Press release
Neuromorphic Computing Market Size & Share - Industry Trend and Forecast 2016 - 2024
The main objective of this report is to define, describe, and forecast the global “Neuromorphic Computing” market on the basis of types of applications, major sectors, deployment models, organization size, and regions. The report contains an analysis of the major factors influencing the growth of the market (drivers, restraints, opportunities, and challenges). It aims to strategically analyze the micromarkets with respect to individual growth trends, prospects, and their contribution to the market. The report attempts to forecast the market size for 5 major regions, namely, North America, Europe, Asia Pacific (APAC), Middle East and Africa (MEA), and Latin America. It contains key vendor profiles and comprehensively analyzes their core competencies. The report also tracks and analyzes competitive developments, including partnerships, collaborations, acquisitions, new product developments, and R&D activities in the market.
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Neuromorphic computing or neuromorphic engineering has been described as the use of large integration systems containing numerous analog circuits allowing the replication of neuro-biological behaviors existing in a human’s nervous system. The neuromorphic computing platform consists of two vital systems based on the custom hardware architecture. Such systems are designed to program neural microcircuits by applying brain-like thought process in cognitive computing and machine learning process. This procedure enables a machine to learn, adapt and function like a human brain does rather than functioning like a normal computer. In addition, to perform such a complex task, the computing platform requires the state-of-the-art circuit technologies and electronic components, which allows the platform to receive new data or knowledge gained from various other sources of neuroscience research, e.g. theoretical neuroscience, brain modelling and experimental neuroscience.
The neuromorphic computing systems are programmed as brain inspiring devices, which are capable for low energy and high speed simulations of synaptic plasticity with spiking neural networks. The two neuromorphic computing systems are BrainScaleS system and SpiNNaker system. The BrainScaleS system is purely based on mixed signal and analogue emulations of neuron, synapse of plasticity models with digital connectivity going up to 10,000 times faster than the real time. The SpiNNaker system on the other hand is based on numerical model, which runs in real time on custom digital multicore chips. The simulation and models for this system is provided in Python script, which uses PyNN API.
Neuromorphic computing is expected to gain huge momentum in the coming years due to the gaining familiarity of neuromorphic computing technology and rising demand for artificial intelligence. Artificial intelligence is used as applications in language processing, computer vision and image processing, translation and chatterbots, and non-linear controls and robotics. In addition, increasing application and usage of software in neuromorphic computing is also set to drive the growth of this market. Softwares in neuromorphic computing is used as various applications such as predictive analysis, machine vision, video monitoring, online learning and data modelling among others. There has been an emerging trend of combining embodied models and neuroscience computation for the application of neuromorphic chips in cognitive and brain-based robots. Major companies in the neuromorphic computing market are improving their efforts in their research and development activities and marketing strategies for the commercialization of neuromorphic chips. Such initiatives is expected to help companies penetrate into new areas of market and create awareness for the new technology and products involved supporting the advancement of neuromorphic computing technology. Moreover, the replacement of Von Neumann chips by neuromorphic chips is also expected to bolster the growth of neuromorphic computing industry, exponentially. Neuromorphic chips exhibit qualities such as low power consumption, high speed accuracy and optimum memory usage. However, limited research and development in this market due to huge investment and advanced technologies required, coupled with complexity in the designing and manufacturing of neuromorphic chips are the major factors inhibiting the growth of neuromorphic computing market.
The neuromorphic computing market can be categorized into five application segments such as image processing, signal processing, object detection, data processing and others. The signal processing market is expected to show significant growth in the coming years owing to the rising demand for acoustics signal and processing of audio. By end-use, the market can be segregated into five segments such as automotive, consumer electronics, automotive, defense, healthcare and others. The consumer electronics is expected to hold the largest share in terms of end-use application of neuromorphic computing. The usage of neuromorphic computing in self-driven and smart vehicles is expected to bring a transition in transportation and furthermore, propel the growth of automotive sector. The usage of neuromorphic chips in satellites for surveillance and aerial imagery is highly in demand in the defense sector.
The key players in the neuromorphic computing market include Hewlett-Packard (U.S.), IBM Corporation (U.S.), Samsung Electronics Co. Ltd. (South Korea), Qualcomm Inc. (U.S.), Intel Corporation (U.S.), Brain Corporation (U.S.), HRL Laboratories (U.S.), General Vision Inc (U.S.), Vicarious (U.S.), Knowm Inc. (U.S.), Numenta (U.S.), and CEA-Leti (France) among others.
The report offers a comprehensive evaluation of the market. It does so via in-depth qualitative insights, historical data, and verifiable projections about market size. The projections featured in the report have been derived using proven research methodologies and assumptions. By doing so, the research report serves as a repository of analysis and information for every facet of the market, including but not limited to: Regional markets, technology, types, and applications.
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The study is a source of reliable data on:
Market segments and sub-segments
Market trends and dynamics
Supply and demand
Market size
Current trends/opportunities/challenges
Competitive landscape
Technological breakthroughs
Value chain and stakeholder analysis
The regional analysis covers:
North America (U.S. and Canada)
Latin America (Mexico, Brazil, Peru, Chile, and others)
Western Europe (Germany, U.K., France, Spain, Italy, Nordic countries, Belgium, Netherlands, and Luxembourg)
Eastern Europe (Poland and Russia)
Asia Pacific (China, India, Japan, ASEAN, Australia, and New Zealand)
Middle East and Africa (GCC, Southern Africa, and North Africa)
The report has been compiled through extensive primary research (through interviews, surveys, and observations of seasoned analysts) and secondary research (which entails reputable paid sources, trade journals, and industry body databases). The report also features a complete qualitative and quantitative assessment by analyzing data gathered from industry analysts and market participants across key points in the industry’s value chain.
A separate analysis of prevailing trends in the parent market, macro- and micro-economic indicators, and regulations and mandates is included under the purview of the study. By doing so, the report projects the attractiveness of each major segment over the forecast period.
Highlights of the report:
A complete backdrop analysis, which includes an assessment of the parent market
Important changes in market dynamics
Market segmentation up to the second or third level
Historical, current, and projected size of the market from the standpoint of both value and volume
Reporting and evaluation of recent industry developments
Market shares and strategies of key players
Emerging niche segments and regional markets
An objective assessment of the trajectory of the market
Recommendations to companies for strengthening their foothold in the market
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