The neuromorphic computing is executed on hardware by threshold switches, transistors and oxide based memristors. Neuromorphic chips are the amalgamation of memristors and transistors deployed over a silicon fabrication chip, which assists to lessen memory consumption in real time manner. Moreover, neuromorphic chips are the digital and analog very large scale integration (VLSI) system which performs as neural systems models. Implementation of neuromorphic chip is likely to increase scalability, performance and sensitivity of machines.

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Artificial intelligence is a machine learning technology that provides the skill to machines to learn with partial programming. This involves the advancement of computer programs and machines which are competent enough to update themselves when being exposed to real time data. Moreover, an innovation in the field of miniaturization of integrated circuits has increased the scope of applications for neuromorphic chip. The neuromorphic chips are small and scalable enough to get easily implemented in different end use products. Rising demand of neuromorphic chip in the field of Internet of Things (IoT) technology is driving the growth of the market. The chips are likely being planted in large supercomputers to enhance the speed of machine learning along with some other neural network-based computations.

Implementation of neuromorphic chips in diverse end use products of different industries including automotive, semiconductor & electronics and healthcare can be identified as future growth opportunity for the market. Neuromorphic chips have application level opportunities in industrial and service robotics.

The global neuromorphic chip market, as mentioned, is of critical future importance to the sectors of defense and automotive. The scope of use of this product in these sectors is expected to increase even further in the coming years, owing to the increasing demand for artificial intelligence. A growing number of industries are showing a large demand for these machines with learning capabilities through partial programming. On paper, the global neuromorphic chip market is capable of producing artificial intelligence that can update itself once exposed to external sources of knowledge in real time. This allows the AI to perform similar tasks in different methods, as per the requirement, giving rise to a large scope of utility for neuromorphic chips in the near future.

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In terms of applications, the global neuromorphic chip market was dominated by the industrial segment in 2014, from the perspective of revenue. Neuromorphic chips already have a significant scope of use in industrial segments such as advanced machine vision. Other application segments of the global neuromorphic chip market include medical, automotive, defense and aerospace, and other minor segments. In terms of function, 30.0% of the global neuromorphic chip market was occupied by signal processing function, in 2014. This was the leading share in the market, owing to the high amount of applications in all its end-use industries.

Geographically speaking, the global neuromorphic chip market was led by North America in terms of market size in 2014. The market is expected to maintain its leading position in the global market in the near future.

Global Neuromorphic Chip Market: By Function

> Signal Processing
> Data Processing
> Image Recognition
> Others

Global Neuromorphic Chip Market: By Application

> Defense and Aerospace
> Automotive
> Medical
> Industrial
> Others

Global Neuromorphic Chip Market: By Geography

> North America
> Europe
> Asia Pacific
> Rest of the World

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