Neuromorphic Chip Market Driven by Miniaturization of Integrated Circuits

Neuromorphic chips are combination of digital and analog very large scale integration (VLSI) system and software, which execute neural systems models. This can be executed on hardware by threshold switches, transistors, and oxide based memristors. These are the electronic chips based on the concept of human brain and are made out of millions of neurons. These are small enough in size, so that it can be placed inside electronic devices and human body easily. Moreover, these chips are placed in one single micron of space which drives the miniaturization of integrated circuits. The increase in application wise penetration of miniaturization of integrated circuits has fuelled the demand for neuromorphic chips.

Logistics, ‘aerospace and defense’ and automotive are some of the sectors where neuromorphic chips are used for image recognition. Growing demand of artificial intelligence is also one of the major drivers for the neuromorphic chip market. Artificial intelligence is a machine learning technology that provides the skill to computers to learn with partial programming. This involves the advancement of computer programs which are competent of updating themselves when exposed to real time data. The artificial intelligence implements neuromorphic chips which help to carry out different operations in different ways. This means the artificial intelligence is likely to perform particular task in different ways instead of following one particular process. Thus evolution of artificial intelligence is also expected to increase the application scopes of neuromorphic chips during the forecast period.

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Complexities in hardware designing of neuromorphic chips can be identified as one of the major restraining factors in this market. The complicated neuromorphic synapses are difficult to implement in overall established hardware chip design. The reason for this complexity is the intricate algorithm and space that is required to be implemented in the structured hardware. Another major complexity is the limitation in memory capacity of neuromorphic chips. With the technological advancements, impact of these restraining factors is expected to decrease during the forecast period.

Implementation of neuromorphic chips in new applications includes logistics and entertainment can be identified as major opportunity for the market. These chips are likely to be used in industrial and service robotics used in logistics to operate independently without human guidance.

Based on function, the market is segmented into signal processing, data processing, image recognition and others. The signal processing function of neuromorphic chip accounted for more than 30% share in 2014 because of the increasing application of these chips in different end use industries including automotive, aerospace and defense and industrial sectors.

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