Self-Learning Neuromorphic Chip Market Segmentation, Competitive Landscape
Self-Learning Neuromorphic Chip Market, by Application (Image Recognition, Signal Recognition, Data Mining), by Vertical (Healthcare, Power & Energy, Automotive
IBM a prominent player in neuromorphic chip market has designed a brain like neuromorphic chip. The chip functions better at image recognition, it is able to accurately classify data much more efficiently, from an energy perspective as compare to traditional processor architectures. The chip can be used in new applications such as mobile computing, IoT, robotics, autonomous cars, and HPC. Qualcomm a key and up-coming player in neuromorphic chip market. It has designed a Zeroth neuromorphic chip program. The company focuses on signing up researchers this year to test its latest technology. HRL Laboratories, LLC, announced that it will continue to develop innovative electronics products and solutions that simulate the cognitive capabilities of biological intelligence in the Defense Advanced Research Projects Agency’s (DARPA) Systems of Neuromorphic Adaptive Plastic Scalable Electronics, or SyNAPSE program. The company has also shared their views on up-coming neuromorphic technology. It stated that researchers in the company developed brain-like microcircuitry in hardware and also manufactures very low-power neuron CMOS circuits, that became the foundation for large-scale neuromorphic circuits.
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North America region is dominating the Self-Learning Neuromorphic Chip market with the largest market revenue. 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. Asia-Pacific region is expected to have fastest growth in the market due to the growing crime rate and increasing infrastructure development.
By application segment the signal recognition is expected to drive the market. The application segment consists of signal recognition, image recognition and data mining. 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.
By vertical segment medical, automotive & transportation accounts for high market share. The major growth driver of self-learning neuromorphic chip market is artificial intelligence and machine learning technology is one of the significant factors aiding the market. However some factors such as lack of knowledge, complexity in designing chip and algorithm related to it are some of the important restraints that may hinder the market.
The self-learning neuromorphic chip market is expected to grow at approximately USD 2 Billion by 2023, at 27% of CAGR between 2017 and 2023.
The prominent players in the global self learning neuromorphic chip market are – 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.) and others.
Self-Learning Neuromorphic Chip market is segmented on the basis of application and vertical.
Self-Learning Neuromorphic Chip Market by Application:
Self-Learning Neuromorphic Chip Market by Vertical:
Power & Energy
Media & Entertainment
Aerospace & Defense
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