Global Neuromorphic Computing Market to reach USD 8.9 billion by 2025.
Global Neuromorphic Computing Market valued approximately USD 1.6 billion in 2016 is anticipated to grow with a healthy growth rate of more than 21% over the forecast period 2017-2025. The major factors driving the growth of the market include growth in the sensors market; rising demand for artificial intelligence and machine learning; increasing adoption of software in applications such as continuous online learning, real-time data streaming, predictive analysis, and data modelling; need for better performing ICs; growing demand for neuromorphic computing in applications such as video monitoring, machine vision, and voice identification; and the end of Moore�s law leading to new ways of computing. The emerging trend of combining neuroscience computation and embodied models has led to an upsurge in demand for design and development of neuromorphic chips for brain-based robots and cognitive robots. Rising need for machine learning tools has further contributed to industry expansion.
Geographically, the Global Neuromorphic Computing market research report split global into several key Regions, with sales (K MT), revenue (Million USD), market share and growth rate of Neuromorphic Computing Industry for these regions, from 2013 to 2025 (forecast), covering
2013 2017 2025 Share CAGR (2017-2025)
United States xx xx xx xx% xx%
EU xx xx xx xx% xx %
Japan xx xx xx xx% xx%
China xx xx xx xx% xx %
India xx xx xx xx% xx%
Southeast Asia xx xx xx xx% xx%
Others xx xx xx xx% xx%
Total xx xx xx xx% xx%
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North America is the largest and rapidly growing market for neuromorphic computing due to the initiatives taken by major chip designing companies such as IBM Corporation (U.S.), Intel (U.S.), and General Vision (U.S.). The global industry is expected to gain momentum in Asia Pacific and South America due to growing demand for automation in emerging nations such as China, India, and Brazil.
The objective of the study is to define market sizes of different segments & countries in recent years and to forecast the values to the coming eight years. The report is designed to incorporate both qualitative and quantitative aspects of the industry within each of the regions and countries involved in the study. Furthermore, the report also caters the detailed information about the crucial aspects such as driving factors & challenges which will define the future growth of the market. Additionally, the report shall also incorporate available opportunities in micro markets for stakeholders to invest along with the detailed analysis of competitive landscape and product offerings of key players.
IBM Corporation,
Hewlett Packard ,
Samsung Electronics co Ltd.,
Intel Corporation,
Qualcomm Inc.,
Brain Corporation,
General Vision Inc.,
HRL Laboratories,
Vicarious,
CEA-Leti and so on.
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On the basis of product, the Global Neuromorphic Computing Industry report displays the production, revenue, price, market share and growth rate of each type, The detailed segments and sub-segment of the market are explained below:
By Application:
Signal Processing
Image Processing
Data Processing
Object Detection
By End Use:
Consumer Electronics
Automotive
Healthcare
Military & Defence
Furthermore, years considered for the study are as follows:
Historical year 2015, 2016
Base year 2017
Forecast period 2018 to 2025
Target Audience of the Global Neuromorphic Computing Market in Market Study:
Key Consulting Companies & Advisors
Large, medium-sized, and small enterprises
Venture capitalists
Value-Added Resellers (VARs)
Third-party knowledge providers
Investment bankers
Investors
Some of the points from Global Neuromorphic Computing Market Research Report are
Chapter 1. Global Neuromorphic Computing Market Definition and Scope
Chapter 2. Research Methodology
Chapter 3. Executive Summary
Chapter 4. Global Neuromorphic Computing Market Dynamics
Chapter 5. Global Neuromorphic Computing Market, By Product
Chapter 6. Global Neuromorphic Computing Market by Application
Chapter 7. Global Neuromorphic Computing Market, Regional Analysis
Chapter 8. Competitive Intelligence
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