ResearchMoz presents professional and in-depth study of "Cognitive Computing: Applications and Global Markets".
Summary
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.
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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.
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.
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.
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.
View Complete TOC with tables & Figures @ https://www.researchmoz.us/cognitive-computing-applications-and-global-markets-report.html/toc
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.
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.
Report Scope
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.
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.
Report Includes
- 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
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- 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
For More Information Kindly Contact:
ResearchMoz
Mr. Nachiket Ghumare,
90 State Street, Albany NY, United States - 12207
Tel: +1-518-621-2074
USA-Canada Toll Free: 866-997-4948
Email: sales@researchmoz.us
Follow us on LinkedIn @ http://bit.ly/1TBmnVG
Follow me on : https://marketinfo247.wordpress.com/
Summary
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.
Get PDF for more Professional and Technical insights @ https://www.researchmoz.us/enquiry.php?type=S&repid=1839743
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.
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.
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.
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.
View Complete TOC with tables & Figures @ https://www.researchmoz.us/cognitive-computing-applications-and-global-markets-report.html/toc
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.
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.
Report Scope
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.
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.
Report Includes
- 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
Make An Enquiry @ https://www.researchmoz.us/enquiry.php?type=E&repid=1839743
- 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
For More Information Kindly Contact:
ResearchMoz
Mr. Nachiket Ghumare,
90 State Street, Albany NY, United States - 12207
Tel: +1-518-621-2074
USA-Canada Toll Free: 866-997-4948
Email: sales@researchmoz.us
Follow us on LinkedIn @ http://bit.ly/1TBmnVG
Follow me on : https://marketinfo247.wordpress.com/
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