Neuromorphic Computing Market Size, Share & Trends Analysis Report By Application (Signal Processing, Image Processing, Data Processing, Object Detection) By End Use, By Region, And Segment Forecasts, 2020 - 2024

Industry Insights

The global neuromorphic computing market size was valued at USD 1.49 billion in 2016, expanding at a CAGR of 20.2% over the forecast period. Increasing demand for artificial intelligence for language processing, translation and chatterbots, nonlinear controls and robotics, and computer vision and image processing, among others is expected to drive market growth.

Rise in the number of applications in the area of automation has presented the industry with several growth opportunities. However, lack of R&D and substantial investments in the industry are anticipated to challenge market growth. Furthermore, high complexity involved in designing these chips, owing to complex algorithms and software compatibility issues of neural processing units, is projected to challenge the industry. Steady replacement of the Von Neumann architecture by neuromorphic chips is acting as another driver propelling market growth. Besides, these chips offer benefits such as low power consumption, higher speed, and optimum memory usage. Growing demand for brain-like computing across various industrial verticals is also substantially energizing prospects for industry growth.

The emerging trend of combining neuroscience computation and embodied models has led to an upsurge in demand for design and development of neuromorphic chips for brain-based robots and cognitive robots. Rising need for machine learning tools has further contributed to industry expansion.

Neuromorphic Computing Market Trends

Artificial intelligence (AI) is gaining traction and is further expected to penetrate a range of verticals such as automotive, banking and finance, law, retail, agriculture, among others. This is due to the self-learning capabilities of the machine learning and deep learning software running on the AI systems. An artificial intelligence (AI) system mainly comprises of three major components; hardware that includes computer and memory, software, and data.

The traditional architecture based on von Neumann includes central processing unit (CPU) optimization through memory improvements, additional of chips, field-programmable gate arrays (FPGAs) and even application-specific integrated circuits (ASICs). This is avoidable if an entirely new architecture, one that is inspired by brain, known as neuromorphic computing. The neuromorphic computing involves neural processing units (NPUs) and spiking neural networks (SNNs) and analog circuits along with spike trains.

The neuromorphic chips have a parallel architecture and are designed to process information in the very same way that a human brain does. This helps achieve the platform that artificial intelligence (AI) seeks in order to process information using machine-learning software. The demand for AI services across a range of verticals that require high computational power with high efficiency can be met using the neuromorphic chips.

Neuromorphic chips will be able to resolve a range of machine learning issues such as classification, clustering, robotics, and combinatorics. For instance, in the banking, finance, and law sector huge amount of data is generated that requires classification and clustering in real-time. This requires high computing power whereas using the traditional architecture involves frequent exchange of information back-and-forth between the CPU and memory unit resulting in low efficiency as it consumes too much energy. The problem can be resolved using the neuromorphic computing as the parallel architecture eradicates the need of exchange of information thereby resulting in high efficiency even at low computation power.

Space missions require high-performance, reliable computing platforms that meet size, weight, and power constraints and can function in challenging environmental and operational conditions, including extreme temperature, high radiation, power loss, and disrupted communications

Application Insights

On the basis of application, the market can be segmented into signal processing, object detection, image processing, data processing, and others. The image processing application segment dominated the market and accounted for over 41.0% of the overall market revenue in 2016. The segment is anticipated to remain dominant throughout the forecast period and witness the fastest growth rate over the coming years. This growth can be attributed to rise in demand for digital cameras and other imaging systems.

The signal processing application segment accounted for more than 30.0% of the total revenue in 2016. The segment is predicted to grow considerably in the coming years, owing to growing demand for processing audio and acoustics signals.

End-use Insights

On the basis of end use, the neuromorphic computing market can be bifurcated into consumer electronics, automotive, healthcare, military and defense, and others. The consumer electronics end-use segment acquired the largest market share of over 60.0% in 2016 and is predicted to continue its dominance over the forecast period.

The automotive end-use segment is expected to witness high demand, due to increasing demand for autonomous cars and smart vehicles. The military and defense segment is also anticipated to gain considerable traction by 2024, owing to accelerating demand for neuromorphic chips in satellites for aerial imagery and surveillance.

Regional Insights

The North America market acquired more than 33.0% of the total market in 2016. This is primarily due to the presence of key neuromorphic chip manufacturers in the region. The global industry is expected to gain momentum in Asia Pacific and South America due to growing demand for automation in emerging nations such as China, India, and Brazil.

The European region is anticipated to offer significant opportunities for industry expansion as significant investments are being made in neuromorphic projects and related R&D activities. In addition, increasing efforts made by prominent universities, such as the University of Manchester and Heidelberg University, in research activities centered on neuromorphic computing are remarkably contributing to industry growth in Europe.

Early adopters in the North American market, such as the U.S. and Canada, are the frontiers of neuromorphic computing system applications. Voice & speech recognition using AI is one of the most significant trends witnessed in the region. For instance, a U.S.-based AI company, Globalme Localization Inc., delivered the accent and dialect audio collection to Sonos Inc., the U.S.-based audio company. Sonos Inc. unified its wireless speakers with smart home assistants by collecting speech and accents data across three countries. The integration facilitated fine-tuning its speech recognition engines to provide a better voice experience.

Asia Pacific region is projected to experience the highest growth throughout the forecast period. The growth is attributable to the rapidly increasing consumption of smart electronic equipment, swift technological advancements, and the increasing prominence of social networking in developing economies, such as India and China. The increasing number of smart devices boosts the requirement of data and signal processing systems. The surging applications of face recollection in surveillance and security systems in China are estimated to fuel market growth in the region.

Key Companies & Market Share Insights

Key industry participants include IBM Corporation; Hewlett-Packard; Samsung Electronics Co. Ltd.; Intel Corporation; Qualcomm Inc.; Brain Corporation; General Vision Inc.; HRL Laboratories; Vicarious; CEA-Leti, Knowm Inc.; and Numenta.

Industry vendors are increasingly leveraging effective marketing strategies for the commercialization of these chips, which will subsequently help companies penetrate newer markets and capture a significant share in the industry.

Neuromorphic Computing Market Report Scope

Segments Covered in the Report

This report forecasts revenue growth at global, regional, and country levels and provides an analysis of the latest industry trends in each of the sub-segments from 2016 to 2024. For the purpose of this study, Grand View Research has segmented the global neuromorphic computing market report based on application, end use, and region:

• Application Outlook (Revenue, USD Million, 2016 - 2024)

  • Signal Processing

  • Image Processing

  • Data Processing

  • Object Detection

  • Others

• End-use Outlook (Revenue, USD Million, 2016 - 2024)

  • Consumer Electronics

  • Automotive

  • Healthcare

  • Military & Defense

  • Others

• Regional Outlook (Revenue, USD Million, 2016 - 2024)

  • North America

    • The U.S.

    • Canada

    • Mexico

  • Europe

    • The U.K.

    • Germany

    • France

  • Asia Pacific

    • China

    • India

    • Japan

  • South America

    • Brazil

  • MEA