Neuromorphic chips, the electronic chips inspired from the human brain, which works with the help of signals sent and received through a network of millions of neurons, are witnessing a significant rise in applications and expected to bring massive changes in the way machines operate.

Encouraging advancements seen in the field of miniaturized integrated circuits and the increased use of such miniature electronic chips across sectors such as medical devices and aerospace are the key factors to have fuelled research and development activities in the neuromorphic chips market.

The neuromorphic chip market is driven primarily due to the increasing demand of artificial intelligence. 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. 

Growth of neuromorphic chip market is hindered due to high cost associated in manufacturing of such chips. Manufacturer faces different tribulations in integrating biological synapses in to a minute hardware which requires just a single micron of space. Complexities in hardware designing are also major restraining factors in this market.

The complicated neuromorphic synapses are difficult to implement in hardware. As of 2015, in developing countries, developments in the field of neuromorphic computing have negatively affected due to lack of availability of technological resources and lack of availability of competent infrastructure. 

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