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4 Ways Healthcare Is Being Transformed by the Cloud – HealthTech Magazine

Healthcare is increasingly turning to the cloud. According to research from Global Market Insights, the North American healthcare cloud-computing market surpassed $8.5 billion in 2018, and the global market could exceed $55 billion by 2025.

That doesnt mean there hasnt been turbulence along the way, particularly when it comes to the public cloud.

The Nutanix Enterprise Cloud Index 2019, based on a survey of 2,650 IT decision-makers in a variety of industries across the world, found that 73 percent of enterprises were migrating some of their applications back on-premises after finding the public cloud a poor fit for their needs. In fact, 85 percent indicated that the best fit for them was hybrid cloud citing its flexibility and perceived superior security.

READ MORE: Discover fivethings made possible in healthcare thanks to the cloud.

No matter the operating model though, healthcare organizations have made astonishing strides in improving care by employing the cloud. Here are four ways the cloud is making a dramatic difference for patients and staff alike:

Dr. Girish Shirali, a pediatric cardiologist at Childrens Mercy Hospital Kansas City, in Missouri, developed an app that is helping to keeping babies alive. Powered by Microsoft and hosted in Azure, the app allows parents of children born with hypoplastic left heart syndrome (HLHS), a serious medical condition requiring multiple surgeries, to upload a range of data several times a day.

Before the application, parents had to log the infants vital signs in a three-ring binder and call the hospital to provide that information weekly; a quarter of HLHS patients died before their second surgery at 6 months of age.

It was a reactive model, Lori Erickson, a nurse practitioner, told Microsoft Transform. Childrens Mercy showed that their proactive remote monitoring model made a dramatic difference in outcomes; in fact, in the first two years of the program, the hospital did not lose a single HLHS patient.

Another benefit of Childrens Mercys approach to HLHS care was a reduction in hospital admittances. The flow of real-time data allowed providers to see problems before they became emergencies.

Erickson gave the example of an infant whose weight gain pattern once would have led to hospitalization. By spotting the issue early, she worked with the parents to course-correct before it became serious.

And its not just the providers who learn to see problems coming the system itself can learn.Rather than the analysis simply telling us that saturation is low, [the system] could instead tell us that the risk of an adverse cardiac event in the next three days just went from 2 percent to 40 percent, and tell us why, Shirali told Microsoft Transform.

Hospitals hold massive amounts of sensitive patient data, and it can be a headache for IT staff to keep every system patched and secure. Thats why Novant Health, based in Winston Salem, N.C., migrated its EHR system to a cloud platform in February of 2019. Since the move, the organization has seen ample benefits.

"We have freed up a tremendous amount of engineering resource time from having to manage that infrastructure, James Kluttz, vice president and CTO of Novant Health, tells Beckers Health IT & CIO Report. We have been able to redeploy our resources to focus on business-driven initiatives. We've been able to realign our resources in unique ways that also drive even more cloud adoption.

That change freed up not only staff but budget as well. With the move, the organization gained insight into what its future cost models would look like. Kluttz mentions that Novant has since hit a home run, staying on track with those models.

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Before merging with AMITA Health last year, Presence Health in Chicago adopted Nutanix Enterprise Cloud to help with their electronic medical records upgrade. The result was a responsive and robust system that gave care providers near immediate access to the information they needed, whenever they needed it.

The hospitals EMR tracked workflow exceptions unacceptable delays in accessing patient records and the cloud helped the organization to immediately halve these.

There was a dramatic improvement the day we cut over to Nutanix the number of exceptions plummeted from 0.8 percent to just 0.4 percent, said Jeremy Bernstein, then interim CTO of Presence Health, in a customer case study. The cloud also facilitated efficient communication among care team members and enabled the provider to implement barcode medication administration, helping to ensure everyone was consistently on the same page.

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12 Highlights from the First Annual Cloud Insight Jam – Solutions Review

Yesterday, Solutions Review hosted our first ever Cloud Insight Jam and it was a huge success! We received more participation from cloud vendors, thought leaders, and IT experts than we could have hoped for, all sharing their thoughts and insights on cloud computing and how they expect the market to change in 2020. In case you missed the event, wed like to share the key highlights from the Insight Jam!

First, wed like to share our video compilation containing clips on advice and best practices for deploying cloud solutions. We compiled advice from 12 experts in the field of cloud from companies across the globe.

We also pulled several Tweets containing valuable cloud insights and predictions that vendors and individuals shared during the event. The intended backbone of the Cloud Insight Jam was to generate discussion and allow experts a forum for them to provide their thoughts. It was great seeing this concept come to life, as all throughout the day, several cloud solution providers and thought leaders Tweeted their perspectives!

Looking for more info on managed service providers for your cloud solutions? Our2020 MSP Buyers Guide contains profiles on the top cloud managed service providers for AWS, Azure, and Google Cloud, as well as questions you should ask vendors and yourself before buying. We also offer a2020 MSP Vendor Mapthat outlines those vendors in a Venn diagram to make it easy for you to select potential providers.

Check us out onTwitterfor the latest in Enterprise Cloud news and developments!

Dan is a tech writer who writes about Enterprise Cloud Strategy and Network Monitoring for Solutions Review. He graduated from Fitchburg State University with a Bachelor's in Professional Writing. You can reach him at dhein@solutionsreview.com

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How the DOD Plans to Bring Its JEDI Cloud Contract to Life – FedTech Magazine

On Oct. 25, the Defense Department awarded its Joint Enterprise Defense Infrastructure cloud contract to Microsoft, capping a yearslong effort to start deploying commercial cloud capabilities for Infrastructure as a Service and Platform as a Service. That was just the beginning.

Senior Microsoft leaders including CEO Satya Nadella, Toni Townes-Whitley (one of FedTechs 30 Federal IT Influencers Worth a Follow in 2019), Jason Zander, Tom Keane and Mark Russinovich were scheduled to meet with Pentagon officials last week to lay the foundation for working together, Nextgov reports. Nadella and members of the Microsoft Azure and public sector teams were to meet with DOD CIO Dana Deasy and other senior DOD technology leaders from Dec. 11-13 as part of requisite activities to prepare the cloud environment, the department confirmed to Nextgov.

The Department of Defense is confident in the JEDI Cloud Contract award and remains focused on getting this critical capability into the hands of our warfighters as quickly and efficiently as possible, DOD spokeswoman Elissa Smith told Nextgov. The departments Cloud Computing Program Office continues to work with Microsoft to prepare the JEDI Cloud environment.

MORE FROM FEDTECH: Follow the 5 Rs of rationalization for an effective cloud migration.

DOD has chosen 14 entities to act as pathfinders for the clouds capabilities. Deasy says those Pentagon components which include the U.S. Special Operations Command, the U.S Transportation Command and the Joint Artificial Intelligence Center will be the first to use JEDI on a more tactical level, according to Federal News Network.

These early adopters have unique missions that are more than just using JEDI for base compute, raw storage capacity, and want to do real unique platform-for-service opportunities on top of that, Deasy said Thursday at the Northern Virginia Chapter of AFCEAs Air Force IT Day in Arlington, Va. The variety of the early adopters allows us to test various principles on JEDI from the tactical edge all the way to the top secret needing to use the cross domain.

Deasy indicated the pathfinder components will be able to learn quickly what it takes to go from the strategic vision to stand up and bring JEDI capabilities to life, Federal News Network reports.

Shortly after the contract was awarded, Peter Ranks, a deputy CIO at the DOD, told reporters after speaking at a Professional Services Council event that awarding JEDI was a prerequisite to faster software development. DOD must modernize the way it builds software as it shifts to commercial cloud infrastructure.

If we get modern cloud infrastructure but dont modernize the way we build software, we will not achieve the promises of cloud computing. We want software capabilities in the hands of warfighters faster, Ranks said during his Vision Federal Market Forecast keynote, according to MeriTalk. We want software that can adjust to changing requirements or the changing dynamics of the battlefield more quickly. That is whats driving our cloud strategy.

We have fooled ourselves into thinking that if we can just hire the cloud provider, it will solve all those problems. Hiring the cloud provider wasnt supposed to be the hard part, Ranks added. Like any other weapons system, mastery of the weapons system is really where the challenge comes in, he added.

The DOD has struggled to run applications, such as the Global Command & Control System Joint, across all combatant commands because the cloud infrastructures of the Army, Air Force and Navy vary widely. Ranks said JEDI aims to fix such issues.

What we need is a focused effort to make sure that we have a provider that is filling the gaps in that current multi-cloud solution, he said, according to FedScoop. For all the cloud providers we have today, they still havent solved those problems of classification, tactical edge and something that is common across the enterprise.

Court documents indicate that the DOD has agreed not to proceed with performance under JEDI until at least Feb. 11, aside from initial preparatory activities, pending a lawsuit Amazon Web Services filed in the U.S. Court of Federal Claims over the award, according to NextGov.

Microsoft says it is pushing ahead with its work on the contract. As the selected contractor to support [the Defense Department] in its mission to modernize its enterprise cloud, we are diligently working with the Cloud Computing Program Office to bring this critical new technology to our men and women in uniform, a Microsoft spokesperson told Nextgov.

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Will Amazon Make a Dent in Cisco’s Revenue With This New Project? – The Motley Fool

Every time Amazon(NASDAQ:AMZN) ventures into a new business, the targeted industry should worry about the risks of competing against such a disruptive player. For instance, traditional retailers have been struggling against Amazon's e-commerce dominance. And the giant retailer has become a leading public cloud computing company with Amazon Web Services (AWS).

Legacy traditional computer network vendors such as Cisco Systems (NASDAQ:CSCO) may be concerned by Amazon's latest move. Last week, the Linux Foundation announced the DENT project, which is aiming at "the creation of network operating system for disaggregated network switches in campus and remote enterprise locations," and Amazon is one of the six premier members of this initiative.But this apparently disruptive technology may actually have a limited impact.

Before cloud computing emerged a few years ago, computer networking had been following the same model over a couple of decades. Network vendors had been selling monolithic, proprietary solutions that integrated network devices with the software to run these boxes. This was great for customers that wanted a network that just works and that would not distract them from their core business.

Giant cloud providers such as Amazon with AWS and Microsoft with Azure required more scale and flexibility at low cost, though. As a result, solutions that disaggregated software from network devices emerged. For instance, Microsoft developed its network operating system SONiC that can run on any compatible network device. The advantage of this technology is cloud titans can run their tailor-made software on top of any hardware that better fits their needs.

And this technology has been having a significant impact on the networking industry. For instance,Arista Networks grew its revenue from $361 million in 2013 to $2.45 billion over the last 12 months thanks to its network solutions that address cloud titans' requirements.

In contrast, Cisco was late to adapt. Its market share in the high-speed data center network segment dropped from 74.4% in 2013 to 46.6% during the first half of this year.And Cisco announced only last week the disaggregation of its software from its hardware for its new data center networking solution.

Image source: Getty Images.

The idea of the DENT project is to applyto smaller and remote networks the same disruptive technology thatconsisted of separating software and hardware in the cloud data center networks. As an illustration, the project's first use case targets the retail industry, which involves many small locations.

Cisco doesn't disclose its revenue from its enterprise and campus business, but the company's largest segment, "infrastructure platforms" (which includes network devices), represented 57.3% of its revenue during the most recent quarter.Besides,a study indicates Cisco controlled 59% of the enterprise and campus markets in 2018.

Thus, with its disruptive technology on the campus and enterprise network, the DENT project represents a real threat to Cisco, but its impact may stay limited.

First, disaggregating network software and hardwaremakes sense for giant cloud providers since their scale allows them to develop their tailor-made technology in an economical way. But smaller companies don't necessarily want to deal with integrating networking software and hardware. They may still just want an integrated and trouble-free solution that connects their remote locations to their networks. The same concept exists with computer operating systems: Linux is available for free and can run on any personal computer, but many companies prefer to pay for Microsoft's operating system because it won't distract them from their core business.

Second, the DENT project is initially targeting the retail industry. However, some retailers may be reluctant to choose a solution provided by their biggest competitor (Amazon) as we saw when theypreferred Microsoft's cloud for their data centers.

Third, companies may worry about potential future integration of DENT with AWS, making their whole network -- remote locations and data centers -- dependent on Amazon's infrastructure and software.

Finally, even if this disruptive technology expands, Cisco can now quickly adapt since it developed a similar disaggregated solution for data centers.

Thus, investors should not expect any meaningful impact from the DENT project for either Amazon or Cisco. This project may actually signal Amazon is preparing to expand its physical footprint with a tailor-made networking solution that would lower its costs to deploy its remote locations.

And even if the DENT project gains traction, Cisco remains an attractive tech stock. The company will quickly adapt because it recently embraced the concept of disaggregating software and hardware in the data center segment.

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Scale Computing says it was proved right on edge over cloud – Data Economy

Data Economy was invited on an exclusive press and analysts tour of Silicon Valley data management companies.

New services andproducts from Valley vendors are promising to aid the bottom lines ofenterprises as they manage hybrid clouds.

Our first round coverage from the IT Press Tour last week covered DDN, StorCentric, Data Dynamics, Komprise and HYCU. The next firm we visited was MinIO in Palo Alto, the open source cloud object storage company that uses containers and Kubernetes orchestration to better support cloud data and management.

MinIO is compatiblewith AWS S3 and S3 Select. The company says more than 750organisations, including Microsoft Azure, use its S3 Gateway. Whilethe open source software for managing data is free, like many opensource vendors MinIO makes its money through support and otherservices.

Basic support is,again, free. But if you want to get an answer to a problem within anhour from MinIOs engineers you pay for one of the companys SUBNETsupport subscriptions. These also include panic buttons thatmake all engineers around the time zones jump to customers urgentproblems to find a collective solution ASAP.

The SUBNET offering isnow being widely pushed globally, with ten SUBNET subscribers inEurope currently on the roster. It is hoped that the largest users ofMinIO, such as Apple located down the road in Cupertino, will paytheir way, considering the large amount of data they are said tohandle via MinIO.

After MinIO we visitedone of the Valleys most famous business hotels, the Rosewood inMenlo Park, where it is often packed out with venture capitalists,expensive cars and their potential clients looking for their earlyfunding.

Indeed, we were introduced to a very well known VC in the form of Peter Levine. He was originally at Veritas, and went on to XenSource, before it was acquired by Citrix. He is now a general partner at venture capital firm Andreessen Horowitz, with his company an investor in the company we were there to see, multi-cloud data management firm Actifio.

Levine told us thatwhile software is eating the world, data was eatingsoftware. Actifio has a solution to this latter problem, it says.

It was at the Rosewoodto launch its latest 10c software, that is designed to turn a singledata lake into a source for accessible business insights usingthe cloud, containers and copy data. It boasts support for sevenpublic cloud platforms and 23 new core technologies.

Actifio CEO AshAshutosh said the firms largest contract is worth $35m with afinancial services company in the US, and that typical contractsstart at $250,000. So the solutions it sells certainly arent for theminnows.

The company is nowlooking for more technology partners and consulting channel partnersto build on the relationships it already has with the likes of IBMand Tata Consultancy Services.

As for the establishedheavyweights of cloud data management, the IT Press Tour also metCommvault and VMware.

At Commvault, press and analysts were presented with a pitch to explain what the New Commvault was after a busy year of changes. The company held its first Commvault GO event to get closer to customers and partners in Florida in 2016, when the stirrings of its first serious cloud break broke.

This may or not havebeen appropriate at the time, as the event was somewhat curtailed asa result of an impending hurricane, with this author and many otherdelegates choosing to fly home early to prevent being trapped in theresort.

Since then, the companyhas held three other Commvault GO events in the US that have not beenaffected by stormy weather, and the organisation seems to havecompleted putting its cloud strategy fully together, although itsreach is still limited more of this later.

In February 2019, thecompany appointed a new CEO. In July this year it launched a newpartner programme, and in September it acquired software-definedprimary and secondary storage management company Hedvig, which othervendors had had their eye on too as an acquisition target.

And in October, thefirm put the icing on the cake with the launch of Metallic, aSaaS-based cloud data management service. The company confirmed itwas committed to giving customers choice as to whether they wanted tobuy Commvault products and services via subscription, perpetual, SaaSor through service provider licenses and deals.

It is also determined to kill the notion that Commvault is mainly an expensive, big box data storage solution for only large companies a description that is still doing the rounds in the wider market. It is a description that Commvault probably started to try and seriously shake off back at Commvault GO 2016, but it wasnt shaking it off quick enough, which is probably partly why the previous senior management was changed this year.

With Hedvig andMetallic, Commvault chief marketing officer Chris Powell reckoned thevendors total addressible market had increased 60%.

Metallic provides coreback-up and recovery, Microsoft Office 365 backup and recovery andendpoint backup and recovery through cloud channel service providers.

But after an Octoberlaunch, it is still only available in the US, with the Commvault teamstill not able to say when it will be extended to any otherterritories. This will happen in 2020, but Commvault so far cannotconfirm whether this will be in the first half or the second half.

Ingram Micro and Arroware established Commvault distributors. Maybe there is an impendingannouncement on further Metallic availability outside the US throughdistributors and service providers, but it does seem rather strangethat a seemingly key product is not moving more quickly to market.

Over at VMware, there was a refresh of what had been launched at VMworld, including the Tanzu set of products to build, run and manage apps in a multi-cloud environment. But the firm was more keen to demonstrate the opportunities created from marrying together the cloud and hyperconverged infrastructure (HCI).

There are two marketsin HCI, the branded systems market and the software supplier one thatsees HCI software used by various brands. On the branded systemsside, Dell Technologies, Nutanix, Cisco, HPE and Lenovo were the topfive in that order in terms of global sales in the third quarter of2019, according to analyst IDC.

But when it comes tothe supply of HCI software, VMware is well ahead of the pack with 38%of the market, according to IDC, with Nutanix on 27.2% and DellTechnologies and Cisco both on under 6%.

Lee Caswell, VP ofmarketing for the VMware HCI business unit, said: Channel partnerswere initially pushing back on the HCI bet as they thought it reducedthe chance to sell more storage. But they are now taking advantage ofusing it to sell more services.

Caswell said that although the mid-range storage market was bigger, it was only expected to grow at a compound annual growth rate of 3% up to 2023. On the other hand, he said, the HCI market is expected to grow at a 20% CAGR over the same period.

Hot HCI rival Nutanixof course, along with others, is rushing to serve the samemulti-cloud environment that VMware is aiming to address with newproducts, and it is good to see other newer companies entering thespace too.

The IT Press Tour will be taking a visit to Israel next spring to see what start-ups and more established companies there are doing in the data space.

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Cloud computing IaaS in Life Science Market Growth Rate by 2026 Top Key Vendors, Trend, Segmentation, Drivers, Challenges and Forecast – Market…

Cloud computing IaaS in Life Science Market Overview:

The report titled Cloud computing IaaS in Life Science Market is one of the most comprehensive and important additions to Verified Market Research archive of market research studies. It offers detailed research and analysis of key aspects of the Cloud computing IaaS in Life Science market. The market analysts authoring this report have provided in-depth information on leading growth drivers, restraints, challenges, trends, and opportunities to offer a complete analysis of the Cloud computing IaaS in Life Science market. Market participants can use the analysis on market dynamics to plan effective growth strategies and prepare for future challenges beforehand. Each trend of the Cloud computing IaaS in Life Science market is carefully analyzed and researched about by the market analysts.

Global Cloud computing IaaS in Life Science market was valued at USD 946.1 million in 2017 and is projected to reach USD 5,245.31 million by 2025, growing at a CAGR of 32.7% from 2018 to 2025.

The report includes detailed analysis of the vendor landscape and thorough company profiling of leading players of the Cloud computing IaaS in Life Science market.The researchers have considered almost all important parameters for company profiling, including market share, recent development, gross margin, future development plans, product portfolio, production, and revenue.

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Leading players covered in the Cloud computing IaaS in Life Science market report:

Insight into Competitive Landscape :

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Market Segment Analysis :

The report offers a comprehensive study of product type and application segments of the Cloud computing IaaS in Life Science market. The segmental analysis provided in the report is based on significant factors such as market share, market size, consumption, production, and growth rate of the market segments studied.Readers of the report are also provided with exhaustive geographical analysis to provide clear understanding of the regional growth of the Cloud computing IaaS in Life Science market. Developed as well as developing regional markets for Cloud computing IaaS in Life Science have been deeply studied to help market players identify profit-making opportunities in different regions and countries.

North America (United States, Canada and Mexico)

Asia Pacific (China, Japan, South Korea, India, Australia, Indonesia, Thailand, Malaysia, Philippines and Vietnam)

Middle East and Africa (Turkey, GCC Countries, Egypt and South Africa)

South America (Brazil and others)

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Table of Content

1 Introduction of Cloud computing IaaS in Life Science Market

1.1 Overview of the Market 1.2 Scope of Report 1.3 Assumptions

2 Executive Summary

3 Research Methodology of Verified Market Research

3.1 Data Mining 3.2 Validation 3.3 Primary Interviews 3.4 List of Data Sources

4 Cloud computing IaaS in Life Science Market Outlook

4.1 Overview 4.2 Market Dynamics 4.2.1 Drivers 4.2.2 Restraints 4.2.3 Opportunities 4.3 Porters Five Force Model 4.4 Value Chain Analysis

5 Cloud computing IaaS in Life Science Market, By Deployment Model

5.1 Overview

6 Cloud computing IaaS in Life Science Market, By Solution

6.1 Overview

7 Cloud computing IaaS in Life Science Market, By Vertical

7.1 Overview

8 Cloud computing IaaS in Life Science Market, By Geography

8.1 Overview 8.2 North America 8.2.1 U.S. 8.2.2 Canada 8.2.3 Mexico 8.3 Europe 8.3.1 Germany 8.3.2 U.K. 8.3.3 France 8.3.4 Rest of Europe 8.4 Asia Pacific 8.4.1 China 8.4.2 Japan 8.4.3 India 8.4.4 Rest of Asia Pacific 8.5 Rest of the World 8.5.1 Latin America 8.5.2 Middle East

9 Cloud computing IaaS in Life Science Market Competitive Landscape

9.1 Overview 9.2 Company Market Ranking 9.3 Key Development Strategies

10 Company Profiles

10.1.1 Overview 10.1.2 Financial Performance 10.1.3 Product Outlook 10.1.4 Key Developments

11 Appendix

11.1 Related Research

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Analysts with high expertise in data gathering and governance utilize industry techniques to collate and examine data at all stages. Our analysts are trained to combine modern data collection techniques, superior research methodology, subject expertise and years of collective experience to produce informative and accurate research reports.

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Global Cloud Computing Industry Emerging Trends and Prospects by leading Players Yahoo Inc. CISCO Systems, IBM Co., Hewlett Packard, Dell Inc. -…

The Latest Research Report published by Global Reports Store on Cloud Computing Industry Forecast 2019-2025. Which contains 120 Pages, 80 Figures, and Tables, With a detailed description of past, present, and future of Cloud Computing Industry along with 15 Companies detailed profile analysis. The global Cloud Computing industry valued approximately USD 209.9 billion in 2016 is anticipated to grow with a healthy growth rate of more than 17.93% over the forecast period 2019-2025.

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The major driver for this industry is the cost-effectiveness. This service of cloud computing helps various organizations to save up to one-third of their annual operations costs. Also, the rising number of SMEs will bolster the use of cloud services. The objective of the study is to define Industry sizes of different segments & countries in previous years and to forecast the values for the next eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry with respect to each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as drivers & restraining factors which will define the future growth of the Industry. Additionally, it will also incorporate the opportunities available in micro Industries for stakeholders to invest, detailed analysis of competitive landscape and product offerings of key players.

Market Player in Cloud Computing Industry:Yahoo Inc.CISCO SystemsIBM Co.Hewlett PackardDell Inc.Akamai TechnologiesVM WareMicrosoft CorporationAmazon Web Services

Market Segmentation:By Service:Infrastructure as a Service (IaaS)Platform as a Service (PaaS)Software as a Service (SaaS)

By Deployment Model:Public CloudPrivate CloudHybrid Cloud

By Organization Size:Small & Medium Size Enterprises (SMEs)Large Enterprises

By End-User:Telecommunications & IT (ICT)HealthcareRetailPublic SectorMedia & EntertainmentBanking, Financial Services and Insurance (BFSI)

By RegionNorth America (USA, Canada)Europe (Germany, U.K., France, Italy, Rest of Europe)APAC (China, India, Japan, Rest of Asia-Pacific)RoW (Latin America, Middle East & Africa)

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High lite Form This Research Report:1 Business Overview: An exhaustive description of the companies operation and business divisions.2 Corporate Strategy: Analysts summarisation of the companies business strategy.3 SWOT Analysis: A detail analysis of company Strength, Weakness, Opportunity, and Threats.4 Company History: Progression of key events associated with the company.5 Major Products and Services: A list of major Products, Services, and Brands of the company.6 Key Competitors: A list of key competitors to the company.7 Important Locations and subsidiaries: a list and contact details of key locations and subsidiaries of the company.

Table of Contents Major Key PointsChapter 1: Executive summaryChapter 2: Scope of the reportChapter 3: Market research methodologyChapter 4: IntroductionChapter 5: Market landscapeChapter 6: Market segmentation by productChapter 7: Key leading countriesChapter 8: Market driversChapter 9: Impact of drivers

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Why Cognitive Technology May Be A Better Term Than Artificial Intelligence – Forbes

One of the challenges for those tracking the artificial intelligence industry is that, surprisingly, theres no accepted, standard definition of what artificial intelligence really is. AI luminaries all have slightly different definitions of what AI is. Rodney Brooks says that artificial intelligence doesnt mean one thing its a collection of practices and pieces that people put together. Of course, thats not particularly settling for companies that need to understand the breadth of what AI technologies are and how to apply them to their specific needs.

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In general, most people would agree that the fundamental goals of AI are to enable machines to have cognition, perception, and decision-making capabilities that previously only humans or other intelligent creatures have. Max Tegmark simply defines AI as intelligence that is not biological. Simple enough but we dont fully understand what biological intelligence itself means, and so trying to build it artificially is a challenge.

At the most abstract level, AI is machine behavior and functions that mimic the intelligence and behavior of humans. Specifically, this usually refers to what we come to think of as learning, problem solving, understanding and interacting with the real-world environment, and conversations and linguistic communication. However the specifics matter, especially when were trying to apply that intelligence to solve very specific problems businesses, organizations, and individuals have.

Saying AI but meaning something else

There are certainly a subset of those pursuing AI technologies with a goal of solving the ultimate problem: creating artificial general intelligence (AGI) that can handle any problem, situation, and thought process that a human can. AGI is certainly the goal for many in the AI research being done in academic and lab settings as it gets to the heart of answering the basic question of whether intelligence is something only biological entities can have. But the majority of those who are talking about AI in the market today are not talking about AGI or solving these fundamental questions of intelligence. Rather, they are looking at applying very specific subsets of AI to narrow problem areas. This is the classic Broad / Narrow (Strong / Weak) AI discussion.

Since no one has successfully built an AGI solution, it follows that all current AI solutions are narrow. While there certainly are a few narrow AI solutions that aim to solve broader questions of intelligence, the vast majority of narrow AI solutions are not trying to achieve anything greater than the specific problem the technology is being applied to. What we mean to say here is that were not doing narrow AI for the sake of solving a general AI problem, but rather narrow AI for the sake of narrow AI. Its not going to get any broader for those particular organizations. In fact, it should be said that many enterprises dont really care much about AGI, and the goal of AI for those organizations is not AGI.

If thats the case, then it seems that the industrys perception of what AI is and where it is heading differs from what many in research or academia think. What interests enterprises most about AI is not that its solving questions of general intelligence, but rather that there are specific things that humans have been doing in the organization that they would now like machines to do. The range of those tasks differs depending on the organization and the sort of problems they are trying to solve. If this is the case, then why bother with an ill-defined term in which the original definition and goals are diverging rapidly from what is actually being put into practice?

What are cognitive technologies?

Perhaps a better term for narrow AI being applied for the sole sake of those narrow applications is cognitive technology. Rather than trying to build an artificial intelligence, enterprises are leveraging cognitive technologies to automate and enable a wide range of problem areas that require some aspect of cognition. Generally, you can group these aspects of cognition into three P categories, borrowed from the autonomous vehicles industry:

From this perspective, its clear that while cognitive technologies are indeed a subset of Artificial Intelligence technologies, with the main difference being that AI can be applied both towards the goals of AGI as well as narrowly-focused AI applications. On the other-hand, using the term cognitive technology instead of AI is an acceptance of the fact that the technology being applied borrows from AI capabilities but doesnt have ambitions of being anything other than technology applied to a narrow, specific task.

Surviving the next AI winter

The mood in the AI industry is noticeably shifting. Marketing hype, venture capital dollars, and government interest is all helping to push demand for AI skills and technology to its limits. We are still very far away from the end vision of AGI. Companies are quickly realizing the limits of AI technology and we risk industry backlash as enterprises push back on what is being overpromised and under delivered, just as we experienced in the first AI Winter. The big concern is that interest will cool too much and AI investment and research will again slow, leading to another AI Winter. However, perhaps the issue never has been with the term Artificial Intelligence. AI has always been a lofty goal upon which to set the sights of academic research and interest, much like building settlements on Mars or interstellar travel. However, just as the Space Race has resulted in technologies with broad adoption today, so too will the AI Quest result in cognitive technologies with broad adoption, even if we never achieve the goals of AGI.

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Why Cognitive Technology May Be A Better Term Than Artificial Intelligence - Forbes

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Artificial intelligence jobs on the rise, along with everything else AI – ZDNet

AI jobs are on the upswing, as are the capabilities of AI systems. The speed of deployments has also increased exponentially. It's now possible to train an image-processing algorithm in about a minute -- something that took hours just a couple of years ago.

These are among the key metrics of AI tracked in the latest release of theAI Index, an annual data update from Stanford University'sHuman-Centered Artificial Intelligence Institutepublished in partnership with McKinsey Global Institute. The index tracks AI growth across a range of metrics, from papers published to patents granted to employment numbers.

Here are some key measures extracted from the 290-page index:

AI conference attendance: One important metric is conference attendance, for starters. That's way up. Attendance at AI conferences continues to increase significantly. In 2019, the largest, NeurIPS, expects 13,500 attendees, up 41% over 2018 and over 800% relative to 2012. Even conferences such as AAAI and CVPR are seeing annual attendance growth around 30%.

AI jobs: Another key metric is the amount of AI-related jobs opening up. This is also on the upswing, the index shows. Looking at Indeed postings between 2015 and October 2019, the share of AI jobs in the US increased five-fold since 2010, with the fraction of total jobs rising from 0.26% of total jobs posted to 1.32% in October 2019. While this is still a small fraction of total jobs, it's worth mentioning that these are only technology-related positions working directly in AI development, and there are likely an increasingly large share of jobs being enhanced or re-ordered by AI.

Among AI technology positions, the leading category being job postings mentioning "machine learning" (58% of AI jobs), followed by artificial intelligence (24%), deep learning (9%), and natural language processing (8%). Deep learning is the fastest growing job category, growing 12-fold between 2015 and 2018. Artificial Intelligence grew by five-fold, machine learning grew by five-fold, machine learning by four-fold, and natural language processing two-fold.

Compute capacity: Moore's Law has gone into hyperdrive, the AI Index shows, with substantial progress in ramping up the computing capacity required to run AI, the index shows. Prior to 2012, AI results closely tracked Moore's Law, with compute doubling every two years. Post-2012, compute has been doubling every 3.4 months -- a mind-boggling net increase of 300,000x. By contrast, the typical two-year doubling period that characterized Moore's law previously would only yield a 7x increase, the index's authors point out.

Training time: The among of time it takes to train AI algorithms has accelerated dramatically -- it now can happen in almost 1/180th of the time it took just two years ago to train a large image classification system on a cloud infrastructure. Two years ago, it took three hours to train such a system, but by July 2019, that time shrunk to 88 seconds.

Commercial machine translation: One indicator of where AI hits the ground running is machine translation -- for example, English to Chinese. The number of commercially available systems with pre-trained models and public APIs has grown rapidly, the index notes, from eight in 2017 to over 24 in 2019. Increasingly, machine-translation systems provide a full range of customization options: pre-trained generic models, automatic domain adaptation to build models and better engines with their own data, and custom terminology support."

Computer vision: Another benchmark is accuracy of image recognition. The index tracked reporting through ImageNet, a public dataset of more than 14 million images created to address the issue of scarcity of training data in the field of computer vision. In the latest reporting, the accuracy of image recognition by systems has reached about 85%, up from about 62% in 2013.

Natural language processing: AI systems keep getting smarter, to the point they are surpassing low-level human responsiveness through natural language processing. As a result, there are also stronger standards for benchmarking AI implementations. GLUE, the General Language Understanding Evaluation benchmark, was only released in May 2018, intended to measure AI performance for text-processing capabilities. The threshold for submitted systems crossing non-expert human performance was crossed in June, 2019, the index notes. In fact, the performance of AI systems has been so dramatic that industry leaders had to release a higher-level benchmark, SuperGLUE, "so they could test performance after some systems surpassed human performance on GLUE."

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Artificial intelligence jobs on the rise, along with everything else AI - ZDNet

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What Is The Artificial Intelligence Of Things? When AI Meets IoT – Forbes

Individually, the Internet of Things (IoT) and Artificial Intelligence (AI) are powerful technologies. When you combine AI and IoT, you get AIoTthe artificial intelligence of things. You can think of internet of things devices as the digital nervous system while artificial intelligence is the brain of a system.

What Is The Artificial Intelligence Of Things? When AI Meets IoT

What is AIoT?

To fully understand AIoT, you must start with the internet of things. When things such as wearable devices, refrigerators, digital assistants, sensors and other equipment are connected to the internet, can be recognized by other devices and collect and process data, you have the internet of things. Artificial intelligence is when a system can complete a set of tasks or learn from data in a way that seems intelligent. Therefore, when artificial intelligence is added to the internet of things it means that those devices can analyze data and make decisions and act on that data without involvement by humans.

These are "smart" devices, and they help drive efficiency and effectiveness. The intelligence of AIoT enables data analytics that is then used to optimize a system and generate higher performance and business insights and create data that helps to make better decisions and that the system can learn from.

Practical Examples of AIoT

The combo of internet of things and smart systems makes AIoT a powerful and important tool for many applications. Here are a few:

Smart Retail

In a smart retail environment, a camera system equipped with computer vision capabilities can use facial recognition to identify customers when they walk through the door. The system gathers intel about customers, including their gender, product preferences, traffic flow and more, analyzes the data to accurately predict consumer behavior and then uses that information to make decisions about store operations from marketing to product placement and other decisions. For example, if the system detects that the majority of customers walking into the store are Millennials, it can push out product advertisements or in-store specials that appeal to that demographic, therefore driving up sales. Smart cameras could identify shoppers and allow them to skip the checkout like what happens in the Amazon Go store.

Drone Traffic Monitoring

In a smart city, there are several practical uses of AIoT, including traffic monitoring by drones. If traffic can be monitored in real-time and adjustments to the traffic flow can be made, congestion can be reduced. When drones are deployed to monitor a large area, they can transmit traffic data, and then AI can analyze the data and make decisions about how to best alleviate traffic congestion with adjustments to speed limits and timing of traffic lights without human involvement.

The ET City Brain, a product of Alibaba Cloud, optimizes the use of urban resources by using AIoT. This system can detect accidents, illegal parking, and can change traffic lights to help ambulances get to patients who need assistance faster.

Office Buildings

Another area where artificial intelligence and the internet of things intersect is in smart office buildings. Some companies choose to install a network of smart environmental sensors in their office building. These sensors can detect what personnel are present and adjust temperatures and lighting accordingly to improve energy efficiency. In another use case, a smart building can control building access through facial recognition technology. The combination of connected cameras and artificial intelligence that can compare images taken in real-time against a database to determine who should be granted access to a building is AIoT at work. In a similar way, employees wouldn't need to clock in, or attendance for mandatory meetings wouldn't have to be completed, since the AIoT system takes care of it.

Fleet Management and Autonomous Vehicles

AIoT is used to in fleet management today to help monitor a fleet's vehicles, reduce fuel costs, track vehicle maintenance, and to identify unsafe driver behavior. Through IoT devices such as GPS and other sensors and an artificial intelligence system, companies are able to manage their fleet better thanks to AIoT.

Another way AIoT is used today is with autonomous vehicles such as Tesla's autopilot systems that use radars, sonars, GPS, and cameras to gather data about driving conditions and then an AI system to make decisions about the data the internet of things devices are gathering.

Autonomous Delivery Robots

Similar to how AIoT is used with autonomous vehicles, autonomous delivery robots are another example of AIoT in action. Robots have sensors that gather information about the environment the robot is traversing and then make moment-to-moment decisions about how to respond through its onboard AI platform.

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What Is The Artificial Intelligence Of Things? When AI Meets IoT - Forbes

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