{"id":241680,"date":"2018-07-16T09:35:05","date_gmt":"2018-07-16T09:35:05","guid":{"rendered":"http:\/\/www.abnewswire.com\/pressreleases\/?p=241680"},"modified":"2018-07-16T09:35:05","modified_gmt":"2018-07-16T09:35:05","slug":"cognitive-computing-market-2018-global-trend-segmentation-and-opportunities-forecast-to-2023","status":"publish","type":"post","link":"https:\/\/www.abnewswire.com\/pressreleases\/cognitive-computing-market-2018-global-trend-segmentation-and-opportunities-forecast-to-2023_241680.html","title":{"rendered":"Cognitive Computing Market 2018 Global Trend, Segmentation And Opportunities Forecast To 2023"},"content":{"rendered":"
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“Cognitive Computing”<\/div>\n<\/div>\n
Cognitive Computing -Market Demand, Growth, Opportunities and Analysis Of Top Key Player Forecast To 2023<\/div>\n

Cognitive Computing <\/strong>Industry<\/strong><\/a><\/p>\n

Description<\/strong><\/p>\n

Wiseguyreports.Com Adds “Cognitive Computing -Market Demand, Growth, Opportunities and Analysis Of Top Key Player Forecast To 2023” <\/strong>To Its Research Database<\/p>\n

Cognitive computing like many IT terms is defined both by its technical capability and applications and by marketing statements. From a technical standpoint, cognitive computing is a system that uses machine learning algorithms to continually increase its “knowledge” from the data it receives. The learning aspect is characterized by the system continuously refining patterns in the data as well as the way data is processed. This learning allows cognitive computing systems to anticipate new problems and model possible solutions in an adaptive and iterative manner. The system also works within a context and can identify and extract contextual elements such as meaning, syntax, time, location, regulation, user profiles, tasks and goals.<\/p>\n

Applications of cognitive computing are derived from data mining, pattern recognition and natural language processing. These applications automate manual processes or augment more basic computing processes. The marketing definition of cognitive computing is to solve problems as well as or better than humans without human assistance. However, cognitive computing may best be applied as an enabler in a process that involves both machines and humans rather than one replacing the other.<\/p>\n

As with the field of artificial intelligence in general, cognitive computing is now coming into practical application because of a convergence of underlying technologies. These include high performance processors and advanced algorithms, which combine to enable computing systems to leverage machine learning, natural language processing and expert systems to provide new value in dealing with consumer and business applications.<\/p>\n

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While cognitive computing represents the continued evolution of artificial intelligence to practical commercial applications, it is currently benefiting from accelerated adoption in the market caused by its ability to make sense of unstructured data. According to some estimates, the amount of data being generated globally is growing at a rate of REDACTED% per year. Most of this growth is from unstructured data types (e.g., data that does not fit neatly into a database, including documents, videos, photos, audio files, presentations, web pages, etc.). Conventional database management systems are not designed toorganize and interpret this data, limiting the applicability of IT organization to make use of it. Entercognitive computing, which can apply new processes to discern patterns that can be used to manage,interpret and act on unstructured data.<\/p>\n

The demand for this kind of deep data analysis and autonomous response is driving the cognitive computing market to grow to $REDACTED billion by 2022 at a compound annual growth rate (CAGR) of REDACTED% for 2017-2022. The market was $REDACTED billion in 2016 and grew to $REDACTED billion in 2017. With a foundation in expert systems the market can be segmented into expert systems, machine learning and natural language processing.<\/p>\n

North America is the leading market with a REDACTED% share, followed by Europe at REDACTED% and Asia-Pacific at REDACTED%. While enterprise is a wide adopter of cognitive computing, governments with the highest growth rates and applications are pioneering cognitive computing in education and healthcare. Within enterprise applications and financial services, operations and marketing are gaining traction.<\/p>\n

Report Scope<\/strong><\/p>\n

The scope of this report covers the overall Cognitive Computing technologies market with market sizing and trends analysis for the most recently completed actuals for 2016 as well as forecasts, trends and compound annual growth rates (CAGRs) for 2017 through 2022.<\/p>\n

The market is segmented by end user, technology and region. End user segments include education, government and enterprise. Applications include the military, healthcare and manufacturing sectors.<\/p>\n

Report Includes<\/strong><\/p>\n

– An overview of the global market for cognitive computing 
– Analyses of global market trends, with data from 2017, 2018, and projections of compound annual growth rates (CAGRs) through 2023 
– Insight into the types of cognitive computing technologies, including natural language processing, neural networks, and expert systems 
– Descriptions of key patents related to the market 
– Information on key components, applications, and market trends 
– Profiles of major players and companies in the market, including Google Deepmind AI Solution, Intel Saffron, Numenta, Welltok Analytics, Cisco Cognitive Threat Analysis and Abbyy<\/p>\n

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 <\/p>\n

Table of Contents <\/strong><\/p>\n

Chapter 1 Introduction 
Study Goals and Objectives 
Reasons for Doing This Study 
Scope of Report 
Information Sources 
Methodology 
Geographic Breakdown 
Analyst’s Credentials 
Related BCC Research Reports 
Chapter 2 Summary and Highlights 
Chapter 3 Market and Technology Background 
Cognitive Computing Defined 
Cognitive Computing and Data Analysis 
Cognitive Computing and Robotics 
Robotic Process Automation 
Cognitive Computing Challenges 
Cognitive Computing and the Cloud 
Deep Learning 
Video Analysis 
Chapter 4 Market Breakdown by Technology Type 
Expert Systems 
Machine Learning 
Machine Intelligence 
Natural Language Processing 
Speech Recognition 
Chapter 5 Market Breakdown by End User 
Enterprise 
Government 
Education 
Chapter 6 Market Breakdown by Application 
Financial Services 
Healthcare 
Military 
Manufacturing 
Other 
Chapter 7 Market Breakdown by Region 
North America 
Latin America 
Europe 
Middle East and Africa 
Asia-Pacific 
Rest of World 
Chapter 8 Analysis of Market Opportunities 
Cognitive Computing Market Landscape 
Opportunities in Finance 
Opportunities in Insurance 
Opportunities in Marketing 
Opportunities in Security 
Opportunities in Healthcare 
Approaches to the Market 
New Developments 
Market Challenges 
Future Directions 
Data Governance 
Chapter 9 Patent Analysis 
Cognitive Technology Patents 
Can an AI System Patent Itself? 
Chapter 10 Company Profiles 
ABBYY 
ALPINE DATA 
AMAZON AWS 
APIXIO 
ATTIVIO 
AVAAMO 
BAIDU MINWA 
C3 IOT 
CISCO COGNITIVE THREAT ANALYSIS 
COGITAI 
COGNITIVESCALE 
CROWDFLOWER 
CUSTOMERMATRIX 
DARKTRACE 
DATABRICKS 
DIGITALGENIUS 
DIGITAL REASONING 
EXPERT SYSTEMS 
GOOGLE DEEPMIND AI SOLUTION 
HEALTHCARE X.0. 
HPE HAVEN ON DEMAND 
IBM WATSON 
INTEL SAFFRON 
IP SOFT 
LOOP AI LABS 
MEDWHAT 
MICROSOFT COGNITIVE SERVICES 
NUMENTA 
NVIDIA 
PERPETUUITI TECHNOSOFT INC. 
PERSADO 
QUALCOMM 
SPARK COGNITION 
WELLTOK ANALYTICS 
WIRETAP<\/p>\n

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