subtle, and The Verges own tests agree with this.

But is Fawkes a silver bullet for privacy? Its doubtful. For a start, theres the problem of adoption. If you read this article and decide to use Fawkes to cloak any photos you upload to social media in future, youll certainly be in the minority. Facial recognition is worrying because its a society-wide trend and so the solution needs to be society-wide, too. If only the tech-savvy shield their selfies, it just creates inequality and discrimination.

Secondly, many firms that sell facial recognition algorithms created their databases of faces a long time ago, and you cant retroactively take that information back. The CEO of Clearview, Hoan Ton-That, told the Times as much. There are billions of unmodified photos on the internet, all on different domain names, said Ton-That. In practice, its almost certainly too late to perfect a technology like Fawkes and deploy it at scale.

Naturally, though, the team behind Fawkes disagree with this assessment. They note that although companies like Clearview claim to have billions of photos, that doesnt mean much when you consider theyre supposed to identify hundreds of millions of users. Chances are, for many people, Clearview only has a very small number of publicly accessible photos, says Zhao. And if people release more cloaked photos in the future, he says, sooner or later the amount of cloaked images will outnumber the uncloaked ones.

On the adoption front, however, the Fawkes team admits that for their software to make a real difference it has to be released more widely. They have no plans to make a web or mobile app due to security concerns, but are hopeful that companies like Facebook might integrate similar tech into their own platform in future.

Integrating this tech would be in these companies interest, says Zhao. After all, firms like Facebook dont want people to stop sharing photos, and these companies would still be able to collect the data they need from images (for features like photo tagging) before cloaking them on the public web. And while integrating this tech now might only have a small effect for current users, it could help convince future, privacy-conscious generations to sign up to these platforms.

Adoption by larger platforms, e.g. Facebook or others, could in time have a crippling effect on Clearview by basically making [their technology] so ineffective that it will no longer be useful or financially viable as a service, says Zhao. Clearview.ai going out of business because its no longer relevant or accurate is something that we would be satisfied [with] as an outcome of our work.

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Cloak your photos with this AI privacy tool to fool facial recognition - The Verge

Global AI in Manufacturing Market 2020-2026: COVID-19’s Impact on the Industry and Future Projections – PRNewswire

Posted on August 9, 2020 by Danzig

DUBLIN, Aug. 7, 2020 /PRNewswire/ -- The "Artificial Intelligence in Manufacturing Market by Offering (Hardware, Software, and Services), Technology (Machine Learning, Computer Vision, Context-Aware Computing, and NLP), Application, End-user Industry and Region - Global Forecast to 2026" report has been added to ResearchAndMarkets.com's offering.

The AI in the manufacturing market is expected to be valued at USD 1.1 billion in 2020 and is likely to reach USD 16.7 billion by 2026; it is expected to grow at a CAGR of 57.2% during the forecast period.

The major drivers for the market are the increasing number of large and complex datasets (often known as big data), evolving Industrial IoT and automation, improving computing power, and increasing venture capital investments. The major restraint for the market is the reluctance among manufacturers to adopt AI-based technologies. The critical challenges facing the AI in the manufacturing market include limited skilled workforce, concerns regarding data privacy, and significant financial and operational impact of the COVID-19 outbreak on manufacturing.

The machine learning technology is expected to account for the largest size of the AI in manufacturing market during the forecast period.

Machine learning's ability to collect and handle big data and its applications in real-time speech translation, robotics, and facial analysis is fuelling its growth in the manufacturing market. AI constitutes various technologies that play a vital role in developing its ecosystem. As AI enables machines to perform activities similar to those performed by human beings, enormous market opportunities have opened.

The predictive maintenance and machinery inspection application of the AI in manufacturing market is projected to hold the largest share during the forecast period.

The predictive maintenance and machinery inspection application held the largest share of the AI in the manufacturing market in 2019. Extensive use of computer vision cameras in machinery inspection, adoption of the Industrial Internet of Things (IIoT), and use of big data in the manufacturing industry are the factors driving the growth of the AI in the manufacturing market for predictive maintenance and machinery inspection application. The increasing demand for reducing the operational costs and machine downtime is also supplementing the growth of predictive maintenance and machinery inspection application in industries.

The automobile industry held the largest size of the AI in manufacturing market in 2019.

The extensive use of computer vision cameras in machinery inspection and adoption industrial IoT are the factors driving the growth of the AI in the manufacturing market for the automobile industry. The application of AI to boost employee productivity, improve quality control, and gain better control over business support functions is supporting the growth of AI in the automobile industry.

Impact of COVID-19 on the AI in the manufacturing market

The market is likely to witness a slight plunge in terms of year-on-year growth in 2020. This is largely attributed to the affected supply chains and limited adoption of AI in manufacturing in 2020 due to the lockdowns and shifting priorities of different industries. The ongoing COVID-19 pandemic has caused disruptions in economies. It is likely to cause supply chain mayhem and eventually force companies and entire industries to rethink and adapt to the global supply chain model.

Many manufacturing companies have halted their production, which has collaterally damaged the supply chain and the industry. This disruption has caused a delay in the adoption of AI-based software and hardware products in the manufacturing sector. The industries have started to restructure their business model for 2020, and many SMEs and large manufacturing plants have halted/postponed any new technology upgrade in their factories in order to recover from the losses caused by the lockdown and economic slowdown.

Research Coverage

The AI in the manufacturing market has been segmented based on offering, technology, application, industry and region. It also provides a detailed view of the market across 4 main regions: North America, Europe, APAC, and RoW.

Key Topics Covered1 Introduction

2 Research Methodology

3 Executive Summary3.1 COVID-19 Impact Analysis: AI in Manufacturing Market3.1.1 Pre-COVID-19 Scenario3.1.2 Post-COVID-19 Scenario

4 Premium Insights4.1 Attractive Opportunities in AI in Manufacturing Market4.2 AI in Manufacturing Market, by Offering4.3 AI in Manufacturing Market, by Technology4.4 APAC: AI in Manufacturing Market, by Industry and Country4.5 AI in Manufacturing Market, by Country

5 Market Overview5.1 Introduction5.2 Market Dynamics5.2.1 Drivers5.2.1.1 Increasingly Large and Complex Dataset5.2.1.2 Evolving Industrial IoT and Automation5.2.1.3 Improving Computing Power5.2.1.4 Increasing Venture Capital Investments5.2.2 Restraints5.2.2.1 Reluctance Among Manufacturers to Adopt AI-Based Technologies5.2.3 Opportunities5.2.3.1 Growth in Operational Efficiency of Manufacturing Plants5.2.3.2 Application of AI for Intelligent Business Process5.2.3.3 Adoption of Automation Technologies to Curb Effects of COVID-195.2.4 Challenges5.2.4.1 Limited Skilled Workforce5.2.4.2 Concerns Regarding Data Privacy5.2.4.3 Significant Financial and Operational Impact of COVID-19 Outbreak on Manufacturing5.3 Value Chain Analysis5.4 Case Studies5.4.1 Siemens Gamesa Uses Fujitsu's AI Solution to Accelerate Inspection of Turbine Blades5.4.2 Volvo Uses Machine Learning-Driven Data Analytics for Predicting Breakdown and Failures5.4.3 Rolls-Royce Using Microsoft Cortana Intelligence for Predictive Maintenance5.4.4 Paper Packaging Firm Used Sight Machine's Enterprise Manufacturing Analytics to Improve Production5.5 Adjacent and Related Markets

6 Artificial Intelligence in Manufacturing Market, by Offering6.1 Introduction6.2 Hardware6.3 Software6.4 Services6.5 Impact of COVID-19 on Various Offering of AI Technology for Manufacturing

7 Artificial Intelligence in Manufacturing Market, by Technology7.1 Introduction7.2 Machine Learning7.3 Natural Language Processing7.4 Context-Aware Computing7.5 Computer Vision7.6 Impact of COVID-19 on Various Technologies of AI in Manufacturing

8 Artificial Intelligence in Manufacturing Market, by Application8.1 Introduction8.2 Predictive Maintenance and Machinery Inspection8.3 Material Movement8.4 Production Planning8.5 Field Services8.6 Quality Control8.7 Cybersecurity8.8 Industrial Robots8.9 Reclamation

9 Artificial Intelligence in Manufacturing Market, by Industry9.1 Introduction9.2 Automobile9.3 Energy and Power9.4 Pharmaceuticals9.5 Heavy Metals and Machine Manufacturing9.6 Semiconductors and Electronics9.7 Food & Beverages9.8 Others

10 Artificial Intelligence in Manufacturing Market, by Region10.1 Introduction10.2 North America10.3 Europe10.4 APAC10.5 RoW

11 Competitive Landscape11.1 Overview11.2 Ranking of Players, 201911.3 Competitive Leadership Mapping11.3.1 Visionary Leaders11.3.2 Dynamic Differentiators11.3.3 Innovators11.3.4 Emerging Companies11.4 Competitive Scenario11.4.1 Product Launches and Developments11.4.2 Collaborations, Partnerships, and Agreements11.4.3 Acquisitions & Joint Ventures

12 Company Profiles12.1 Key Players12.1.1 Nvidia12.1.2 Intel12.1.3 IBM12.1.4 Siemens12.1.5 General Electric (GE) Company12.1.6 Google12.1.7 Microsoft12.1.8 Micron Technology12.1.9 Amazon Web Services (AWS)12.1.10 Sight Machine12.2 Other Companies12.2.1 Progress Software Corporation (DataRPM)12.2.2 AIbrain12.2.3 General Vision12.2.4 Rockwell Automation12.2.5 Cisco Systems12.2.6 Mitsubishi Electric12.2.7 Oracle12.2.8 SAP12.2.9 Vicarious12.2.10 Ubtech Robotics12.2.11 Aquant12.2.12 Bright Machines12.2.13 Rethink Robotics GmbH12.2.14 Sparkcognition12.2.15 Flutura

For more information about this report visit https://www.researchandmarkets.com/r/erpy1o

Research and Markets also offers Custom Research services providing focused, comprehensive and tailored research.

Media Contact:

Research and Markets Laura Wood, Senior Manager [emailprotected]

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Global AI in Manufacturing Market 2020-2026: COVID-19's Impact on the Industry and Future Projections - PRNewswire

Introducing The AI & Machine Learning Imperative – MIT Sloan

Posted on August 9, 2020 by Danzig

Topics The AI & Machine Learning Imperative

The AI & Machine Learning Imperative offers new insights from leading academics and practitioners in data science and artificial intelligence. The Executive Guide, published as a series over three weeks, explores how managers and companies can overcome challenges and identify opportunities by assembling the right talent, stepping up their own leadership, and reshaping organizational strategy.

Leading organizations recognize the potential for artificial intelligence and machine learning to transform work and society. The technologies offer companies strategic new opportunities and integrate into a range of business processes customer service, operations, prediction, and decision-making in scalable, adaptable ways.

As with other major waves of technology, AI requires organizations and managers to shed old ways of thinking and grow with new skills and capabilities. The AI & Machine Learning Imperative, an Executive Guide from MIT SMR, offers new insights from leading academics and practitioners in data science and AI. The guide explores how managers and companies can overcome challenges and identify opportunities across three key pillars: talent, leadership, and organizational strategy.

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The series launches Aug. 3, and summaries of the upcoming articles are included below. Sign up to be reminded when new articles launch in the series, and in the meantime, explore our recent library of AI and machine learning articles.

In order to achieve the ultimate strategic goals of AI investment, organizations must broaden their sights beyond creating augmented intelligence tools for limited tasks. To prepare for the next phase of artificial intelligence, leaders must prioritize assembling the right talent pipeline and technology infrastructure.

Recent technical advances in AI and machine learning offer genuine productivity returns to organizations. Nevertheless, finding and enabling talented individuals to succeed in engineering these kinds of systems can be a daunting challenge. Leading a successful AI-enabled workforce requires key hiring, training, and risk management considerations.

AI is no regular technology, so AI strategy needs to be approached differently than regular technology strategy. A purposeful approach is built on three foundations: a robust and reliable technology infrastructure, a specific focus on new business models, and a thoughtful approach to ethics. Available Aug. 10.

CFOs who take ownership of AI technology position themselves to lead an organization of the future. While AI is likely to impact business practices dramatically in the future across the C-suite, its already having an impact today and the time for CFOs to step up to AI leadership is now. Available Aug. 12.

To remain relevant and resilient, companies and leaders must strive to build business models in a way that ensures three key components are working together: AI that enables and powers a centralized data lake of enterprise data, a marketplace of sellers and partners that make individualized offers based on the intelligence of the data collected and powered by AI, and a SaaS platform that is essential for users. Available Aug. 17.

Acquiring the right AI technology and producing results, while critical, arent enough. To gain value from AI, organizations need to focus on managing the gaps in skills and processes that impact people and teams within the organization. Available Aug. 19.

Ally MacDonald (@allymacdonald) is a senior editor at MIT Sloan Management Review.

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Introducing The AI & Machine Learning Imperative - MIT Sloan

NIH launches imaging AI collaboration for COVID-19 and beyond – FierceBiotech

Posted on August 9, 2020 by Danzig

The National Institutes of Health is turning to artificial intelligence and imaging scans to not only help detect cases of COVID-19 earlier, but to potentially personalize treatments for the spreading disease.

In lung CT scans, the novel coronavirus leaves telltale signs that distinguish it from other respiratory diseasessmall white spots and a slightly obscuring haze, described by radiologists as ground glass, that indicates fluid build-up and damage to the tissue. Abnormalities are found in the heart scans and ultrasounds of many COVID-19 patients as well.

A collaboration funded by the NIHs National Institute of Biomedical Imaging and Bioengineering aims to develop new diagnostics and machine learning algorithms to quickly assess the severity of an infectionand predict a persons responses to different treatments.

This program is particularly exciting because it will give us new ways to rapidly turn scientific findings into practical imaging tools that benefit COVID-19 patients, NIBIB Director Bruce Tromberg said. It unites leaders in medical imaging and artificial intelligence from academia, professional societies, industry and government to take on this important challenge.

RELATED: Coronavirus tests the value of artificial intelligence in medicine

The resulting Medical Imaging and Data Resource Center will operate a large, open-source repository that will gather COVID-19 chest images from tens of thousands of patients, allowing researchers to evaluate both lung and cardiac tissue data, ask critical research questionsand develop predictive COVID-19 imaging signatures that can be delivered to healthcare providers, said Guoying Liu, director of the NIBIBs MRI program.

The database will be hosted at the University of Chicago, and co-led by a trio of medical imaging societies: the American College of Radiology, the Radiological Society of North America and the American Association of Physicists in Medicine.

In addition, the center will support five infrastructure development projects and oversee 12 research projects, covering about 20 university labsall with an initial focus on COVID-19, but with plans to expand its imaging data services and AI development to other diseases in the future.

RELATED: To screen COVID-19 patients for heart problems, FDA clears several ultrasound, AI devices

COVID-19 is our immediate target, but the MIDRC will ultimately enable the medical and scientific communities to mobilize images and data for work against other existing diseases and future healthcare threats, said the University of Washingtons Paul Kinahan, chair of the AAPMs research committee.

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NIH launches imaging AI collaboration for COVID-19 and beyond - FierceBiotech

Announcing Sight Tech Global, an event on the future of AI and accessibility for people who are blind or visually impaired – TechCrunch

Posted on August 9, 2020 by Danzig

Few challenges have excited technologists more than building tools to help people who are blind or visually impaired. It was Silicon Valley legend Ray Kurzweil, for example, who in 1976 launched the first commercially available text-to-speech reading device. He unveiled the $50,000 Kurzweil Reading Machine, a boxy device that covered a tabletop, at a press conference hosted by the National Federation of the Blind.

The early work of Kurzweil and many others has rippled across the commerce and technology world in stunning ways. Todays equivalent of Kurzweils machine is Microsofts Seeing AI app, which uses AI-based image recognition to see and read in ways that Kurzweil could only have dreamed of. And its free to anyone with a mobile phone.

Remarkable leaps forward like that are the foundation for Sight Tech Global, a new, virtual event slated for December 2-3, that will bring together many of the worlds top technology and accessibility experts to discuss how rapid advances in AI and related technologies will shape assistive technology and accessibility in the years ahead.

The technologies behind Microsofts Seeing AI are on the same evolutionary tree as the ones that enable cars to be autonomous and robots to interact safely with humans. Much of our most advanced technology today stems from that early, challenging mission that top Silicon Valley engineers embraced to teach machines to see on behalf of humans.

From the standpoint of people who experience vision loss, the technology available today is astonishing, far beyond what anyone anticipated even 10 years ago. Purpose-built products like Seeing AI and computer screen readers like JAWS are remarkable tools. At the same time, consumer products, including mobile phones, mapping apps and smart voice assistants, are game changers for everyone, those with sight loss not the least. And yet, that tech bonanza has not come close to breaking down the barriers in the lives of people who still mostly navigate with canes or dogs or sighted assistance, depend on haphazard compliance with accessibility standards to use websites and can feel as isolated as ever in a room full of people.

In other words, we live in a world where a computer can drive a car at 70 MPH without human assistance but there is not yet any comparable device to help a blind person walk down a sidewalk at 3 MPH. A social media site can identify billions of people in an instant but a blind person cant readily identify the person standing in front of them. Todays powerful technologies, many of them grounded in AI, have yet to be milled into next-generation tools that are truly useful, happily embraced and widely affordable. The work is underway at big tech companies like Apple and Microsoft, at startups, and in university labs, but no one would dispute that the work is as slow as it is difficult. People who are blind or visually impaired live in a world where, as the science fiction author William Gibson once remarked, The future is already here its just not very evenly distributed.

That state of affairs is the inspiration for Sight Tech Global. The event will convene the top technologists, human-computer interaction specialists, product designers, researchers, entrepreneurs and advocates to discuss the future of assistive technology as well as accessibility in general. Many of those experts and technologists are blind or visually impaired, and the event programming will stand firmly on the ground that no discussion or new product development is meaningful without the direct involvement of that community. Silicon Valley has great technologies, but does not, on its own, have the answers.

The two days of programming on the virtual main stage will be free and available on a global basis both live and on-demand. There will also be a $25 Pro Pass for those who want to participate in specialized breakout sessions, Q&A with speakers and virtual networking. Registration for the show opens soon; in the meantime, anyone interested may request email updates here.

Its important to note that there are many excellent events every year that focus on accessibility, and we respect their many abiding contributions and steady commitment. Sight Tech Global aims to complement the existing event line-up by focusing on hard questions about advanced technologies and the products and experiences they will drive in the years ahead assuming they are developed hand-in-hand with their intended audience and with affordability, training and other social factors in mind.

In many respects, Sight Tech Global is taking a page from TechCrunchs approach to its AI and robotics events over the past four years, which were in partnership with MIT and UC Berkeley. The concept was to have TechCrunch editors ask top experts in AI and related fields tough questions across the full spectrum of issues around these powerful technologies, from the promise of automation and machine autonomy to the downsides of job elimination and bias in AI-based systems. TechCrunchs editors will be a part of this show, along with other expert moderators.

As the founder of Sight Tech Global, I am drawing on my extensive event experience at TechCrunch over eight years to produce this event. Both TechCrunch and its parent company, Verizon Media, are lending a hand in important ways. My own connection to the community is through my wife, Joan Desmond, who is legally blind.

The proceeds from sponsorships and ticket sales will go to the nonprofit Vista Center for the Blind and Visually Impaired, which has been serving Silicon Valley area for 75 years. The Vista Center owns the Sight Tech Global event and its executive director, Karae Lisle is the events chair. We have assembled a highly experienced team of volunteers to program and produce a rich, world-class virtual event on December 2-3.

Sponsors are welcome, and we have opportunities available ranging from branding support to content integration. Please email sponsor@sighttechglobal.com for more information.

Our programming work is under way and we will announce speakers and sessions over the coming weeks. The programming committee includes Jim Fruchterman (Benetech / TechMatters), Larry Goldberg (Verizon Media), Matt King (Facebook) and Professor Roberto Manduchi (UC Santa Cruz). We welcome ideas and can be reached via info@sighttechglobal.com

For general inquiries, including collaborations on promoting the event, please contact info@sighttechglobal.com.

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Announcing Sight Tech Global, an event on the future of AI and accessibility for people who are blind or visually impaired - TechCrunch

9 Saint Lucia Resorts That Are Open Right Now Caribbean Journal – Caribbean Journal

Posted on August 9, 2020 by Danzig

Saint Lucia was one of the first destinations to relaunch tourism when the island reopened its borders at the beginning of June, and its open to tourists including those from the United States.

What youll find in Saint Lucia are many resorts with widely spaced accommodations ideal for social distancing, and strong safety protocols for hotels, transportation, and attractions.

All travelers to Saint Lucia must submit a pre-arrival travel registration form and proof of having received a negative COVID-19 PCR test within seven days of arrival on-island. Visitors must have reservations at (and confie to) a hotel that has been certified as compliant with Saint Lucias COVID-19 safety protocols in order to be admitted into the country. (See more on the islands policies here). Happily, Saint Lucias diverse hotel stock specializes in resorts youll never want to leave.

So where can you stay if youre planning to visit? Here are the resorts that have received COVID-19 certification and are open right now.

Ladera: Three-walled suites 1,000 feet above the beach and with spectacular views of the Piton mountains make a stay at Ladera seem otherworldly in other words, the perfect place for escape. Just 37 rooms means plenty of elbow room for guests.

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9 Saint Lucia Resorts That Are Open Right Now Caribbean Journal - Caribbean Journal

Royal Caribbean, Marriott and Cisco Earnings on Tap in Week Ahead – TheStreet

Posted on August 9, 2020 by Danzig

Next week will see earnings reports from a hard-hit cruise operator, a hotel operator and a networking giant, among others.

Royal Caribbean Cruises Ltd. (RCL) - Get Report is expected to report a loss of $988.5 million, or $4.82 a share, on sales of $47.4 million before the market opens on Monday, based on a FactSet survey of 12 analysts.

In the same period a year ago, the company posted earnings of $2.54 a share on sales of $2.8 billion. It reported net income of $249.7 million.

The stock has risen 25.5% since the company last reported earnings on May 20.

In the upcoming quarter, analysts are forecasting a loss of $931.2 million, or $4.65 a share, on sales of $212.5 million.

For the year, analysts project revenue of $3 billion.

Marriott International, Inc. (MAR) - Get Report is expected to report a loss of $136.3 million, or 41 cents a share, on sales of $1.7 billion after the market closes on Monday, based on a FactSet survey of 23 analysts.

In the same period a year ago, the company posted earnings of $1.56 a share on sales of $5.3 billion. It reported net income of $375 million.

The stock has risen 9.8% since the company last reported earnings on May 11.

In the upcoming quarter, analysts are forecasting adjusted net income of $35.5 million, or 15 cents a share, on sales of $2.6 billion.

For the year, analysts project revenue of $12.2 billion.

Occidental Petroleum Corporation (OXY) - Get Report is expected to report a loss of $1.52 billion, or $1.68 a share, on sales of $3.9 billion after the market closes on Monday, based on a FactSet survey of 23 analysts.

In the same period a year ago, the company posted earnings of 97 cents a share on sales of $4.4 billion. It reported net income of $628 million.

The stock has risen 0.9% since the company last reported earnings on May 5.

In the upcoming quarter, analysts are forecasting a loss of $726.3 million, or 75 cents a share, on sales of $4.6 billion.

For the year, analysts project revenue of $19.2 billion.

Cisco Systems, Inc. (CSCO) - Get Report is expected to report net income of $3.1 billion, or 74 cents a share, on sales of $12.1 billion after the market closes on Wednesday, based on a FactSet survey of 25 analysts.

In the same period a year ago, the company posted earnings of 83 cents a share on sales of $13.4 billion. It reported net income of $3 billion.

The company offered guidance of 72 to 74 cents a share on May 14, a day after its last financial report. Shares have risen 8.9% since then.

In the upcoming quarter, analysts are forecasting net income of $3.2 billion, or 75 cents a share, on sales of $12.2 billion.

For the year, analysts project revenue of $49.2 billion.

Applied Materials, Inc. (AMAT) - Get Reportis expected to report net income of $881.3 million, or 95 cents a share, on sales of $4.2 billion after the market closes on Thursday, based on a FactSet survey of 23 analysts.

In the same period a year ago, the company posted earnings of 74 cents a share on sales of $3.6 billion. It reported net income of $666 million.

The stock has risen 16.9% since the company last reported earnings on May 14.

In the upcoming quarter, analysts are forecasting net income of $942.7 million, or $1.02 a share, on sales of $4.4 billion.

For the year, analysts project revenue of $16.6 billion.

Applied Materials is currently trading at a price-to-forward-earnings ratio of 15.3 based on the 12-month estimates of 25 analysts surveyed by FactSet.

Read what Jim Cramer is telling his investment club members about earnings season at Action Alerts PLUS.

Originally posted here:

Royal Caribbean, Marriott and Cisco Earnings on Tap in Week Ahead - TheStreet

Belgium and the Bahamas off safe list – ABTA Magazine

Posted on August 9, 2020 by Danzig

Change comes into place on 4am on Saturday August

Travellers arriving in the UK fromBelgium, Andorra and the Bahamas will be forced to quarantine for 14 days after the countries were removed from the governments travel corridors list.

The Department for Transport said that data from the joint biodiversity centre and Public Health England indicated a significant change in both the level and pace of confirmed cases in the countries.

The change comes into place on 4am on Saturday August 8. Scotland has also withdrawn the countries from its list.

The Foreign & Commonwealth Office now advises against all but essential travel to Belgium, Andorra and the Bahamas.

Data shows we need to remove Andorra, Belgium and The Bahamas from our list of #coronavirus Travel Corridors in order to keep infection rates DOWN. If you arrive in the UK after 0400 Saturday from these destinations, you will need to self-isolate for 14 days.

Belgium recoded more than 70,000 Covid-19 cases this week, meaning it has a rate of 27.8 new cases per 100,000 people. This is compared to the UKs 8.4.

Estonia, Latvia, Slovakia,Slovenia, and St Vincent and the Grenadines were added to the list on July 24, butSpainwas removed on July 25 andLuxembourgwas removed on July 31.

More: Get information on overseas travel in our travel advice sectionMore: Sign up to our Weekly Digest for an overview of travel news

The government is under increased pressure to implement a testing regime at borders amid the confusion caused by changes to thetravel corridors list.

In the wake of the Department for Transport removingSpainfrom its safe list and the change in FCO advice, which was subsequentlyextended toinclude the Canary and BalearicIslands, the chief executive of Heathrow has renewedcalls for testing.

As many of our customers have experienced, its difficult to plan a holiday that way, let alone run a business.Testing offers a way to safely open up traveland trade to some of the UKs biggest markets which currently remain closed, John Holland-Kaye told BBC Radio 4sTodayprogramme.

He said: The UK needs a passenger testing regime and fast, adding that without it, Britain is just playing a game of quarantine roulette.

Matt Hancock has said he hasabsolutely no regrets about the quickchange in advice on Spain and saidmore countries could be removed from the exemption list within days.

The health secretary said officials were looking all of the time at coronavirus cases in other countries.

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Belgium and the Bahamas off safe list - ABTA Magazine

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Announcing Sight Tech Global, an event on the future of AI and accessibility for people who are blind or visually impaired – TechCrunch

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Royal Caribbean, Marriott and Cisco Earnings on Tap in Week Ahead – TheStreet

Belgium and the Bahamas off safe list – ABTA Magazine