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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 TMR 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
  • Europe
  • 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 TMR 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 TMR 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 TMR helps you break down the complex scenario and bring resiliency in uncertain times.

The report sheds light on various aspects and answers pertinent questions on the market. Some of the important ones are:

1. What can be the best investment choices for venturing into new product and service lines?

2. What value propositions should businesses aim at while making new research and development funding?

3. Which regulations will be most helpful for stakeholders to boost their supply chain network?

4. Which regions might see the demand maturing in certain segments in near future?

5. What are the some of the best cost optimization strategies with vendors that some well-entrenched players have gained success with?

6. Which are the key perspectives that the C-suite are leveraging to move businesses to new growth trajectory?

7. Which government regulations might challenge the status of key regional markets?

8. How will the emerging political and economic scenario affect opportunities in key growth areas?

9. What are some of the value-grab opportunities in various segments?

10. What will be the barrier to entry for new players in the market?

Note: Although care has been taken to maintain the highest levels of accuracy in TMR’s reports, recent market/vendor-specific changes may take time to reflect in the analysis.

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Neuromorphic Computing Market

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