Artificial intelligence (AI) term was coined by John McCarthy, defined it as “the science and engineering of making intelligent machines”. The field was founded on the claim that a central property of humans, intelligence can be so precisely described that a machine can be made to simulate it. The general problem of simulating (or creating) intelligence has been broken down into a number of specific sub-problems. These consist of particular traits or capabilities that researchers would like an intelligent system to display. These include reasoning, knowledge, planning, learning, natural language processing (communication), perception and the ability to move and manipulate objects.
AI is further divided into two categories: narrow AI and general AI. Narrow AI systems can perform only the specific task that they were trained to perform, while general AI systems would be capable of performing a broad range of tasks, including those for which they were not specifically trained. General AI systems do not yet exist.
Remarkable progress has been made on what is known as Narrow AI, which addresses specific application areas such as playing strategic games, language translation, self-driving vehicles, and image recognition. Narrow AI underpins many commercial services such as trip planning, shopper recommendation systems, and ad targeting, and is finding important applications in medical diagnosis, education, and scientific research. These have all had significant societal benefits and have contributed to the economic vitality of the Nation.”
General AI (sometimes called Artificial General Intelligence or AGI) refers to a notional future AI system that exhibits apparently intelligent behavior at least as advanced as a person across the full range of cognitive tasks. Attempts to reach General AI by expanding Narrow AI solutions have made little headway over many decades of research. The current consensus of the private-sector expert community, with which the NSTC Committee on Technology concurs, is that General AI will not be achieved for at least decades.
Machine Learning (ML) [a subfield of AI] has now become a pervasive technology, underlying many modern applications including internet search, fraud detection, gaming, face detection, image tagging, brain mapping, check processing and computer server health-monitoring. There is a wide variety of algorithms and processes for implementing ML systems.
AI has gotten more accurate and much faster at image detection. It’s also improved at parsing the grammatical structure of sentences, answering multiple-choice questions and translation. Today, AI forms the basis of computer systems handling tasks such as voice recognition and translation on smartphones, piloting driverless cars, and controlling robots that automate chores in homes and factories.
Artificial intelligence (AI) is widely accepted as having the potential to create significant economic value. In research, AI is being used in a growing number of applications, such as processing the enormous amounts of data that underpin fields including astronomy and genomics, producing climate models and weather forecasts, and identifying signs of disease in medical imaging.
On the official website of The White House, the report, dubbed “Preparing for the future of Artificial Intelligence,” authors state that Artificial Intelligence (AI) has the potential to help address some of the biggest challenges that society faces.” Smart vehicles may save hundreds of thousands of lives every year worldwide, and increase mobility for the elderly and those with disabilities. Smart buildings may save energy and reduce carbon emissions. Precision medicine may extend life and increase quality of life. Smarter government may serve citizens more quickly and precisely, better protect those at risk, and save money. AI-enhanced education may help teachers give every child an education that opens doors to a secure and fulfilling life. “New artificial intelligence applications will have an impact in various fields, including manufacturing, business, stock market analysis, economic inclusion, criminal justice, environment, transportation, health care and space exploration. Accenture analyzed 12 developed economies and found that AI has the potential to double their annual economic growth rates by 2035.
Revenues have also skyrocketed. The International Data Corporation (IDC), a market research company based in Framingham, Massachusetts, predicts that worldwide revenues for the AI market will total $156.5 billion in 2020, an increase of 12.3% over 2019. Although growth in 2020 is slower than in previous years due to the economic impact of the COVID-19 pandemic, the IDC expects that global revenues will surpass $300 billion in 2024.
Artificial intelligence (AI) race among countries
AI Competition Is the New Space Race that has ensued between countries like US, EU China and Russia, each planning to take a lead in this strategic technology. Governments and regulators play a critical role in fostering, or hindering, how technology benefits accrue for their citizens, and the role of academia and research institutes is also crucial for AI technology to develop.
There are several country rankings of AI strength across the world. Those that focus on metrics such as patents and research publications tend to list China first, followed by the US, with third place disputed between European and Asian countries including South Korea, Japan and India. However, taking a broader approach using a composite AI-readiness index (from Oxford Insights) that factors in governance, skills and education, infrastructure and data, and government/public services reveals the top three countries to be Singapore, the UK and Germany.
Trung Ghi and Abhishek Srivastava, who co-authored an article called “The global AI arms race – How nations can avoid being left behind” about the global landscape for AI, and which countries are leading and lagging in the AI arms race. On behalf of the government of Singapore they recently conducted a comparative review of 10 of the top 20 countries.
“AI can contribute to or improve on almost every product, service, or infrastructure that countries are built on,” Abhishek says. “AI will lead to better products, and help you win with your products. Better AI enables you to offer a better customer experience, better features, and a lower price point. So leading governments understand this well, and are building infrastructure around it.”
In their research, Trung and Abhishek assessed countries according to four primary factors or key dimensions::
- AI start-up activity, including investment in AI startups per capita, number of AI start-ups per capita, and number of AI unicorns per capita
- AI-related jobs, including percentage of AI-related jobs in the economy
- Adoption of AI by private industry, including level of AI adoption among top 10 listed companies, extent of AI government support for small and medium-sized enterprises (SMEs), and funds committed to AI adoption
- AI knowledge/skills capability, including H-index (i.e., quality/quantity) in AI publications, weighted citation index in AI, university-led/-funded incubators in top five universities, and AI patents filed per capita
Some of their observations are
- Leading countries have broad coverage across the impact metrics, with a stronger bias towards one or more, based on their context. For example, Germany is the strongest in the sample in private sector adoption of AI, driven by government support of AI-based industrial digitization focused on SMEs and university AI R&D programs that have strong bias for commercialization.
- Canada, the US and Singapore all have strong scores in AI knowledge/skills capability.
- Israel, Singapore and the US have mature and welldefined AI governance frameworks with clear regulatory set-ups, well-established national and regional AI offices, and strong cyber-security and AI risk management practices.
Abhishek says, “When we look at these four dimensions, we see that China is putting a lot of effort into AI and building these capabilities. But in terms of private adoption, we were pleasantly surprised to see smaller countries like Israel and Singapore are taking a big lead. They are the crucible of the labs of the world, so to speak.”
The United States and China are also power players in the world of AI. Long-term, we know that more data leads to better AI, so the scale of China and the U.S. is going to play out with the amount of data they collect.
The U.S. also leads the way in designing algorithms and developing the next wave of AI tech. Because of that innovation, they are able to attract the best talent, which becomes a virtuous cycle for the country. Within the private sector, Germany has a substantial amount of AI-related jobs, especially in SME and manufacturing.
The analysis showed that ensuring local and global AI talents were developed, attracted, and retained was central to national AI success. We found that:
- The US has almost 40 percent of the global AI talent, while Israel and Singapore have the highest scores for AI workforce and talent development from a tertiary education perspective.
- Countries such as Germany, the US and Canada have been able to attract new AI talent into their economies over the last few years, while China, Israel and Singapore have been unable to retain and grow their talent pools.
A country’s national AI talent strategy should therefore aim to create a virtuous cycle in which an AI ecosystem fosters AI talent concentration, which, in turn, drives private innovation and economic development, boosting the AI ecosystem further. Based on our observations, a coordinated policy effort across academic institutions, public sector support and incentives for private players has the highest likelihood of being successful in creating this virtuous cycle.
Finally, the study showed that countries with AI strategies across multiple dimensions, including clearly defined national AI visions, investment in AI benefits, and protections for data usage, had higher likelihood of success compared to countries that focused on fewer dimensions.
Private investment in AI companies
In 2020, private investments in artificial intelligence (AI) from the United States amounted to almost 23.6 billion U.S. dollars, making it the leading destination for AI private investments. Ranked second is China, with 9.9 billion U.S. dollars in funding. The source adds that it is important to note that China has strong public investments in AI
China saw more than $65m of private investment in 2019, while the US saw just above $14m, and the UK a little over $5m. China has also already allocated future state investments in AI one-and-a-half times greater than every other country in the world combined, according to the Global AI Index. This ramping up in AI investment has seen China leap from a pool of other thriving Asia-Pacific economies measured by their GDP, to become a serious and leading threat in the field of AI to the US.
The 2019 AI Index Report, published by the Stanford Institute for Human-Centered Artificial Intelligence in California, estimates that global private investment in AI in 2019 was more than US$70 billion. The US, China and Europe took the largest share; Israel, Singapore and Iceland were found to invest heavily in per capita terms. Start-ups founded on AI technologies are a major part of the ecosystem, garnering more than $37 billion globally in investments in 2019, up from $1.3 billion raised in 2010, according to the report.
Source: Nature Index; Data used were sourced from Dimensions, an inter-linked research information system provided by Digital Science
US is leveraging technologies such as artificial intelligence, autonomous systems and human-machine networks to equalise advances made by the nations opponents in recent years. Between 2011 and 2015, the US published almost 25,500 papers, according to the same source. US ranks as the top country with the most AI companies. With over 1000 companies and US$10 billion in venture capital, the US is likely to become an AI superpower. Then there’s companies like IBM, Microsoft, Google, Facebook, and Amazon. Not only do they publish a significant amount of papers, but they also invest heavily in AI.
“When we say we’re injecting AI and autonomy into the grids, we’re looking at five different things,” the deputy secretary Bob Work said. These include autonomous learning systems for handling big data and determining patterns, human-machine collaboration for more timely relevant decision making, and assisted human operations through technology assistance like exoskeletons or wearable electronics, he added. Other capabilities, Work said, are advanced human-machine combat teaming such as with manned and unmanned systems working together, and network-enabled autonomous weapons and high-speed weapons like directed energy, electromagnetic rail guns and hypersonics.
With an eye to the potential benefits of AI-based technologies, the US National Science Foundation (NSF) announced in August 2020 that it is establishing five new institutes focused on different topics, each led by a different university, and each to receive $20 million over five years. One, led by the University of Oklahoma in Norman, will use AI systems to improve climate forecasting accuracy. Another, at the University of Texas at Austin, will focus on the next generation of machine-learning algorithms. A third, led by the University of Colorado Boulder, will apply AI technologies to teaching and learning. The fourth, headed by the University of Illinois at Urbana-Champaign, will explore the discovery and synthesis of new materials and drugs using AI systems.
And a fifth, led by MIT, will investigate how AI can improve research in fundamental physics. The NSF has put out a call for proposals for eight more AI institutes, which it plans to announce next year. “We have a long history of supporting basic research in artificial intelligence,” says Erwin Gianchandani, the NSF’s deputy assistant director for computer and information science and engineering. In addition, the US Department of Agriculture’s National Institute of Food and Agriculture has committed to funding another two institutes each with $20 million over five years to apply AI to questions of crop yield, pest resistance and food distribution.
The data, which assessed the research performance, start-up funding and supercomputing prowess of 54 countries, is derived from the Global AI Index. It suggests a coming and radical power shift from economies that are “no longer defined by gross domestic product (GDP) or geography…[but] according to their capacity to take part in a global system shaped by artificial intelligence.” The report looks at the impact of private investment in artificial intelligence, while also considering the critical role public, or state, finance can have on a country’s global ranking. While the UK was ranked third in the Global AI Index for private investment in AI companies in 2019, the US, and China especially, rocketed ahead.
China emerged as new leader in AI
China has overtaken the United States to become the world leader in deep learning research, a branch of artificial intelligence (AI) inspired by the human brain, according to White House reports that aim to help prepare the US for the growing role of artificial intelligence in society. Already the potential impact of AI on GDP in China is expected to be greater than in the U.S. or Western Europe. That is also projected to translate into stronger job creation potential in the country, according to a new report from PwC released at the World Economic Forum’s Annual Meeting of The New Champions in Tianjin Sept. 2018. Compared with other countries, the United States and China are spending tremendous research attention on deep learning.
IN JULY 2017, CHINA’S government issued a sweeping new strategy with a striking aim: draw level with the US in artificial intelligence technology within three years, and become the world leader by 2030. Scopus database, the largest abstract and citation database of peer-reviewed literature showed that number of papers relating to artificial intelligence shows that 28% were affiliated with European authors, followed by China (25%), and the U.S. (17%). Findings showed that in 2014, about 30% of AI patents originated in the U.S, followed by South Korea and Japan, which each hold 16% of AI patents. Of the top inventor regions, South Korea and Taiwan have experienced the most growth, with the number of AI patents in 2014 nearly 5x that in 2004. Tsinghua University’s China AI Development Report, released summer 2018, which shows that China has the greatest number of total published patents relating to AI, followed by the U.S. and Japan
The United States has historically been the leader in AI-related research output, having accumulated the highest number of publications over the past two decades. But China has ramped up its output in recent years. In each year from 2016 to 2019, China produced more AI-related papers than any other nation, according to Dimensions. Over this period, China’s output of AI-related research increased by just over 120%, whereas output in the US increased by almost 70%. In 2019, China published 102,161 AI-related papers, and the US published 74,386. India, which came in third, published 23,398.
Source: Nature Index; Data used were sourced from Dimensions, an inter-linked research information system provided by Digital Science
Publication numbers aren’t the whole story, says Jeffrey Ding, a PhD student at the Future of Humanity Institute at the University of Oxford, UK, who studies China’s AI strategy. In the AI Index Report, which uses citation numbers to measure the quality of AI papers, papers from China were cited about 20% less than the world average in 2019, whereas papers from the US were cited about 40% more than average. “Just pumping out raw numbers of papers that don’t have a lasting impact isn’t really useful,” says Ding. “It’s more important to keep up with the technology frontier.”
The rate of increase is remarkably steep, reflecting how quickly China’s research priorities have shifted. The quality of China’s research is also striking, as indicated by number of papers that were cited at least once by other researchers, an indication that the papers were influential in the field. From e-commerce to self-driving cars or search engines, AI will play a fundamental role in the success of Companies like Baidu for autonomous driving, Alibaba for smart cities and Tencent for AI in healthcare.
Tencent, based in Shenzhen, in southern China, operates a range of online and mobile services, including the hugely popular social mobile apps WeChat and QQ. The company created its AI lab in April, and it is growing rapidly. Baidu, has had a dedicated AI research lab for several years, and it now regularly publishes fundamental advances. Tencent, which runs the social networking service WeChat, has access to over one billion users on its platform, while Baidu is the country’s largest search provider and Alibaba is its biggest e-commerce platform. Combined, they are worth around US$ 1 trillion.
China is likely to emerge as the world’s largest market for autonomous vehicles and mobility services, worth more than $500 billion by 2030, according to an annual report on the nation’s innovation economy by the South China Morning Post and 500 Startups, a Silicon Valley venture fund and seed accelerator. “China is poised to be a leader in AI because of its great reserve in AI talent, excellent engineering education and massive market for AI adoption,” says Kai-Fu Lee, a former Microsoft and Google executive who is now chief executive of Sinovation Ventures.
According with the Times Higher Education rankings, Japan stands in third place, with about 11,700 papers published. Indeed, this is not surprising. With an ageing population and decreasing workforce, AI will play a vital role in the Japanese economy. Even now, about 55% of work activities in Japan could be automated. With current technology. Its manufacturing sector, according to the HBR article, has a 71% automation potential. In the US, that number stands at 60%. And in office and administrative work, the difference is 16% to 9%.
However, what distinguishes Japan from other countries is a consistent concept underlying all introduced regulation – the vision of Society 5.0. This new form of society is saturated with AI-related technology, which not only improves the lives of its members, but also creates new aspects and new values. Individual needs are met in a timely and proportionate manner allowing for fulfilled and contented lives. With society 5.0 as a targeted outcome, the recently updated AI Strategy 2019 contains a wide spectrum of necessary actions comprising both facilitating the development of AI and utilizing it for the advancement of industry and society.
The strategy aims not only to improve situation on a national level, targeting five designated priority areas (manufacturing, transportation and logistics, health and medical care, agriculture and disaster response) but also globally – by helping solve major societal problems like ageing society or labour shortage, diversification of energy sources, GHG reduction or more efficient waste management, which lines up perfectly with achieving Sustainable Development Goals. According to the strategy, the solutions developed in Japan would then be made available for the world and if realised successfully, it might just be the advantage that Japan needs to win over its competitors.
Japan’s advancements in artificial intelligence could soon have an impact on everyday government operations. Japan’s plan to use AI for state purposes is part of the strategy for a “fourth industrial revolution,” a central part of the government’s economic growth plan, according to the Yomiuri. The AI will scan hospital records and other documents to determine insurance payouts, according to a company press release, factoring injuries, patient medical histories, and procedures administered. Automation of these research and data gathering tasks will help the remaining human workers process the final payout faster, the release says.
At the moment, Japan along with the rest of the world struggles with a lack of educated professionals capable of handling AI-related technologies. The short-term relief could be brought by encouraging more women to participate in the job market and attracting skilled resources form overseas. In the long-term perspective, Japan is preparing for major educational system reform, introducing AI into curricula and making it obligatory part of the university entrance exam, creating a learning inducive environment for students (sufficient network infrastructure and access to communication devices) and facilitating lifelong learning for the existing workforce.
The UK is not much behind Japan, though. In fact, when it comes to published research papers on deep learning, it has already passed Japan. With close to 100 published papers, the UK became number 3 on the topic. As for total published papers on AI, between 2011 to 2015, the number was 10,100 – slightly behind Japan. The UK has published around 18,200 academic papers on the subject to date, ahead of Canada, France, Germany and even China. But it is facing increasing competition from “fast-moving and high-intensity” economies that include Singapore, Israel, Ireland and Finland, who are outperforming the UK on funding, AI-related research groups and research quality.
Access to massive data sets on which to train machine-learning systems is one advantage that both the US and China have, says Daniel Araya, a policy analyst at the Center for International Governance Innovation, a think tank in Ontario, Canada. Europe, on the other hand, has stringent data laws, which protect people’s privacy, but limit its resources for training AI algorithms. “So, it seems unlikely that Europe will produce very sophisticated AI as a consequence,” he says. “China is at the opposite end of the spectrum, where it has few data protections, and huge access to varied and diverse pieces of data.”
According to the Financial Times, DeepMind, founded in 2010, in Britain is today a world leader in AI. It employs 250 researchers, from mathematicians to neuroscientists.
Finally, the 5th country with the most published researched papers on AI is Germany. Between 2011 to 2015, the number stood at nearly 8,000. Germany, like China, also plans to become a leading hub for artificial intelligence. According to an FT article, Germany’s Max Planck Society, two technical universities, and its leading exporting state are combining their artificial research intelligence together with companies like Porsche, Daimler, and Bosch. The Cyber Valley, as they call it, is the result of this, and it has even received support from Amazon, who plans to open a lab there. AI research in Germany is conducted at universities and also at non-university research institutions. Almost all universities host an AI research section. The spectrum ranges from small monothematic working groups to large interdisciplinary departments and covers a variety of topics.
Amir Husain, a computer scientist who founded Spark Cognition, a company in Austin, Texas, points to Germany, which maintains a strong economy that relies on exports of products such as machine parts and automobiles, even though lower-income countries can provide low-wage labour for manufacturing. Germany has been able to compete by using automation to keep manufacturing costs down, while keeping quality and productivity high. AI could reinforce this advantage by powering the next generation of automation technologies. “Anybody that has mastery over this technology and is investing in implementing it retains an economic lead,” says Husain. Institutions in Germany, such as the Fraunhofer Society, Europe’s largest application-oriented research organization, have been emphasizing Industry 4.0, a national strategic initiative from the German government to introduce more digital innovation and advanced robotics into manufacturing and supply-chain management.
Germany, like Japan, is also experiencing a working population decline. What’s more, it too has a high automation potential, standing at 47.9%. Its strong industry capabilities, combined with powerful companies and good education make it a fertile ground for AI. Researchers in Germany are developing software that uses machine learning to predict the amount of energy generated by renewables over the next few days. This early warning system, called EWeLiNE, was modelled after a similar program in the U.S. In 2015, neuroscientists in Germany have brought vision of dexterous robots a step closer to reality, predicting and recording the hand positions of monkeys, and then uploading them to a robotic hand.
“Germany and Europe have what it takes to be world leaders in industrial AI,” said Dr. Michael Bolle, board of management member and Bosch CDO/CTO, at today’s digital presentation of the Bosch AI Future Compass. More specifically, he added, they have unique specialist and domain knowledge that allows them to use AI in areas such as quality control, energy efficiency, and improving manufacturing efficiency. In this respect, the relatively high level of acceptance for industrial AI revealed in the survey is encouraging: “For the future of Germany and Europe as an industrial location, it is enormously important to have the backing of the general public and of key institutions.”
Significant growth of Artificial intelligence in India
India has a robust IT ecosystem and all the capabilities to democratize any technology. Globally, we are recognized as a country that has a huge AI-skilled workforce. India is proceeding in the direction of digital transformation, the increasing penetration of digital technologies has encouraged artificial intelligence in India by the current government. India can certainly become the next artificial intelligence superpower through zealous innovation and consistent R&D in the technology front.
Similarly as Google, Oracle, Microsoft, and Amazon are fighting to serve the cloud computing and machine learning needs of the US government, the following three to five years may cause a similar dynamic within India. As the Indian government pushes for digitization and sanctions more AI activities, private firms will run to win huge contracts– adding to the pool of assets to grow new technologies and turn out new AI and data science-related startups.
The Indian startup sector has already witnessed tremendous upscaling and notable collaborations with global tech giants. Indian entrepreneurs today, have a better understanding of business models and are well-informed about the technologies that are in play. Indian startups today are applying AI to create solutions for verticals like BFSI, healthcare, manufacturing, retail etc. and also for others like agriculture, fisheries, marine resources, water management, alternative medicines, safety and empowerment of women, which were earlier unexplored.
According to a report by Accenture, artificial intelligence can possibly add US$957 billion, or 15% of India’s present gross value in 2035. The blend of the technology, information and ability that make intelligent systems possible has arrived to the critical mass, driving exceptional growth in AI investment.
During the AI conference hosted by Sberbank, the Russian president made a number of important statements, including: “We devote serious resources to the creation and implementation of these (AI) technologies – both financial and administrative. And this is not about spending these funds, buying prestigious gadgets or other household appliances. AI is not a so-called trendy hype, not a prestigious trend that will fade away tomorrow, the day after tomorrow. No, that will not happen.”
As stated by Gref, the country’s first AI institute is being created with the involvement of leading national and international scientists. The Russian internet services company Yandex, well-known in Turkey, is included in the list of the top five largest investors in the world in R&D in the field of AI. Both Sberbank and Yandex have already launched their virtual assistants Athena and Alice, which have developed into something more than just personalized voice search services on the internet.
Global Artificial Intelligence (AI) Market
Amid the COVID-19 crisis, the global market for Artificial Intelligence (AI) estimated at US$47.1 Billion in the year 2020, is projected to reach a revised size of US$291.5 Billion by 2026, growing at a CAGR of 34.3% over the analysis period. Services, one of the segments analyzed in the report, is projected to grow at a 34.1% CAGR to reach US$154.8 Billion by the end of the analysis period. A
The growth in the Software segment is readjusted to a revised 31.7% CAGR for the next 7-year period. This segment currently accounts for a 37.9% share of the global Artificial Intelligence (AI) market. The increasing penetration of chatbots or virtual assistants for providing customer assistance in various end-use industries including e-commerce and banking is expected to further enhance demand for AI-based software and systems.
The Artificial Intelligence (AI) market in the U.S. is estimated at US$28.9 Billion in the year 2021. The country currently accounts for a 41.4% share in the global market. China, the world`s second largest economy, is forecast to reach an estimated market size of US$53.6 Billion in the year 2026 trailing a CAGR of 40.9% through the analysis period. Among the other noteworthy geographic markets are Japan and Canada, each forecast to grow at 28.8% and 30.2% respectively over the analysis period. Within Europe, Germany is forecast to grow at approximately 32.5% CAGR while Rest of European market (as defined in the study) will reach US$70.9 Billion by the end of the analysis period.
The dominant share of the US is mainly attributed to the widespread adoption of AI technology in several end-use industries including media, e-commerce and manufacturing. Increased funding for developing and advancing AI technology and applications, and a robust technical adoption base are also favoring growth.
Europe, is the second largest regional AI market. Europe is expected to witness a significant increase in the deployments of cloud-based AI solutions, driven by the growing consumer demand for on-demand and faster access to data and relatively easy document control. Europe`s AI market is likely to benefit from the European Commission`s plans to invest €20 billion for AI research during the period 2018-2020 in order to fuel R&D initiatives for businesses and government.
Growth in Asia-Pacific including China is propelled by the increasing adoption of natural language processing (NLP) and deep learning technologies in sectors such as marketing, finance, law, and agriculture. The market also benefits from the rapid pace of improvements being seen in computing power, data storage capacity and processing capabilities, which facilitate adoption of AI technology in sectors such as healthcare and automotive.
The constant decline in hardware costs is fueling growth in the hardware segment. By type of hardware, processor captures the largest share of the AI chipsets market, due mainly to the rising demand for high computing processors for running AI algorithms in servers and for the development of edge devices. In the global Hardware segment, USA, Canada, Japan, China and Europe will drive the 38.2% CAGR estimated for this segment. These regional markets accounting for a combined market size of US$7.8 Billion in the year 2020 will reach a projected size of US$74.8 Billion by the close of the analysis period. China will remain among the fastest growing in this cluster of regional markets. Led by countries such as Australia, India, and South Korea, the market in Asia-Pacific is forecast to reach US$9.8 Billion by the year 2026.
Select Competitors are Accenture, AIBrain, Inc., Amazon Web Services, Baidu, Inc., BIGO Technology, ByteDance Ltd, Cisco Systems, Inc., CloudMinds, Dell Technologies, eGain Corporation, Esri, Facebook, Inc., General Electric Company, Google, Inc., Habana Labs Ltd, Inspur, Intel Corporation, International Business Machines Corporation (IBM), IPsoft Inc, Micron Technology, Inc., Microsoft Corporation, Mobileye, an Intel Company, NetEase Fuxi Lab, NetEase, Inc, Next IT Corporation, NICE inContact, Nuance Communications, Inc., NVIDIA Corporation, Omron Robotics and Safety Technologies, Inc, Oracle Corporation, Rockwell Automation, Inc., Salesforce.com, inc., Samsung Electronics Co., Ltd., SAP SE, SAS Institute Inc., Siemens AG, Smartron India Private Limited, The Hewlett-Packard Company, Trifo, Xilinx, Inc.
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