AI talk: FX Week Europe panellists dont see much use for complex machine learning in FX

Artificial intelligence can be particularly useful in asset classes where there are thousands of instruments available to trade, but it is not deemed as practical in a market such as foreign exchange, where the overall number of currency pairs is limited and even less so in the majors, remarked panellists at the 2019 FX Week Europe conference.

While the panellists did not completely disregard the potential for AI in FX, they did not believe it is as relevant as it is for equities, for example.

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Artificial intelligence in FX 'may be hype' - FX Week

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Yes, artificial intelligence (AI) is proving itself to be a worthwhile tool in the business arena at least in focused, preliminary projects. Intelligent chatbots are a classic example. Now its a question of how quickly it can be expanded to deliver on a wider basis across the business to automate decisions around inventory or investments, for example.

Theres progress on this front, as shown in McKinseys latest survey of 2,360 executives, which shows a nearly 25 percent year-over-year increase in the use of AI in various business processes and there has been a sizable jump in companies spreading AI across multiple processes.

A majority of executives in companies that have adopted AI report that it has increased revenues in areas where it is used, and 44 percent say it has reduced costs, the surveys authors, Arif Cam, Michael Chui, and Bryce Hall, all with McKinsey, state.

The results also show that a small share of companies the authors call them AI high performers are attaining outsize business results from AI. Close to two in three companies, 63 percent, report revenue increases from AI adoption in the business units. Respondents from high performers are nearly three times likelier than their lagging counterparts to report revenue gains of more than 10 percent, the survey shows.

The leading AI use cases include marketing and sales, product and service development, and supply-chain management. In marketing and sales, respondents most often report revenue increases from AI use in pricing, prediction of likelihood to buy, and customer-service analytics, the surveys authors report. In product and service development, revenue-producing use cases include the creation of new AI-based products and new AI-based enhancements. And in supply-chain management, respondents often cite sales and demand forecasting and spend analytics as use cases that generate revenue.

What are these high performers doing differently? Strategy is a key area. For example, 72 percent of respondents from AI high performers say their companies AI strategy aligns with their corporate strategy, compared with 29 percent of respondents from other companies. Similarly, 65 percent from the high performers report having a clear data strategy that supports and enables AI, compared with 20 percent from other companies. Also, the application of standardized tools to be used across the enterprise is more likely to be seen at high performers.

Adoption of Strategic AI Approaches:

Retraining workers is also a key differentiator, the survey shows. One-third of high performers, 33%, indicate the majority of their workforce has received AI-related training over the past year, compared to five percent of lagging organizations. Over the next three years, 42% of high performers intend to extend such training to most of their workers, versus only 17% of their lagging counterparts.

For AI to take hold, the McKinsey authors urge ramping up workforce retraining. Even the AI high performers have work to do in several key areas, the surveys authors point out. Only 36 percent of respondents from these companies say their frontline employees use AI insights in real time for daily decision making. A minority, 42 percent, report they systematically track a comprehensive set of well-defined key performance indicators for AI. Likewise, only 35 percent of respondents from AI high performers report having an active continuous learning program on AI for employees.

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It Pays To Break Artificial Intelligence Out Of The Lab, Study Confirms - Forbes

Artificial intelligence (AI) -- the capability of a machine to mimic human thinking and behavior -- is one of the biggest growth trends today.Spending on AI systems will increase by more than two and a half times between 2019 and 2023, from $37.5 billion to $97.9 billion, for a compound annual growth rate of 28.4%,according to estimates by research firm IDC. Other sources are projecting even more torrid growth rates.

There are two broad ways you can get exposure to the AI space:

With this background in mind, let's look at which AI stocks are performing the best so far this year (through Nov. 25) and which one is my choice for best AI stock for 2020.

Image source: Getty Images.

The following chart isn't meant to be all-inclusive, as that would be impossible, and the chart has limits on the number of metrics. Notable among the companies missing areAdvanced Micro Devices and Intel. They were left out largely because NVIDIA is currently the leader in supplying AI chips. While there are things to like about shares of both of these companies, NVIDIA stock is the better play on AI, in my view.

Data by YCharts.

Graphics processing unit (GPU) specialist NVIDIA (NASDAQ:NVDA), e-commerce and cloud computing service titanAmazon, computer software and cloud computer service giant Microsoft, Google parent and cloud computing service provider Alphabet, old technology guard and multifaceted AI player IBM, and Micron Technology, which makes computer memory chips and related storage products, would best be put in the first category above. They produce and sell AI-related products and/or services. They're all also probably using AI internally, with Amazon and Alphabet being notably heavy users of the tech to improve their products.

iPhone makerApple (NASDAQ:AAPL), social media leader Facebook (NASDAQ:FB), video-streaming king Netflix, and Stitch Fix, an online personal styling service provider, would best be categorized in the second group since they're either primarily or solely using AI to improve their products and services.

Now let's look at some basic stats for the three best performers of this group.

Company

Market Cap

P/E(Forward)

Wall Street's 5-Year Estimated Average Annual EPS Growth

5-Year Stock Return

Apple

NVIDIA

Facebook

S&P 500

--

--

Data sources: YCharts (returns) and Yahoo! Finance (all else). P/E = price-to-earnings ratio. EPS = earnings per share. Data as of Nov. 25, 2019.

On a valuation basis alone, Facebook stock looks the most compelling when we take earnings growth estimates into account. Then would come Apple and then NVIDIA. However, there are other factors to consider, with the biggie being that projected earnings growth is just that, projected.

There's a good argument to be made that NVIDIA has a great shot at exceeding analysts' earnings estimates. Why? Because it has a fantastic record of doing so, and all one needs to do is listen to enough quarterly earnings calls with Wall Street analysts to realize why this is so: A fair number of them don't seem to have a strong grasp of the company's operations and products. (I'm not knocking, as most analysts don't have technical backgrounds, and they cover a lot of companies.)

Facebook stock probably has the potential to continue to be a long-term winner. But it's relatively high regulatory risk profile makes it not a good fit for all investors. Moreover, it will likely have to keep spending a ton of money to help prevent "bad actors" from using its site for various nefarious purposes. Indeed, this is one of the major internal functions for which the company is using AI. It also uses the tech to recognize and tag uploaded images, among other things.

Apple uses AI internally in various ways, with the most consumer-facing one being powering its voice assistant Siri. It's the best of these three stocks for more conservative investors, as it has a great long-term track record and pays a modest dividend.NVIDIA, however, is probably the better choice for growth-oriented investors who are comfortable with a moderate risk level.

Image source: Getty Images.

NVIDIA is the leading supplier of graphics cards for computing gaming, with AMD a relatively distant second. In the last several years, it's transformed itself into a major AI player, or more specifically, a force to be reckoned with in the fast-growing deep-learning category of AI. Its GPUs are the gold standard for AI training in data centers, and it's now making inroads into AI inferencing. (Inferencing involves a machine or device applying what it's learned in its training to new data. It can be done in data centers or "at the edge" -- meaning at the location of the machine or device that's collecting the data.)

NVIDIA is in the relatively early stages of profiting from many gigantic growth trends, including AI, esports, driverless vehicles, virtual reality (VR), smart cities, drones, and more. (There is some overlap in these categories, as AI is involved to some degree in most of NVIDIA's products.) There are no pure plays on AI, to my knowledge, but NVIDIA would probably come the closest.

Link:

The Best Artificial Intelligence Stocks of 2019 -- and The Top AI Stock for 2020 - The Motley Fool

SALT LAKE CITY The Salt Lake and Ogden-Clearfield areas are among the top 10 regions in the United States that will be most affected by the rise of artificial intelligence, according to a study recently released by Washington D.C.-based research group the Brookings Institution.

In the past, research has suggested that AI will disproportionately affect blue-collar and low-income workers, like factory employees or office clerks, who will soon find themselves replaced by machines. But past research hasnt often distinguished between the coming effects of advancements in robotics and software, and those of artificial intelligence, or computers that can plan, learn, reason and problem solve.

As robotics and software become more sophisticated, theyll replace employees in industries like manufacturing, construction or clerical work, the study claims. But artificial intelligence will change the world of the white-collar worker more than anything else and Salt Lake and Ogden will be in the thick of it.

In fact, AI will disproportionately affect areas that specialize in industries like technology, engineering, science, transportation, manufacturing and law, the study shows. And Utahs booming tech sector has not gone unnoticed.

Among the most AI-exposed large metro areas are San Jose, Calif., Seattle, Salt Lake City and Ogden, Utah all high-tech centers, the study reads.

Those four tech hubs are joined in the top 10 most-affected areas by agriculture, logistics and manufacturing centers like Bakersfield, California; Greenville, South Carolina; Detroit, Michigan; and Louisville, Kentucky.

Higher educated and higher paid workers will be most affected by the rise of AI in the coming decades, and workers with bachelors degrees will be more than five times as exposed to artificial intelligence as workers with high school degrees, the study shows.

Eventually, AI will be a significant factor in the future work lives of relatively well-paid managers, supervisors and analysts, according to the report.

Nobody can predict the future, said Dan Ventura, a computer science professor at Brigham Young University who specializes in artificial intelligence research.

While the studys methodology and predictions are kind of cool and better than nothing, theyre just that: predictions, Ventura explained. And the study acknowledges its shortcomings, too.

While the present assessment predicts areas of work in which some kind of impact is expected, it doesnt specifically predict whether AI will substitute for existing work, complement it, or create entirely new work for humans, the study reads.

AI is getting disturbingly good at pattern recognition and pattern matching, including tasks like facial recognition or medical diagnosing from images, Ventura said. But it falls short in other areas.

AI is not good at judgement right now. And even to the extent that it is good at judgement, people dont trust it and dont know if they can trust it. So theyre not going to turn that kind of thing over to AI. At least, they shouldnt, he said.

So while Ventura believes jobs that require skills like pattern recognition may be threatened, those that involve judgment calls are probably safe for a while.

Whats interesting about this (study) is the claim that theyre making that, probably for the first time, this sort of displacement concern, it isnt focused on lower education, lower skill its the other kind of people that theyre worried about. And I think thats pretty interesting, even if Im not sure I buy it all the way, he said.

Ventura does predict, however, that even if AI replaces certain high-skill jobs, new jobs will pop up in response. The rise of artificial intelligence will most likely require (at least in the beginning) something like AI quality control to ensure that the new technology isnt making mistakes.

AI is not good at judgement right now. And even to the extent that it is good at judgement, people dont trust it.Dan Ventura, BYU computer science professor

And while the rise of AI may cause some workforce casualties along the way, Ventura expects the labor market will adapt to the technological advancements, as it has throughout all of human history.

Mark Knold, chief economist of Utahs Department of Workforce Services, agrees.

His research shows that there simply arent enough workers to maintain the size of the U.S. economy as it stands. Instead, the labor market must either allow more immigrants into the country, let the economy shrink in size, or let machines do some of the work, he said.

Artificial intelligence wont replace workers, it will replace missing workers, he argues.

"A lot of these studies can leave you the impression with a fear of the future, Knold said. I think thats the wrong takeaway from studies like this. Theres always new technologies coming that threaten old technologies and workers in those old technologies. But yet, as time goes on, they transition to the new ones, and things are even bigger and better.

If workers are going to be ready to adapt to the change artificial intelligence brings to the workforce, education will need to adapt too, Ventura explained.

But the BYU professor believes the states educational system is already behind, even at the university level.

In my little computer science environment, were not out of touch with it at all, he said. But if you look at the general education program (at BYU), theres nothing. Theres no computer science (or) algorithmic stuff in general education. Its just not a thing.

Utahs fast-growing tech companies have been aware of a talent gap for awhile as they scramble to find employees to fill their ever-expanding needs. But research shows that unless children are exposed to computer science at an early age, theyre much less likely to choose it as a career.

While Utah is working to bring computer science to all K-12 schools in the state by 2022, its a difficult feat, and educational curriculums dont change nearly as fast as technology.

If this AI boom continues to happen, and technology continues to march forward, and we see some of these paradigm-shifting kinds of things, thatll just make us even more behind, Ventura said.

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Artificial intelligence will affect Salt Lake, Ogden more than most areas in the nation, study shows - KSL.com

AI will help in better administration of justice delivery and constitution, says Chief Justice Of India SA Bobde

Automation will, however, not replace humans, CJI adds

Authorities will continue to use human translators to validate and correct output of AI-based tools

After creating waves across startups, artificial intelligence (AI) seems to have now entered the doors of justice. The Chief Justice of India, SA Bobde, has recently said that the Supreme Court has proposed to introduce a system of AI which would help in better administration of justice delivery and constitution.

The CJI also made it clear that the automation would not replace humans. He said that the judiciary would continue to rely on the knowledge and wisdom of judges and the deployment of an AI integration would help reduce the number of pending cases and improve the efficiency of the judicial system.

We propose to introduce, if possible, a system of artificial intelligence. There are many things which we need to look at before we introduce ourselves. We do not want to give the impression that this is ever going to substitute the judges, said the CJI at the Constitution Day function organised by the Supreme Court Bar Association.

Reiterating how automation would not take away jobs, Justice Bobde said the law functions in a uniquely complex environment that lawyers and judges are best placed to navigate. He also said that the authorities would continue to use human translators to validate and correct the output of the AI-based translation tools.

Union Law Minister Ravi Shankar who was also present at the Constitution Day function said that India had started a startup movement in 2015 and India has now become the third-largest country in terms of startups. He also said that more than 24K startups have come up since 2015 out of which more than 10K are startups on information technology.

Indian startups have been changing the face of many industries including ecommerce marketing, banking, healthcare, fintech among others by deploying AI.

Bill Gates, who was on a three-day visit to India, also spoke about how startups in India have revolutionized the healthcare sector by using automation. Gates spoke about how smartphones are changing how chronic diseases are detected. He also added that this kind of technology has helped the world make a lot of progress. We have miracle tools provided by current AI, like cancer detection. What we have today is a tool that can take AI and create an ultrasound device where when a woman is pregnant is going to see if it is going to be a complicated pregnancy, he added.

With hundreds of companies across verticals moving their data to the cloud, AI has become very important and Indians are contributing a lot towards the global AI ecosystem. The government is also looking to solve bring huge data sets to the public domain for startups to leverage and create solutions in more sectors.

Read more from the original source:

SC Proposes Introduction Of Artificial Intelligence In Justice Delivery System - Inc42 Media

DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence in Precision Health" book from Elsevier Science and Technology has been added to ResearchAndMarkets.com's offering.

Artificial Intelligence in Precision Health: From Concept to Applications provides a readily available resource to understand artificial intelligence and its real time applications in precision medicine in practice. Written by experts from different countries and with diverse background, the content encompasses accessible knowledge easily understandable for non-specialists in computer sciences. The book discusses topics such as cognitive computing and emotional intelligence, big data analysis, clinical decision support systems, deep learning, personal omics, digital health, predictive models, prediction of epidemics, drug discovery, precision nutrition and fitness. Additionally, there is a section dedicated to discuss and analyze AI products related to precision healthcare already available.

Key Topics Covered:

Section 1: Artificial Intelligence Technologies 1. Interpretable Artificial Intelligence: Addressing the Adoption Gap in Medicine 2. Artificial Intelligence methods in computer-aided diagnostic tools and decision support analytics for clinical informatics 3. Deep learning in Precision Medicine 4. Machine learning systems and precision medicine: a conceptual and experimental approach to single individual statistics 5. Machine learning in digital health, recent trends and on-going challenges 6. Data Mining to Transform Clinical and Translational Research Findings into Precision Health

Section II: Applications and Precision Systems/Application of Artificial Intelligence 7. Predictive Models in Precision Medicine 8. Deep Neural Networks for Phenotype Prediction: Application to rare diseases 9. Artificial Intelligence in the management of patients with intracranial neoplasms 10. Artificial Intelligence to aid the early detection of Mental Illness 11. Use of Artificial Intelligence in Alzheimer Disease Detection 12. Artificial Intelligence to predict atheroma plaque vulnerability 13. Decision support systems in cardiovascular medicine through artificial intelligence: applications in the diagnosis of infarction and prognosis of heart failure 14. Artificial Intelligence for Decision Support Systems in Diabetes 15. Clinical decision support systems to improve the diagnosis and management of respiratory diseases 16. Use of Artificial Intelligence in Neurosurgery and Otorhinolaryngology (Head and Neck Surgery) 17. Use of Artificial Intelligence in Emergency Medicine 18. Use of Artificial Intelligence in Infectious diseases 19. Artificial Intelligence techniques applied to patient care and monitoring 20. Use of artificial intelligence in precision nutrition and fitness

Section III: Precision Systems 21. Artificial Intelligence in Precision health: Systems in practice

Authors

For more information about this book visit https://www.researchandmarkets.com/r/i5n12k

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2019 Artificial Intelligence in Precision Health - Dedication to Discuss & Analyze AI Products Related to Precision Healthcare Already Available -...

Adam Spunberg, Global Director of Tech Exploration

On November 19, APICS (American Production and Inventory Control Society, now known as ASCM, Association for Supply Chain Management) hosted a representative from Anheuser-Busch InBev who specializes in artificial intelligence (AI) and machine learning innovation. The representative, Adam Spunberg, works out of the Newark office and is the global director of tech exploration.

In his position Spunberg monitors and oversees innovation in the supply chain area of the company. Additionally, he focuses on bringing the company together through new technology and using AI to do something spectacular that couldn't be done before. Through his experience, he has learned that innovation is a mixture of having great ideas and then generating support for those great ideas. Anheuser-Busch InBev has four main checkpoints for filtering these innovative ideas: idea prioritization, quality check, zone demand and direct sponsorship.

Idea prioritization focuses on filtering through ideas to find the most prominent and useful for the industry. Quality check ensures that the innovative idea doesn't exist in another company or at another Anheuser-Busch InBev location. Zone demand is analyzing which areas or satellite locations have the need for this innovation. Lastly, direct sponsorship refers to getting the support from the appropriate people needed within the company to move forward.

Building upon these checkpoints, Spunberg was able to share a variety of projects that Anheuser Busch InBev has been pursuing with the use of AI and machine learning. One project has included the use of AI video training. This project uses an online video library that has videos on how to complete every necessary task in the breweries. Using AI, the words spoken in these videos can be broken down into written text that becomes the captions in the video. Additionally, this AI software can translate both the audio and captions into another language.

Additionally, AI is being used to identify packaging defects within the factory assembly lines. This is achieved through a model that quickly snaps pictures of cans flowing through the assembly line. The software is then able to compare these pictures to existing pictures in order to determine if the individual can is in either good or bad quality. This allows the quality checking process for packaging defects to shift from manual labor to a technological feat.

Another use of AI is the advanced process control project, which offers a digital version of a production environment. More specifically, Anheuser Busch InBev replicates the environment of steam generation from a boiler in a model that accounts for the many variables expressed in the real-life environment. Once the digital environment is proven to be accurate to the real-life environment, then the proprietor can test different situations and events in this digital environment.

Spunberg also spoke about AI filtration optimization, which is not only applicable to Anheuser Busch InBev, but also many other companies and students. Anheuser Busch InBev utilizes Microsoft as their cloud computing basis. However, this prevents them from being able to utilize Google cloud and the services Google offers. In order to remedy this, AI has been used to develop new, cutting edge technology that creates an extra gateway layer that can process Google documents and data into Microsoft outputs.

As Spunberg concluded his presentation he emphasized, "Find your humanity in AI" -- highlighting the importance of giving back to less fortunate communities with the power that AI can bring. Using geo systems, Spunberg hopes to be able to optimize routes for the distribution of necessary supplies in third world countries. "Try to think about what you can do to leave your mark on the world and make life better for others."

Read more here:

Global Director of Tech Exploration Discusses Artificial Intelligence and Machine Learning at Anheuser-Busch InBev - Seton Hall University News &...

Expert insights on taking personalization to the next level.

November25, 20194 min read

Opinions expressed by Entrepreneur contributors are their own.

Michael Bower helps companies provide cool experiences to their customers on the web. As CEO of Sellry, an ecommerce solutions company, he combines creativity with the latest technology to propel brands into the future. Alongside clients, Sellry works to reimagineand designthe future of ecommerce.

What new technology do you think will greatly impact consumer-facing startups in the near future?

AR is going to completely change many industries. We've seen applications where you can just point your phone at something and it'll tell you about it. We've also seen smart mirrors. There's even APIs where it'll measure your body from a photograph with a degree of accuracy. A lot of these APIs are nearly real-time. Some of them can even look at multiple different subjects at the same time and figure out many things about them. It's the future.

Related:The Future ofAugmented Reality(Infographic)

How soon do you think this will be a common practice?

We did an experiment this year. We built out an augmented reality experience of an imaginary office space for an ecommerce trade show. We wanted to see how relatable it was.Would people get it? Would they understand it? And what we found was, it's still a little bit early. Enterprises are toying with the idea, some of them are trying things, especially in the sports and entertainment industries. Fashion is obviously trying things for sizing. I think that we're looking at 2021 for when we pass that early adopter stage and start getting into the early majority.

What industry do you think will be the first to benefit from AR?

I think certain industries like real estate, architecture and B2B sales will adopt it faster because AR will give them the ability in the fields to conduct a demonstration or to evaluate a pitch better. There are enormous companies in those spaces already investing absolutely insane amounts of money into AR.

What about artificial intelligence? How are companies using it to enhance the customer experience?

If you've ever looked at the cookies that are stored on your machine, they're crazy. Some of them will think that you're probably into things that you're totally not into. I've looked at my cookies and been like, Wow, they think I'm interested in soap operas, which I'm totally not. Cookies are notoriously unreliable. And that's what most people are using for advertising and retargeting. Basically, its a "spray and pray" approach. What we want to do is help companies take better advantage of their audience, the people that are on their site and telling them real things about themselves.

Related:4EcommerceTrends to Watch

Can you give an example?

Let's say that we're dealing with a supplements company. Right now, we're segmenting based on a few factors, and we think we know who our customer is. And we've done a lot of testing that is assumption based. Meaning we're taking things that we already know and we're using that to drive our decision-making. Now, the AI tooling for this stuff is already in principle there, where you can just turn on artificial intelligence and it'll figure out who your customer is, how you should message them, what is the cadence of doing that. But right now for the mid-market and even for certain specialized enterprise markets, the AI tooling takes a long time to deploy, so it's not quite there all the way in a deployable manner.Within a couple of years it will be.

How can companies that currently dont use data science prepare to implement artificial intelligence as it becomes more widely available?We encourage companies to really dial into customer discovery and understanding the customer deeply. And then build out a higher fidelity version of current generation personalization and segmentation going on. And then based on that, within the next couple of years we're wanting to have the ability to deploy for our clients technical wizardry that's going to basically take those human-defined segments and personas, and take them even farther. AI-based segmentation and the ability for the mid-market to adopt AI is going to be super amazing and exciting.

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How Augmented Reality and Artificial Intelligence Are Helping Entrepreneurs Create a Better Customer Experience - Entrepreneur

Manufacturing plays a central role in the global economy, and its a field where the promise of artificial intelligence (AI) is clear driving productivity, growth and employment.

But with the manufacturing sector among the first to reap the benefits of AI at scale, industrial businesses will also find themselves at the forefront of responding to some of the challenges of AI, from skills and culture, to ethics and responsibility.

It is these responses that will define our collective and individual success. Chris Harries, worldwide manufacturing industry solutions director for Microsoft, took to the main stage at Manufacturing Leaders Summit 2019 to explain more.

He began by charting the start of the First Industrial Revolution when the steam engine first appearance on the scene and changed the course of human history.

Almost everything we understand about how goods are produced, how societies are organised and how economies operate can be traced back to that moment, Harries noted.

Today, we are in the early stages of another technology-driven transformation; the catalyst this time is artificial intelligence (AI).

Harries described AI as a collective term for technologies that can sense their environment, think, learn and take action in response to what theyre sensing and their objectives.

At the granular level, AI can be built into processes we already run today, such as HSE compliance (see image right), as well as to create completely new solutions and capabilities, he continued.

Taken collectively the potential for change is vast, and like the First Industrial Revolution, manufacturing is again leading the way in adopting a new technology to create new products and services, transform processes, and revolutionise productivity.

Unlike with the First Industrial Generation, we wont need to wait a century to feel the full effects.

Over just the past couple of years, AI has already transformed how we work, live, learn, and play in dramatic ways. And the pace of change is accelerating.

The promise of AI in manufacturing hasnt been definitively calculated, with various studies and projections offering a wide spectrum of potential:

With our customers, were seeing the early signs of realising benefits through AI, most often through improved product quality, production and supply chain efficiencies, and the effectiveness of their service operations, Harries explained.

But as the sector starts to reap the benefits of AI, manufacturers also find themselves at the forefront of responding to some of the challenges.

Earlier this year, Microsoft collaborated with author Greg Shaw to publish The Future Computed: AI for Manufacturing.

In researching for the book, Shaw interviewed dozens of customers, policy makers, labor representatives and other stakeholders from around the world to find the story behind the impact of AI on the manufacturing sector and its workforce.

Through the course of these interviews, six themes began to emerge:

1. Manufacturers around the world are already seizing the AI opportunity.

More than that, they are seeing that the value of AI extends beyond productivity to include everything from workplace safety to process efficiencies, predictive maintenance, intelligent supply chains, and higher value, higher quality products.

2. To take full advantage of AI, companies are undergoing a cultural transformation that requires strong, committed leaders and engaged workers who are involved in decisions-making and implementation at every level of the process.

Companies seeing the greatest gains from AI today are those that are embracing change and eliminating the barriers between information systems and people, so they could create a seamless information supply chain that utilises their entire digital estate.

Removing these barriers is just as much about corporate culture as it is about technology implementation.

3. The managers inside production operations who are closest to the workforce care the most about AIs impact on employees.

Their focus on creating a better company translates to a commitment to create safer work environments, and to increasing productivity through providing better opportunities and fewer repetitive and unsatisfying jobs.

And because they put their people first, they are eager to adopt technologies that will have a positive impact on workers.

4. There is widespread optimism that AI will lead to more and better jobs over the long term; but disruption and dislocation are inevitable.

Everyone is concerned that manufacturing will face a significant talent shortage and wonders where the next generation of bright students with the right skills and training will come from.

Therefore, there is a very real need to create a talent pipeline filled with people who have the knowledge and capabilities to fill tomorrows manufacturing jobs.

Businesses, governments, educational institutions and labor organisations will all need to work together to forge new partnerships that are focused on skills and workforce development.

5. Its not just about digital skills, this new generation of technologies will also need a new generation of policies and laws.

It is clear that as manufacturers implement AI into their processes and incorporate it in their products, they are looking for new guidelines and updated legal frameworks that will clarify their obligations and help them anticipate potential issues.

To encourage the adoption of AI technologies in ways that strengthen worker safety, create more jobs, and promote economic growth and national competitiveness, regulators are eager to update existing laws so that they reflect the realities of our digital world.

6. AI is a journey and it will be different for everyone. And deploying AI is fundamentally different than implementing traditional software solutions.

This is not a build once, roll out worldwide technology that can be left in the hands of the IT team. For companies to reap the full benefits, AI systems need to continuously learn.

They must also be trained, monitored, evaluated and improved to guard against unconscious bias, and to avoid privacy violations and safety issues.

To ease the way forward, Microsoft has produced a framework to help companies assess their needs and determine what AI solutions to implement, and when.

This operational model begins at the foundational level for companies that are just beginning to explore what AI really is and how it can help them become a data-driven organisation.

It then moves through increasing levels of knowledge, culture change, and digital expertise until companies reach the level of maturity and tech intensity needed to apply AI ethically, responsibly, and successfully across their organisation.

Earlier this year, Microsoft in partnership with INSEAD also launched the AI Business School, a free, on-demand, masterclass series designed specifically for business leaders to empower them to get results from AI.

The course covers setting an AI strategy, enabling an AI-ready culture, fostering responsible and trustworthy AI, and finally an introduction to the full range of AI technologies that you could use to transform your organisation and ecosystem,

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Manufacturing Leaders' Summit: Realising the promise of Artificial Intelligence - Manufacturer.com

Artificial Intelligence (AI) is a key driver for innovation in the global digital reality market, which includes immersive technologies such as virtual reality (VR), augmented reality (AR), X Reality (XR or Cross Reality) and Artificial Intelligence (AI) itself. Various reports project that advancements in technology such as 5G, artificial intelligence, edge computing, and robotics are expected to transform the augmented and virtual reality experiences in the near future. One by ResearchAndMarkets stated that: The immersive technology market, including augmented and virtual reality, is expected to see huge growth in the next 5 years. Technological advancements such as 5G and artificial intelligence will transform the augmented and virtual experiences in the future. 5G will bring improved mobile broadband along with advanced capacity, more uniform experience with steadily high data rates, and lower latency which will improve the screen and equipment quality of AR and VR devices. Some of the significant impacts of 5G across sectors could be enabling virtually crafted workplaces and fully interactive and emulating in-office work environments. Active companies in the markets this week include Micron Technology, Inc.,Hawkeye Systems, Inc.(OTCQB:HWKE),NVIDIA Corporation(NASDAQ:NVDA),Intel Corporation(NASDAQ:INTC),International Business Machines Corporation(NYSE:IBM).

Thereportprojected that: The AR and VR market revenue is expected to reach$55.01 billionby 2021. Growth will mainly be derived by AR and VR applications in manufacturing and simulation modeling. This transformation will give rise to future opportunities in sectors such as media, gaming, telepresence, retail, medicine, and education. The hardware market of AR and VR will grow tremendously by 2021, mainly due to a 10-fold increase in AR and VR headset shipments by 2021. VR application in the manufacturing sector is projected to increase by 98.9% between 2017 and 2021. AR application in the education and training sector will see tremendous growth by 2021 due to rising investments in smart cities development and defense security applications.

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Hawkeye Systems, Inc.(OTCQB:HWKE)NEWS:Hawkeye Systems Future Subsidiary Issued Patent on Groundbreaking Technology Advancing Holographic Capture HawkeyesRadiant Images, a Company under contract to be acquired by Hawkeye Technologies, Inc., today announced that the United States Patent and Trademark Office has issued US Design Patent 860,296 covering immersive capture systems utilized for holographic imaging. This proprietary technology is applicable for rapid development in immersive technologies such as virtual reality (VR), augmented reality (AR), X Reality (XR or Cross Reality) and Artificial Intelligence (AI).

The newly patented technology is the latest in a string of accomplishments and accolades for Radiant Images, including three industry awards in recent months for technical achievements in the field of immersive technology and artificial intelligence. Also, in early 2019, Radiants proprietary technology, utilized in its AXA Stage, was installed at Sony Pictures for its next-gen innovation movie studios.

We have built a reputation as explorers and innovators in the area of capture technology, and our breakthrough achievements make us well positioned to continue to lead the way to the next level, saidMichael Mansouri, co-founder of Radiant Images. The seemingly impossible in now achievable. Its an exciting time.

Radiant Images proprietary AXA Volumetric Capture Stage System is an accurate and adaptive volumetric and light field stage, utilizing highly accurate camera positioning for volumetric, light field, and AI software. The modular system supports 100+ cameras inside a sphere and captures from every possible viewpoint to create a more engaging and dynamic immersive experience for virtual reality, augmented reality, XR and all forms of immersive experiences and future communication devices.

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The AXAs camera positioning accuracy is the key to automation and algorithms for all volumetric and light field capture, placing the capturing system on the forward edge of this technology.

The patent is part of an intellectual property portfolio at Radiant Images that includes numerous other patent-pending applications that together are dramatically accelerating the next technology cycle for the entertainment industry and beyond.

Radiant is focused on applying its core technologies to help advance artificial intelligence, WAMI Wide Area Motion Imaging, and automotive and manufacturing line scanning. Its systems providing live streaming and real-time image analysis of immersive 360-degree video can be applied to a variety of industries and use cases, from the battlefield to the factory floor.

Micron Technology, Inc.(NASDAQ:MU) recently unveiled the worlds highest-capacity industrial microSD card Micro i300 1TB microSDXC UHS-1 to address the edge storage needs of the video surveillance market and other industrial applications. The new Microni300 1TB microSD card is based on Microns advanced 96-layer 3D quad-level cell (QLC) NAND technology, now making it cheaper for small- to medium-sized deployments to have primary storage in the camera compared to a centralized storage architecture. The i300 microSD card enables users of video surveillance systems to capture and store more than three months of high-quality video footage on-device and at the edge.

Microns i300 industrial-grade microSD cards for edge storage open the possibility for a broad range of video surveillance as a service deployments that no longer require local network video recorders, saidAmit Gattani, senior director of Segment Marketing in Microns Embedded Business Unit. Microns 96-layer 3D QLC NAND is instrumental in helping us deliver 1TB of storage in a microSD form factor and at a breakthrough price point to accelerate edge storage and cloud-based service models.

NVIDIA Corporation recently introduced NVIDIA Magnum IO, a suite of software to help data scientists and AI and high performance computing researchers process massive amounts of data in minutes, rather than hours. Optimized to eliminate storage and input/output bottlenecks, Magnum IO delivers up to 20x faster data processing for multi-server, multi-GPU computing nodes when working with massive datasets to carry out complex financial analysis, climate modeling and other HPC workloads.

Intel Corporationrecently unveiled its vision for extending its leadership in the convergence of high-performance computing (HPC) and artificial intelligence (AI) with new additions to its data-centric silicon portfolio and an ambitious new software initiative that represents a paradigm shift from todays single-architecture, single-vendor programming models.

Addressing the increasing use of heterogeneous architectures in high-performance computing, Intel expanded on its existing technology portfolio to move, store and process data more effectively by announcing a new category of discrete general-purpose GPUs optimized for AI and HPC convergence. Intel also launched the oneAPI industry initiative to deliver a unified and simplified programming model for application development across heterogenous processing architectures, including CPUs, GPUs, FPGAs and other accelerators. The launch of oneAPI represents millions of Intel engineering hours in software development and marks a game-changing evolution from todays limiting, proprietary programming approaches to an open standards-based model for cross-architecture developer engagement and innovation.

International Business Machines Corporationrecently announced Cloud Pak for Security, featuring industry-first innovations to connect with any security tool, cloud or on-premise system, without moving data from its original source. Available today, the platform includes open-source technology for hunting threats, automation capabilities to help speed response to cyberattacks, and the ability to run in any environment.

Cloud Pak for Security is the first platform to leverage new open-source technology pioneered by IBM, which can search and translate security data from a variety of sources, bringing together critical security insights from across a companys multicloud IT environment. The platform is extensible, so that additional tools and applications can be added over time.

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Artificial Intelligence Will Facilitate Growth of Innovative Kinds of VR and AR Platforms - AiThority