Top 10 emerging technologies of 2019

By TheWAY - 6월 27, 2019

The Internet of Things (IoT) is the emerging technology offering the greatest opportunities to create new business and revenues, according to CompTIA's second annual Top 10 Emerging Technologies report, released Monday.

The 10 technologies named in the report were ranked according to the near-term business and financial opportunities each creates for IT firms and other business technology companies, and selected by the organization's Emerging Technology Community.

1. IoT

IoT is driving business changes by providing the data needed to improve marketing, increase sales, and decrease costs, the report found.

"Everybody in the technology world, as well as many consumers, is hearing the term Internet of Things," Frank Raimondi, a member of the CompTIA Emerging Technology Community leadership group who works in strategic channel and business development for Chargifi, said in a press release.

However, "to say it's confusing and overwhelming is an understatement," he added. "IoT may mean many things to many people, but it can clearly mean incremental or new business to a channel partner if they start adding relevant IoT solutions with their existing and new customers. More importantly, they don't have to start over from scratch."

2. Artificial Intelligence (AI)

AI is already significantly impacting the way customers interact with businesses via intelligent websites and bots, and these tools are becoming increasingly commoditized and integrated into daily work, the report noted.

"The largest impacts across all industries—from retail to healthcare, hospitality to finance—are felt when AI improves data security, decision-making speed and accuracy, and employee output and training," Maddy Martin, community vice chair and head of growth and education for Smith.ai, said in the release. "With more capable staff, better-qualified sales leads, more efficient issue resolution, and systems that feed actual data back in for future process and product improvements, companies employing AI technologies can use resources with far greater efficiency. Best of all, as investment and competition increase in the AI realm, costs are reduced."

3. 5G

The rise of 5G networks is increasing our ability to move, manipulate, and analyze data across wireless platforms, according to CompTIA. As 5G rolls out more fully in the coming years, it will drive the development of more complex apps to solve problems and increase growth across industries.

"The development and deployment of 5G is going to enable business impact at a level few technologies ever have, providing wireless at the speed and latency needed for complex solutions like driverless vehicles," Michael Haines, community chair and director of partner incentive strategy and program design for Microsoft, said in the release. "Additionally, once fully deployed geographically, 5G will help emerging markets realize the same 'speed of business' as their mature counterparts. Solution providers that develop 5G-based solutions for specific industry applications will have profitable, early-mover advantages."

4. Serverless computing

Serverless computing allows organizations to create a NoOps IT environment that is automated and abstracted from underlying infrastructure, reducing operational costs and allowing businesses to invest in developing new capabilities that add more value, the report found.

Serverless computing was new on the list this year, along with robotics, replaced quantum computing, and automation, CompTIA noted.

5. Blockchain

More organizations are exploring and implementing blockchain to solve the increased need to secure and manage transactions across the internet.

"Blockchain came down crushing from its peak of hype cycle, and that's probably for the best," said Julia Moiseeva, a member of the community's leadership group and founder of CLaaS (C-Level as a Service) Management Solutions Ltd, in the release. "Now that the luster of novelty and furor of the masses are gone, the dynamic of work around blockchain took a complete U-turn, again, for the best."

6. Robotics

Robotics is automating routine processes by using machines to make businesses faster, less expensive, and more efficient, the report found.

7. Biometrics

Biometrics—including face, fingerprint, and retina scans—are becoming mainstream methods for verifying identity. These methods will form the secure foundation for solutions delivered by IT companies moving forward, CompTIA said.

8. 3D printing

3D printing offers a solution for the low volume manufacturing of complex parts, as well as fast local production of difficult-to-find products, the report noted. As more affordable products become available, opportunities for this industry will continue to grow, it added.

9. Virtual reality (VR)/Augmented reality (AR)

Using VR, AR, mixed reality, AI, and sensor technologies can help organizations improve operational efficiency and individual productivity, according to the report.

10. Drones

Drones enable robotic automation with fewer geographical restrictions, the report noted. Opportunities for development and integration are high for this market, it added.

For more, check out 5 tech trends your business can't afford to ignore on TechRepublic.

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Does Big Data have a pivotal role in the future of customer experience?

By TheWAY - 6월 18, 2019

Does Big Data have a pivotal role in the future of customer experience?

Big Data is very important, and there is no doubt about this fact. Big Data has proven its mettle over the period of time. It has definitely become one of the most valuable, innovative and exciting technological offerings for the world.

A huge collection of information is collected from a wide variety of sources. That data is maintained and analyzed. Then, the companies can churn out useful insights from the huge pool of information. Therefore, at the end of the data analysis is the key.

The trick is how to find out which data needs to be analyzed and for what. First, companies need a Big Data strategy to analyze the data. The strategy should also include the main purpose of Big Data. For example, say if a company wants to find out useful insights pertaining to the market conditions or the industry trends, they will have to collect and analyze the data related to the market and the industry.

Big Data is used by plenty of different teams and parts of the company. Apart from being used extensively by the sales and marketing teams, Big Data is used by the customer service teams of the firm. In fact, Big Data consulting helps the companies to understand their customer and the target audience better.

Customer Experience is becoming more important

Every profit generating business is reliant on the number of clients and customers. The main aim of every business is to amplify the number of customers and clients. However, customer retention also plays a major role. The company can gain benefits by attracting more customers and clients, but it is also important for them to retain the existing set of customers. In fact, they can even try to get more business from existing customers and clients. This is exactly where the role of customer experience comes into the picture. Only if a customer is happy with the company will he or she stick with a business.

Here’s how Big Data helps to improve the customer experience:

Big Data helps to understand the customer' purchase history

A company can learn a lot about the customer through their purchase history. Thus, if you want to offer more suggestions and recommendations to the customers, then first, it is important to analyze the data related to the purchase history of the customer. The insights generated from the analysis will help the firms to know more about the customers, thus, they will be in a better position to offer products, services and even suggestions to the customers. And, better suggestions and recommendations surely amplify the customer experience offered to the customers.

Big Data analysis makes it easy to know the behavioral pattern of the target audience

Personalization and customization play a major role when it comes to offering good customer experience. To offer a much more personalized and customized customer experience, a company has to study its target audience and its customers better. The insights related to the behavioral patterns, interests, demands and needs of the customer will help the company to offer a better experience. With the help of Big Data analysis, companies can also track the complete journey of the customer, which eventually help us to know more about the customer.

Big Data plays a major role in enhancing the customer experience that a company offers. With the help of Big Data, companies can understand their customers better, thus, they are in a position to curate much more powerful and effective campaigns. At the same time that Big Data is generated from various sources, a wide range of information can be collected, and much more useful insights can be generated. It is important for the company to understand its customers better, and to offer them a remarkable customer experience.

source : https://www.business.com/articles/big-data-role-in-the-future-of-customer-experience/

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14 Essential Leadership Skills For The 4th Industrial Revolution

By TheWAY - 6월 16, 2019

14 Essential Leadership Skills For The 4th Industrial Revolution

Just because your colleagues in the future workplace will include artificial intelligence and bots, doesn’t mean that human leadership skills won’t be necessary. In fact, leadership skills will be vital to success. Tomorrow’s fast-moving, interconnected and technology-driven world will require leaders to adapt to the new realities of the 4th industrial revolution in order to succeed. While some individuals are born with innate leadership abilities, the leadership skills of the future workplace can also be learned by individuals with a passion for doing so.

15 Essential Leadership Skills During The 4th Industrial Revolution

14 Essential Leadership Skills During The 4th Industrial Revolution

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14 Leadership Skills of the Future Workplace

Actively Agile

Due to the speed of change in the future workplace, leaders will have to agile and able to embrace and celebrate change. Successful leaders during the 4th industrial revolution will see change not as a burden but as an opportunity to grow and innovate.

Emotional intelligence (EQ)

Just as employees will need a healthy amount of emotional intelligence, it will be critical for leaders in the future workplace to be able to perceive, understand and manage emotions—theirs and their team’s.

Humbly Confident

Tomorrow’s leaders will need to find a balance between confidence in their own abilities and decisions, and being humble about their place in the organization. Future leaders will take all the unique skills of the team working together to drive initiatives and leaders won’t be viewed as the critical cog to success. Tomorrow’s leaders will encourage others to shine.

Accountable

Leaders will need to earn the respect of their team by holding themselves accountable. The workplace of the future will become more transparent and collaborative. In this environment, it’s crucial for a leader’s actions to be in alignment with the company’s goals and objectives.

Visionary

In any organization there are multiple stakeholders and a future leader will need a big-picture vision and be able to understand how each stakeholder, whether it's employees, suppliers, shareholders or another, will be impacted by decisions. This requires a leader to strategically determine how to meet all stakeholders' needs effectively.

Courageous

There won’t be a clear roadmap to follow in the workplace of the future. This requires a leader to have the courage to face the unknown and navigate difficult circumstances. Possibly even more essential is the courage to change course in the event the situation calls for a new strategy.

Flexible

Leaders will need flexibility in the future to accommodate the shifting demands of workers, workspaces, and tools. What resulted in success in the past won't be the formula for tomorrow's success, so leaders need to flex to accommodate the new reality. And, the reality is expected to shift regularly, so leaders won't be able to be complacent.

Tech Savvy

The 4th industrial revolution fuelled by technologies such as artificial intelligence, blockchain, robotics, internet of things, big data, augmented reality, and more. Just about every industry and company will change because of technology. Leaders will need to understand and have conversations and make decisions about technology. The ability to understand what tech can do for an organization is essential, and leaders must continuously embrace new platforms and tech tools.

Intuitive

As a result of the influx of machines into the future workplace, leaders will need to be even more human. A human’s intuition is the ability to “read” what’s not being said and is at the moment a uniquely human skill. A leader who is willing to have conversations around what’s not being said and to hear the good, bad and ugly from their team will be poised for future success.

Collaborative

Future leaders won’t stay in their corner office. It will be imperative that leaders in the future work alongside their employees and get to know their strengths and weaknesses to help them acquire new skills and help drive their professional development. They will be very collaborative.

Quick learners

Leaders will need to quickly assess a situation and learn what they need in order to make effective decisions. Along with this, they will need to be open to coaching and learning from the subject matter experts on their team.

Culturally intelligent

Our future workplaces will be diverse and global. Effective leadership requires someone adept at appreciating and leveraging the differences every individual brings to the team from their individual perspectives.

Authentic

With a multigenerational and multicultural workforce, leaders will need to exude authenticity. These are the ones best able to build connections and trust. Leaders will need to be authentic in times of uncertainty and failure just as they need to be when they are excited about success.

Focus

While the pace of the future workplace will be quick and it will require flexibility, a future leader will need to maintain focus on the objectives of the organization. They provide the stability employees need even when the pace of change could make it easy to pivot from one priority to another. A strong leader will be able to cut through the chaos and make sure everyone knows what’s important.

source : https://www.forbes.com/sites/bernardmarr/2019/05/13/15-essential-leadership-skills-during-the-4th-industrial-revolution/#7de715fda3a0

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How Far Are We From Achieving Artificial General Intelligence?

By TheWAY - 6월 14, 2019

How Far Are We From Achieving Artificial General Intelligence?

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These days, when you browse the internet for news on artificial intelligence, you’ll find out about new AI that just managed to do something humans do, yet far better. Present day AI can detect cancers better than human doctors, build better AI algorithms than human developers, and beat the world champions at games like chess and Go. Instances like these may lead us to believe that perhaps, there's not a whole lot that artificial intelligence can not do better than us humans. The realization of AI’s superior and ever-improving capabilities in different fields has evoked both hope and caution from the global tech community as well as the general public. While many believe the rise of artificial general intelligence can massively benefit humanity by raising our standard of living and status as a civilization, some believe the development may lead to global doom.

While the debate on whether the development of artificial general intelligence or artificial superintelligence is promising or pernicious rages on, the jury on when such advanced forms of AI will come into existence is also still out. These are important questions that do deserve the coverage and debate they are subjected to. However, before worrying about the future of AI it is necessary to first know what artificial general intelligence exactly is, what it would take to achieve it, and how far existing AI capabilities are from getting there.

What is the current state of artificial intelligence?

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The internet abounds with stories of stunning applications that exist today, culminating from years of artificial intelligence research. Similar to the aforementioned example of AI systems that can diagnose cancers with greater accuracy than human doctors, there are many other fields where specialized artificial intelligence is replicating human-like reasoning and cognition.

For instance, deep learning algorithms used by social media sites are becoming increasingly adept at recognizing objects, people, and even detailed characteristics of these objects and people. Modern computer vision technology driven by deep learning can now identify people in images posted to social media, the position of the person in the image, their expressions, and any accessories they might be wearing. This gives AI systems the ability to perceive images similar to the way humans do. These systems can go beyond simply identifying people from images and even analyze subtle patterns to discern non-obvious attributes. One example is a Stanford University study that shows how deep neural networks can identify people’s sexual orientation just by analyzing their faces -- an ability that is highly unlikely to be present in humans.

Another instance of AI systems performing human-like feats is natural language processing (NLP), where AI can understand speech or text delivered in natural language. AI is becoming proficient in understanding the meaning of text and speech as part of applications such as chatbots and virtual assistants in smartphones (think of Siri, Cortana, etc.) And advancements in natural language generation, which is the generation of information in normal human language, is being used in numerous applications where machines are required to respond to people voice or text.

With such developments, the gap between human intelligence and artificial intelligence seems to be diminishing at a rapid rate. This might give you the impression that powerful artificial intelligence systems or artificial general intelligence systems may not be too far out in the future. However, it is vital to understand that it takes more than just performing specific tasks better than humans to qualify as artificial general intelligence.

What exactly is artificial general intelligence?

Put simply, Artificial General Intelligence (AGI) can be defined as the ability of a machine to perform any task that a human can. Although the aforementioned applications highlight the ability of AI to perform tasks with greater efficacy than humans, they are not generally intelligent, i.e., they are exceedingly good at only a single function while having zero capability to do anything else. Thus, while an AI application may be as effective as a hundred trained humans in performing one task it can lose to a five-year-old kid in competing over any other task. For instance, computer vision systems, although adept at making sense of visual information, cannot translate and apply that ability to other tasks. On the contrary, a human, although sometimes less proficient at performing these functions, can perform a broader range of functions than any of the existing AI applications of today.

While an AI has to be trained in any function it needs to perform with massive volumes of training data, humans can learn with significantly fewer learning experiences. Additionally, humans -- and (perhaps one day) agents with artificial general intelligence -- can generalize better to apply the learnings from one experience to other similar experiences. An agent having artificial general intelligence will not only learn with relatively less training data but will also apply the knowledge gained from one domain to another. For example, an AGI agent that has been trained to process one language using NLP can potentially be able to learn languages having shared roots and similar syntaxes. Such a capability will make the learning process of artificially intelligent systems similar to that of humans, drastically reducing the time for training while enabling the machine to gain multiple areas of competency.

Can AI ever achieve general intelligence?

Artificial intelligence systems, especially artificial general intelligence systems are designed with the human brain as their reference. Since we ourselves don’t have the comprehensive knowledge of our brains and its functioning, it is hard to model it and replicate it working. However, the creation of algorithms that can replicate the complex computational abilities of the human brain is theoretically possible, as suggested by the Church-Turing thesis, which states -- in simple words -- that given infinite time and memory, any kind of problem can be solved algorithmically. This makes sense since deep learning and other subsets of artificial intelligence are basically a function of memory, and having infinite (or a large enough amount of) memory can mean that problems of the highest possible levels of complexity can be solved using algorithms.

How far are we from artificial general intelligence?

Although it might be theoretically possible to replicate the functioning of a human brain, it is not practicable as of now. Thus, capability-wise, we are leaps and bounds away from achieving artificial general intelligence. However, time-wise, the rapid rate at which AI is developing new capabilities means that we might be get close to the inflection point when the AI research community surprises us with the development of artificial general intelligence. And experts have predicted the development of artificial intelligence to be achieved as early as by 2030. A survey of AI experts recently predicted the expected emergence of AGI or the singularity by the year 2060.

Thus, although in terms of capability, we are far from achieving artificial general intelligence, the exponential advancement of AI research may possibly culminate into the invention of artificial general intelligence within our lifetime or by the end of this century. Whether the development of AGI will be beneficial for humanity or not is still up for debate and speculation. So is the exact estimate on the time it will take for the emergence of the first real-world AGI application. But one thing is for sure -- the development of AGI will trigger a series of events and irreversible changes (good or bad) that will reshape the world and life as we know it, forever.

source : https://www.forbes.com/sites/cognitiveworld/2019/06/10/how-far-are-we-from-achieving-artificial-general-intelligence/#3c133cbc6dc4

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Fortnite: How Artificial Intelligence and Analytics Make It More Fun

By TheWAY - 6월 12, 2019

Fortnite: How Artificial Intelligence and Analytics Make It More Fun

The multiplayer online shoot 'em up Fortnite is the most popular video game in the world, with more than 250 million players.

Fortnite: How Artificial Intelligence and Analytics Make It More Fun

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It is also representative of a relatively new paradigm in gaming – one that has altered the software landscape until it has become almost unrecognizable in recent years. Known as games-as-a-service (GaaS), the game is funded through subscriptions and regular transactions by its players rather than a one-off fee.

Although this may not seem all that new to those of us old enough to remember the coin-guzzling likes of Pac Man and Space Invaders, GaaS means the continuous revenue stream funds ongoing development and improvement of the game.

And its cloud-based nature (along with the vast userbase) means huge amounts of data is available to developers Epic – the game generates a staggering two petabytes per month. All of this can be mined for insights into what keeps their players coming back for more – and contributed towards generating $3 billion in profitduring 2018.

Data is the fuel of artificial intelligence. Every piece of data players generate by interacting with each other, and the platform can now be analyzed with smart algorithms and used to make the game more entertaining and immersive, which in turn helps to grow the user base.

These analytics – running on tools including Amazon Sagemaker – are used to identify KPIs such as the length of time players are engaging with the game – be that hours per day or sessions per week – and understand what it is that provides the “hook” that keeps players coming back.

Once this is done, the company can make changes to the game's internal structure, such as deploying different gameplay modes encouraging players to interact in different ways, to drive growth across its key metrics.

Much of Epic’s infrastructure supporting Fortnite is built on Amazon’s AWS cloud service, and the company’s director of platform, Chris Dyl, told AWS Summit in New York “We use the data for everything, from ARPU (average revenue per user) to game analysis and improvements.”

At peak times, the Fortnite analytics pipeline ingests 40gb of data every minute into the Epic data lake, that as of last year was reported to stand at 14 petabytes in size, and to be growing by two petabytes a month.

The precise details of how data is used to improve gameplay and drive player engagement are kept under wraps. But tools and services related to data analytics that it is known to use include Amazon S3, the Apache Spark cluster computing framework, and the Tableau visualization software.

As with other GaaS operations, it is likely that Epic use their data to balance gameplay within Fortnite’s “battle royale” tournaments – free-for-all skirmishes where 100 players compete to be the last man or woman standing in an ever-shrinking arena.

Additionally, design decisions such as the implementation of new gameplay modes will be based on what is learned about the types of battle that are popular with the userbase.

Because battles in Fortnite are relatively free-form, rather than being structured around missions or objectives as is the norm in video games, Epic can use analytics and AI to make interesting psychological observations around player behavior. Will players tend to go it alone in a "lone wolf" fashion, or will they form temporary alliances and pacts to work together on self-determined objectives – such as taking down stronger players or holding strategically important terrain? What level of risk are players willing to take when it comes to exposing themselves or leaving cover, to collect better weapons and equipment? AI can be used to monitor this "emergent" gameplay and adapt the challenge to suit players' style.

Emergent gameplay is nothing too new in gaming and marks a trend away from games where every individual element was hand-crafted by human game designers, towards allowing players to create rules for themselves in a "sandbox" environment. AI is a natural next step in this evolution, enabling the prospect of "virtual referees" that can adapt to what players are doing and ensure the game's infrastructure adapts too, to cope with this behavior.

Epic had also developed a great deal of its own infrastructure itself – way before Fortnite existed, its Unreal Engine was one of the most commonly used gameplay engines in both independent and "triple-A," big studio game design.

Carrying on this tradition, it recently made Epic Online Services freely available – a platform for creating, maintaining, and managing massively multiplayer, cloud-based games.

The move into the cloud and AI technology taken by Epic is driven by its partnership with Tencent, which invested $330 million in exchange for a 40% share of the company in 2012. Tencent is the most gaming-focused of the Chinese tech giants. It has pioneered the development of the cloud, mobile and microtransaction infrastructure rolled out by Fortnite, and now being adopted across the games industry.

SOURCE : https://www.forbes.com/sites/bernardmarr/2019/06/10/fortnite-how-artificial-intelligence-and-analytics-make-it-more-fun/#4cc3dd901b31

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Artificial Intelligence Will Change Healthcare as We Know It

By TheWAY - 6월 10, 2019

Machine learning and deep neural networks have spurred significant advances in artificial intelligence.
Major AI applications in healthcare include diagnostics, robotic surgeries and virtual nursing assistants.
Healthcare AI is projected to reach $6.6 billion in value by 2021.
Adoption of AI could save the U.S. healthcare industry $150 billion annually by 2026.

In Star Wars: The Empire Strikes Back, Luke Skywalker is rescued from the frozen wastes of Hoth after a near-fatal encounter, luckily to be returned to a medical facility filled with advanced robotics and futuristic technology that treat his wounds and quickly bring him back to health. Of course, that's the stuff of science fiction … for now.

The healthcare industry could be headed toward yet another high-tech makeover (even as it continues to adapt to the advent of electronic health records systems and other healthcare IT products) as artificial intelligence (AI) improves. Could AI applications become the new normal across virtually every sector of the healthcare industry? Many experts believe it is inevitable and coming sooner than you might expect.

What is artificial intelligence?

AI could be simply defined as computers and computer software that are capable of intelligent behavior, such as analysis and learning. It is a broad category at the cutting edge of technological development, growing and changing every day.

Machine learning and neural networks

Machine learning is the foundation of modern AI and is essentially an algorithm that allows computers to learn independently without following any explicit programming. As machine learning algorithms encounter more data, the algorithms' performance improves.

Deep learning is a subset of machine learning that functions in a similar way with a slight twist. Deep learning goes a step further, making inferences based on the data it has encountered before. In other words, deep learning enables an AI application to draw its own conclusions. It works through an artificial neural network, which is a set of machine learning algorithms that work in tandem. A neural network loosely resembles the human brain, with a series of "neurons" that "fire" when certain stimuli (in this case, data) are present.

"Conventional machine learning solutions aren't cognitive; they are trained from data but lack the ability to leap beyond missing or broken data and build a hypothesis about potential actions," said AJ Abdallat, CEO of Beyond Limits. "Machine learning can be effective in detecting something anticipated, but it fails when confronted by the unexpected."

To take artificial intelligence to the next level, Abdallat said, developers must emphasize both deductive and inductive reasoning, and emulate those cognitive patterns in the machines they design. A benefit of dynamic, deep learning solutions, he added, is that they can explain their reasoning and conclusions, a major benefit for complex decision-making.

How is AI used in healthcare?

AI is still a relatively new technology, especially in the healthcare industry where adoption remains in its infancy. As AI and machine learning tools become more sophisticated, their use cases have expanded; however, adoption of AI remains low, according to John Frownfelter, chief medical information officer at Jvion.

"We're still in the hype phase where many organizations are trying to understand how it fits into an overall strategy," said Frownfelter. "Early AI was seen … with more of an emphasis on pattern recognition for billing processes. It has evolved to a much more sophisticated use of deep machine learning and leveraging the power of big data."

Modern AI applications include wide-ranging use cases, from cybersecurity to radiographic imaging, Frownfelter said. As AI applications continue to improve, the entire healthcare industry could undergo a shift. Here are some of the major ways AI is expected to shape healthcare in the coming years.

Diagnostics

AI excels at categorizing data, especially once it has been exposed to large amounts of data on the subject. That creates great promise for AI when it comes to diagnostics – medical imaging analysis and patient medical records, genetics, and more can all be combined to improve diagnostic outcomes. Moreover, AI tools can use similar information to craft unique treatment approaches and offer recommendations to doctors.

"The really interesting developments are in the clinical arena," said Frownfelter. "Clinical prescriptive analytics is probably the closest AI is getting to support direct patient care in 2019."

Robot-assisted surgery

Robotic surgeries allow surgeons to use smaller tools and make more precise incisions. Surgeons (and patients) could also benefit from AI by combining medical records with real-time data during operations, as well as drawing on data from previous successful surgeries of the same type. Accenture, a technology consulting firm, estimates that AI-enabled, robot-assisted surgery could save the U.S. healthcare industry $40 billion annually by 2026.

Virtual nursing assistants

Think of virtual nursing assistants like an Alexa for your hospital bedside. These virtual assistants replicate the typical behavior of a nurse by assisting patients with their daily routines, reminding them to take medications or go to appointments, helping answer medical questions and more. Accenture estimates that virtual nursing assistants could be the second-largest source of annual savings for the U.S. healthcare industry, cutting as much as $20 billion in costs.

Administrative workflow assistance

Naturally, medical practices, hospitals and other points of care result in a great deal of paperwork. In fact, it was consolidating and digitizing these records that led to the industry-wide adoption of electronic health records systems. AI has already started to make its way into these systems and can be used to streamline administrative functions as well. Accenture estimates that new efficiencies in administrative workflow due to emerging AI technologies could result in $18 billion in annual savings.

Patient engagement

Already, automated scheduling and appointment reminders are commonplace, but the face of patient engagement could soon become more robotic (and yet, at the same time, more personal.)

"There has, rightly so, been a focus on how AI can be used to better diagnose and cure patients," said Phil Marshall, co-founder of Conversa Health. "That's important, but now we are seeing a shift to the ways AI can extend into the patient experience."

For example, patients who are concerned about a specific condition or the side effects of treatment could query a chatbot at any time, even when their doctor is not available, Marshall said.

"Imagine a cancer patient undergoing radiation [who] is unfamiliar with what is a normal side effect and what isn't. Now, instead of worrying through the night until the doctor's office opens, the chatbot can let them know," he said.

The economics of artificial intelligence in healthcare

What is all this worth? Accenture estimates the top 10 AI applications in healthcare could save the industry $150 billion annually by 2026. The AI healthcare market itself is projected to be worth $6.6 billion by 2021, which represents a massive compound annual growth rate of 40% since 2014 but also a modest investment when compared with the anticipated savings directly related to the adoption of AI.

"Investment and adoption of clinical AI is still low, but that is beginning to accelerate," said Frownfelter. "The most significant development in the next year is likely to be increased understanding and acceptance of AI."

SOURCE :https://www.businessnewsdaily.com/15096-artificial-intelligence-in-healthcare.html

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Top 10 emerging technologies of 2019

1. IoT

2. Artificial Intelligence (AI)

3. 5G

4. Serverless computing

5. Blockchain

6. Robotics

7. Biometrics

8. 3D printing

9. Virtual reality (VR)/Augmented reality (AR)

10. Drones

Does Big Data have a pivotal role in the future of customer experience?

Does Big Data have a pivotal role in the future of customer experience?

Customer Experience is becoming more important

Here’s how Big Data helps to improve the customer experience:

Big Data helps to understand the customer' purchase history

Big Data analysis makes it easy to know the behavioral pattern of the target audience

14 Essential Leadership Skills For The 4th Industrial Revolution

14 Essential Leadership Skills For The 4th Industrial Revolution

How Far Are We From Achieving Artificial General Intelligence?

How Far Are We From Achieving Artificial General Intelligence?

What is the current state of artificial intelligence?

What exactly is artificial general intelligence?

Can AI ever achieve general intelligence?

How far are we from artificial general intelligence?

Fortnite: How Artificial Intelligence and Analytics Make It More Fun

Fortnite: How Artificial Intelligence and Analytics Make It More Fun

Artificial Intelligence Will Change Healthcare as We Know It

What is artificial intelligence?

Machine learning and neural networks

How is AI used in healthcare?

Diagnostics

Robot-assisted surgery

Virtual nursing assistants

Administrative workflow assistance

Patient engagement

The economics of artificial intelligence in healthcare

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