The Neuromorphic Computing Market is expected to grow from USD 6.6 Million in 2020 to USD 272.9 Million by 2027, at a CAGR of 86.0% during the forecast period.
Latest added Neuromorphic Computing Market research study by MarketDigits offers detailed product outlook and elaborates market review till 2026. The market Study is segmented by key regions that is accelerating the marketization. At present, the market is sharping its presence and some of the key players in the study are Samsung Electronics, Intel Corporation, HRL Laboratories, Numenta, CEA-Leti, IBM. The study is a perfect mix of qualitative and quantitative Market data collected and validated majorly through primary data and secondary sources.
This report studies the Neuromorphic Computing Market size, industry status and forecast, competition landscape and growth opportunity. This research report categorizes the Neuromorphic Computing Market by companies, region, type and end-use industry.
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Scroll down 100s of data Tables, charts and graphs spread through Pages and in-depth Table of Content on “Neuromorphic Computing Market, By Technology (Hardware, Software), Industry Vertical (IT-Telecom, Medical, Consumer Electronics, Aerospace- Defense, Automotive, Industrial, Others), Application (Data Mining, Image Recognition, Object Detection, Signal Recognition) and Geography – Global Forecast to 2026”. Early buyers will get 10% customization on study.
To Avail deep insights of Neuromorphic Computing Market Size, competition landscape is provided i.e. Revenue Analysis (M $US) by Company (2018-2020), Segment Revenue Market Share (%) by Players (2018-2020) and further a qualitative analysis is made towards market concentration rate, product/service differences, new entrants and the technological trends in future.
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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.
This study by MarketDigits is all-encompassing framework of the dynamics of the market. It mainly comprises critical assessment of consumers’ or customers’ journeys, current and emerging avenues, and strategic framework to enable CXOs take effective decisions.
Our key underpinning is the 4-Quadrant Framework EIRS that offers detailed visualization of four elements:
- Customer Experience Maps
- Insights and Tools based on data-driven research
- Actionable Results to meet all the business priorities
- Strategic Frameworks to boost the growth journey
The study strives to evaluate the current and future growth prospects, untapped avenues, factors shaping their revenue potential, and demand and consumption patterns in the global market by breaking it into region-wise assessment.
The following regional segments are covered comprehensively:
- North America
- Asia Pacific
- Latin America
- The Middle East and Africa
The EIRS quadrant framework in the report sums up our wide spectrum of data-driven research and advisory for CXOs to help them make better decisions for their businesses and stay as leaders.
Below is a snapshot of these quadrants.
1. Customer Experience Map
The study offers an in-depth assessment of various customers’ journeys pertinent to the market and its segments. It offers various customer impressions about the products and service use. The analysis takes a closer look at their pain points and fears across various customer touchpoints. The consultation and business intelligence solutions will help interested stakeholders, including CXOs, define customer experience maps tailored to their needs. This will help them aim at boosting customer engagement with their brands.
2. Insights and Tools
The various insights in the study are based on elaborate cycles of primary and secondary research the analysts engage with during the course of research. The analysts and expert advisors at MarketDigits adopt industry-wide, quantitative customer insights tools and market projection methodologies to arrive at results, which makes them reliable. The study not just offers estimations and projections, but also an uncluttered evaluation of these figures on the market dynamics. These insights merge data-driven research framework with qualitative consultations for business owners, CXOs, policy makers, and investors. The insights will also help their customers overcome their fears.
3. Actionable Results
The findings presented in this study by MarketDigits are an indispensable guide for meeting all business priorities, including mission-critical ones. The results when implemented have shown tangible benefits to business stakeholders and industry entities to boost their performance. The results are tailored to fit the individual strategic framework. The study also illustrates some of the recent case studies on solving various problems by companies they faced in their consolidation journey.
4. Strategic Frameworks
The study equips businesses and anyone interested in the market to frame broad strategic frameworks. This has become more important than ever, given the current uncertainty due to COVID-19. The study deliberates on consultations to overcome various such past disruptions and foresees new ones to boost the preparedness. The frameworks help businesses plan their strategic alignments for recovery from such disruptive trends. Further, analysts at MarketDigits helps you break down the complex scenario and bring resiliency in uncertain times.
The base year for calculation in this Neuromorphic Computing Market business report is taken as 2020 while the historic year is 2019 which will tell how the market will perform in the forecast years by informing what the market definition, classifications, applications, & engagements are. This Neuromorphic Computing Market report is also all-embracing of the data which covers market definition, classifications, applications, engagements, market drivers & market restraints that are based on the SWOT analysis. A large scale Neuromorphic Computing Market report is a comprehensive study about the market which tells about the market status in the forecast period of 2021-2027.
All viewpoints in the report are based on iterative validation by engaging influencer, experts of the market, whose opinions supersede all other research methodologies. Both primary and secondary approach are used and detailed product portfolio / service offering were analysed and have been presented in a separate chapter of competitive landscape along with company profile.
Detailed Insights on Market Concentration Rate:
CR4, CR8 and HHI Index Analysis of Overall Market
Comparative Market Share Analysis (Y-o-Y)
Emerging Players – Heat Map Analysis
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Table of Contents
1 Market Overview
1.1 Global Neuromorphic Computing Introduction
1.2 Market Analysis by Type
1.3 Market Analysis by Applications
1.4 Market Analysis by Regions
1.5 Market Dynamics
1.5.1 Market Opportunities
1.5.2 Market Risk
1.5.3 Market Driving Force
2 Manufacturers Profiles
2.1.1 Business Overview
2.1.2 Neuromorphic Computing Type and Applications
2.1.3 Neuromorphic Computing Sales, Price, Revenue, Gross Margin and Market Share (2021-2027)
3 Global Neuromorphic Computing Market Competition, by Manufacturer
4 Global Neuromorphic Computing Market Analysis by Regions
5 Region 1, Type, Application and Manufacturers
10 Global Neuromorphic Computing Market Segment by Type
11 Neuromorphic Computing Market Segment by Application
12 Neuromorphic Computing Market Forecast (2021-2027)
13 Sales Channel, Distributors, Traders and Dealers
14 Research Findings and Conclusion
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