The time an airplane spends waiting for a gate after landing or waiting in line to take off could also be reduced. A group at SITA focused on airport management systems is helping to design technology that can synthesize data from many sources, including changing aircraft arrival times, weather conditions at destination airports and logistical issues to improve runway schedules and gate assignments.

Artificial intelligence software can also make a difference with rebooking algorithms, Mr. Etzioni said. When weather or mechanical issues disrupt travel, the airlines speed in recomputing, rerouting and rescheduling matters, he said.

The data streams get even more complex when the whole airport is considered, Ms. Stein of SITA said. A number of airports are creating a digital twin of their operations using central locations with banks of screens that show the systems, people and objects at the airport, including airplane locations and gate activity, line lengths at security checkpoints, and the heating, cooling and electrical systems monitored by employees who can send help when needed. These digital systems can also be used to help with emergency planning.

The same types of thermal, audio and visual sensors that can be used to supply data to digital twins are also being used to reduce equipment breakdowns. Karen Panetta, the dean of graduate engineering at Tufts University and a fellow at the Institute of Electrical and Electronics Engineers, said hand-held thermal imagers used before takeoff and after landing can alert maintenance crews if an area inside the airplanes engine or electrical system is hotter than normal, a sign something may be amiss. The alert would help the crew schedule maintenance right away, rather than be forced to take the aircraft out of service at an unexpected time and inconvenience passengers.

At the moment, people, rather than technology, evaluate most of the data collected, Dr. Panetta said. But eventually, with enough data accumulated and shared, more A.I. systems could be built and trained to analyze the data and recommend actions faster and more cost effectively, she said.

Air travel isnt the only segment of the transportation industry to begin using artificial intelligence and machine learning systems to reduce equipment failure. In the maritime industry, a Seattle company, ioCurrents, digitally monitors shipping vessel engines, generators, gauges, winches and a variety of other mechanical systems onboard. Their data is transmitted in real time to a cloud-based A.I. analytics platform, which flags potential mechanical issues for workers on the ship and on land.

A.I. systems like these and others will continue to grow in importance as passenger volume increases, Ms. Stein said. Airports can only scale so much, build so much and hire so many people.

Link:
Air Travelers Cant See All of It, but More Tech Is Moving Them Along - The New York Times

As the superyacht industry welcomes a new generation of crew, with new demands and expectations, the operational experience on board will need to evolve to suit their needs. While vessels are growing more complex, Gunther Alvarado, head of yacht management and marine operation at Al Seer Marine, believes systems need to be updated to keep up with the technology crew are used to in their everyday lives.

Seventy per cent of crew in our fleet are millennials and Generation Z. These generations are born with an iPhone in their hand, said Alvarado during a panel discussion at The Superyacht Forum2019. We need to make our systems a lot more interactive, from flag states and regulatory bodies, to make it easy for crew to access information and automatically remind them about things to do.

The inevitable integration of artificial intelligence (AI) and machine learning (ML) on board will have an impact on the crew of the future, with the potential to transform operations such as navigation, maintenance and even service. Our owners have these technologies in their own businesses and homes, so it wont be long until they want them on their yachts, says Mike Blake, president of Palladium Technologies.

Our owners have these technologies in their own businesses and homes, so it wont be long until they want them on their yachts...

The commercial shipping industry is already testing autonomous vessels, and superyacht captains only drive the yacht a small percentage of the time anyway, so AI systems can take it over because they have an endless attention span to do the repetitive task of monitoring all the information in the bridge. AI will also be used in the engine room to monitor all systems at once and predict any failures. It could even be used in the interior I think we will have systems that will read who the guests are and be able to give a much better service.

Joseph Adir, founder and CEO of WinterHaven, agrees that AI and ML are going to transform the way in which superyachts are operated. The continued growth of IoT technology utilising deep-learning computer systems and high-volume data analytics on OnPrem and Cloud will deliver greater benefits for superyacht owners in the future, says Adir.

Integrating IoTs and sensors connected to Edge ML, all aggregated into a large AI/ML platform, will deliver a smart interactive 3D interface on board [that] will give all stakeholders an in-depth view of the asset. Artificial Intelligence and Machine Learning can then be used to mine the big data and monitor all equipment and systems on board for performance management and optimisation, as well as predictive maintenance.

Safe operation on yachts will likely rely on using this technology alongside a documented and structured manual check process. These future solutions will then not only increase safety on board, but also eventually reduce the need for human-machine interaction by automating selected tasks and processes, while the captain and crew remain at the centre of critical decision-making and on-board expertise.

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Technology - Integrating artificial intelligence on board - Superyacht News - The Superyacht Report

Political polarization is ripping America apart. References to a second American civil war no matter how far-fetched reveal a bitterly divided nation. Indeed, the Founding Fathers worst nightmare is coming to pass.

For all of its promise, technology bears much of the blame for fracturing America. For one, social media platforms create powerful echo chambers that feed us a nonstop diet of one-sided, hyper-partisan news and commentary. This dangerous phenomenon where our beliefs are constantly reinforced and rarely challenged is not unique to liberals or conservatives. Instead, it is a function of technology capitalizing on an ever-expanding cultural and social divide.

But what if technology could be harnessed to reverse this corrosive effect on American society and its underlying cause? Moreover, at a time when factual news reporting is all too often immediately dismissed as fake, we are in desperate need of voices broadly respected by all Americans.

Enter Americas Founding Fathers and machine learning.

Despite the passage of centuries, Americans of all political stripes continue to invoke the ideas and writings of the Founders. Few figures hold more sway or command more respect among political pundits, politicians and everyday patriots than Adams, Hamilton, Jay, Jefferson, Madison and Washington.

While it may seem far-fetched on its face, what if artificial intelligence and machine learning could bring these titans of history back to life to weigh in on the challenges facing the United States today?

Artificial intelligence, in short, amounts to providing machines with enough data to make decisions or predictions without human input. Autonomous cars, for example, drive around American cities gathering real-time experience to inform decision-making. The challenge with driverless cars, however, is that staggering amounts of data are required to predict the many surprises that these machines are likely to encounter on the road.

But when it comes Americas Founding Fathers, we have all the data that we need in their writings, speeches and legislative records to resurrect them through machine learning. Indeed, the Founders discussed and debated the most contentious issues from the media to taxation, education, religion and beyond that America confronts today. Human nature, after all, ensures that history tends to repeat itself.

Bringing the Founders back through artificial intelligence processes would bestow enormous benefits. For one, the addition of such revered and respected voices would allow us to regain some semblance of civility in public discourse. Indeed, it would be difficult to denigrate Jefferson or Madisons take on contemporary issues such as the national debt or impeachment as partisan fake news.

Most importantly, the most corrosive effects of hyper-partisan, ratings-driven media outlets and the social media platforms that enable them would be blunted, reining in the extreme division and political polarization gripping America.

To be sure, significant challenges would accompany such an ambitious venture. The process of coding the Founders writings and records into mathematical vectors digestible by machines could prove complex, stretching current capabilities to their limitations. The same is true for the all-important task of accurately translating the issues dividing America today into machine-readable data. But the good news is that significant groundwork has been done in this arena: Artificial intelligence and neural networks already conduct political predictions as well as complex, issue-based analyses.

With little potential for profit, securing adequate funding for such an endeavor will also prove challenging. But thanks to initiatives such as Googles Artificial Intelligence for Social Good and grants supporting AI-enabled fact-checking, there is reason for optimism. Indeed, the inherently ethical and positively disruptive nature of such technology may attract broad support from an ideologically diverse cross-section of civically-minded institutions and individuals.

Ultimately, the Founding Founders lasting gift to the American people is a treasure trove of wisdom on civil discourse, shared values and sound governance. At a time when America finds itself dangerously divided, we must not hesitate to harness the Founding Fathers collective legacy for the betterment of the nation that they cherished so dearly.

Marik von Rennenkampff served as an analyst with the U.S. Department of States Bureau of International Security and Nonproliferation, as well as an Obama administration appointee at the U.S. Department of Defense. Follow him on Twitter @MvonRen.

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How to save America with artificial intelligence | TheHill - The Hill

Stationed at the frontier of accelerating artificial intelligence (AI) landscape, organizations need to validate executives who make nimble, informed decisions about where and how to employ AI in their business. Encouraging the industry-wide digital transformation, the widespread technology has permeated more organizations and more parts within organizations spanning the C-suite executives as well. The very fundamentals of leadership need to be rethought, from overall strategy to customer experience, in order to deploy AI appropriately while considering the human capital too.

As the conventional business leaderships are giving way to new approaches, opportunities, and threats as a result of broader AI adoption, the new set of AI executives are ready to take over the challenge to drive better innovation and competitiveness. Several C-level executives, in todays dynamic AI culture, are confident enough to wheel their organizations leadership team towards the ability to adapt significant and innovative AI approaches across the business.

As it stands now, top AI executives are not only evolving at a rapid pace but also revamping their surroundings for better technology implementation. Moreover, their employees and fellow teammates support them with full-confidence while promoting the positive aspects of AI. To excel further, the C-level executives press over the need to train the leadership team on AI as a top priority.

Despite, business leaders optimism about artificial intelligence and the opportunities it presents, they cannot neglect the fact regarding its potential risks. A number of C-level executives and their leadership team are hesitant to invest in AI technologies because of security or privacy concerns. However, showcasing the brave and progressive attributes of leadership, while ensuring security through innovation, some prominent executives are performing experiments with AI capabilities, and evidently, those are the ones who form the clan of topmost AI executives across the industry.

As claimed by certain market reports, business executives are showered with great success in AI across five major industries retail, transportation, healthcare, financial services, and technology itself. Tracing the success-map of such leaders, executives across various other sectors are admittingly adopting AI capabilities more aggressively than before.

In the age of AI, business executives must focus on embedding AI into their strategic plans which would subsequently enable such frontrunners develop an enterprise-wide strategy for AI, that inclusive business segments can follow. Moreover, as a part of the leadership team, they are responsible to look after financial aspects of the organization as well, therefore, applying AI to revenue and customer engagement opportunities will help them explore the use of technology for various revenue enhancements and client experience initiatives while tracing their own progress.

AI executives should also focus on employing multiple options for acquiring AI and developing innovative applications in an effort to accelerate the adoption of AI initiatives via access to a wider pool of talent and technology solutions.

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Leadership in the age of Artificial Intelligence - Analytics Insight

Technological advancements throughout time have caused periods of huge change across industries and jobs roles. Currently, it is the rapid advances in automation and Artificial Intelligence (AI) technologies which have the potential to significantly disrupt global supply chains. However, the question remains how and to what extent these changes will impact in supply chain roles?

What is apparent is that automation and AI will likely transform almost all work to some degree, due to its ability to enhance the productivity of some workers and replace the work of others. When assessing the impact of these advances, the opinions of experts and pundits can by and large be broadly placed into two buckets that AI & automation leads to functions being substituted or complemented.

The rapid advancement in AI and automation means that, at a not universally agreed upon time in the future, the ability of computers and robots will soon surpass that of workers in numerous tasks. Consequently, when computers are both better and more cost effective than workers, the human workforce will be replaced through labour substitution.

The replacement of workers will happen not just in warehousing (robots) and transportation (self-driving trucks) but also in supply chain planning and execution with automated forecasting, exception handling and replenishment. One study has forecasted that about 47 per cent of US jobs are at risk of computerisation. Another study looked at the impacts of robots in employment opportunities in US manufacturing and found significant decreases in both employment and wages.

The more optimistic view is that there will be an AI-driven shift in the workforce, as technology increases the opportunity for workers who are not in direct competition with it. Whilst technology may depress employment for certain types of labour, it has the potential to create new needs and new opportunities through the creative destruction of the complementary effect.

This is exemplified when looking at the introduction of the spreadsheet in the early 1980s first with VisiCalc and then Lotus 1-2-3. This made manipulating large quantities of related data much easier without time consuming and error-prone methods. Suddenly, you could change commodity costs, currency exchange rates, component prices or interest rates and instantly see the impact on revenues and profits into the future. In the finance and accounting discipline (e.g. in supply chain finance) it simplified routine bookkeeping and made many tasks simpler like modelling alternate scenarios.

This technology tremendously impacted the demand for bookkeepers (44 per cent less in number between 1985 and 2017) but greatly increased the need for people who could run the numbers on this new software like accountants, financial managers and management consultants. In the United States between 1985 and 2017, the ranks of accountants and auditors had grown 41 per cent to 1.8 million, while financial managers and management consultants had nearly quadrupled to 2.1 million.

A pessimistic view is that advances in AI and automation will be so rapid, that machines will eventually be better than humans in most activities, and as access to the technology becomes mainstream it will be the default choice for businesses. Consequently, there will be a few highly paid workers who will still be employed and the rest will struggle to find work, or be stuck in jobs that are poorly paid, unstable and stressful.

Alternatively, economist Roger Bootle takes a more optimistic view in his book The AI Economy: Work, Wealth and Welfare in the Robot Age. Bootle theorises that AI and robotics would improve productivity and drive economic growth, whilst at the same time release people from performing the most mundane, boring and unfulfilling tasks. New jobs will be created, including those that will always need a human touch with increased social, collaboration and design skills.

Which of these alternate visions of the future should we believe? Recent history has not been able to support convincingly the optimists or the pessimists. Unemployment is a record low which suggests that automation has not led to labour displacement. On the other hand, economists have been pointing out that the growth in overall productivity attributed to technology has been consistently disappointing. Though Erik Brynjolfsson, who studies the economics of information technology, suggests in his explanation of the productivity paradox, that measurements of the impacts may be time delayed and that the wrong (old economy) measures are being used.

Whether you fall in the side of pessimism or optimism, what is clear is that technology is causing tremendous disruption in supply chains and for professionals to survive and thrive, they will have to begin to re-invent themselves.

It is not just technological advancements that are driving the re-invention of the supply chain, but rising customer expectations has also had a monumental impact. Customers increasingly expect products and services in their hands more quickly, whilst also demanding a more personalised experience and all this at a lower cost. These changing consumer demands requires faster order fulfilment times and super-efficient delivery. To do this businesses must invent an entirely new way to architect, design and manage supply chains across broader ecosystems, new technologies and new roles and skill sets.

The new supply chain roles being created will increasingly require working directly with customers, customer facing departments, product development, manufacturing and logistics to define the right product and service portfolios. This customer co-creation paradigm will drive the need for supply chain professionals, that can orchestrate the silos across organisations, while at the same time leveraging the latest modelling and analytical tools for insights and decision making.

The high level of cooperation needed in the new roles will require the leveraging of AI and automation to make intelligent decisions around new product attributes, product portfolios, product pricing and distribution, network design, product flow paths, capacity, inventory placement and transportation modes. The emergence of the digital twin of the supply chain, is key to making those interconnected trade-offs, in order to deliver in an environment of ever-changing customer needs, at new levels of speed and scale.

The supply chain ecosystem has always been at its core a people business. As AI and automation enter the mainstream humans and machines can no longer just co-exist but work together to achieve common goals. This cooperation will ultimately benefit all involved as it leads to a more efficient and sustainable supply chain that delivers better business outcomes.

Vikram Murthi, Vice President, Industry Strategy, LLamasoft

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How Artificial Intelligence and Automation may reshape supply chain roles as we know them? - ITProPortal

In 2019, in an article for German publication 'Trends im Asset Management', an Invesco fund manager participated in a Q&A about the future of investment.

The very first question went to the heart of a shift that is reshaping this industry and many others: "How much time do you have left before the machines take over?"

Although frivolous, the implication was undeniably relevant. The story of artificial intelligence (AI) and machine learning (ML) has long been defined by alternating bouts of optimism and dread, with the prospect of change encouraging eager expectation and the actual realisation of change prompting an alarm firmly rooted in fears of human obsolescence.

The biggestartificialintelligencethemes for the next decade

Of course, there is nothing unique about such reactions. They have been sparked by many transformative innovations in many settings through many ages.

Disruption invariably brings winners and losers, and it is this inevitability that demands the weighing of manifest benefits against negative externalities.

For several decades now the most efficient way to handle vast amounts of data has been to feed them into a machine.

Even relatively unsophisticated algorithms can make sense of huge masses of information millions of times more quickly than a human can.

Computers assist us in avoiding knee-jerk reactions, in distinguishing empiricism from quirk and coincidence and in applying a more systematic, rules-defined approach.

'A marriage between humans and machines': How AllianzGI is embracingartificialintelligence

But does this mean that they are fundamentally superior? As we continue to wrestle with both the scope and the limitations of AI and ML, asset managers are facing a challenging balancing act - so in which direction, if any, are the scales likely to tip?

Asset managers are still coming to terms with the pros and cons of AI and ML. So are their clients. So is academia. So are regulators and policymakers.

This much was clear from a recent Cambridge Judge Business School conference, which Invesco was privileged to co-host at The Royal Society.

The event explored where the AI/ML phenomenon stands at present and where it might lead in the years to come.

Scholars, industry figures and other stakeholders addressed topics such as "black box" concerns, regulatory and ethical issues - especially in relation to data privacy - and the broader "promise and pitfalls" of AI and ML.

The liveliest session resulted from a discussion about human-AI/ML interaction. Some contributors cautioned that the AI/ML revolution has barely begun, while others predicted that it will turn out to be far less impactful than widely envisaged.

The hidden tech treasures among UK growth stocks

Tellingly, everyone stressed the importance of a prudent combination of human and machine inputs.

This is an essential point, because the history of innovation and disruption in any field has repeatedly demonstrated that meaningful progress lies in a blend of what we know works well and what we know can be improved.

The relationship between humans and machines, whether in the sphere of asset management or elsewhere, presents a fascinating and recurring test of this rule of thumb.

As a report of the conference observed, it is worth recalling what is now thought of as the first-ever study of AI. Conducted more than 70 years ago by computer scientist and cryptanalyst Alan Turing, the most celebrated of World War II's codebreakers, it set out to determine whether machines can do what humans can.

The focus has long since shifted to what machines can do that humanscannot, yet it is also vital to recognise the opposite - that is, what humans can do that machines cannot.

Science-fiction has traditionally portrayed ostensibly omniscient machines as fatally flawed. Arguably the most well-known example is2001'sHAL 9000, which was forcibly disconnected after descending into what author Arthur C Clarke dubbed a "Hofstadter-Mbius loop".

Driven by "big data" and algorithms rather than by pseudo-human emotions, today's computers might not exhibit HAL's murderous tendencies; yet science-fact is increasingly evidencing their fallibility.

Google Flu Trendsoffers an interesting illustration: launched in 2008 and quietly retired three years later, it proved incapable of fulfilling its intended task - presaging flu epidemics - because neither the data suppliers nor the algorithms understood flu well enough to make the concept work.

Similarly, consider the idea of predictive policing. In theUS, as well as causing controversy around the reinforcement of biases, this algorithm-driven approach has performed well in in relation toincidents of drug-dealing, assault and gang violence but has proven of much less use in tackling crimes of passion and homicides.

Why? A reasonable explanation is that commonplace crimes produce a data set that is too enormous for a human to make sense of but which is perfectly suited to the power of algorithmic analysis.

Conversely, because they are merficully rare, other crimes generate insufficient data for a machine to exploit but enough to benefit from a seasoned police officer's intuition and experience.

In other words,there is a place for a computer's impartial, hyper-processed extrapolations; and there is also a place for a human's subjective, hard-won expertise.

The truth is that intelligence comes in many forms, not all of them the exclusive preserve of algorithms.

As philosopher AJ Ayer once remarked: "It's much easier to imagine a machine creating works of art than appreciating them."

Irving John Good was a contemporary of Turing at Bletchley Park, the top-secret home of Britain's wartime cryptanalysts.

In 1965 he wrote: "The first ultra-intelligent machine is the last invention that man need ever make, provided that the machine is docile enough to tell us how to keep it under control."

Today, with technology advancing at an unprecedented rate, the threat of computers outstripping their creators might never have been more realistic.

The World Economic Forum has officially acknowledged "the singularity" - the moment when machines become infinitely more intelligent than humans - as one of the most pressing issues around AI and ML.

Tesla founder Elon Musk has even posited that machines could render humansuselessunless efforts to merge the two are dramatically stepped up.

In the absence of a "high-bandwidth interface to the brain", he says, the proliferation of computers "smarter than the smartest human on Earth" could end life as we know it. The prophecies of doom will no doubt keep coming.

Yet Invesco's aforementioned fund manager felt able to answerTrends im Asset Management's opening question thus: "I'm not worried about that."

What makes him so confident? Why is he so sure that AI and ML will not railroad their flesh-and-bones counterparts into redundancy?

His conviction, which we would all do well to share, stems from a belief that technology is not here tooverpower us: it is here toempower us.

As long as we remember this crucial caveat, AI and ML should help augment the decision-making, performance and services that asset managers can offer.

If we appreciate what we do well and what computers and their algorithms do well - and, by extension, if we accept what each does better than the other - then the outcomes, overall, should be immensely positive.

The fact is that we have an amazing opportunity to utilise the best of both worlds - human and machine - to deliver investment solutions of unprecedented effectiveness.

Henning Stein is global head of thought leadership at Invesco

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Will artificial intelligence empower us or overpower us? - Investment Week

Illumitex has been known for several years as a supplier of LED lighting products for the greenhouse industry, among others. However, the companys launch last year of its new FarmVisionAI computer-vision artificial intelligence platform, seemed to set the path for a new journey for the company.

Last week, that transition become official, as Illumitex CEO Jeff Bisberg announced the company is pivoting to become a pure agriculture technology company that will deploy edge vision systems, edge AI, and cloud services to provide visualization and augmented intelligence for controlled environment agriculture.

With installations ramping, we are seeing that FarmVisionAI is more valuable to growers than LED lighting, and we are refocusing our resources to accelerate deployments Bisberg says. By capturing images of every plant at every moment, we create a unique data-set that allows us to close the digital feedback loop and drive amazing new outcomes, at scale, for our customers.

Greenhouse Grower reached out to Bisberg to get additional thoughts on the move, and what it means for Illumitex and for the horticulture industry.

Jeff Bisberg: First and foremost, the shift is about FarmVisionAI focus and providing digital solutions to help farmers make better decisions faster. While our LED business was growing rapidly, almost 50% year over year for multiple years, the explosion of LED solutions for horticulture into the marketplace creates an intensity and noise to the farmer-lighting-buyer that is an additional barrier to effectively communicating our value message. We were ramping up digital as our main differentiation, and this move really allows us to focus all of our resources on improving the FarmVisionAI digital experience.

Bisberg: We have fulfilled final orders and have minimal amount of residual inventory to liquidate. We have had some discussions on transitioning our products to other companies, as we have state-of-the-art fixtures that have excellent proven performance in many growing operations, but this is not a key part of the strategy. We are looking for partners on the lighting side that will work closely with us, as it still makes a lot of sense to deploy FarmVisionAI along with lighting.

Bisberg: Feedback ranges, but because we present the imagery like Google Earth inside the greenhouse, it feels very familiar and intuitive to our users. The reaction that I love the best is, why hasnt this been done before? Visual analysis has always been a central part of farming and now we are just moving it from analog (your eyes) to digital (our cameras). The reality is that folks go blind to all the charts, numbers, and dials of many other digital systems, so well win because we tap into growers native behaviors.

Bisberg: Growing plants at scale is very complicated, and it will be a long time before AI replaces anyone. The farmer should think of AI as a new tool that they can use, maybe like a new kind of shovel, to help make their job a little easier, its just software, not hardware. Someday it might replace someone, but didnt the tractor replace people too?

Bisberg: High-value crops make the most sense, and cannabis just happens to be the highest value. A small positive change in output has a huge benefit that can pay down the costs of new technology. As the technology continues to get better, it will cross over to lower-value crops. Cannabis is the killer app for ag tech, just like that early ear piece mic/speaker was the killer app for Bluetooth. In some sense, outdoor precision agricultures failure is that it started with low value crops like corn. Its just too expensive to improve an acre of corn in the middle of a massive farm to make a monetary difference.

Bisberg says FarmVisionAI provides three groups of features that can be of high value to an operation:

Some of the benefits of FarmVisionAI include:

Illumitexs FarmVisionAI can be deployed in any grow architecture from containers, to vertical, to warehouse, to greenhouse. It is easy to install, without the need for motors or tracks, and does not require the deployment of registration markers in the grow. Cameras are wireless and connect to the cloud through Illumitex-deployed gateways and on-site server.

Currently, the system works with leafy greens and determinant plants. While the first AI algorithms are cannabis focused, new detections can be activated with as little as 10,000 images of the desired detection target.

Brian Sparks is senior editor of Greenhouse Grower and editor of Greenhouse Grower Technology. See all author stories here.

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What Illumitexs Shift to Artificial Intelligence Means for the Future of Horticulture - Greenhouse Grower

Would you be surprised to learn a 120-year-old company is transforming its business with artificial intelligence and technology? Akron, Ohio-based tire maker Goodyear might not be the first company you think of when discussing technological innovation, but they continue to announce intriguing developments and offer proof via new initiatives and products that they are altering operations to be competitive in the future.

The Amazing Ways Goodyear Uses Artificial Intelligence And IoT For Digital Transformation

Tire Technology

Regardless if it's an autonomous, electric, or a traditional vehicle, they all need a solid foundation of the right tire for the specific demands of the vehicle. Goodyear uses internet of things technology in its Eagle 360 Urban tire. The tire is 3D printed with super-elastic polymer and embedded with sensors. These sensors send road and tire data back to the artificial intelligence-enhanced control panel that can then change the tread design to respond to current road conditions on the fly and share info about conditions with the broader network. If the tire tread is damaged, the tire moves the material and begins self-repair.

Goodyears intelligent tires are in use on a new pilot program with Redspher, a European transportation and logistics company operating in 19 countries. The fleet benefits from the tire's ability to monitor and track tire pressure, vehicle data, and road conditions. This data is then analyzed by Goodyears algorithms to gain insights about maintenance needs and ways to improve the safety and performance of the fleet.

Another tire innovation from Goodyear is the Oxygene model, another 3D-printed tire that has embedded sensors connected to the internet of things and also uses living moss and photosynthesis to power its electronics. The self-generated electricity powers onboard sensors, an AI-processing unit, as well as a light strip that illuminates when a driver brakes or changes lanes. The living moss feature may be unusual, but it shows the company's commitment to pushing and pursuing solutions to help the environment and to be relevant in the future. The tire is 3D printed from rubber powder from recycled tires.

Goodyear is also at the forefront of providing tires designed for the specific needs of electronic vehicles. Traditional tires can wear up to 30% faster on electric vehicles according to the companys testing. Goodyears Eagle F1 Asymmetric 3 tire was selected for Audis e-tron electric SUV.

B2C and B2B E-Commerce

In 2015, Goodyear was the first tire manufacturer to offer tires sales online to consumers. They followed that up in 2019 with GoodyearTruckTires.com, an e-commerce solution for commercial tire dealers.

AI Technology Provides Predictive Analytics

In addition to transportation and logistics companies such as Redspher leveraging Goodyear's predictive analytics, car-sharing, and ride-hailing services stand to benefit from the company's tire maintenance program. In a pilot program with STRATIM, a company whose platform tracks and oversees fleet maintenance for more than 50 mobility services in North America, Goodyears technology and tires will help maximize the fleets uptime.

With several partnerships, including with YourMechanic, Local Motors, and Envoy Technologies, Goodyear is rolling out its predictive tire-servicing tools to a wider audience that touches on many of transportation's hottest development areas including mobile car repair, autonomous vehicles, and car-sharing.

Investments for the Future

Goodyear announced a new $100 million venture fund called Goodyear Ventures at CES 2020. Dedicated to supporting startups that will facilitate "sustainable, safe, and new mobility experiences," the venture fund shows Goodyear's commitment to bringing traditional and startup businesses together to propel solutions for the future.

The company also unveiled AndGo, a fleet vehicle servicing platform, that delivers continuous care to company fleets through routine inspections and tire monitoring via Goodyears intelligent tires, but also collects data to provide valuable predictive maintenance.

One of the pillars of Goodyears corporate responsibility mandate is the advancement of mobility-focused on connected, autonomous, and electric vehicles. Along with the company's tire innovation and proactive services program, they are committed to making driving safer and more sustainable.

At the operational level, Goodyear has also leveraged the power of technology to increase its productivity. Goodyear is running an internet of things proof-of-concept using sensor data from the factory floor to inform maintenance needs. Investments in workplace modernization make Goodyear operations (in more than 150 countries, 48 manufacturing facilities and research and development centers in Germany, Luxembourg, China, and the United States) poised to innovate even faster in the future. The company is also exploring how Microsoft HoloLens and other technologies could impact virtual tire modeling and design.

Continue reading here:
The Amazing Ways Goodyear Uses Artificial Intelligence And IoT For Digital Transformation - Forbes

This article appeared originally on WallyBoston.com

By Dr. Wally Boston

As an avid follower of information technology trends, I have read hundreds of articles and several dozen books about artificial intelligence (A.I.) over the past six years. A few of the books have been reviewed on WallyBoston.com beginning in 2014 (see Our Final Invention: Artificial Intelligence and the End of the Human Era,The Future of the Professions: How Technology Will Transform the Work of Human Experts,RISE OF THE ROBOTS: Technology and the Threat of a Jobless Future,The Glass Cage: Automation and Us, andReview of The Second Machine Age: Work, Process, and Prosperity in a Time of Brilliant Technologies by Erik Brynjolfsson and Andrew McAfee). Recently, two items triggered my Spidey sense (a term coined by Marvel Comics for the ability of superhero Spiderman to sense when something was about to happen).

Fortune Magazines February 2020 issue dedicated its cover and a substantial portion of its articles to A.I. I have nothing against Fortune, but it is not the source that I generally consult for breaking news about innovations in technology. The editors chose to publish articles on five different A.I.-related topics (1) an article about The Quest for Human-Level A.I., (2) an article about the progress of A.I. in enabling natural language processing to end the challenge in translating languages, (3) an article about Tik Tok, an addictive video app powered by A.I. and owned by a Chinese company, (4) an article about Medicine by Machine and how A.I. is matching gene therapy treatments with existing drugs, (5) how A.I. is enabling human resource departments to screen applicants and better match needs with candidates, and (6) how A.I. is assisting the fertility industry in improving success rates and other innovations. If you are unfamiliar with A.I., I recommend reading these articles in Fortune for a good overview of the technologys capabilities.

The second item that triggered this blog article was a marketing email from EdX, the joint venture from Harvard and MIT that provides college courses for individuals interested in learning about topics from the experts teaching at elite institutions. This weeks email was about the courses offered at EdX related to A.I. The header on the EdX email was: The A.I. Revolution is Here. There were links to courses from the University of Montreal, the University of Washington, Tel Aviv University, Curtin University, the University of Pennsylvania, IBM, Harvard University, the University of California at Berkeley, the University of Texas at Austin, RedHat, Linux Foundation, the Technische Universitt Mnchen (Technical University of Munich), Israel X the Campus for the Israeli National Product for Digital Learning, and Columbia University. If I had the time, I wouldnt mind signing up for all of these courses. Regardless of which course you or I would take, the real issue is how do you get up to speed on A.I.?

Getting up to speed on artificial intelligence is relative to what your professional status is. If you are an employee with no involvement or knowledge of artificial intelligence, read the Fortune articles, read my blog reviews of books on the topic, and maybe one or two books. There are and will continue to be many jobs eliminated because of the advances of A.I. technology. Keep it in your rear-view window if you are a line worker and not a manager. If you are a manager, you need to be on top of the technology and how it may be capable of enhancing your outcomes as well as replacing many members of your team. If you are a CEO, you need to be aware of A.I.s capabilities and implement it before your competitors do. If you are a committed, lifelong learner, youll be okay. If not, please start educating yourself to be in a situation where you can recover if your job is eliminated through automation.

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Artificial Intelligence Is Everywhere Will You Be Prepared? - InCyberDefense

Artificial intelligence is on its way to remodel the Middle Eastern energy sector. It is predicted to optimize energy production and distribution through smart grid technology, in addition to multiplying the use of solar and wind power that is already soaring. A smart grid system is a self-sufficient electricity network system automated to manage the supply chain. This system optimizes efficiency, for increased financial gain; all while serving as a more sustainable, reliable, and qualitative way to supply energy.

The American consulting firm McKinsey & Companys report Artificial Intelligence: Transforming the Future of Energy and Sustainability predicts that AI technologies could generate $3.5 trillion to $5.8 trillion annually across energy industries. The data is a product of seventy reports from consultants, journalists, and government documents speaking on AIs predicted impact.

Further predictions come from the PwC, speculating AI to raking in $320 billion for the Middle Eastern economies, while reducing greenhouse gas emissions by 4%, both by the end of the decade.

Their data suggest that the annual growth in the contribution of AI to GDP will range between 20-34% per year across the Middle East, with the fastest growth in the UAE followed by Saudi Arabia:

The World Future Energy Summit in Abu Dhabi also emphasized the correlation between sustainability gains and financial benefits with the help of artificial intelligence.

Dr Alexander Ritschel, Head of Technology at Masdar spoke at the summit, adding that AI promises major advances in energy efficiency by making our cities in particular much more responsive to the way we consume power.

The members of the Gulf Cooperation Council are moving away from their reliance on oil, and while they still remain the largest producers per capita, their transition towards sustainable energy is picking up pace. Vision 2030 Programs are shifting investors toward technological sectors, and away from oil, promoting innovation and sustainability.

The demand for energy within the Middle East is anticipated to increase by 20% by 2050. The goal is for renewable energy to account for over half of that power supply, and artificial intelligence might be the determining factor.

See the rest here:
The Middle East is calling on artificial intelligence to restructure its' energy sector - Kawa News