IntroductionIn 1950s, when computer first evolved it used mechanical systems with combination of cogs and gears for the computing. Currently, we are using semiconductor chips which uses drastically reduced space and hence give us much more efficient computing. As Moore,s law predicts the doubling of transistors in an Integrated Circuit (IC) every two years i.e. even faster computing. Going beyond the prediction we are moving forward with Neuromorphic chips. A crucial feature of neuromorphic computing includes understanding the morphology of individual neurons and circuits. Its applications and description of the overall architectures in creating some desirable computations can be done by the neuromorphic computing. It also affects how information is represented in the process and the robustness to damage. Incorporates learning and development can be accounted for using this technology and it adapts to the local change and in the long term facilitates an evolutionary change. Neuromorphic computing is an interdiscplinary subject. It takes inspirations from various fields of study such as biology, physics, mathematics, computer science, and electronic engineering. These subjects help to fabricate the artificial neural systems. For example, in vision systems, head-eye systems and autonomous robots in which the physical architecture and the designing principles are based on the biological nervous systems as that in a living organism. A subclass of neuromorphic computing systems is neuromemristive systems. Main focus on the use of memristors are to implement neuroplasticity. Neuroplasticity or neural plasticity is a term that is described by a lasting change to the brain throughout an individual’s course of life. So, neuromorphic computing mainly focuses on mimicking the biological behavior, neuromemristive systems focus on abstraction of the brain memory in the living organisms. There are several neurons that which when implemented with memristors have an application in pattern recognition applications. Some of these applications are reported in voice recognition, face recognition and object recognition. So, future of neuromorphic technology has a great aspect in security of information as well as storage of large volume of data which can help develop artificial intelligence to make life easier.Business conceptWe intend take make these chips which can handle complex AI computations with ease and can start a new revolution. We are entering the internet zone where we have enormous amount of data and information. The complexity of our codes has gone manifold. This technology tries to imitate the efficient functioning of our brain. Each of the neuron can determine whether the incoming signal is to be passed or not. It requires altogether a different kind of compiler that can help understand these decisions.We propose to use this concept of neuro-morphic computing using AI. That would make the computations even faster and efficient. We intend to use it for supporting strong AI systems, making smartphones smarter and data mining. Ai systems are becoming more complex and this 9000x computing using 2000 times lesser power would help it become more powerful.Scope and applicationsThe basic on which Neuromorphic chip is built is to replicate and morph human brain neural network. Neurons in brain are connected with synapse and each neuron has a layer of myelin which help in transferring of information at faster rate. The ultimate aim of neuromorphic chip is to build artificial neural system which has fundamental characteristics of human brain. The idea of mimicking the basic properties of nervous system is that if we can comprehensively replicate a brain neural network on silica the learning behaviour will emerge subsequently. Though this technology has immense spectrum. Below image explains a few of the many capabilities this technology has got and how this technology can morph human retina for sophisticated visual advancements in detecting multiple objects in visual field.Current ScenarioNeuromorphic systems which are in operation currently:1 – IBM’s TrueNorth2 – The SpiNNaker Project3 – The BrainScaleSApplications Interaction with intelligent machines will change fundamentally with neuromorphic computing. Some of the applications include smartphone sensors, robots, smart cars or olfactory detection. In essence this technology could be final step in building smart machines which can learn, reason, remember which is very difficult with current technology. 1 – Health issues – Brain like computes could be used in therapeutic procedures, help create artificial retina, impact medical imaging, using AI to predict plausible disease. 2 – Surveillance – Enhancement of surveillance could be the next big thing that could be enhanced like never before with the help of intelligent cameras equipped with video analysis capabilities.3 – Economy – NMC could help analyses huge data of financial market to help financial forecasting. NMC can be used in monitoring agriculture, data mining, cloud computing etc. 4 – Environment – Monitoring weather in an efficient way. Could also improve data mining and pattern dramatically with the help of pattern recognition system to monitor biosphere processes.5 – Military and security – NMC has immense application in drone equipped with human brain like chip which can learn and recognize sites and objects previously visited even if there is alteration in the site. NMC robots can be sent to combat zones where they can decide and act and take course of action independently. This can be used in Micro-bots.Business PlanThe Problem/Opportunity: Smart devices being our best friends so far and satiating our daily demands efficiently we sometimes still get annoyed by the irksome notifications or unwanted data outputs which do not interests our requirements. How would it be if everyone possesses a customized smart device which suits their necessities and behaved just like their owners? What if your smartphone have a physical brain programmed in such a way to take care of your likes and dislikes without your interference? This is possible through neuromorphic chip.Technology/ Scenario Analysis: This is also termed as brain computing where a smartphone would become hyper smart with a potential brain made of neural inspired computer chip. It functions by using VLSI technology by mimicking neuro biological circuits of a human nervous system. These help us in obtaining desirable computations, self-incorporation of learning and development, possesses plasticity (ability to tune to new changes) and acquiring resistance to damages. Currently it is used in many applications in defence research, agriculture, and medical research. Its implementation in smart devices would enable lots of power saving along with improved efficiency and productivity.Competitor Analysis: Currently many IT and electronics companies are laying emphasis on incorporating this technology in smart devices such as Qualcomm, IBM etc.Go-to Market Strategy/Consumer Relationship: The relation with the customers will be held through a product launch of this new feature device and also by leading campaigns in various platforms such as social media, TV advertisements etc. The campaign would during the development stage of mobile devices and will intensify few days before the launch.