The global Artificial Neural Network (ANN) market size was USD 160.8 Million in 2021 and register a revenue CAGR of 18.7% over the forecast period, according to a latest analysis by Emergen Research. The growing popularity of image processing and character recognition and increasing demand for ANN in various end-use industries such as BFSI, medical, and others are key factors driving revenue growth of the global Artificial Neural Network market.
An ANN is a computing system or information processing paradigm that incorporates elements from the biological neural networks that mimic the human brain. Although the systems are not precisely the same as biological neural systems, they are designed to process information in a manner unlike that of the human and animal brains. The networks are made up of numerous linked neurons that cooperate to accomplish certain objectives. ANNs learn from examples in a manner similar to how humans do. As a result, an ANN can be trained to perform a specific task, such as character recognition or data classification. As a part of the learning process, the system must be adjusted to a connection.
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The major companies Covered in the report are:
Google LLC, International Business Machines Corporation, Oracle Corporation, Microsoft Corporation, Intel Corporation, Qualcomm Technologies, Inc., Alyuda Research, LLC., Ward Systems Group, Inc., Starmind, and Clarifai Inc., Others
ANNs are extensively employed in a variety of medical disciplines, especially in cardiology. ANNs have been widely used in radiology, radiological image analysis, electronic signal analysis, and diagnostics. Many researchers have employed ANNs for modeling in clinical research and medicine. Pharmaceutical epidemiology and medical data mining are two fields where ANN applications are adopted increasingly. ANN is also being used by healthcare organizations to improve care delivery at a lower cost. Although there are many well-known uses for ANN in diagnostics, ANN is also being used more and more in healthcare administration.
The development of handwriting recognition systems uses artificial neural networks. When reading handwriting in a more streamlined manner, neural networks assist in simulating how the human brain functions. It enables machines to interpret the handwriting on par with or better than human ability. In order to support applications based on deep learning, AI chips are created with a special architecture and include AI acceleration. In comparison to typical semiconductor devices, AI processors offer more parallel processing capabilities and have ten times more competing power in ANN applications. Specialized AI hardware has more bandwidth than estimated to allocate four to five times than conventional Central Processing Units (CPU). Rapid technological advancements and the development of new algorithms along with better processors to support the use of AI are expected to drive revenue growth of the market.
However, issues including a shortage of qualified AI professionals and a sluggish adoption of neural networks for different AI applications in poorer nations are limiting revenue growth of the market. Lack of competent personnel with the necessary experience to incorporate ANN in significant projects across several industries. These challenges can be overcome with time through continuous development and innovation of ANN and new sophisticated algorithms.
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Some Key Highlights from the Report
On 4 August 2021, Microsoft Corporation announced that a neural network has been developed by its researchers with 135 billion parameters and deployed in Bing to improve search results for users. The neural network is described as the largest universal AI that the company has run in production and is one of the most sophisticated AI models ever detailed publicly It evaluates the search terms that users submit to the business’s Bing search engine and assists in locating the websites that are most pertinent to their queries.
The solution segment is expected to register a rapid growth rate over the forecast period due to higher accuracy and sophisticated algorithms to perform certain tasks such as speech recognition and image classification. In addition, the growing adoption of AI solutions by various end-use industries is expected to boost revenue growth of the market.
The on-cloud segment revenue accounted for the largest share in 2021 due to the presence of eminent cloud platforms such as AWS, Microsoft Azure, and Google Cloud Platform that provide machine learning solutions and AI tools, which simplify the work of data scientists and ML engineers.
The data mining segment revenue is expected to grow at a rapid rate over the forecast period, which can be attributed to the increasing adoption of neural networks for performing data mining over conventional tools due to their effectiveness
The North America market is expected to account for largest revenue share over the forecast period due to the presence of major IT companies such as Google LLC, Microsoft Corporation, Intel Corporation, and others in several countries of the region. These companies have made high investments in developing an artificial neural network that can effectively solve complicated business problems and help in decision-making across various industries.
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Emergen Research has segmented the global Artificial Neural Network market based on offering, deployment, application, industry vertical, and region:
Offering Outlook (Revenue, USD Million, 2019-2030)
Software
Services
Deployment Outlook (Revenue, USD Million, 2019-2030)
On-Premise
On-Cloud
Application Outlook (Revenue, USD Million, 2019-2030)
Image Processing
Fraud Detection
Data Mining
Others
Industry Vertical Outlook (Revenue, USD Million, 2019-2030)
BFSI
Medical
Retail and Sales
Others
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Regional Outlook (Revenue, USD Million, 2019–2030)
North America
U.S.
Canada
Mexico
Europe
Germany
U.K.
France
Spain
BENELUX
Rest of Europe
Asia Pacific
China
India
Japan
South Korea
Rest of APAC
Latin America
Brazil
Rest of LATAM
Middle East & Africa
Saudi Arabia
U.A.E.
Israel
Rest of Middle East & Africa
Highlights of Table of Contents (TOC):
Overview of Global Artificial Neural Network Market
Competitive analysis of the Artificial Neural Network market
Regional analysis of Global Artificial Neural Network market production and revenue
Regional analysis of Global Artificial Neural Network market supply, consumption, and export & import
Type-based market analysis of global Artificial Neural Network production, revenue, and price trends
Application-based analysis of the global Artificial Neural Network market
Manufacturer profiles, manufacturing cost, and upstream and downstream analysis of global Artificial Neural Network market
Global Artificial Neural Network market forecast (2021-2030)
Conclusion of the research report
Appendix
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