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Ad Servers for Advertisers Market to Witness a Pronounce Growth During 2026 – News By ReportsGO

Ad Servers for Advertisers Market to Witness a Pronounce Growth During 2026

The research report on Ad Servers for Advertisers market encompasses a detailed evaluation of the past and present business scenario to offer a conclusive overview of the industry performance over 2021-2026. It sheds light on the sizes and shares the markets and sub-markets, highlighting the key driving forces, challenges, and lucrative prospects governing the industry dynamics.

According to experts, Ad Servers for Advertisers market size is projected to record notable growth over the forecast period, registering XX% CAGR throughout.

The research literature further offers crucial information on the competitive arena, emphasizing on the strategies adopted by key players that proved to be successful, to aid businesses ensure an upward growth trajectory in the forthcoming years. Besides, the study attempts to answer all the queries of clients pertaining to business implications of Covid-19 pandemic.

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Market snapshot:

Regional outlook:

Product landscape outline:

Application spectrum summary:

Competitive arena overview:

Key Questions Answered in the Market Report:

Table of Contents:

1 Scope of the Report

1.1 Market Introduction

1.2 Years Considered

1.3 Research Objectives

2. Executive Summary

3. Global Ad Servers for Advertisers market by Company

4. Ad Servers for Advertisers market by Region

5. Market Drivers, Challenges and Trends

6. Marketing, Distributors and Customer

7. Global Ad Servers for Advertisers Market Size Forecast

8. Ad Servers for Advertisers Market Key Players Analysis

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Enhanced Role for Startup, Entrepreneurs with IT Infrastructure for Secured National Reincarnations – thepolicytimes.com

The term startup is talk of the town nowadays, and it is the most popular topic! Many people define the startup as the tech business and with less than 100 employees. Many people want to become entrepreneurs and open their own businesses. Much needed thing is to explain all about startups to clarify the concept of startups for young and enthusiastic entrepreneurs in the making.

Start ups play a key role in supporting the growth and development of a countrys economy as well as in improving the quality of life for citizens.Economic development preserves and raises the communitys standard of living through a process of human and physical infrastructure developmentFoster cooperative international tie up and technological support through Start up programmes of bilateral and multilateralinterest.Make cities and human settlements inclusive, safe, resilient, and sustainable.

In accordance with the Countries Global Ranking of Startup Ecosystem 2020 by global innovation mapping and research company StartupBlink, India ranked at 23rd position, a drop of 6 places from 17th position in 2019. The ranking has been topped by the United States (US), followed by the United Kingdom (UK), and Israel at 2nd & 3rd position. It should be noted that India is home to the third largest startup ecosystem.

Among the top 100 startup cities, only four India cities were named in 2020 Cities Global Ranking of Startup Ecosystem while total of 38 cities made it to the worlds top 1000 cities with startup ecosystem.

7.1% of the startups in the world operate in the Fintech industry. Followed by Life sciences and healthcare with 6.8%, Artificial intelligence with 5.0%, Gaming 4.7%, Adtech 3.3%, and Edtech with 2.8%. Even though there isnt completely accurate data about industry distribution, its clear that modern startups gravitate towards the internet and digital technologies. With this information we can also see which industry is best for startups now.

The United States is the leading country by the number of startups (63,703) by a long shot. The second on the list is India, with just 8,301 startups, and the third spot is occupied by the UK, with 5,377 startups.

To put things into perspective, the US has almost three times more startups than the rest of the following 9 countries in the world combined.There are currently more than 600 Unicorn companies around the world. However, most of them are in China or the United States.Unicorn companies are startups that are valued at $1 billion or more. Most unicorn companies today are involved in the global sharing economy, where they can make quick gains.

Second place is held firmly by China, with 25% of all unicorn companies in the world. Third and fourth places are constantly being traded by India and the United Kingdom, with about 5% of unicorns or around 20 companies each.

The value of e-commerce sales globally is around $3.5 trillion, with rapid growth expected in the future.That is why e-commerce is one of the most popular industries for new startups. The next industry in line is Fintech Financial technology.

Online financial services have been booming since the introduction of PSD2.Another big focus of new startups is cybersecurity. These companies understand how important online security will be in the future. FoodTech combines food and technology, specifically the internet, to deliver products to customers another popular industry for startups.With over US$16 billion of investments in 2018, EdTech is becoming another popular startup industry that provides educational technology solutions to people worldwide.

95% of entrepreneurs that create startups have at least a bachelors degree.Many people say that education is not important. They point to Mark Zuckerberg and Elon Musk as examples. However, most of the people involved in some of the worlds most successful startups have a higher education.

Look at the honest statistics below about how many startup businesses fail, this information will give you an idea of what percentage of startups are successful:

The primary reason for these numbers is a lack of ability to offer a product for a target market. Many companies arent able to generate interest in their products or services. Some companies also struggle with marketing. They donot have the finances to do it right and present what they have to offer to the right segment of the public.

Another reason for startup failure is poor team organization. Companies are unable to develop a group of people that will work together effectively towards the same goals.

19% of startup leaders agree that competition is the greatest challenge when starting a business.

The second biggest challenge is cash flow (12%), taxes (11%), economy (11%), and growth is last with 10%. Other startups face a variety of other challenges.

The startup industry will continue to be the driving factor for global innovation and business growth for many years. However, companies need to learn how to adjust to trends while being sustainable and efficient so that more startups can survive long term.

Entrepreneurs are rightly known as national assets and individuals who are motivated to a great degree. These are the people responsible for changing the way of life of the people in a country. They arent only adding to their own account with a successful venture, rather they create wealth in the society with these ventures. For the jobless, these entrepreneurial ventures are boon due to the immense job opportunities that come in the market. More jobs are always reflective of a well-balanced society and one that is geared for progress. If the production function model is to be taken into account then entrepreneurial capital is truly of great importance to the entire nation. In India, innovation has taken leaps and bounds of growth in the fields of IT, Education, Health care, etc. due to the numerous start-ups in these domains. If you take a closer look, innovativeness has achieved more growth due to the reign of entrepreneurship. There are numerous competitors in the same domain and hence the need for something new and added quality is always rife to gain more market space and popularity. Here are some of the major impacts that entrepreneurs have on the Indian economy.

It is rightly said that people are of utmost importance in everything you do. If you have got the right people, business models and product will surely find a way into the market. There are numerous youth and fearless entrepreneurs in India that have taken huge strides to bring about a positive change in the economy of the country. On a deeper insight, entrepreneurship is the driving force in the market. However, there are people who have the idea that entrepreneurship is all about the struggle of a man to start a project or business on his/her own, it isnot true. The struggle is far behind and the focus should be on the growth it offers to the country.

Right from gathering workforce, funding, resources and creating an organisational structure, these are the things that encompass the idea of entrepreneurship. What remains a question is how the practice benefits the Indian Economy.

Promoting capital formation: The idle savings of the people are mobilised by the entrepreneurs by providing them with new opportunities. Resources are employed so that people can set up their own enterprises. With these kinds of entrepreneurial activities, value addition the wealth of the nation is assured. Such creation of wealth adds to the industrial and economic growth of the nation. More capital formation means that a noticeable increase in the overall production of the nation.

Job creation: If success is to be achieved in entrepreneurial ventures, then it is to be understood that the work will need more than two hands. Varying skills sets are needed for a project to become successful, and this is where a new scope for jobs opens to the people. Thriving business setups makes sure that the job queues are cut to half in a particular geographical area. Given the fact that unemployment at a large scale in an unending problem prevailing in the country, skilled and technically qualified people are sure to land a job with these opportunities.

Regional development: India vs. Bharat is a debate that has been prevalent for a long period of time and truly the difference in the growth of rural and urban areas is immense in the nation. However, 73% of households are in the rural area and therefore there is a need for balanced regional development. Entrepreneurial ventures remove the disparities between rural and urban areas with the help of industrialisation. The benefits from these ventures lead to community development such as road, education, health, and entertainment. Dwelling habits in slums and congestions are reduced as they have job opportunity and can sustain a better living.

Decentralises economic power: Monopoly takes growth when the industrial set up is more prevalent in the nation and hence the economic power is only within the hands of selected few. Through entrepreneurship, economic power is distributed to subsequent contributors and hence the wealth is no longer decentralised. It makes society a lot more balanced and paves overall development.

Increases GDP and per capita income: Every entrepreneurial venture adds to the economy of the nation. Every innovation in the market is improving the quality of service and hence helping the market to be further advanced. Resource and skill mobilisation in an effective manner helps in developing prospects in the market as well as adding substantially to the economy of the nation. These help to let the gross national product along with per capita income in the place.

As new ideas and innovations keep coming in the market on a daily basis, variety in the market gets a major boost along with prices that are competitive in order to gather better space in the market. It enables people to avail them for leading a better life and without compromising on their budget. It helps boost the standard of living of the people and suddenly the nation becomes a better place to live for even with minimal finances.

Export trade boost: The export trade gets a huge boost since entrepreneurs produce goods in large quantities and there is enough to be exported to foreign countries. Foreign exchange amount is enhanced with this and thus greater economic independence is achieved. All these only points towards a single point agenda of national development and financial growth.

Backward and forward linkages: The essential target of every entrepreneur is to maximise capital flow with the help of rapid innovations which they come up with. Backward and forward linkages are influenced by these practices and hence better economic growth is achieved. Such linkage theory reflects the fact that meaningful investments are being done in the country and there is a plan behind every step taken financially.

It is a fact that competition in the market is sure to come when there are entrepreneurs vying for the attention of the same consumer base in a market. Several producers in the same domain will make sure that each of them will be in search of better facilities which they can provide to their customers. Also, there will be a price war in the market and the one with the best quality will sustain for the longest period of time. It benefits the customer as they can now afford the services without burning a hole in their pockets.

Social change beyond imagination: Entrepreneurs are all about breaking the traditional idea of freedom and further expanding it because the sky is the limit now. The dependency on the lower level of technology and outdated systems are a thing of past as they can be easily replaced with local producers or through imports. The underdeveloped countries are getting access to high end technology to get the work done and as a result they are coming up with new goods and ideas. It is economically viable to them because the cost of living is low for people based in underdeveloped countries. The economic freedom they get along with the wide array of choice make it the best-suited system of production in any given economic set up.

On the other hand, there are always grimmest to any positive aspect. As flawless the system may look on the outset, it is difficult to master unless you are a crafter agent in the domain. Proper education and sense of the market must be imbibed in a person before they are ready to wave off their entrepreneurial venture. If they fail, then it is a massive financial loss for the person and the employed people will find it hard to get their salaries. Additionally, the resource base of the country is stressed with such initiatives. Over exploitation of natural resources are always a threat and it can lead to serious consequences later.

IT infrastructure refers to the composite hardware, software, network resources and services required for the existence, operation and management of an enterprise IT environment.

IT infrastructure allows an organization to deliver IT solutions and services to its employees, partners and/or customers and is usually internal to an organization and deployed within owned facilities.

Developers rely on platforms throughout the IT software development process to connect data, process it, increase their go-to-market velocity, and stay ahead of the competition with new and existing products. They have enormous amounts of end-user data on hand, and productivity infrastructure can remove barriers to access, integrate and leverage this data to automate the workflow.

Access to rich interaction data combined with pre-trained ML models, automated workflows and configurable front-end components enables developers to drastically shorten development cycles. Through enhanced data protection and compliance, productivity infrastructure safeguards critical data and mitigates risk while reducing time to ROI.

IT infrastructure consists of all components that somehow play a role in overall IT and IT-enabled operations. It can be used for internal business operations or developing customer IT or business solutions.

Typically, a standard IT infrastructure consists of the following components:

Hardware: This is the physical part of an IT infrastructure and comprises all the elements necessary to support the basic functioning of the machines and devices constituting the infrastructure itself.Servers, computers, storage and data centers, switches, hubs and routers, as well as all other equipment such as the power, cooling, cabling and dedicated rooms.

Software: It refers to all the applications used by the enterprise both for internal purposes and to provide its services to customers. Software includes web servers, Enterprise resource planning (ERP), customer relationship management (CRM), productivity applications and the operating system (OS).

The OS is the most important software component and is responsible for managing the hardware itself and connect the physical resources to the network infrastructure.

Network: Although is not strictly necessary for an IT infrastructure to function, the network is essential to establish internal and external communication of all elements and devices.

The network part includes all the hardware and software elements necessary to ensure network enablement, internet connectivity, firewall and security. It ensures that personnel get access to stored and transferred data only from strictly controlled access points to reduce the risk of data theft or damage.

Meatware: Since they contribute to constituting the enterprise environment and guarantee its functions, associated personnel and processes such as ITOps or DevOps are also part of an IT infrastructure.

Human users, such as network administrators (NA), developers, designers and end users with access to any IT appliance or service are also part of an IT infrastructure, specifically with the advent of user-centric IT service development.

Traditional Vs. Cloud Infrastructures: All the components mentioned above that constitute a traditional infrastructure are usually owned by the enterprise itself and managed within their own facilities.

The larger the IT infrastructure, the more space, power, personnel, and money will be needed to run it. Today, part of this infrastructure can be virtualized and rented from third-party services to cut the costs.

Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS) are all relatively new options that allow businesses to rent software, infrastructure, services and human resources from external vendors who will deliver them using the internet. All the components rented are hosted and managed in cloud servers that employ their own IT infrastructures.

Since all these resources are built on virtualization technology, they can easily be scaled up or down as the needs of the business employing them changes.Set of physical devices and software required to operate enterpriseIT infrastructure Components:

Technology has impacted and improved the way companies conduct their business, including communication, productivity, and speed in making business decisions. Which is why the importance of managed IT infrastructure cannot be underplayed.

IT infrastructure consists of all elements that support the management and usability of data and information. These include physical hardware and facilities, data storage and retrieval, network systems, legacy interfaces and software to support the business goals of the organization. The structure also includes hiring, training, policy, testing, process, upgrades and repairs.

Infrastructure management is the process of managing the components of a companys information technology. Having appropriate methods in place for the management of the IT infrastructure allows for improved performance, improved availability and quick solutions for various issues that could arise.

A managed IT infrastructure is important because it provides structure and control for diverse technical operations which involve hardware, software and networking in both the physical and virtual environment. IT infrastructure management is also responsible for

The benefits of IT structure management all stem from the ease of operation, clarity of information and reporting and cost saving. Behavior that supports this outcome includes

While new technologies present powerful opportunities for organizations, they also introduce challenges. The pace of change in IT is unprecedented. The mobile devices and cloud-based technologies that have brought in so many possibilities have also introduced several devices, platforms and apps for IT departments to manage and secure. These challenges add up to significant expenses such as cost of hiring and training qualified workers, purchasing the infrastructure to support and so on. Rather than struggle to keep pace with technology themselves, organizations hire service providers for help. The third-party service providers help with cloud deployments, data center solutions, mobile initiatives, collaboration tools and security. They offer a holistic approach resulting in higher standards as compared to organizations that handle it in-house. Turning to a trusted partner offers several advantages including:

If a company does not have a team dedicated to managing its IT infrastructure, it will be impossible to predict or manage disasters as they come along. This reactive approach can lead to lengthy downtimes and major data loss. Therefore, being proactive will save a lot of money for the company during disasters and in their aftermath and provide for budget for such emergencies.

Outsourcing functions such as cybersecurity and app development to a partner with technically skilled and specialized engineers in new and emerging technologies alleviates the pressure from the company.

If data is deleted, lost, corrupted, or compromised, it can be restored with the help of backups that have incorporated as part of the IT infrastructure. A careful and efficiently managed backup process reduces downtime, maintains productivity andcontinues to provide outstanding customer satisfaction.

IT organizations spend months deploying large systems. Outsourcing the management of the IT infrastructure helps an organization to scale up or scale down depending on the demand.

There are no more standard/fixed work hours any longer and it only makes sense to have a support system that is working constantly to support users. This can be supported by the service provider in an organized manner.

In addition to regular audits, organizations are also obligated to meet standards and requirements in accordance with the laws of the state. Laws could pertain to safety, reporting and security. All this can be handled by the service provider without adding the burden on the in-house staff.

Improving the infrastructure helps to improve agility, reduce time, effort and cost to manage the IT infrastructure internally. Simplifying equipment and processes will help to better identify weaknesses and necessary improvements in the infrastructure. There are a few important practices that simplify the management of IT infrastructure of an organization and improve its efficiency.

The concept of IT HUB is derived in tune from Secured Governance through a revolution that requires upturning all the procedures evolved through years of efforts and experience. It realizes the tools for bringing about effective and sustainable changes in the system. The methodology has been evolved through hands on experience in dealing with the industry and governmental system. When identifying and determining development potential within an economy a set of criteria is required against which to evaluate whether the effort being undertaken possesses development potential or not. The set of criteria serves as an evaluation tool to identify areas with potential for development and opportunities within each of the local economic sectors.

The IT HUB will provide innumerable benefits in the following way:

Today we find the valuation due to infrastructure growth is not optimally channelized towards infrastructure development and results in inequalities in society. Secured Governance compliments the present PPP (Public Private Participation) developmental model, by ensuring balanced participation of the private and public sector taking advantage of value and valuation of IT HUB thereby yielding higher returns. This valuation of infrastructure, which grows many folds, needs to be shared by society and by the Government to support infrastructure development, ensuring balanced growth.

Secured Governance for Information Technology will provide for high quality commercial development along IT HUB, which serve as Techno Economic HUB. These HUBs will be part of existing or new development project. These HUBs will not only facilitate telecom users but also promotes commercial units generating employment and revenue from the defined region. The HUBs aid to boost employment generation and sustainable investment opportunity in a big way. It is expected to attract billion crore rupees over the next five years and generating millions of direct and indirect employment opportunities in region. With the robust outlook of the IT sector, it is expected that India will see private and foreign participation in the development and financing of IT HUB infrastructure, engineering services, equipment supply and technology partnership in digital communication.

By,Dr P. Sekhar,Chairman,Unleashing India,Global Smart City Panel,MTGF

Summary

Article Name

Enhanced Role for Startup, Entrepreneurs with IT Infrastructure for Secured National Reincarnations

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In accordance with the Countries Global Ranking of Startup Ecosystem 2020 by global innovation mapping and research company StartupBlink, India ranked at 23rd position, a drop of 6 places from 17th position in 2019.

Author

TPT News Bureau

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THE POLICY TIMES

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Of All Things: Artificial intelligence is real | News | montgomerynews.com – Montgomery Newspapers

There seem to be a lot of articles about artificial intelligence in newspapers and magazines these days. Some of the other stuff in print makes me think that what we need is more regular intelligence,

Last week, the legislative branch of the 27-country European Union headquartered in Brussels announced plans to restrict the use of artificial intelligence. Its an attempt to head off abuse of artificial intelligence technology, instead of waiting for it to be a problem the way the United States does.

Artificial intelligencesimulates humanintelligencein computers that are programmed to think and act like human beings. (Hey, what could go wrong?)

Originally,artificial intelligence meant a machine doing something that would have previously needed human intelligence.From what Im reading these days, I worry that the artificial intelligence may be more intelligent than the human kind.

All of the major computer companies seem to offervirtual personal assistants (Microsoft Cortana, Apple Siri, Amazon Alexa and Google Assistant, for instance.)

Alexa, for another instance, can handle your e-mail, your shopping list, the radio and television, cooking, a wake-up call, communication with friends and family, and generally canrun your life.

Its hard to believe (at least for an old guy like me) to read about some of the things artificial intelligence can do.

For instance, some artificial intelligence systems can allow you todeposit checks in the bank from your living room, and, if necessary, some can decipher the handwriting on the check.

Artificial intelligence can also detect fraudulent use of a credit card by observing the users normal credit card spending patterns.

Youre likely to run into that sort of electronic voodoo any time in these ever-increasing days of artificial intelligence.

The intelligence algorithms can detect and remove hate speech, faster than a human censor can. They are able to identify key words and phrases.

Google maps, Im told, not only tell you how to drive to a destination, but, thanks to an artificial intelligence algorithm, tell you what time youll get there, based on traffic conditions.

The Google app algorithm remembers the edges of buildings that have been fed into the system after the owner has manually identified them.

Another feature is the electronic (or possibly voodoo again) recognizing and understanding of handwritten house numbers.(On paper, I presume, not on the houses.)

The scary thing about the foregoing is that the people who devise, and write about, all this new technology claim that the field of artificial intelligence is still in its infancy. More programs are still to come, they tell us, that will much more accurately replicate human capabilities.

I wonder how long it will be before the computers tell us to just go home and take a nap, and theyll take care of everything.

Next thing you know, dear reader, weekly columns like this may be turned out by artificial intelligence, instead of the good old fashioned writers like me. Please dont tell me that you wont know the difference.

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Artificial Intelligence and Machine Learning Drive the Future of Supply Chain Logistics – Supply and Demand Chain Executive

Artificial intelligence (AI) is more accessible than ever and is increasingly used to improve business operations and outcomes, not only in transportation and logistics management, but also in diverse fields like finance, healthcare, retail and others. An Oxford Economics and NTT DATA survey of 1,000 business leaders conducted in early 2020 reveals that 96% of companies were at least researching AI solutions, and over 70% had either fully implemented or at least piloted the technology.

Nearly half of survey respondents said failure to implement AI would cause them to lose customers, with 44% reporting their companys bottom line would suffer without it.

Simply put, AI enables companies to parse vast quantities of business data to make well-informed and critical business decisions fast. And, the transportation management industry specifically is using this intelligence and its companion technology, machine learning (ML), to gain greater process efficiency and performance visibility driving impactful changes bolstering the bottom line.

McKinsey research reveals that 61% of executives report decreased costs and 53% report increased revenues as a direct result of introducing AI into their supply chains. For supply chains, lower inventory-carrying costs, inventory reductions and lower transportation and labor costs are some of the biggest areas for savings captured by high volume shippers. Further, AI boost supply chain management revenue in sales, forecasting, spend analytics and logistics network optimization.

For the trucking industry and other freight carriers, AI is being effectively applied to transportation management practices to help reduce the amount of unprofitable empty miles or deadhead trips a carrier makes returning to domicile with an empty trailer after delivering a load. AI also identifies other hidden patterns in historical transportation data to determine the optimal mode selection for freight, most efficient labor resource planning, truck loading and stop sequences, rate rationalization and other process improvement by applying historical usage data to derive better planning and execution outcomes.

The ML portion of this emerging technology helps organizations optimize routing and even plan for weather-driven disruptions. Through pattern recognition, for instance, ML helps transportation management professionals understand how weather patterns affected the time it took to carry loads in the past, then considers current data sets to make predictive recommendations.

The Coronavirus disease (COVID-19) put a tremendous amount of pressure on many industries the transportation industry included but it also presented a silver lining -- the opportunity for change. Since organizations are increasingly pressed to work smarter to fulfill customers expectations and needs, there is increased appetite to retire inefficient legacy tools and invest in new processes and tech tools to work more efficiently.

Applying AI and ML to pandemic-posed challenges can be the critical difference between accelerating or slowing growth for transportation management professionals. When applied correctly, these technologies improve logistics visibility, offer data-driven planning insights and help successfully increase process automation.

Like many emerging technologies promising transformation, AI and ML have, in many cases, been misrepresented or worse, overhyped as panaceas for vexing industry challenges. Transportation logistics organizations should be prudent and perform due diligence when considering when and how to introduce AI and ML to their operations. Panicked hiring of data scientists to implement expensive, complicated tools and overengineered processes can be a costly boondoggle and can sour the perception of the viability of these truly powerful and useful tech tools. Instead, organizations should invest time in learning more about the technology and how it is already driving value for successful adopters in the transportation logistics industry. What are some steps a logistics operation should take as they embark on an AI/ML initiative?

Remember that the quality of your data will drive how fast or slow your AI journey will go. The lifeblood of an effective AI program (or any big data project) is proper data hygiene and management. Unfortunately, compiling, organizing and accessing this data is a major barrier for many. According to a survey conducted by OReilly, 70% of respondents report that poorly labeled data and unlabeled data are a significant challenge. Other common data quality issues respondents cited include poor data quality from third-party sources (~42%), disorganized data stores and lack of metadata (~50%) and unstructured, difficult-to-organize data (~44%).

Historically slow-to-adopt technology, the transportation industry has recently begun realizing the imperative and making up ground with 60% of an MHI and Deloitte poll respondents expecting to embrace AI in the next five years. Gartner predicts that by the end of 2024, 75% of organizations will move from piloting to operationalizing AI, driving a five times increase in streaming data and analytics infrastructures.

For many transportation management companies, accessing, cleansing and integrating the right data to maximize AI will be the first step. AI requires large volumes of detailed data and varied data sources to effectively identify models and develop learned behavior.

Before jumping on the AI bandwagon too quickly, companies should assess the quality of their data and current tech stacks to determine what intelligence capabilities are already embedded.

And, when it comes to investing in newer technologies to pave the path toward digital transformation, choose AI-driven solutions that do not require you to become a data scientist.

If youre unsure how to start, consider partnering with a transportation management system (TMS) partner with a record of experience and expertise in applying AI to transportation logistics operations.

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Artificial intelligence taking over DevOps functions, survey confirms – ZDNet

The pace of software releases has only accelerated, and DevOps is the reason things have sped up. Now, artificial intelligence and machine learning are also starting to play a role in this acceleration of code releases.

That's the word from GitLab's latest surveyof 4,300 developers and managers, which finds some enterprises are releasing code ten times faster than in previous surveys. Almost all respondents, 84%, say they're releasing code faster than before, and 57% said code is being released twice as fast, from 35% a year ago. Close to one in five, 19%, say their code goes out the door ten times faster.

Tellingly, 75% are using AI/ML or bots to test and review their code before release, up from 41% just one year ago. Another 25% say they now have full test automation, up from 13%.

About 21% of survey respondents say the pace of releases has accelerated with the addition of source code management to their DevOps practice (up from 15% last year), the survey's authors add. Another 18% added CI and 13% added CD. Nearly 12% say adding a DevOps platform has sped up the process, while just over 10% have added automated testing.

Developers' roles are shifting toward the operations side as well, the survey shows. Developers are taking on test and ops tasks, especially around cloud, infrastructure and security. At least 38% of developers said they now define or create the infrastructure their app runs on. About 13% monitor and respond to that infrastructure. At least 26% of developers said they instrument the code they've written for production monitoring -- up from just 18% last year.

Fully 43% of our survey respondents have been doing DevOps for between three and five years -- "that's the sweet spot where they've known success and are well-seasoned," the survey's authors point out. In addition, they add, "this was also the year where practitioners skipped incremental improvements and reached for the big guns: SCM, CI/CD, test automation, and a DevOps platform."

Industry leaders concur that DevOps has significantly boosted enterprise software delivery to new levels, but caution that it still tends to be seen as an IT activity, versus a broader enterprise initiative. "Just like any agile framework, DevOps requires buy-in," says Emma Gautrey, manager of development operations at Aptum. "If the development and operational teams are getting along working in harmony that is terrific, but it cannot amount to much if the culture stops at the metaphorical IT basement door. Without the backing of the whole of the business, continuous improvement will be confined to the internal workings of a single group."

DevOps is a commitment to quick development/deployment cycles, "enhanced by, among other things, an enhanced technical toolset -- source code management, CI/CD, orchestration," says Matthew Tiani, executive vice president at iTech AG. But it takes more than toolsets, he adds. Successful DevOps also incorporates "a compatible development methodology such as agile and scrum, and an organization commitment to foster and encourage collaboration between development and operational staff."

Then organizations aspects of DevOps tend to be more difficult, Tiani adds. "Wider adoption of DevOps within the IT services space is common because the IT process improvement goal is more intimately tied to the overall organizational goals. Larger, more established companies may find it hard to implement policies and procedures where a complex organizational structure impedes or even discourages collaboration. In order to effectively implement a DevOps program, an organization must be willing to make the financial and human investments necessary for maintaining a quick-release schedule."

What's missing from many current DevOps efforts is "the understanding and shared ownership of committing to DevOps," says Gautrey. "Speaking to the wider community, there is often a sense that the tools are the key, and that once in place a state of enlightenment is achieved. That sentiment is little different from the early days of the internet, where people would create their website once and think 'that's it, I have web presence.'"

That's where the organization as a whole needs to be engaged, and this comes to fruition "with build pipelines that turn red the moment an automated test fails, and behavioral-driven development clearly demonstrating the intentions of the software," says Gautrey. "With DevOps, there is a danger in losing interaction with individuals over the pursuit of tools and processes. Nothing is more tempting than to apply a blanket ruling over situations because it makes the automation processes consistent and therefore easier to manage. Responding to change means more than how quickly you can change 10 servers at once. Customer collaboration is key."

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Global Artificial Intelligence in Healthcare Markets Report 2021: Growing Investment in AI Healthcare Start-ups & Increasing Cross-Industry…

DUBLIN, May 14, 2021 /PRNewswire/ -- The "Artificial Intelligence in Healthcare Market Forecast to 2027 - COVID-19 Impact and Global Analysis by Component, Application, End User, and Geography" report has been added to ResearchAndMarkets.com's offering.

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Robot Assisted Surgery Segment to Grow at Faster CAGR During 2020-2027

Artificial Intelligence (AI) in Healthcare Market is expected to reach US$ 107,797.82 million by 2027 from US$ 3,991.23 million in 2019; it is estimated to grow at a CAGR of 49.8% from 2020 to 2027.

The report highlights trends prevailing in the market, and the factors driving and hindering the market growth. The growth of the artificial intelligence in healthcare market is attributed to the rising application of artificial intelligence in healthcare, growing investment in AI healthcare start-ups, and increasing cross-industry partnerships and collaborations. However, dearth of skilled AI workforce and imprecise regulatory guidelines for medical software is the major factor hindering the market growth.

Based on application, the artificial intelligence in healthcare market is segmented into robot assisted surgery, virtual assistants, administrative workflow assistants, connected machines, diagnosis, clinical trials, fraud detection, cybersecurity, dosage error reduction, and others. The clinical trials segment held the largest market share in 2019, and the robot assisted surgery segment is estimated to register the highest CAGR during the forecast period. Rising adoption of robotic surgeries due to better surgical outcomes offer lucrative opportunities for the growth of robotic assisted surgery segment.

The artificial intelligence in healthcare market is expected to witness substantial growth post-pandemic. The global healthcare infrastructure has observed that, in order to develop and maintain sustainable healthcare setup, utilization of computational technologies such as artificial intelligence becomes crucial. Moreover, majority of the market players have focused on development of AI-powered models to fight against coronavirus pandemic.

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In addition, several number of research centers and governments have actively participated in the building of robust AI technologies which are assisting the healthcare professionals to work efficiently even under shortage of resources. These factors will eventually drive the market growth.

Microsoft, Koninklijke Philips N.V., Intel Corporation, General Electric Company, Alphabet Inc., NVIDIA CORPORATION, Nuance Communications, Inc., Siemens Healthineers AG, Arterys Inc., and Johnson & Johnson Services, Inc. are among the leading companies operating in the artificial intelligence in healthcare market.

Key Topics Covered:

1. Introduction1.1 Scope of the Study1.2 Research Report Guidance1.3 Market Segmentation

2. Artificial Intelligence in Healthcare Market - Key Takeaways

3. Research Methodology

4. Global Artificial Intelligence in Healthcare - Market Landscape4.1 Overview4.2 PEST Analysis4.3 Expert Opinions

5. Artificial Intelligence in Healthcare Market - Key Market Dynamics5.1 Market Drivers5.1.1 Rising Application of Artificial Intelligence (AI) in Healthcare5.1.2 Growing Investment in AI Healthcare Start ups5.1.3 Increasing Cross-Industry Partnerships and Collaborations5.2 Market Restraints5.2.1 Dearth of Skilled AI Workforce and Imprecise Regulatory Guidelines for Medical Software5.3 Market Opportunities5.3.1 Increasing Potential in Emerging Economies5.4 Future Trends5.4.1 AI in Epidemic Outbreak Prediction and Response5.5 Impact Analysis

6. Artificial Intelligence in Healthcare Market - Global Analysis6.1 Global Artificial Intelligence in Healthcare Market Revenue Forecast And Analysis6.2 Global Artificial Intelligence in Healthcare Market, By Geography - Forecast And Analysis6.3 Market Positioning of Key Players

7. Artificial Intelligence in Healthcare Market Analysis - By Component7.1 Overview7.2 Artificial Intelligence in Healthcare Market Revenue Share, by Component (2019 and 2027)7.3 Software Solution7.4 Hardware7.5 Services

8. Artificial Intelligence in Healthcare Market Analysis - By Application8.1 Overview8.2 Artificial Intelligence in Healthcare Market Revenue Share, by Application (2019 and 2027)8.3 Robot Assisted Surgery8.4 Virtual Assistants8.5 Administrative Workflow Assistants8.6 Connected Machines8.7 Diagnosis8.8 Clinical Trials8.9 Fraud Detection8.10 Cybersecurity8.11 Dosage Error Reduction

9. Artificial Intelligence in Healthcare Market Analysis - By End User9.1 Overview9.2 Artificial Intelligence in Healthcare Market, by End-User, 2019 and 2027 (%)9.3 Hospitals & Healthcare Providers9.4 Patients9.5 Pharma and Biotech Companies9.6 Healthcare Payers

10. Global Artificial Intelligence in Healthcare Market - Geographical Analysis

11. Impact of COVID-19 Pandemic on Global Artificial Intelligence in Healthcare Market11.1 North America: Impact Assessment of COVID-19 Pandemic11.2 Europe: Impact Assessment Of COVID-19 Pandemic11.3 Asia-Pacific: Impact Assessment of COVID-19 Pandemic11.4 Middle East and Africa: Impact Assessment of COVID-19 Pandemic11.5 South and Central America: Impact Assessment of COVID-19 Pandemic

12. Artificial Intelligence (AI) in Healthcare Market -Industry Landscape12.1 Overview12.2 Growth Strategies in the Artificial Intelligence in Healthcare Market, 2019-202012.3 Inorganic Growth Strategies12.3.1 Overview12.4 Organic Growth Strategies12.4.1 Overview

13. Company Profile13.1 Key Facts13.2 Business Description13.3 Products and Services13.4 Financial Overview13.5 SWOT Analysis13.6 Key Developments

Microsoft

Koninklijke Philips N.V.

Intel Corporation

General Electric Company

Alphabet Inc.

NVIDIA CORPORATION

Nuance Communications, Inc.

Siemens Healthineers AG

Arterys Inc.

Johnson & Johnson Services, Inc.

For more information about this report visit https://www.researchandmarkets.com/r/59o3z6

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Global Artificial Intelligence in Healthcare Markets to 2027: Robot Assisted Surgery Segment to Register the Highest Growth Rate -…

DUBLIN--(BUSINESS WIRE)--The "Artificial Intelligence in Healthcare Market Forecast to 2027 - COVID-19 Impact and Global Analysis by Component, Application, End User, and Geography" report has been added to ResearchAndMarkets.com's offering.

Robot Assisted Surgery Segment to Grow at Faster CAGR During 2020-2027

Artificial Intelligence (AI) in Healthcare Market is expected to reach US$ 107,797.82 million by 2027 from US$ 3,991.23 million in 2019; it is estimated to grow at a CAGR of 49.8% from 2020 to 2027.

The report highlights trends prevailing in the market, and the factors driving and hindering the market growth. The growth of the artificial intelligence in healthcare market is attributed to the rising application of artificial intelligence in healthcare, growing investment in AI healthcare start-ups, and increasing cross-industry partnerships and collaborations. However, the dearth of skilled AI workforce and imprecise regulatory guidelines for medical software are the major factors hindering the market growth.

Based on application, the artificial intelligence in healthcare market is segmented into robot assisted surgery, virtual assistants, administrative workflow assistants, connected machines, diagnosis, clinical trials, fraud detection, cybersecurity, dosage error reduction, and others. The clinical trials segment held the largest market share in 2019, and the robot assisted surgery segment is estimated to register the highest CAGR during the forecast period. Rising adoption of robotic surgeries due to better surgical outcomes offer lucrative opportunities for the growth of robotic assisted surgery segment.

The artificial intelligence in healthcare market is expected to witness substantial growth post-pandemic. The global healthcare infrastructure has observed that, in order to develop and maintain sustainable healthcare setup, utilization of computational technologies such as artificial intelligence becomes crucial. Moreover, majority of the market players have focused on development of AI-powered models to fight against coronavirus pandemic.

In addition, several number of research centers and governments have actively participated in the building of robust AI technologies which are assisting the healthcare professionals to work efficiently even under shortage of resources. These factors will eventually drive the market growth.

Microsoft, Koninklijke Philips N.V., Intel Corporation, General Electric Company, Alphabet Inc., NVIDIA CORPORATION, Nuance Communications, Inc., Siemens Healthineers AG, Arterys Inc., and Johnson & Johnson Services, Inc. are among the leading companies operating in the artificial intelligence in healthcare market.

Key Topics Covered:

1. Introduction

1.1 Scope of the Study

1.2 Research Report Guidance

1.3 Market Segmentation

2. Artificial Intelligence in Healthcare Market - Key Takeaways

3. Research Methodology

4. Global Artificial Intelligence in Healthcare - Market Landscape

4.1 Overview

4.2 PEST Analysis

4.3 Expert Opinions

5. Artificial Intelligence in Healthcare Market - Key Market Dynamics

5.1 Market Drivers

5.1.1 Rising Application of Artificial Intelligence (AI) in Healthcare

5.1.2 Growing Investment in AI Healthcare Start ups

5.1.3 Increasing Cross-Industry Partnerships and Collaborations

5.2 Market Restraints

5.2.1 Dearth of Skilled AI Workforce and Imprecise Regulatory Guidelines for Medical Software

5.3 Market Opportunities

5.3.1 Increasing Potential in Emerging Economies

5.4 Future Trends

5.4.1 AI in Epidemic Outbreak Prediction and Response

5.5 Impact Analysis

6. Artificial Intelligence in Healthcare Market - Global Analysis

6.1 Global Artificial Intelligence in Healthcare Market Revenue Forecast And Analysis

6.2 Global Artificial Intelligence in Healthcare Market, By Geography - Forecast And Analysis

6.3 Market Positioning of Key Players

7. Artificial Intelligence in Healthcare Market Analysis - By Component

7.1 Overview

7.2 Artificial Intelligence in Healthcare Market Revenue Share, by Component (2019 and 2027)

7.3 Software Solution

7.4 Hardware

7.5 Services

8. Artificial Intelligence in Healthcare Market Analysis - By Application

8.1 Overview

8.2 Artificial Intelligence in Healthcare Market Revenue Share, by Application (2019 and 2027)

8.3 Robot Assisted Surgery

8.4 Virtual Assistants

8.5 Administrative Workflow Assistants

8.6 Connected Machines

8.7 Diagnosis

8.8 Clinical Trials

8.9 Fraud Detection

8.10 Cybersecurity

8.11 Dosage Error Reduction

9. Artificial Intelligence in Healthcare Market Analysis - By End User

9.1 Overview

9.2 Artificial Intelligence in Healthcare Market, by End-User, 2019 and 2027 (%)

9.3 Hospitals & Healthcare Providers

9.4 Patients

9.5 Pharma and Biotech Companies

9.6 Healthcare Payers

10. Global Artificial Intelligence in Healthcare Market - Geographical Analysis

11. Impact of COVID-19 Pandemic on Global Artificial Intelligence in Healthcare Market

11.1 North America: Impact Assessment of COVID-19 Pandemic

11.2 Europe: Impact Assessment Of COVID-19 Pandemic

11.3 Asia-Pacific: Impact Assessment of COVID-19 Pandemic

11.4 Middle East and Africa: Impact Assessment of COVID-19 Pandemic

11.5 South and Central America: Impact Assessment of COVID-19 Pandemic

12. Artificial Intelligence (AI) in Healthcare Market -Industry Landscape

12.1 Overview

12.2 Growth Strategies in the Artificial Intelligence in Healthcare Market, 2019-2020

12.3 Inorganic Growth Strategies

12.3.1 Overview

12.4 Organic Growth Strategies

12.4.1 Overview

13. Company Profile

13.1 Key Facts

13.2 Business Description

13.3 Products and Services

13.4 Financial Overview

13.5 SWOT Analysis

13.6 Key Developments

For more information about this report visit https://www.researchandmarkets.com/r/3obq2z

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Here’s What the Dreams of Google’s Artificial Intelligence Look Like – Analytics Insight

What if computers had the ability to dream? They can, in reality. Googles innovative DeepDream software is turning Artificial Intelligence neural networks inside out to comprehend how computers think.

When a bunch of artificial brains at Google began producing surreal images from otherwise standard photos, engineers contrasted what they saw to dreamscapes. Their image-generation method was termed Inceptionism and the code that powered it was called DeepDream.

Wikipedia says DeepDream is a computer vision program created by Google engineer Alexander Mordvintsev that uses a convolutional neural network to find and enhance patterns in images via algorithmic pareidolia, thus creating a dream-like hallucinogenic appearance in the deliberately over-processed images.

Color scrolls, spinning shapes, stretched faces, swirling eyeballs, and awkward patterns of shadow and light feature in the computer-generated images. The computers seemed to be hallucinating in an astonishingly human manner. The aim of the project was to see how well a neural network could identify different animals and environments by having the machine explain what is observed.

So, what really is going on in the dreaming neural networks and what does this mean for the future of Artificial intelligence?

The result reveals a lot about where artificial intelligence is headed, as well as why it could be more imaginative, ambiguous, and unpredictable than wed like.

The Google artificial neural network is modeled after the central nervous system of animals and functions similarly to a computer brain. When engineers feed a picture to the network, the first layer of neurons examines it. This layer then communicates with the next layer, which attempts to represent the image. This process continues 10 to 30 rounds, with each layer defining and alienating main elements until the picture is deduced. The neural network then informs us what the entity is that it has valiantly attempted to identify, often with little progress. This is the method for recognizing images.

After that, the Google team realized they could reverse the procedure. They hoped to learn more about what qualified features the networks knew and didnt by giving it complete freedom and asking it to interpret and improve an input picture in such a way as to evoke a specific interpretation.

What happened next was quite remarkable. The researchers discovered that these neural networks could not only distinguish between different images but that they also had enough knowledge to produce images, culminating in these unexpected computational representations. The network, for example, produced these unusual images in response to the teams requests for common objects such as insects, bananas, and much more.

According to IFL Science, computers have the ability to see images in objects in a way that artists can only dream of replicating. It sees buildings within clouds, temples in trees, and birds in leaves. Highly detailed elements seem to pop up out of nowhere. This processed image of a cloudy sky proves that Googles artificial neural network is the champion of finding pictures in a cloudy sky.

This technique, which creates images where there arent any, is aptly called inceptionism. There is an inceptionism gallery where you can explore the computers artwork.

Finally, the designers gave the computer full, free reign over its artwork. The final pieces were beautiful pictures derived from a mechanical mind what the engineers are calling dreams. The blank canvas was simply an image of white noise. The computer pulled out patterns from the noise and created dreamscapes: pictures that could only come from an infinite imagination.

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This Cardiologist is Using Artificial Intelligence in Heart Medicine – Influencive

There is a common myth that heart disease is more of a problem for men than women, however women and men die at equal rates from heart disease. Studies have shown that mens heart health is more researched and prioritized over womens heart health which creates an issue in diagnostics.

Misdiagnosis or under diagnosis plague women with hidden heart issues and they wont always get the treatment they need. Because of this irritating and unethical issue, cardiologist and researcher, Dr. Amod Amritphale is working to change this outcome of heart health in women.

Symptoms of heart disease in women are very different than men, but the warning signs for men are published more in the media and are known to be more obvious than for women. Because of this, one woman will die every minute of cardiovascular disease and ninety percent of women have at least one risk factor that could tell them they have a chance of heart disease later on. Many more women die from cardiovascular disease than men and the gap is still widening.

A lot of women with significant symptoms have been misdiagnosed as having anxiety or stress instead. We have to work on this advocacy to assure that women can have the resources and diagnostic tools they need to stay healthy and have access to treatment, Dr. Amritphale states. As the director of the Womens Heart Program at the University of South Alabama and the University Hospital in Mobile, Alabama, and as an Interventional Cardiologist, he can provide extensive literature for highlighting the issue. I have taken up the onus to educate women of middle age to teach them the signs of heart disease and preventive methods so that they can seek help before it is too late, he says.

Whats different about Dr. Amritphales methodology is that not only is he advocating for, treating, and making preventative changes for women and their risk of heart disease, but he is also doing so using computer algorithm programs that he designed. He is also the Director of Cardiovascular Research at the University. I am involved in extensive research. My focus of research is Use of Machine learning and Artificial Intelligence in making better decisions in the field of medicine and I am also using national databases like HCUP.

I use this program to develop algorithms that help identify patients who are at increased risk of bad outcomes so that we can preemptively identify them and help them before the worsening of disease processes occur. This helps people live better and live longer and prevents untimely or early death, Dr. Amritphale says. This method is uniquely his, and he is revolutionizing how people can detect, treat, and determine cardiovascular treatment success with these programs he uses in daily practice.

With various cardiovascular treatments and surgical processes, Dr. Amritphale is able to detect and predict whether or not patients will need to return for an unplanned readmission with his artificial intelligence computer algorithm. From the abstract from his academic study, he and his team of researchers had successful results.

We present a novel deep neural network-based artificial intelligence prediction model to help identify a subgroup of patients undergoing carotid artery stenting who are at risk for short term unplanned readmissions. Prior studies have attempted to develop prediction models but have used mainly logistic regression models and have low prediction ability. The novel model presented in this study boasts 79% capability to accurately predict individuals for unplanned readmissions post carotid artery stenting within 30 days of discharge, (Amritphale, A., Chatterjee, R., Chatterjee, S. et al. Predictors of 30-Day Unplanned Readmission After Carotid Artery Stenting Using Artificial Intelligence. Adv Ther (2021). https://doi.org/10.1007/s12325-021-01709-7).

Anything that could give rise to smarter-than-human intelligencein the form of Artificial Intelligence, brain-computer interfaces, or neuroscience-based human intelligence enhancement wins hands down and Dr. Amritphale is harnessing this power for the betterment of society as a whole said Dr. Khanijao an Internal Medicine & Pulmonary specialist from Maimonides Medical Center, New York.

This innovation is the next step to making sure womens heart health is properly researched, recognized, diagnosed, and treated. His advocacy and computer algorithm are seventy-nine percent accurate to determine the healing, successes of a treatment, and any risk factors that would bring the patient back within thirty days after cardiac stenting surgery.

The global impact of Dr. Amritphales research and work is such that ultimately more people are living healthier and longer lives. Dr. Amritphale is an authority in the field, and researchers/clinicians the world over should follow in the new vistas opened up by his research. said prominent cardiologist Dr. A. Joseph.

Dr. Amritphale is at the top of his endeavor when it comes to leading research for treating patients with advanced heart blockages. The condition called refractory angina is one where all medications have proven inadequate and patients are utterly suffering. In patients with such advanced disease, he has shown a pathway to clinicians & researchers worldwide to use mechanical and invasive therapies.

This has opened up new vistas of researchers and has been cited by many researchers, notably those at University Hospital Richmond Medical Center in Ohio. (Amritphale A, Amritphale N. Refractory Angina: the Current State of Mechanical Therapies. Curr Cardiol Rep. 2019 Apr 22;21(6):46. doi: 10.1007/s11886-019-1134-8. PMID: 31011835.)

Heart health strategy and prioritization is important and Dr. Amritphale made the changes to make sure it wont be overlooked. With his research in machine learning and as an authority in this field, he is changing the future of the threat of heart disease for everyone, especially women and guiding researchers at a global scale.

Published May 15th, 2021

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Artificial Intelligence in Gaming Market 2021 Size, Status and Business Outlook Ubisoft, EA, Tencent, Sony, Microsoft, Playtika, Activision Blizzard …

Artificial Intelligence in Gaming Market with COVID-19 Impact by Component, Application, Services, and Region- Forecast to 2027

The Global Artificial Intelligence in Gaming Market Research Report 2021-2027 is a significant source of keen information for business specialists. A report published by Market Insights Reports is an overall investigation and thorough information in regards to the market size and market elements of the Artificial Intelligence in Gaming. It furnishes the business outline with development, historical and futuristic cost analysis, income, demand, and supply information (upcoming identifiers). The research analysts give a detailed depiction of the worth chain and its wholesaler examination. The Artificial Intelligence in Gaming market study gives extensive information which upgrades the agreement, degree, and use of this report. This is a latest report, covering the COVID-19impact on the market.

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Top Companies in the Global Artificial Intelligence in Gaming Market are Ubisoft, EA, Tencent, Sony, Microsoft, Playtika, Activision Blizzard, NetEase, Nintendo, Square Enix, Konami, Take-Two Interactive, NCSoft, Google, Baidu, IBM, SAP, Intel, Salesforce, Brighterion, KITT.AI

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On-Premise

Cloud-based

Based on Application, the Global Artificial Intelligence in Gaming Market are divided into-

PC Gaming

TV Gaming

Smartphone & Tablet Gaming

The current Artificial Intelligence in Gaming market possibilities of the sector additionally have been analyzed. Furthermore, prime strategical activities in the market, which incorporate product advancements, and acquisitions, partnerships are discussed. Artificial Intelligence in Gaming Organization Coverage (Company Profile, Sales Revenue, Price, Gross Margin, Main Products, and so on)

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The report contains detailed country-level analysis, market revenue, market value and forecast analysis of ingestion, revenue and Artificial Intelligence in Gaming market share,growth speed, historical and forecast (2016-2027) of these regions are covered:

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