Neuromorphic Computing Market Size, Share and Trends Analysis, By Component (Hardware and Software), Type, By Application, By End-Use (Aerospace & Defense, Automotive, Consumer Electronics, Healthcare, Industrial, and Others), and By Region, Forecast 2024-2031

Global Neuromorphic Computing Market Overview and Key Insights:

The global neuromorphic computing market size reached USD 78.5 Million in 2023 and is expected to register a revenue CAGR of 50.2% during the forecast period. Neuromorphic computing is a computing technique that replicates how the human brain functions. It requires creating hardware and software that imitate the neuronal and synaptic structures and functions that the brain uses to process information.

Market Drivers:

Growing demand for AI based microchips is a key driver of revenue growth in the global Neuromorphic Computing market. Neuromorphic computing has enormous potential: it could lead to increased automation and smarter systems in industries ranging from manufacturing to services. Neuromorphic computing, for example, allows robots to interpret sensory information more quickly, boosting their capacity to navigate and interact in complicated situations. It might be utilized for industrial inspection and exploration jobs in areas inaccessible to humans. Furthermore, neuromorphic systems are enhancing computer vision skills, allowing machines to analyse and comprehend images and videos more quickly.

Furthermore, technological advancements for Neuromorphic Computing sector are also another key driver driving the market growth. On April 2024, Intel announced that it had created the world’s largest neuromorphic system. This large-scale neuromorphic system, code-named Hala Point, was initially deployed at Sandia National Laboratories and uses Intel’s Loihi 2 processor. It aims to support research for future brain-inspired artificial intelligence (AI) and addresses challenges related to the efficiency and sustainability of today’s AI.

Market Opportunity:

Rise in the adoption of Neuromorphic Computing in the industrial sector acts as an opportunity for the global Neuromorphic Computing market. Neuromorphic computing, inspired by the design of the human brain, is emerging as a transformative technology with far-reaching implications for manufacturing automation. Using neuromorphic computing, predictive maintenance is improved by analysing equipment data to identify patterns that flag probable breakdowns. This proactive practice reduces downtime and extends the life of machines by resolving issues before they escalate. Neuromorphic systems’ adaptive learning characteristics make them useful for optimizing supply chain procedures. These technologies can assess and forecast demand variations, streamline logistics, and improve supply chain efficiency. On October 2024, Mercedes-Benz has established a partnership with the Ontario Vehicle Innovation Network (OVIN), the province’s flagship automotive and mobility project. The goal is to enhance startup creation and scouting efforts in North America while also promoting the commercialization of automotive innovation. Separately, the company wants to begin a research relationship with the University of Waterloo in Ontario, focusing on neuromorphic computing for automated driving applications. This move complements Mercedes-Benz’s ongoing R&D initiatives in Canada.

Recent Trends:

Recent trends include the demand for edge computing, expanding applications in consumer electronics and IoT, and advancements in neuromorphic chips.

Adoption of electric vehicles is a recent trend in Neuromorphic Computing market. Artificial Intelligence is anticipated to contribute USD 15.7 trillion to the global economy by 2030, with neuromorphic computing contributing significantly to this development. To process millions of requests every day, digital assistants such as Siri and Google Assistant require huge, energy-intensive data centres. As a result, devices require a persistent network connection to use these services. Neural networks that use neuromorphic computation can also be more effective in pattern recognition and other types of connectionism. Because the chips provide faster speeds and lower latency, AI can have a greater learning capacity when addressing issues, resulting in more accurate results.

On October 2024, BrainChip, a specialist in edge artificial intelligence (edge AI), has launched the Akida Pico, the latest addition to its Akida line of brain-inspired neuromorphic processors. Like its predecessors, it employs neuromorphic processing technology inspired by the human brain to efficiently handle selected machine learning and artificial intelligence workloads; however, unlike its predecessors, the Akida Pico has been designed to consume the least amount of power while still providing adequate compute performance.

Restraints & Challenges:

Lack of benchmarks and standards pose a significant hurdle to the implementation of neuromorphic computing. There aren’t many standards for neuromorphic computing in terms of architecture, hardware, or software. Neuromorphic systems lack explicitly defined and established benchmarks, sample datasets, testing tasks, and metrics, making it difficult to measure performance and demonstrate efficacy. Furthermore, neuromorphic computing is a multidisciplinary field that draws on biology, computer science, electronics engineering, mathematics, neuroscience, and physics. This makes it difficult to understand outside of an academic lab that specializes in neuromorphic research.

Component Segment Insights and Analysis:

Based on the component, the neuromorphic computing market is segmented into hardware and software.

Hardware segment contributed largest share and highest revenue growth in 2023. Neuromorphic hardware duplicates the structure and function of the brain, allowing for highly efficient, low-power computing. It uses memristors to simulate synaptic connections and spiking neural networks to model neuron communication. They use analog computation and event-driven processing, making them suited for real-time activities such as robotics, with adaptability provided via spike-timing-dependent plasticity (STDP) learning. Notably, neuromorphic technology has high power efficiency, making it perfect for battery-powered devices.

On June 2023, SynSense, the world’s leading commercial producer of ultra-low-power neuromorphic hardware and application solutions, has announced the availability of the Speck Demo Kit. This little development module allows users to rapidly and easily deploy and evaluate their event-based neuromorphic vision apps. The kit includes SynSense’s Speck dynamic vision module, an ultra-low-power Bluetooth controller chip, and regularly used peripherals. The Demo Kit is a reduced embedded hardware platform that allows users to test and verify neuromorphic application models while also creating prototypes.

Software segment is expected to have a significant share throughout the forecasted period. Neuromorphic software is made up of algorithms and models that function more like biological brains than standard computer systems, which use the von Neumann paradigm. Spiking neural networks are an example of neuromorphic software. On October 2024, Opteran, a natural intelligence business, said that Airbus Defence and Space, with cooperation from the European Space Agency (ESA) and the United Kingdom Space Agency, will test Opteran Mind, its general-purpose neuromorphic software, in Airbus space rovers. Opteran has reverse engineered natural brain mechanisms into a software mind, allowing autonomous machines to navigate even the most difficult surroundings without the need for considerable data or training.

Application Segment Insights and Analysis:

Based on the application, the neuromorphic computing market is segmented into image recognition, signal recognition, data mining, process optimization, and others.

Process Optimization segment contributed largest share in 2023. Constrained optimization looks for the values of input variables that minimize or maximize a particular objective function while keeping the variables under constraints. This type of difficulty is common throughout scientific disciplines and industry. Constrained optimization is a promising application for neuromorphic computing because it closely resembles the dynamics of spiking neural networks. Implemented on massively parallel neuromorphic hardware, such a spiking neural network may analyse conflicts and cost functions involving several variables at the same time, updating all variables accordingly. This enables for speedy convergence to an ideal state. Furthermore, the fine-scale timing dynamics of SNNs enable them to easily escape local minima.

For instance, on September 2021, Intel launched Loihi 2, its second-generation neuromorphic research chip, as well as Lava, an open-source software platform for creating neuro-inspired applications. Their unveiling demonstrates Intel’s continuous advancement in neuromorphic technology. Loihi 2 overcomes a practical constraint of Loihi by providing faster, more flexible, and standard input/output interfaces. Loihi 2 chips will offer Ethernet connections, glueless integration with a broader range of event-based vision sensors, and larger Loihi 2 chip mesh networks.

Data Mining segment accounted for the fastest growth rate during the forecasted period. Simulating neural networks enables neuromorphic devices to provide simultaneous data analysis, energy efficiency, and error resistance. Neuromorphic computing, which mimics the human brain’s neural structures and operational methods, has the potential to alter the fields of robotics and autonomous systems. Neuromorphic systems enable high energy efficiency, real-time computing, and adaptive learning by incorporating brain-inspired techniques like as spike-based communication, synaptic plasticity, and event-driven processing. The robotics community has mostly focused on certain research areas such as sensing, perception, sensor fusion, data analysis, state estimation, localization, simultaneous localization and mapping (SLAM), and the use of AI to solve various image processing problems.

End-Use Segment Insights and Analysis:

Based on the end-Use, the neuromorphic computing market is segmented into aerospace & defense, automotive, consumer electronics, healthcare, industrial, and others.

Consumer electronics segment contributed largest share in 2023. AI technology has led to a shift in consumer electronics towards data-driven applications. Neuromorphic computing is emerging as the next-generation technology for consumer devices, meeting the demand for high memory capacity, quick processing speed, and sophisticated data computation. Neuromorphic computing technologies, inspired by the human brain, can manage large amounts of unstructured data and serve as AI accelerators in consumer devices like smartphones, laptops, and desktops. Neuromorphic computing technologies offer parallel, efficient, and scalable computational solutions with significant implications for smart manufacturing, grids, homes, and cities, impacting consumers’ daily lives.

On June 2024, Innatera, the leading inventor in ultra-low power neuromorphic computers, revealed that its Series A investment round was oversubscribed, resulting in an impressive influx of capital reaching USD 21 million. Investors Innavest and InvestNL led the Series A extension, which also included existing Series A investors EIC Fund, MIG Capital, Matterwave Ventures, and Delft Enterprises. Innatera demonstrated their neuromorphic solutions for wearables, smart home, and consumer electronics applications.

Automotive segment accounted for the fastest growth rate during the forecasted period. The public’s acceptance of semi-autonomous and even completely autonomous vehicles is getting closer than ever before as image processing and object recognition technologies continue to advance in speed and accuracy. Autonomous vehicles can make judgments almost instantly due to neuromorphic computers, which drastically cut down on latency—the delay that occurs when data is transmitted to and from the cloud. On May 2024, IBM and Honda Motor Co., Ltd. announced the signing of a Memorandum of Understanding (MOU) outlining their intent to collaborate on long-term joint research and development of next-generation computing technologies required to overcome challenges related to processing capability, power consumption, and design complexity for the realization of future software-defined vehicles (SDVs). The MOU, in particular, highlights prospective cooperation research topics in specialized semiconductor technologies such as brain-inspired computing and chiplet technologies, with the goal of drastically improving processing performance while reducing power consumption.

Geographical Outlook:

North America is registered highest market share in neuromorphic computing market in 2023. The regional market is driven by significant technological infrastructure and advancement in AI technologies. Furthermore, collaborations and innovations by market players Neuromorphic Computing sector is further augmenting the growth of the market. On February 2023, Prophesee has announced a collaboration with Qualcomm Technologies, Inc. to improve Prophesee’s Event-based Metavision sensors for usage with premium Snapdragon mobile platforms, bringing the speed, efficiency, and quality of neuromorphic-enabled vision to mobile devices. The technical and business collaboration will provide mobile device developers with a quick and efficient way to take advantage of the Prophesee sensor’s ability to dramatically improve camera performance, particularly in fast-moving dynamic scenes (e.g., sports scenes) and low light, due to its groundbreaking event-based continuous and asynchronous pixel sensing approach.

U.S. is expected to have the highest market share in North America neuromorphic computing market. Growing adoption of AI, technological advancements in neuromorphic chips are primary key drivers driving the market growth. On December 2024, Brainchip Holdings Ltd., the world’s first commercial developer of neuromorphic artificial intelligence IP, announced that it has been awarded a USD1.8 million contract by the Air Force Research Laboratory (AFRL) for neuromorphic radar signal processing. This award was made through the SBIR program, which is a US federal government program that funds small enterprises’ research and development to serve government missions.

Asia Pacific is registered the fastest growth rate during the forecasted period. Asia Pacific is developing as a major region growth in Neuromorphic Computing due to the development in the AI sector and growing adoption of neuromorphic computing in various end-use industries. On June 2024, researchers from the Chinese Academy of Sciences, together with other scientists, created Speck, a low-power neuromorphic device capable of dynamic computation. This system-level chip, which combines algorithm, software, and hardware design, exemplifies the inherent benefits of ‘brain-like’ computation by combining high-level neural mechanisms. Speck combines a dynamic optical sensor with a neuromorphic chip into a single chip, resulting in exceptionally low power consumption at rest. It does visual tasks with only 0.7 milliwatts, delivering an energy-efficient, responsive, and low-power solution for AI applications.

Europe is to register a considerable market share in Neuromorphic Computing market in 2023. Increase in research and development activities and government initiatives in promoting AI research and technologies are key factors driving the region’s revenue growth. On April 2021, CEA-Leti announced the commencement of an EU initiative to create a new class of algorithms, devices, and circuits that mimic the multi-timescale processing of biological neural systems. The project’s name stands for Memory Technologies with Multi-Scale Time Constants for Neuromorphic Architectures. The findings will be used to develop neuromorphic computing systems capable of efficiently processing real-world sensory inputs and natural time-series data in real-time, as demonstrated by a working laboratory prototype.

Competition Analysis:

The neuromorphic computing market is characterized by a fragmented structure, with several players competing across various segments and regions. List of major players included in the neuromorphic computing market report are:

• IBM Corporation
• Intel Corporation
• Samsung Electronics Co. Ltd
• Applied Brain Research Inc.
• BrainChip Holdings Ltd.
• General Vision Inc.
• GrAI Matter Labs
• Hewlett Packard Enterprise Development LP
• Qualcomm Technologies Inc.
• SK HYNIX INC.
• SynSense
• HRL Laboratories, LLC
• Vicarious FPC Inc.
• Nepes Corporation

Strategic Developments in Neuromorphic Computing Market:

• In October 2024, SynSense, the world’s leading commercial supplier of ultra-low-power sensory processing hardware and application solutions, announced the successful completion of a strategic fundraising round worth tens of millions of RMB. Maxvision and RunWoo led the round. SynSense will use the cash to expedite the development of its 3D neuromorphic processor, DYNAP™-CNN2. This technological advancement will enable SynSense to extend their high-speed vision solutions to autonomous systems such as drones, robotics, and self-driving cars.
• In March 2023, TDK Corporation has announced the development of a neuromorphic element known as a “spin-memristor” with extremely low power consumption. This element, which mimics the energy-efficient operation of the human brain, has the potential to reduce the power consumption of AI applications to one-tenth that of standard devices. Working with the French research agency CEA (Alternative Energies and Atomic Energy Commission), TDK demonstrated that its “spin-memristor” can serve as the foundation of a neuromorphic device.

Key Advantages for Stakeholders:

Navistrat Analytics’ industry report provides an in-depth quantitative analysis of various market segments, historical and current trends, market forecasts, and dynamics within the global market. The historical years covered in this report are 2021 to 2022, with 2023 serving as the base year for market size calculations. The forecast period extends from 2024 to 2031.

The report includes an executive summary and a comprehensive overview of market drivers, restraints, opportunities, and challenges (DROC), along with insights into regulatory standards. It features detailed analyses such as PORTER’s Five Forces, SWOT, and PESTLE, as well as assessments of technological trends and the competitive landscape.

PORTER’s Five Forces analysis helps stakeholders evaluate the impact of new entrants, competitive rivalry, supplier power, buyer power, and substitution threats, enabling them to assess the level of competition and the attractiveness of the global market. The competitive landscape provides stakeholders with a clear understanding of the current market positions of key players, offering valuable insights into their competitive environment.

Scope And Key Highlights Of The Neuromorphic Computing Market Report:

The neuromorphic computing market report offers a detailed analysis of market size, including historical revenue (in USD Million) data for 2021-2022 and revenue forecasts for 2024-2031 across the following segments:

• Component Outlook (Revenue, USD Million; 2021-2031)
  • Hardware
  • Software

• Type Module Outlook (Revenue, USD Million; 2021-2031)
  • Spiking Neural Network (SNN) Chips
  • Analog Neuromorphic Chips
  • Digital Neuromorphic Chips
  • Memristor based Neuromorphic Chips
  • Hybrid Neuromorphic Chips

• Application Outlook (Revenue, USD Million; 2021-2031)
  • Image Recognition
  • Signal Recognition
  • Data Mining
  • Process Optimization
  • Others

• End-Use Outlook (Revenue, USD Million; 2021-2031)
  • Aerospace & Defense
  • Automotive
  • Consumer Electronics
  • Healthcare
  • Industrial
  • Others

• Regional Outlook (Revenue, USD Million; 2021-2031)
  • North America
    • U.S.
    • Canada
    • Mexico
  • Europe
    • Germany
    • France
    • U.K.
    • Italy
    • Spain
    • Benelux
    • Nordic Countries
    • Rest of Europe
  • Asia Pacific
    • China
    • India
    • Japan
    • South Korea
    • Oceania
    • ASEAN Countries
    • Rest of APAC
  • Latin America
    • Brazil
    • Rest of LATAM
  • Middle East & Africa
    • GCC Countries
    • South Africa
    • Israel
    • Turkey
    • Rest of MEA

Frequently Asked Questions (FAQ) About The Neuromorphic Computing Market Report