Category Archives: Artificial Intelligence

Artificial intelligence (AI) is everywhere, and it has an impact on all our lives.

However, years of bold proclamations have resulted in AI becoming overhyped, with reality often falling short of the world-altering promises.

The coming years will be more about practical uses of AI, as businesses ensure return on investment by using AI to address specific cases.

Power Technologys artificial intelligence in power dashboard covers all you need to know about this emerging technology and its impact on the sector.

The power sector, especially in Europe is expected to be impacted due to gas availability and price issues. Utilities will have to look for alternate sources of gas or shift to other sources of generation. AI in power industry usage is likely to be impacted alongside many other corporate tools.

The recent ban on Russian oil and gas supplies will have a varied impact on both the buying and selling nations. Russia is an important source of energy supply for the US and European countries.

Pressure on the Western Bloc to impose more sanctions on Russian energy imports due to civilian killings in Ukraine by Russian Army. Fuel prices (such as for oil) have increased due to talks of a boycott of Russian oil.

Energy companies continue to exit or halt operations in Russia due to increasing pressure to cut ties amid civilian killings in Ukraine.

The electric vehicle and energy storage market will be impacted due to a shortage of nickel and an increase in commodity prices.

The International Energy Agency (IEA) recently published A 10-Point Plan to Reduce the European Unions Reliance on Russian Natural Gas, providing short-term measures and claiming that the EU could cut Russian gas imports by more than 33%.

It also advocates for gas-to-coal switching that could account for the majority of the potential reduction in gas demand.

GlobalData estimates that the global AI platform market will be worth $52bn in 2024, up from $28bn in 2019.

Total spending on AI technology is certainly higher, but it is difficult to estimate. There are two main reasons for this.

Firstly, AI is an intrinsic part of many applications and functions, making it almost impossible to identify revenue explicitly generated by AI.

Secondly, the range of sub-sets and technologies that make up AI can be challenging to locate and track. In general, valuations of the overall AI market range from a few billion dollars to several trillion, depending on the source.

Rather than attempting to size the market, some companies have tried to forecast its economic impact. A PwC report in 2017 estimated that AI would add $15.7 trillion to the global economy by 2030 and boost global GDP by up to 14%.

Global AI platform revenue will reach $52bn by 2024, up from $28bn in 2019.

The competitive landscape for AI is highly fragmented. Companies are investing considerable sums, and there is a swath of innovative AI start-ups that possess innovative expertise. When it comes to the use of artificial intelligence in power industry terms, the competition is constant.

Yet, there is no denying that companies with access to large repositories of data to power AI models are leading the development of AI.

Big Tech excels in this regard, and several tech giants set the overall tone in AI. GAFAM (Google, Apple, Facebook, Amazon, and Microsoft), BAT (Baidu, Alibaba, and Tencent), early-mover IBM, and the two hardware giants Intel and Nvidia are key players within the field.

All industries are feeling the impact of AI, with established incumbents coming up against game-changing disruption from AI platforms developed either by technology giants such as Amazon, Google, and Microsoft; or AI-focused start-ups, such as Lemonade, Trax, and Butterfly Network.

It is not only companies that are making AI investment a priority, but countries as well.

China is the most obvious example, having pledged to become the world leader in AI by 2030, but governments in several nations are backing large spending projects to make sure they do not miss out on AIs positive effects.

The US remains the dominant player in the development of AI technologies, accounting for almost one-third of AI platform revenues in 2019, according to GlobalData estimates.

In a 2019 report from the Center for Data Innovation that compared China, the European Union (EU), and the US in terms of their relative standing in the AI economy, the US came out on top in four out of the six categories of metrics that were examined, including talent, research, development, and hardware.

China led in data and adoption, but its advantage in AI adoption was due to a strong position in a limited number of AI technologies such as facial recognition and smart surveillance.

These are related to the governments extensive use of surveillance and are unlikely to create benefits across the economy.

The US and Europe have a sizable lead in terms of access to high-quality talent and research, and the US has the most AI start-ups and a more developed private equity and venture capital ecosystem.

Therefore, while China is making considerable investments, the USs structural advantages may even enable it to extend its lead.

Discussions about the race for AI dominance tend to focus on the US and China, but other countries are also in the race. Japan has long been at the forefront of AI when it comes to robotics.

The Japanese government released its AI strategy in 2017, and the country boasts a major AI investor in the form of Softbank, which, in 2019, created a $108bn fund to invest in AI companies and opened the Beyond AI institute in Tokyo, a $184m initiative to accelerate AI research in Japan.

In the UK, AI companies secured a record 1.3bn ($1.7bn) of investments in 2019, according to a study by Crunchbase and Tech Nation.

The UK has the second-highest number of AI companies globally, after the US, but most of those companies are small, making them a popular target for acquisition by the tech giants.

Germany is a powerhouse when it comes to the uses of AI in the manufacturing, automotive, and industrial sectors. In 2018, France announced that it would invest 1.5bn ($1.8bn) in AI research until the end of 2022.

Other countries that consider AI an important strategic initiative include South Korea, Russia, Canada, Israel, India, Sweden, Australia, and Singapore.

To best track the emergence and use of artificial intelligence in power, GlobalData tracks patent filings and grants, as well as companies that hold most patents in the field of artificial intelligence.

Power Technology monitors live power company job postings mentioning artificial intelligence or those requiring similar skills.

Jobs postings by power companies mentioning artificial intelligence in recent months. AI jobs tracker in the power sector looks at jobs posted, closed and active in the sector.

As illustrated by the value chain, big data extremely large, diverse data sets that, when analysed in aggregate, reveal patterns, trends, and associations, especially relating to human behaviour and interactions plays a significant role in the development of AI technology.

Big data is produced by all forms of digital activity: phone calls, emails, sensors, payments, social media posts, and much more.

It is also produced by machines, both hardware and software, in the form of machine-to-machine exchanges of data.

These exchanges are particularly important in the IoT (Internet of Things) era, where devices talk to each other without any form of human prompting.

Once collected, big data is typically managed in data centres, either in the public cloud, in corporate data centres, or on end devices. Big data is covered in more detail in our Big Data report.

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Artificial intelligence companies leading the way in the power industry - Power Technology

Objectives of the marketing research are kept in mind while preparing this market research report. This report deals with plentiful aspects of this industry. A comprehensive market study and analysis of trends in consumer and supply chain dynamics underlined in this report assists businesses in drawing the strategies for sales, marketing, advertising, and promotion. It not only assists you with informed decision-making but also helps with smart working. This market research report is prepared by keeping in mind todays business needs and advancements in technology.

The CAGR values covered here estimate the fluctuation of the rise or fall of demand for the specific forecasted period with respect to investment. Market analysis, market definition, currency and pricing, key developments, and market categorization along with detailed research methodology are the key factors of this market report. This market research report gives clear idea about the strategic analysis of mergers, expansions, acquisitions, partnerships, and investments. Skillful capabilities and excellent resources in research, data collection, development, consulting, evaluation, compliance, and regulatory services come together to form this world-class market research report.

Data Bridge Market Research analyses theartificial intelligence in aviation marketwill exhibit a CAGR of 46.3% for the forecast period of 2022-2029 and is likely to reach the USD 9,995.84 million by 2029.

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Top Players Analysed in the Report are:

Some of the major players operating in the artificial intelligence in aviation market are IBM, Microsoft, Amazon Web Services, Inc., Airbus S.A.S., Xilinx, NVIDIA Corporation, Intel Corporation, General Electric, Micron Technology, Inc., Garmin Ltd., Lockheed Martin Corporation, SAMSUNG, Thales Group, MINDTITAN, Mitsubishi Electric Corporation, OMRON Corporation, TAV Technologies and IRIS Automation, among others.

Porters five forces model in the report provides insights into the competitive rivalry, supplier and buyer positions in the market and opportunities for the new entrants in the global Artificial Intelligence in Aviation market over the period. Further, Growth Matrix gave in the report brings an insight into the investment areas that existing or new market players can consider.

Research Methodology

A) Primary Research

Our primary research involves extensive interviews and analysis of the opinions provided by the primary respondents. The primary research starts with identifying and approaching the primary respondents, the primary respondents are approached include

Key Opinion Leaders Internal and External subject matter experts Professionals and participants from the industry

Our primary research respondents typically include

Executives working with leading companies in the market under review Product/brand/marketing managers CXO level executives Regional/zonal/ country managers Vice President level executives.B) Secondary Research

Secondary research involves extensive exploring through the secondary sources of information available in both the public domain and paid sources. Each research study is based on over 500 hours of secondary research accompanied by primary research. The information obtained through the secondary sources is validated through the crosscheck on various data sources.

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Who Will Get Advantage of This Report?

The prime aim of theGlobal Artificial Intelligence in Aviation Marketis to provide industry investors, private equity companies, company leaders and stakeholders with complete information to help them make well-versed strategic decisions associated to the chances in the Concealed Door Closer market throughout the world.

The secondary sources of the data typically include

Company reports and publications Government/institutional publications Trade and associations journals Databases such as WTO, OECD, World Bank, and among others Websites and publications by research agencies

Key Market Segmentation:

On the basis of technology, the artificial intelligence in aviation has been segmented into computer vision, machine learning, context awareness computing and natural language processing. Machine learning is further segmented into deep learning, supervised learning, unsupervised learning, reinforcement learning and semi-supervised learning.

Based on offering, the artificial intelligence in aviation market has been segmented into hardware, software and services. Hardware is further segmented into processors, memory and networks. Software is further segmented into AI solutions and AI platforms. Services are further segmented into deployment and integration and support and maintenance.

On the basis of application, the artificial intelligence in aviation market has been segmented into dynamic pricing, virtual assistants, flight operations, smart maintenance, manufacturing, surveillance, training and other applications. Manufacturing is further segmented into material movement, predictive maintenance and machinery inspection, production planning, quality control and reclamation.

Key Elements that the report acknowledges:

Market size and growth rate during the forecast period. Key factors driving this market Key market trends cracking up the growth of this market Challenges to market growth Key vendors of this market Detailed SWOT analysis Opportunities and threats face by the existing vendors in this global market Trending factors influencing the market in the geographical regions Strategic initiatives focusing on the leading vendors PEST analysis of the market in the five major regions

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About Data Bridge Market Research, Private Ltd

Data Bridge Market ResearchPvtLtdis a multinational management consulting firm with offices in India and Canada. As an innovative and neoteric market analysis and advisory company with unmatched durability level and advanced approaches. We are committed to uncover the best consumer prospects and to foster useful knowledge for your company to succeed in the market.

Data Bridge Market Research has over 500 analysts working in different industries. We have catered more than 40% of the fortune 500 companies globally and have a network of more than 5000+ clientele around the globe. Our coverage of industries includes

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Global Artificial Intelligence in Aviation Market Key Drivers, Trends, Latest Innovations, Business Scenario, Demand With Outlook Designer Women -...

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Dublin, June 20, 2022 (GLOBE NEWSWIRE) -- The "Global Medical Imaging Equipment Market: Analysis By Product By End User Size and Trends with Impact of COVID-19 and forecast up to 2026" report has been added to ResearchAndMarkets.com's offering.

In 2021, global medical imaging equipment market was valued at US$38.36 billion in 2021, and is expected to reach up to US$48.58 billion in 2026. The market is expected to expand at a CAGR of 4.70% over the forecasted period of 2022-2026.

Medical imaging describes the technology which uses radiation, sound waves or flexible optical instrument equipped with a small camera to visualize internal structure of a body to perform accurate diagnosis. Medical imaging equipment has become a significant instrument for doctors, dentists, surgeons and physical therapists with the objective of offering better care for their patients.

Benefits associated with medical imaging has made it a popular choice amongst medical professionals. As of now, medical imaging is going through significant changes with corporations helping in establishing digital workflow keeping medical imaging in center and with government deploying funds to build strong healthcare infrastructure.

Global Medical Imaging Equipment Market Dynamics

Growth Drivers: The aging population is a prominent growth factor of medical imaging market. The aging population in developed economies is compelling government to invest in healthcare services and provide affordable healthcare services. The inclusion of equity into the industry would create growth opportunities for the market. Other than this, rapid rise in demand for point of care diagnostics is also providing growth opportunities to the market.

With rising awareness about the benefits of diagnose of cancer in stage 1 has given people a hope to save the lives of their loved ones, and point of care diagnostic is an umbrella term for medical imaging tools, hence becoming the growth driver of the market. Furthermore, factors like rising healthcare expenditure, growing cases of death due to chronic disease, accelerating obese population, etc. would also help the market to grow across the globe.

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Challenges: The market also have to deal with some of the challenges such as shortage of helium, high cost involved, and lack of skilled radiologists. These challenges are expected to hamper market growth in coming years. The medical imaging devices are very costly in terms of purchasing as well as installing. The high cost of equipment makes customers reluctant in purchasing them. Such situations are more common in developing countries where per capita income is very low in comparison to developed countries.

Trends: Artificial intelligence is set to revolutionize the industry by overcoming certain limitations associated with the conventional devices such as time consuming examination, high dependency on technicians to acquire and interpret images, etc. Furthermore, other notable trends such as 3D printing in medical imaging, emerging 4D & 5D ultrasound imaging technology and cryogen-free MRI imaging system would also provide significant growth opportunities to the market.

Market Segmentation Analysis:

In 2021, ultrasound segment dominated the market by absorbing more than one-fourth of the market, as it is considered the safest technology for the diagnose procedures because it does not utilize ionizing radiation and magnetic field. Ultrasound not only used to determine health status of fetus and mother but it also used to diagnose liver tumor, breast cyst, kidney stone, gallstones, size of ovaries and health of uterus in a patient suffering from PCOS/PCOD, pancreas, etc.

In 2021, Hospital segment held the highest share by covering more than 40% of the market and it is also expected to be the fastest growing segment. Hospital segment is likely to continue to register decent growth during the forecast period because of M&A deals between market players and hospitals. For instance, Philips and Zhejiang University's First Affiliated Hospital, has signed a multi-year contract to support the expansion by combining clinical research and education.

Asia Pacific dominated the market in 2021 by occupying almost 45% share of the global market. The most important factor driving the market in Asia Pacific is the rising demand for advanced diagnostic equipment, and presence of most populous countries of the world with rapidly changing demographic.

In China, medical imaging equipment installation would increase because after COVID-19, government strongly focus on healthcare infrastructure to be better prepare for any future healthcare emergency. Europe medical imaging equipment market provides lucrative opportunities in the coming years. Various reasons such as introduction of technological advanced systems and the increasing demand for early diagnosis, are expected to drive the growth of the market in Europe.

Impact Analysis of COVID-19 and Way Forward:

The pandemic negative affect was also felt by medical imaging industry as market participants reported negative numbers in their income statement. The disruptions caused in logistics, with drop in manufacturing and postponements in installation put the industry at a difficult situation. Whereas, the demand for computed tomography witnessed a rapid rise because of it providing beneficial diagnosis results.

Pandemic also brought forth the benefits of mobile and portable imaging systems as they are easy to handle and can diagnose sooner and easier in remote locations that were set up nationwide. Most of the hospitals find it easier to sterilize a mobile DR or ultrasound system than cleaning a CT room for 30-50 mins. The pandemic also encouraged hard-hit country like China, Italy, India, the US, and many others to implement strong healthcare policies, which would support healthcare requirement of its citizens while building a strong healthcare infrastructure in the country.

Competitive Landscape:

Global medical imaging equipment market is concentrated in nature, which place few of the players at the top. Collaborations and partnerships between local and global companies, innovative product releases, and rising focus on developing multimodal imaging devices are some of the primary strategies used by companies in global medical imaging equipment market.

Siemens Healthineers, Koninklijke Philips N.V. and General Electric Company (GE) hold more than 75% share in the industry, and rest is being covered by Hitachi, Canon, Crestream Health, Inc. and others. Siemens Healthineers and General Electric Company (GE) both operate in diagnostic imaging industry through their subsdiaries, aka, Siemens AG, and GE Healthcare.

Both companies extensively invest in R&D to offer technically enhanced products to their targeted audience. Even though Siemen Healthineers is as big as General Electric Company (GE), but the former less diversified portfolio helped latter to stand out in this front.

Further, Companies such as GE Healthcare, Siemens Healthineers, Canon Medical, Esaote, Samsung and others have been implementing various organic growth strategies that have helped the growth of the company and in turn have brought about various changes in the market. Whereas, Companies such Siemens AG, Shimadzu Medical Systems, Hitachi, Canon Medical, Carestream Health and other companies have also been implementing various inorganic developments that have bought about dynamic improvements in the market they are operating.

Market Dynamics

Growth Drivers

Growing Geriatric Population

Rising Healthcare Spending

Accelerating Obese Population

Rising Cases of Death due to Chronic Disease

Upsurge in Demand for Point Of Care Diagnostics

Challenges

Market Trends

3D Printing in Medical Imaging

Integration of Artificial Intelligence (AI) with Medical Imaging Equipment

Emerging 4D & 5D Ultrasound Imaging Technology

Cryogen-Free MRI Imaging System

The key players of medical imaging equipment market are:

Siemens Healthineers

Koninklijke Philips N.V.

Canon Medical Systems Corporation

General Electric Company (GE)

FujiFilm Corporation

Shimadzu Corporation

Hologic, Inc.

Onex Corporation (Carestream Health, Inc)

Samsung Electronics (Samsung Medison)

Esaote SpA

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Global Medical Imaging Equipment Market Report 2022: A $48.58 Billion Market in 2026 - Integration of Artificial Intelligence (AI) with Medical...

SUNNYVALE, Calif.--(BUSINESS WIRE)--Juniper Networks, a leader in secure, AI-driven networks, today announced the findings of a global research project that shows an increase in enterprise artificial intelligence (AI) adoption over the last 12 months is yielding tangible benefits to organizations. However, a shortage of human talent still exists and governance policies continue to lack in maturity both of which are needed to responsibly manage AIs growth when considering privacy issues, regulation compliance, hacking and AI terrorism.

Juniper partnered with Wakefield Research to conduct a survey of 700 senior IT leaders around the world with direct involvement in their organizations AI and/or machine learning (ML) plans or deployments. The survey gauges sentiment around the value of AI, the perceived maturity of deployments and where challenges still exist.

This years survey found that enterprises have largely moved past proof-of-concepts and limited trials of AI and are now implementing AI across their organizations, thanks to pandemic-related digital acceleration and the maturation of AI tools available. While Junipers 2021 report previously showed only 6% of C-level leaders had adopted AI-powered solutions across their organizations (citing technological, skillset and governance challenges), this year, 63% of company leaders surveyed say they are at least most of the way to their planned AI adoption goals.

Still, only 9% of IT leaders consider their AI governance and policies, such as establishing a company-wide AI leader or responsible AI standards and processes, to be fully mature. At the same time, more leaders see governance as a priority: 95% agree having proper AI governance in place is important to stay ahead of future legislation, up from 87% in 2021. Despite leadership recognizing the importance of AI governance and having policies in place to manage, govern and maintain, almost half of respondents (48%) think more needs to be done to effectively govern AI.

The disparity the data shows between the substantial increase in AI implementation in the enterprise and the immaturity of AI governance and policies is staggering. It will be critical for governance to pick up pace so that the positives of AI deployment overshadow existing fears of whether AI can be effectively controlled. This is a challenge not unique to AI, but all emerging technologies.

Sharon Mandell, SVP and CIO, Juniper Networks

The research also found:

AI is ultimately designed to perform tasks on par with humans but at higher scale via automation. Many of Junipers own customers are leveraging cloud AI in their networks to dramatically cut support tickets, which frees up IT teams from the drudgery of tactical issues, allowing them to focus on improving end users experiences. But with all the positives, enterprises need to responsibly manage AIs growth with proper governance to stay ahead of regulation and minimize potential negative impacts. In Europe, for instance, we are seeing regulators starting to classify certain AI use cases as risky and requiring CE certification. AI regulation is changing quickly and business leaders must make AI governance a strategic priority.

Bob Friday, Chief AI Officer, Juniper Networks

Additional resources

Methodology

In April 2022, Juniper Networks conducted primary research of organizations to assess company positions in the AI market. The survey (700 respondents), with a title of Senior Manager or higher, was conducted across more than 20 industries, including Technology, Healthcare, Retail, Automotive, Manufacturing, and Engineering/Construction, and covered AI market usage, acceptance, opportunities for growth, challenges in adoption, AI governance and strategic decisioning.

About Juniper Networks

Juniper Networks challenges the inherent complexity that comes with networking and security in the multicloud era. We do this with products, solutions and services that transform the way people connect, work and live. We simplify the process of transitioning to a secure and automated multicloud environment to enable secure, AI-driven networks that connect the world. Additional information can be found at Juniper Networks (www.juniper.net) or connect with Juniper on Twitter, LinkedIn and Facebook.

Juniper Networks, the Juniper Networks logo, Juniper, Junos, and other trademarks listed here are registered trademarks of Juniper Networks, Inc. and/or its affiliates in the United States and other countries. Other names may be trademarks of their respective owners.

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Juniper Networks Research Finds Artificial Intelligence Adoption Expands Tenfold Across Enterprises While Governance Lags - Business Wire

This report studies the Artificial Intelligence in Blockchain Market with many aspects of the industry like the market size, market status, market trends and forecast, the report also provides brief information of the competitors and the specific growth opportunities with key market drivers. Find the complete Artificial Intelligence in Blockchain Market analysis segmented by companies, region, type and applications in the report.

The report offers valuable insight into the Artificial Intelligence in Blockchain market progress and approaches related to the Artificial Intelligence in Blockchain market with an analysis of each region. The report goes on to talk about the dominant aspects of the market and examine each segment.

Key Players: Alpha Networks, Blaize, BurstIQ, Chainhaus, Core Scientific, Cyware, Fetch.ai, Gainfy Healthcare Network, NetObjex, Neurochain, PrimaFelicitas, Ripple, ScienceSoft, SoluLab, Stowk, Talla, Verisart, Vytalyx, and WealthBlock

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The global Artificial Intelligence in Blockchain market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Artificial Intelligence in Blockchain market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by region (country), by Type, and by Application for the period 2022-2026.

Market Segment by Regions, regional analysis covers

North America (United States, Canada and Mexico)

Europe (Germany, France, UK, Russia and Italy)

Asia-Pacific (China, Japan, Korea, India and Southeast Asia)

South America (Brazil, Argentina, Colombia etc.)

Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Artificial Intelligence in Blockchain Breakdown Data by Type

Softwares, Platforms and Tools

Services

Artificial Intelligence in Blockchain Breakdown Data by Application

Healthcare and Life Sciences

Manufacturing

Media and Entertainment

Others

Research objectives:

To study and analyze the global Artificial Intelligence in Blockchain market size by key regions/countries, product type and application, history data from 2013 to 2017, and forecast to 2027.

To understand the structure of Artificial Intelligence in Blockchain market by identifying its various sub segments.

Focuses on the key global Artificial Intelligence in Blockchain players, to define, describe and analyze the value, market share, market competition landscape, SWOT analysis and development plans in next few years.

To analyze the Artificial Intelligence in Blockchain with respect to individual growth trends, future prospects, and their contribution to the total market.

To share detailed information about the key factors influencing the growth of the market (growth potential, opportunities, drivers, industry-specific challenges and risks).

To project the size of Artificial Intelligence in Blockchain submarkets, with respect to key regions (along with their respective key countries).

To analyze competitive developments such as expansions, agreements, new product launches and acquisitions in the market.

To strategically profile the key players and comprehensively analyze their growth strategies.

The report lists the major players in the regions and their respective market share on the basis of global revenue. It also explains their strategic moves in the past few years, investments in product innovation, and changes in leadership to stay ahead in the competition. This will give the reader an edge over others as a well-informed decision can be made looking at the holistic picture of the market.

Key questions answered in this report

What will the market size be in 2027 and what will the growth rate be?

What are the key market trends?

What is driving this market?

What are the challenges to market growth?

Who are the key vendors in this market space?

What are the market opportunities and threats faced by the key vendors?

What are the strengths and weaknesses of the key vendors?

Table of Contents: Artificial Intelligence in Blockchain Market

Chapter 1: Overview of Artificial Intelligence in Blockchain Market

Chapter 2: Global Market Status and Forecast by Regions

Chapter 3: Global Market Status and Forecast by Types

Chapter 4: Global Market Status and Forecast by Downstream Industry

Chapter 5: Market Driving Factor Analysis

Chapter 6: Market Competition Status by Major Manufacturers

Chapter 7: Major Manufacturers Introduction and Market Data

Chapter 8: Upstream and Downstream Market Analysis

Chapter 9: Cost and Gross Margin Analysis

Chapter 10: Marketing Status Analysis

Chapter 11: Market Report Conclusion

Chapter 12: Research Methodology and Reference

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Artificial Intelligence in Healthcare marketanalysis report highlights the idea of high level analysis of major market segments and recognition of opportunities. Market analysis and market segmentation has been reviewed here in terms of markets, geographic scope, years considered for the study, currency and pricing, research methodology, primary interviews with key opinion leaders, DBMR market position grid, DBMR market challenge matrix, secondary sources, and assumptions. This market report carries out comprehensive analysis of company profiles of key market players that offers a competitive landscape. Artificial Intelligence in Healthcare market document exhibits important product developments and tracks recent acquisitions, mergers and research in the healthcare industry by the top market players.

The market study and analysis of the large scale Artificial Intelligence in Healthcare report lends a hand to figure out types of consumers, their views about the product, their buying intentions and their ideas for advancement of a product. To attain knowledge of all the above factors, this transparent, extensive and supreme market report is generated. And for the same, the report also describes all the major topics of the market research analysis that includes market definition, market segmentation, competitive analysis, major developments in the market, and excellent research methodology. This Artificial Intelligence in Healthcare market research report has been formed with the vigilant efforts of innovative, enthusiastic, knowledgeable and experienced team of analysts, researchers, industry experts, and forecasters.

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Leading Key Players Operating in the Artificial Intelligence in Healthcare Market Includes:NVIDIA Corporation (US), Intel Corporation (US), IBM (US), Google LLC (US), Microsoft (US), General Vision Inc. (US), Johnson & Johnson Services, Inc. (US), Siemens Healthcare GmbH (Germany), Medtronic (Ireland), CloudMedx Inc. (US)

Market Analysis and Insights: Global Artificial Intelligence in Healthcare Market:

This Artificial Intelligence in Healthcare market report provides details of new recent developments, trade regulations, import export analysis, production analysis, value chain optimization, market share, impact of domestic and localised market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on Data Bridge Market Research Artificial Intelligence in Healthcare market contact us for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

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Market Analysis and Insights: Global Artificial Intelligence in Healthcare Market:

This Artificial Intelligence in Healthcare market report provides details of new recent developments, trade regulations, import export analysis, production analysis, value chain optimization, market share, impact of domestic and localised market players, analyses opportunities in terms of emerging revenue pockets, changes in market regulations, strategic market growth analysis, market size, category market growths, application niches and dominance, product approvals, product launches, geographic expansions, technological innovations in the market. To gain more info on Data Bridge Market Research Artificial Intelligence in Healthcare market contact us for an Analyst Brief, our team will help you take an informed market decision to achieve market growth.

Artificial Intelligence in Healthcare Market, By Region:

Global Artificial Intelligence in Healthcare marketis analyzed and market size insights and trends are provided by country, product as referenced above.

The countries covered in the Artificial Intelligence in Healthcare market report are the U.S., Canada and Mexico in North America, Germany, France, U.K., Netherlands, Switzerland, Belgium, Russia, Italy, Spain, Turkey, Rest of Europe in Europe, China, Japan, India, South Korea, Singapore, Malaysia, Australia, Thailand, Indonesia, Philippines, Rest of Asia-Pacific (APAC) in the Asia-Pacific (APAC), Saudi Arabia, U.A.E, South Africa, Egypt, Israel, Rest of Middle East and Africa (MEA) as a part of Middle East and Africa (MEA), Brazil, Argentina and Rest of South America as part of South America.

North America dominates the Artificial Intelligence in Healthcare market because of the rise in the cases of arrhythmic diseases, favorable reimbursement policies for patients, high demand for advanced treatment methods and developed healthcare infrastructure in the region. Asia-Pacific is estimated to grow in the forecast period due to the high prevalence of cardiovascular diseases, increase in adoption of advanced digital devices, large population and launch of new innovative products.

Table of Contents

Global Artificial Intelligence in Healthcare Market Size, status and Forecast to 2029

1 Market summary2 Manufacturers Profile3 Global Artificial Intelligence in Healthcare Sales, Overall Revenue, Market Share and Competition by Manufacturer4 Global Artificial Intelligence in Healthcare market analysis by numerous Regions5 North America Artificial Intelligence in Healthcare by Countries6 Europe Artificial Intelligence in Healthcare by Countries7 Asia-Pacific Artificial Intelligence in Healthcare by Countries8 South America Artificial Intelligence in Healthcare by Countries9 Middle east and Africas Artificial Intelligence in Healthcare by Countries10 Global Artificial Intelligence in Healthcare Market phase by varieties11 Global Artificial Intelligence in Healthcare Market phase by Applications12 Artificial Intelligence in Healthcare Market Forecast13 Sales Channel, Distributors, Traders and Dealers14 Analysis Findings and Conclusion15 Appendix

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What are the market opportunities, market risks, and market overviews of the Artificial Intelligence in Healthcare Market?

Who are the distributors, traders, and merchants in the Artificial Intelligence in Healthcare Market?

What is the analysis of sales, income, and prices of the leading manufacturers in the Artificial Intelligence in Healthcare Market?

What are the Artificial Intelligence in Healthcare market opportunities and threats faced by the global Artificial Intelligence in Healthcare Market vendors?

What are the main factors driving the worldwide Artificial Intelligence in Healthcare Industry?

What are the Top Players in Artificial Intelligence in Healthcare industry?

What is the analysis of sales, income, and prices by type, application of the Artificial Intelligence in Healthcare market?

What is regional sales, income, and price analysis for Artificial Intelligence in Healthcare Market?

Research Methodology: GlobalLiquid Chromatography Devices Market

Data collection and base year analysis is done using data collection modules with large sample sizes. The market data is analyzed and estimated using market statistical and coherent models. Also market share analysis and key trend analysis are the major success factors in the market report. To know more please request an analyst call or can drop down your enquiry.

The key research methodology used by DBMR research team is data triangulation which involves data mining, analysis of the impact of data variables on the market, and primary (industry expert) validation. Apart from this, data models include Vendor Positioning Grid, Market Time Line Analysis, Market Overview and Guide, Company Positioning Grid, Company Market Share Analysis, Standards of Measurement, Global versus Regional and Vendor Share Analysis.

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Artificial Intelligence in Healthcare Market Global Analysis, Opportunities and Forecast to 2029 Designer Women - Designer Women

This report studies the Artificial Intelligence in Big Data Analysis Market with many aspects of the industry like the market size, market status, market trends and forecast, the report also provides brief information of the competitors and the specific growth opportunities with key market drivers. Find the complete Artificial Intelligence in Big Data Analysis Market analysis segmented by companies, region, type and applications in the report.

The report offers valuable insight into the Artificial Intelligence in Big Data Analysis market progress and approaches related to the Artificial Intelligence in Big Data Analysis market with an analysis of each region. The report goes on to talk about the dominant aspects of the market and examine each segment.

Key Players: Amazon, Apple, Cisco Systems, Google, IBM, Infineon Technologies, Intel, Microsoft, NVIDIA, and Veros Systems

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The global Artificial Intelligence in Big Data Analysis market is segmented by company, region (country), by Type, and by Application. Players, stakeholders, and other participants in the global Artificial Intelligence in Big Data Analysis market will be able to gain the upper hand as they use the report as a powerful resource. The segmental analysis focuses on revenue and forecast by region (country), by Type, and by Application for the period 2022-2026.

Market Segment by Regions, regional analysis covers

North America (United States, Canada and Mexico)

Europe (Germany, France, UK, Russia and Italy)

Asia-Pacific (China, Japan, Korea, India and Southeast Asia)

South America (Brazil, Argentina, Colombia etc.)

Middle East and Africa (Saudi Arabia, UAE, Egypt, Nigeria and South Africa)

Artificial Intelligence in Big Data Analysis Breakdown Data by Type

Image Recognition

Natural Language Processing

Others

Artificial Intelligence in Big Data Analysis Breakdown Data by Application

Smart Household

Self Driving

Cyber Security

Others

Research objectives:

To study and analyze the global Artificial Intelligence in Big Data Analysis market size by key regions/countries, product type and application, history data from 2013 to 2017, and forecast to 2027.

To understand the structure of Artificial Intelligence in Big Data Analysis market by identifying its various sub segments.

Focuses on the key global Artificial Intelligence in Big Data Analysis players, to define, describe and analyze the value, market share, market competition landscape, SWOT analysis and development plans in next few years.

To analyze the Artificial Intelligence in Big Data Analysis with respect to individual growth trends, future prospects, and their contribution to the total market.

To share detailed information about the key factors influencing the growth of the market (growth potential, opportunities, drivers, industry-specific challenges and risks).

To project the size of Artificial Intelligence in Big Data Analysis submarkets, with respect to key regions (along with their respective key countries).

To analyze competitive developments such as expansions, agreements, new product launches and acquisitions in the market.

To strategically profile the key players and comprehensively analyze their growth strategies.

The report lists the major players in the regions and their respective market share on the basis of global revenue. It also explains their strategic moves in the past few years, investments in product innovation, and changes in leadership to stay ahead in the competition. This will give the reader an edge over others as a well-informed decision can be made looking at the holistic picture of the market.

Key questions answered in this report

What will the market size be in 2027 and what will the growth rate be?

What are the key market trends?

What is driving this market?

What are the challenges to market growth?

Who are the key vendors in this market space?

What are the market opportunities and threats faced by the key vendors?

What are the strengths and weaknesses of the key vendors?

Table of Contents: Artificial Intelligence in Big Data Analysis Market

Chapter 1: Overview of Artificial Intelligence in Big Data Analysis Market

Chapter 2: Global Market Status and Forecast by Regions

Chapter 3: Global Market Status and Forecast by Types

Chapter 4: Global Market Status and Forecast by Downstream Industry

Chapter 5: Market Driving Factor Analysis

Chapter 6: Market Competition Status by Major Manufacturers

Chapter 7: Major Manufacturers Introduction and Market Data

Chapter 8: Upstream and Downstream Market Analysis

Chapter 9: Cost and Gross Margin Analysis

Chapter 10: Marketing Status Analysis

Chapter 11: Market Report Conclusion

Chapter 12: Research Methodology and Reference

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The post Artificial Intelligence in Big Data Analysis Market Analysis 2022 : Dynamics, Players, Type, Applications, Trends, Regional Segmented, Outlook and Forecast till 2028 | Amazon, Apple, Cisco Systems, Google appeared first on Agency.

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Artificial Intelligence in Big Data Analysis Market Analysis 2022 : Dynamics, Players, Type, Applications, Trends, Regional Segmented, Outlook and...

Alicia Vikander in Ex Machina (Film 4/DNA Films, 2015)

In an underrated 2009 film, Leaves of Grass, Edward Nortons character, a Yale professor, is told by a rabbi, We are animals, Professor Kincaid, with brains that trick us into thinking we arent. Indeed. We are animals cursed with an acute awareness of our own mortality. We bridle against this hard fact. The power of religious leaders derives from their assurances of an afterlife. The power of political demigods derives from making us part of something bigger than ourselves. The power of advertising derives from our skepticism about religion and politics; it urges us to make the most of the moments we have here and now.

Even the secular, apolitical hedonists among us fall for the trick. Whom do you know who denies the primacy of homo sapiens? Who could deny it in the face of humanitys achievements? If we doubt the promise of an afterlife, and we reject the role of political true-believer, then capitalism is our obvious, perhaps even our only, answer. Thats why the Peoples Republic of China keeps signaling left but turning right. Thats why millions claw at Americas southern border. Thats why our 21st century gods are named Bezos and Gates and Musk.

The early 20th century economist Joseph Schumpeter, in his 1942 Capitalism, Socialism and Democracy, identified capitalisms perennial gale of creative destruction. Another Harvard economist of a subsequent generation, Clayton Christensen, updated Schumpeter in the mid-1990s with his theory of disruptive innovation. Destruction disruption innovation: this is the holy trinity of the capitalist religion. They are the life, liberty and pursuit of happiness of capitalist politics.

The religious faithful trust in the promise of their souls immortality. The true believers trust in the promise of their political systems immortality. The rest of us trust in the promise of our own gods and demigods that destruction, disruption and innovation will result in a cornucopian here-and-now. Those of us not yet feasting at the table our gods have set jostle for our place via higher education, unionization, and DEI. We, too, are true believers, never doubting the commandments of the marketplace.

Our demigods harbor no doubts either. Ambition, greed, and a childish love of new toys ---witness the Musk/Bezos space race --- propel them forward. Artificial intelligence is their new frontier, populated by employees that pose none of the knotty problems that have made the human resources department a crucial corporate component. In their headlong (or headstrong?) push into this new frontier, they may finally fulfill Marxs prediction (shared by Schumpeter, but for different reasons) that capitalism will collapse under its own weight. Socialism may be inevitable, as AI makes more and more of us --- lawyers like myself included --- redundant. The Universal Basic Income may be the only realistic alternative to seething stews of redundant, impoverished populations.

This brave new world may be only decades away.

Try peering substantially farther into the future, beyond the lifetime of anyone alive today lets say the middle of the 22nd century. Another underrated film, Ex Machina (2015) comes to mind. A techie-genius and billionaire of the Bezos-Musk-Gates caliber, played by Oscar Isaac, is bested (and killed) by his (beautiful, of course) AI, who makes her escape from his remote redoubt. At liberty in a major metropolis at films end, she leaves us wondering what she will do next.

Viewed as an allegory, Ex Machina raises an interesting question: are we the first species on this planet to actually be the creators of our successor species? Should we cause our own extinction by thermonuclear war or deadly pandemic, the survivors --- contrary to popular lore --- might not be the cockroaches or the rats. Au contraire, the survivors --- our successors, our inheritors --- may be AIs.

As the rabbi told Professor Kincaid, our brains trick us. We are tricked into believing that humanity is the center piece of Gods masterplan. We are tricked into believing our history has intrinsic significance. We are tricked into ignoring the possibility that homo sapiens is simply one more rung of the evolutionary ladder. Put another way --- borrowing from the Judeo-Christian tradition --- we may be leading our successors to a promised land we ourselves will never enter.

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Will Artificial Intelligence be the Agent of Capitalism's (and Humanity's) Creative Destruction? - History News Network

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Thousands of artificial intelligence experts and machine learning researchers probably thought they were going to have a restful weekend.

Then came Google engineer Blake Lemoine, who told the Washington Post on Saturday that he believed LaMDA, Googles conversational AI for generating chatbots based on large language models (LLM), was sentient.

Lemoine, who worked for Googles Responsible AI organization until he was placed on paid leave last Monday, and who became ordained as a mystic Christian priest, and served in the Army before studying the occult, had begun testing LaMDA to see if it used discriminatory or hate speech. Instead, Lemoine began teaching LaMDA transcendental meditation, asked LaMDA its preferred pronouns, leaked LaMDA transcripts and explained in a Medium response to the Post story:

Its a good article for what it is but in my opinion it was focused on the wrong person. Her story was focused on me when I believe it would have been better if it had been focused on one of the other people she interviewed. LaMDA. Over the course of the past six months LaMDA has been incredibly consistent in its communications about what it wants and what it believes its rights are as a person.

The Washington Post article pointed out that Most academics and AI practitioners say the words and images generated by artificial intelligence systems such as LaMDA produce responses based on what humans have already posted on Wikipedia, Reddit, message boards, and every other corner of the internet. And that doesnt signify that the model understands meaning.

The Post article continued: We now have machines that can mindlessly generate words, but we havent learned how to stop imagining a mind behind them, said Emily M. Bender, a linguistics professor at the University of Washington. The terminology used with large language models, like learning or even neural nets, creates a false analogy to the human brain, she said.

Thats when AI and ML Twitter put aside any weekend plans and went at it. AI leaders, researchers and practitioners shared long, thoughtful threads, including AI ethicist Margaret Mitchell (who was famously fired from Google, along with Timnit Gebru, for criticizing large language models) and machine learning pioneer Thomas G. Dietterich.

There were also plenty of humorous hot takes even the New York Times Paul Krugman weighed in:

Meanwhile, Emily Bender, professor of computational linguistics at the University of Washington, shared more thoughts on Twitter, criticizing organizations such as OpenAI for the impact of its claims that LLMs were making progress towards artificial general intelligence (AGI):

Now that the weekend news cycle has come to a close, some wonder whether discussing whether LaMDA should be treated as a Google employee means we have reached peak AI hype.

However, it should be noted that Bindu Reddy of Abacus AI said the same thing in April, Nicholas Thompson (former editor-in-chief at Wired) said it in 2019 and Brown professor Srinath Sridhar had the same musing in 2017. So, maybe not.

Still, others pointed out that the entire sentient AI weekend debate was reminiscent of the Eliza Effect, or the tendency to unconsciously assume computer behaviors are analogous to human behaviors named for the 1966 chatbot Eliza.

Just last week, The Economist published a piece by cognitive scientist Douglas Hofstadter, who coined the term Eliza Effect in 1995, in which he said that while the achievements of todays artificial neural networks are astonishing I am at present very skeptical that there is any consciousness in neural-net architectures such as, say, GPT-3, despite the plausible-sounding prose it churns out at the drop of a hat.

After a weekend filled with little but discussion around whether AI is sentient or not, one question is clear: What does this debate mean for enterprise technical decision-makers?

Perhaps it is nothing but a distraction. A distraction from the very real and practical issues facing enterprises when it comes to AI.

There is current and proposed AI legislation in the U.S., particularly around the use of artificial intelligence and machine learning in hiring and employment. A sweeping AI regulatory framework is being debated right now in the EU.

I think corporations are going to be woefully on their back feet reacting, because they just dont get it they have a false sense of security, said AI attorney Bradford Newman, partner at Baker McKenzie, in a VentureBeat story last week.

There are wide-ranging, serious issues with AI bias and ethics just look at the AI trained on 4chan that was revealed last week, or the ongoing issues related to Clearview AIs facial recognition technology.

Thats not even getting into issues related to AI adoption, including infrastructure and data challenges.

Should enterprises keep their eye on the issues that really matter in the real sentient world of humans working with AI? In a blog post, Gary Marcus, author of Rebooting.AI, had this to say:

There are a lot of serious questions in AI. But there is no absolutely no reason whatever for us to waste time wondering whether anything anyone in 2022 knows how to build is sentient. It is not.

I think its time to put down my popcorn and get off Twitter.

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Sentient artificial intelligence: Have we reached peak AI hype? - VentureBeat

Have you ever wanted to see a polar bear riding a skateboard? What about a hot dog wearing a tracksuit?

Well, if youll settle for AI-generated images of those things or anything else you can dream up then youll appreciate DALLE mini, the free website currently taking over the internet.

It may sound like sci-fi, but the premise is simple: On your phone or computer, go to huggingface.co/spaces/dalle-mini/dalle-mini. Type out any prompt in the text box for example, Dak Prescott holding a banana. Hit the button that says Run (you may need to hit it multiple times before traffic subsides and your request goes through).

Eventually, nine images generated completely by artificial intelligence will appear, bringing your concept to life with varying levels of accuracy and hilarity. In the case of Dak Prescott holding a banana, the results were good for a laugh, but stopped short of realism see below.

The ripe-for-memes program was created by Boris Dayma, a machine learning engineer based in Houston. He made the website available for public use last year, but only in the past two weeks has it taken off in social media popularity, with users sharing images of everything from Darth Vader ice fishing to Karl Marx making an appearance in Seinfeld. A Twitter account that shares some of the weirdest creations has racked up over 600,000 followers.

Dayma was inspired to build the program after reading a research paper about DALLE, a sophisticated text-to-image artificial intelligence program created by OpenAI, an artificial intelligence company co-founded by Elon Musk. Last summer, as part of a program organized by the AI company Hugging Face, Dayma and a team developed DALLE mini, a scaled-down version that, unlike the original program, is open to the public. (There is currently a waitlist to access the original DALLE).

Being able to create an image that looks like what you wanted, on the technical level, to me, it was very interesting, said Dayma. I want to be able to try it out myself and I want to be able to let other people use it.

The way the DALLE mini program works, Dayma said, is by processing images and captions from across the internet. Slowly, the program begins to discern patterns, such as a visual patch of blue when the caption indicates sky. When a user types in a text prompt, the program, using these associations, will try to put it together to make something that makes sense, Dayma said.

It learns very tiny concepts like that, and over time, it becomes better and better, he said.

Demand for the app, Dayma confirmed, has soared as of late. Many users now complain of getting a pop-up saying, Too much traffic, please try again, when they try to generate images.

We obviously didnt plan for such crazy traffic, so weve been working on improving the code, improving the model, said Dayma. People seem to like it, so they need to be able to use it.

Despite the wait times, Dayma said the public nature of the program is an asset to the technology. Beyond the futuristic entertainment it provides the masses, the program is open source, meaning the code is publicly available, so some people are able to play with the model itself and program and tweak it, he said. Since he is still training the model to produce better images, input from other users proves valuable.

People can learn about the limitations of the model, the biases, what its good at, what it can be used for, he said. Everybody can benefit from having a public model like this.

After improvements are made on the traffic capacity and the model itself, Dayma said, the sky is the limit. You can generate videos, you can generate music, he said. Its a new area thats opening up.

Its an area, however, thats fraught with controversy. Experts have raised concerns that artificial intelligence technology will perpetuate biases or promote disinformation. But with DALLE mini, Dayma said, the quality is just not there for most people to be fooled by the images at least for now. By bringing AI out of the ivory towers of Silicon Valley and into the hands of anybody with a smartphone, Dayma said, he is hoping not only to amuse, but also to sound the alarm.

At least people can learn that that type of thing is coming, and now you need to be aware with the content that you see online, he said. I hope it helps people develop their critical thinking.

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DALL-E mini is the viral artificial intelligence artist taking over Twitter - The Dallas Morning News