Self-Learning Neuromorphic Chip Market 2017-2023: Key Findings, Regional Analysis, Key Players Profiles and Future Prospects
Market Highlights
The regional wise segmentation of self-learning
neuromorphic chip market consists of North America, Europe, Asia-Pacific and
Rest of the World. North America is one of the most competitive markets across
the globe with various regional players and a few large international players
in self-learning neuromorphic chip market.
Europe region is growing with a slow pace in
hardware market. Emerging economies from countries such as Germany, UK, France,
Russia, Italy, Benelux and Spain is driving Self-Learning Neuromorphic
Chip Market. Moreover, Asia-Pacific is also expected to have
potential growth in the forecast period due to increasing investment of major
players in self-learning neuromorphic chip market.
The self-learning neuromorphic chip market is expected
to grow at approximately USD 2 Billion by 2023, at 14% of CAGR between 2017 and
2023.
Taste the market data and market information presented through more than
30 market data tables and figures spread over 100 numbers of pages of the
project report. Avail the in-depth table of content TOC & market synopsis
on “Self-Learning Neuromorphic
Chip Market - Forecast to 2023”.
Major Key Players:
·
IBM (U.S.)
·
Qualcomm (U.S.)
·
HRL Laboratories
(U.S.)
·
General Vision
(U.S.)
·
Numenta (U.S.)
·
Hewlett-Packard
(U.S.)
·
Samsung Group
(South Korea)
·
Intel Corporation
(U.S.)
·
Applied Brain
Research Inc. (U.S.)
·
Brainchip Holdings
Ltd. (U.S.)
Self-Learning Neuromorphic Chip Market Segmentation:
The self-learning neuromorphic chip market has been
segmented on the basis of application and vertical. By application segment the
signal recognition application is expected to drive the market. The signal
recognition technology can be used in commercial, healthcare, consumer
electronics, automotive, aerospace and defense and industries.
The advancements in image recognition technology
and its application in numerous application such as portable devices, home
automation, robotics and digital health is propelling the market. The chip is
used in image sensor that compose of back side illumination is used in
smartphones and tablet computer owing to its focus speed of 300ms or less and
low lighting condition.
Market Research Analysis:
Regional analysis
for self-learning neuromorphic chip market is studied in different geographic
regions such as North America, Europe, Asia-Pacific and Rest of World. North
America region is the prominent player in the self-learning neuromorphic chip market
due to advanced technological implementation in hardware system. Owing to the presence of major market players, large market
of image recognition and implementation of self-learning neuromorphic chip in
numerous application such as wearables, consumer electronics, medical,
aerospace and others is driving the market. European region is growing with a slow pace in the self-learning
neuromorphic chip market.
Asia-Pacific
region is expected to be fastest growing region in the self-learning
neuromorphic chip market owing to advanced infrastructure development from
countries such as China and India that is boosting the market growth.
Increasing urbanization, business expansion across and industrial developments
is driving the growth of self-learning neuromorphic chip market in the region.
Segments:
Self-Learning Neuromorphic Chip market is segmented on the basis of application and vertical.
Self-Learning Neuromorphic Chip market is segmented on the basis of application and vertical.
Self-Learning Neuromorphic Chip Market by Application:
- Image Recognition
- Signal Recognition
- Data Mining
Self-Learning Neuromorphic Chip Market by Vertical:
- Healthcare
- Power & Energy
- Automotive
- Media & Entertainment
- Aerospace & Defense
- Smartphones
- Consumer Electronics
- Others
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Intended Audience
- Investors and consultants
- System Integrators
- Government Organizations
- Research/Consultancy firms
- Technology solution providers
- IT Solution Providers
- Original Equipment Manufacturers
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