Neuromorphic Chip Market Size was valued at USD 44.77 Million in 2023 and is expected to reach USD 2734.8 Million by 2031 and grow at a CAGR of 67.2% over the forecast period 2024-2031.
A neuromorphic chip, an application-specific integrated circuit (ASIC) microchip, is crafted to replicate the functionalities of the human nervous system and brain. This involves leveraging software solutions and very-large-scale-integrated (VLSI) systems to emulate human cognition and perception. Enhanced with artificial synapses and neurons, fabricated using silicon, these chips facilitate processing akin to the human brain's capabilities. Increasingly, neuromorphic chips are being integrated with AI and machine learning systems to enhance data processing and decision-making. The burgeoning neuromorphic chip market is fueled by its capacity to mimic the processing prowess of the human brain, offering efficient, low-power, and real-time data processing capabilities prized in diverse industries. The fundamental objective of neuromorphic chips is to augment the efficiency of AI systems, particularly in resource-constrained settings, by harnessing the energy-efficient principles of the human brain.
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KEY DRIVERS:
It is usually focused on either fast computation or low power.
Better-performing integrated circuits, increased demand for artificial intelligence and machine learning, and an increase in the number of cross-industry alliances and collaborations.
The progression of integrated circuits and semiconductor technology has resulted in enhanced ICs that can manage increasingly intricate computational tasks. This enhancement in performance has sparked a surge in the demand for AI and ML technologies across diverse sectors, including healthcare, finance, automotive, and manufacturing. AI and ML applications often necessitate substantial computational capabilities to efficiently process extensive datasets and train intricate models. Furthermore, the widespread adoption of AI and ML has spurred a rise in collaborative efforts and partnerships spanning multiple industries. Companies are joining forces to capitalize on each other's expertise and resources, facilitating innovation acceleration and the resolution of shared challenges. These partnerships may entail technology firms collaborating with sector-specific enterprises to develop AI-driven solutions tailored to specific use cases or industries, thus propelling further progress in AI and ML technologies. In essence, the combination of improved integrated circuits, escalating demand for AI and ML, and increased collaboration among industry stakeholders is reshaping the Chip landscape and fostering innovation across various sectors.
RESTRAINTS:
While neuromorphic chips show great potential across various applications, they are still in the developmental stage, encountering several significant hurdles before achieving widespread adoption. These challenges revolve around intricate issues in design, fabrication, and software tools. Designing neuromorphic chips involves complex processes aimed at emulating the functions of the human brain, while achieving precision in fabrication poses technical challenges. Moreover, the development of specialized software tools is crucial to enhance performance and compatibility with existing systems. Addressing these challenges is paramount to ensure the reliability and scalability of neuromorphic chip technology for broader acceptance. Additionally, the considerable cost associated with neuromorphic chip development and manufacturing presents a notable barrier to accessibility, mainly due to the intricacies of design, specialized equipment requirements, and limited production scale. Efforts to mitigate these cost barriers, such as increased research investment and economies of scale in manufacturing, are indispensable for improving affordability and accessibility. Furthermore, the dynamic ecosystem surrounding neuromorphic chips presents integration challenges, including a scarcity of specialized software tools and expertise among application specialists. To bolster and expand the neuromorphic chip ecosystem, fostering collaboration, investing in education and training initiatives, and promoting interdisciplinary research endeavors are crucial steps. Successfully overcoming these challenges has the potential to unlock breakthroughs in fields such as artificial intelligence, robotics, and neuroscience.Top of Form
OPPORTUNITIES:
Adoption of speech recognition or biometric recognition.
The integration of speech recognition or biometric recognition technologies entails incorporating systems capable of precisely identifying and understanding spoken language or distinctive physical characteristics across a wide array of applications. Speech recognition technology empowers devices to comprehend human speech, transforming it into text or commands, thus facilitating its utilization in virtual assistants, dictation software, customer service systems, and smart home devices, ultimately enhancing user interaction and operational efficiency. Conversely, biometric recognition verifies and authenticates individuals based on biological traits like fingerprints, irises, faces, or voices, ensuring heightened security and precision in access control, identity verification, and law enforcement applications. Fueled by advancements in machine learning and computational capabilities, these technologies are progressively integrated into various sectors such as healthcare, finance, government, and retail, aiming to augment user experiences, fortify security measures, and streamline operational processes. Nevertheless, the prevalence of ethical and privacy concerns regarding the handling of sensitive biometric data underscores the imperative for cautious deliberation in their widespread adoption.
CHALLENGES:
As artificial intelligence (AI) capabilities advance, ethical issues concerning bias, fairness, and responsible development practices become increasingly relevant. Neuromorphic chips, with their capacity to replicate human-like cognitive processes, introduce ethical concerns regarding data privacy, algorithmic transparency, and societal impact. Developers must ensure that applications powered by neuromorphic chips adhere to ethical principles, fostering fairness, accountability, and transparency. Addressing these ethical considerations necessitates interdisciplinary collaboration among technologists, ethicists, policymakers, and stakeholders to establish guidelines, regulations, and best practices that prioritize the ethical and responsible utilization of neuromorphic chip technology. By integrating ethical considerations into the design, development, and implementation of neuromorphic chip-based systems, we can harness the transformative potential of this technology while mitigating potential risks and societal harms.
The COVID-19 epidemic has had an impact on the global neuromorphic computing market in a variety of verticals. Neuromorphic chips were first used in medical equipment in the year 2020. Watson, an analytical tool created by IBM Corp. (US), is designed to be linked with neuromorphic circuits and used for medical imaging analytics. Watson is a human-like analytical system. As a result, the medical industry's market is expected to grow. As a result of the pandemic, work from home (WFH) has become the new trend, increasing supply and demand for IT peripherals and propelling the neuromorphic computing market in the IT & telecommunications sector forward.
IMPACT OF RUSSIAN UKRAINE WAR
The Russia-Ukraine crisis has reverberated across various sectors, including electronics and semiconductors, indirectly impacting the neuromorphic chip market. Neuromorphic chips, which emulate the neural structures of the human brain, are driving advancements in AI and machine learning, addressing issues such as high-power consumption and inefficiency in traditional computing architectures. Particularly, these chips find increasing application in the automotive industry, notably in autonomous driving technologies, for their efficiency in classification tasks and performance in noisy environments. Companies like Intel and Brain Chip are actively developing neuromorphic chips for diverse applications, driven by their capacity to efficiently handle data-intensive tasks with lower power consumption.
However, the Russia-Ukraine conflict has introduced uncertainties and potential disruptions to the global semiconductor supply chain, indirectly impacting the development and deployment of neuromorphic chips. Geopolitical actions, such as the EU's restrictions on chip exports to Russia in response to the crisis, could have ripple effects on the semiconductor industry as a whole. While specific reports on the direct impact of the crisis on the neuromorphic chip market are scarce, it's evident that broader challenges faced by the semiconductor industry, exacerbated by geopolitical tensions, could influence the trajectory of neuromorphic chip development, production, and adoption. Nonetheless, ongoing innovations and partnerships in the field underscore its resilience and growth potential amidst these challenges.
IMPACT OF ECONOMIC SLOWDOWN
Amidst the ongoing global economic slowdown, industries, including the neuromorphic chip market, experience diverse impacts, though specific details regarding its direct correlation remain elusive. Nonetheless, insights into general trends within the neuromorphic chip sector shed light on its response to prevailing economic conditions. Notably, the market demonstrates significant growth driven by rising demand for artificial intelligence-based microchips and the integration of neuroplasticity with electronics. Collaborations and advancements, such as Edge Impulse's enterprise-grade machine learning algorithms and SynSense's partnership with BMW for smart cockpit integration, underscore the market's dynamism and potential for innovation. Furthermore, robust competition among major players like IBM Corporation, Intel Corporation, and Qualcomm Incorporated intensifies, with a focus on new product developments and strategic alliances. Regionally, North America leads, buoyed by its strong presence across aerospace, defense, IT, and telecommunication sectors, while Europe and the Asia-Pacific region witness notable growth, particularly in France and China. Despite challenges posed by reduced investment and cautious R&D spending, persistent demand for AI and ML applications, alongside advancements in energy-efficient computing solutions, may mitigate these impacts. The market's emphasis on innovation and efficiency, combined with its diverse applications across industries, positions it well to navigate the complexities of the global economic landscape.
BY COMPONENTS
Software
Hardware
The Neuromorphic Chip market comprises two sub-segments: Hardware and Software. In 2023, the Software segment dominated with the largest market share. The push for miniaturization in integrated circuits is propelled by consumer demand for smaller, more cost-effective products. Industries such as smartphones, healthcare, and automotive extensively employ smart sensors and emergency smart technology. Consequently, recent years have witnessed a rise in the complexity of hardware design due to advancements in miniaturization technologies.
BY APPLICATION
Signal Recognition
Image Recognition
Data Mining
BY VERTICAL
Aerospace & Defense
Automotive
Industrial
It & Telecom
Medical
Others
In 2023, the Automotive segment secured the leading market share. Top-tier automotive manufacturers are making substantial investments to attain Level 5 autonomy in self-driving vehicles, leading to a surge in demand for artificial intelligence neuromorphic chips. To meet the stringent requirements of high throughput and low power consumption in the autonomous driving market, continuous enhancements in AI algorithms are essential. Neuromorphic circuits excel in classification tasks and offer versatility across various autonomous driving scenarios. Moreover, they demonstrate superior efficiency in noisy environments, such as self-driving cars, compared to conventional static deep learning methods.
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North America emerged as the frontrunner in the global market, and this dominance is anticipated to persist in the forthcoming forecast period. Meanwhile, the Asia-Pacific region is poised to exhibit the swiftest growth in the Neuromorphic Chip Market. The surge in adoption of neuromorphic Chip for security purposes is anticipated to propel market growth within this region. North America is projected to retain the lion's share of the global neuromorphic Chip market. This dominance is underpinned by widespread recognition of the benefits of neuromorphic Chip across key industries such as aerospace, military & defense, and medical. In North America, the United States leads the charge, leveraging artificial intelligence across sectors like medical and automotive for applications such as machine learning, natural language processing (NLP), image processing, and speech recognition. Conversely, the Asia-Pacific region is anticipated to capture the second-largest market share and exhibit the most rapid compound annual growth rate (CAGR). Within the APAC market, China, Japan, and South Korea are poised to be the primary contributors. Notably, China stands out as the predominant AI market in APAC, closely followed by Japan, thus positioning China as a promising market for neuromorphic Chip applications in machine learning and natural language processing.
REGIONAL COVERAGE:
North America
US
Canada
Mexico
Europe
Eastern Europe
Poland
Romania
Hungary
Turkey
Rest of Eastern Europe
Western Europe
Germany
France
UK
Italy
Spain
Netherlands
Switzerland
Austria
Rest of Western Europe
Asia Pacific
China
India
Japan
South Korea
Vietnam
Singapore
Australia
Rest of Asia Pacific
Middle East & Africa
Middle East
UAE
Egypt
Saudi Arabia
Qatar
Rest of the Middle East
Africa
Nigeria
South Africa
Rest of Africa
Latin America
Brazil
Argentina
Colombia
Rest of Latin America
REGIONAL ANALYSES
The key players in the neuromorphic chip market are Hewlett Packard Enterprise, Intel Corp., Brain chip Holdings Ltd., IBM, Innatera, Koniku, Samsung Electronics Limited, General Vision Inc., Qualcomm, Nepes Corp, Ceryx Medical & Other Players.
Samsung Electronics Limited-Company Financial Analysis
RECENT DEVELOPMENT
In April 2022: Accenture and the Indian Institute of Science (IISc) Bengaluru initiated a partnership to conduct research and development (R&D) in cloud continuum and neuromorphic Chip at the Accenture Centre for Advanced Chip in India. This collaboration entails joint research projects and the co-development of intellectual properties and cutting-edge Chip technologies. These advancements encompass AI at the edge, spanning cloud, edge, quantum, and neuromorphic Chip, along with sustainable software engineering initiatives.
| Report Attributes | Details |
|---|---|
| Market Size in 2023 | US$ 44.77 Million |
| Market Size by 2031 | US$ 2734.8 Million |
| CAGR | CAGR of 67.2% From 2024 to 2031 |
| Base Year | 2023 |
| Forecast Period | 2024-2031 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Components (Software, Hardware) • By Application (Signal Recognition, Image Recognition, Data Mining) • By Vertical (Aerospace & Defense, Automotive, Industrial, IT & Telecom, Medical, Others) |
| Regional Analysis/Coverage | North America (US, Canada, Mexico), Europe (Eastern Europe [Poland, Romania, Hungary, Turkey, Rest of Eastern Europe] Western Europe] Germany, France, UK, Italy, Spain, Netherlands, Switzerland, Austria, Rest of Western Europe]), Asia Pacific (China, India, Japan, South Korea, Vietnam, Singapore, Australia, Rest of Asia Pacific), Middle East & Africa (Middle East [UAE, Egypt, Saudi Arabia, Qatar, Rest of Middle East], Africa [Nigeria, South Africa, Rest of Africa], Latin America (Brazil, Argentina, Colombia, Rest of Latin America) |
| Company Profiles | Hewlett Packard Enterprise, Intel Corp., Brain chip Holdings Ltd., IBM, Innatera, Koniku, Samsung Electronics Limited, General Vision Inc., Qualcomm, Nepes Corp. and Ceryx Medical. |
| Key Drivers | • It is usually focused on either fast computation or low power. • Better-performing integrated circuits, increased demand for artificial intelligence and machine learning, and an increase in the number of cross-industry alliances and collaborations. |
| Restraints | • Technological immaturity regarding neuromorphic chip technology. |
The Neuromorphic Chip Market was valued at USD 44.77 Million in 2023.
The expected CAGR of the global Neuromorphic Chip Market during the forecast period is 67.2%.
The Asia Pacific region is anticipated to record the Fastest Growing in the Neuromorphic Chip Market.
The Automotive segment is leading in the market revenue share in 2023.
The North America region with the Highest Revenue share in 2023.
TABLE OF CONTENTS
1. Introduction
1.1 Market Definition
1.2 Scope
1.3 Research Assumptions
2. Industry Flowchart
3. Research Methodology
4. Market Dynamics
4.1 Drivers
4.2 Restraints
4.3 Opportunities
4.4 Challenges
5. Impact Analysis
5.1 Impact of Russia-Ukraine Crisis
5.2 Impact of Economic Slowdown on Major Countries
5.2.1 Introduction
5.2.2 United States
5.2.3 Canada
5.2.4 Germany
5.2.5 France
5.2.6 UK
5.2.7 China
5.2.8 Japan
5.2.9 South Korea
5.2.10 India
6. Value Chain Analysis
7. Porter’s 5 Forces Model
8. Pest Analysis
9. Neuromorphic Chip Market, By Component
9.1 Introduction
9.2 Trend Analysis
9.3 Software
9.4 Hardware
10. Neuromorphic Chip Market, By Application
10.1 Introduction
10.2 Trend Analysis
10.3 Signal Recognition
10.4 Image Recognition
10. 5 Data Mining
11. Neuromorphic Chip Market, By Vertical
11.1 Introduction
11.2 Trend Analysis
11.3 Aerospace & Defense
11.4 Automotive
11.5 Industrial
11.6 It & Telecom
11.7 Medical
11.8 Others
12. Regional Analysis
12.1 Introduction
12.2 North America
12.2.1 USA
12.2.2 Canada
12.2.3 Mexico
12.3 Europe
12.3.1 Eastern Europe
12.3.1.1 Poland
12.3.1.2 Romania
12.3.1.3 Hungary
12.3.1.4 Turkey
12.3.1.5 Rest of Eastern Europe
12.3.2 Western Europe
12.3.2.1 Germany
12.3.2.2 France
12.3.2.3 UK
12.3.2.4 Italy
12.3.2.5 Spain
12.3.2.6 Netherlands
12.3.2.7 Switzerland
12.3.2.8 Austria
12.3.2.9 Rest of Western Europe
12.4 Asia-Pacific
12.4.1 China
12.4.2 India
12.4.3 Japan
12.4.4 South Korea
12.4.5 Vietnam
12.4.6 Singapore
12.4.7 Australia
12.4.8 Rest of Asia Pacific
12.5 The Middle East & Africa
12.5.1 Middle East
12.5.1.1 UAE
12.5.1.2 Egypt
12.5.1.3 Saudi Arabia
12.5.1.4 Qatar
12.5.1.5 Rest of the Middle East
11.5.2 Africa
12.5.2.1 Nigeria
12.5.2.2 South Africa
12.5.2.3 Rest of Africa
12.6 Latin America
12.6.1 Brazil
12.6.2 Argentina
12.6.3 Colombia
12.6.4 Rest of Latin America
13. Company Profiles
13.1 Hewlett Packard Enterprise
13.1.1 Company Overview
13.1.2 Financial
13.1.3 Products/ Services Offered
13.1.4 SWOT Analysis
13.1.5 The SNS View
13.2 Intel Corp
13.2.1 Company Overview
13.2.2 Financial
13.2.3 Products/ Services Offered
13.2.4 SWOT Analysis
13.2.5 The SNS View
13.3 Brain chip Holdings Ltd
13.3.1 Company Overview
13.3.2 Financial
13.3.3 Products/ Services Offered
13.3.4 SWOT Analysis
13.3.5 The SNS View
13.4 IBM
13.4.1 Company Overview
13.4.2 Financial
13.4.3 Products/ Services Offered
13.4.4 SWOT Analysis
13.4.5 The SNS View
13.5 Innatera
13.5.1 Company Overview
13.5.2 Financial
13.5.3 Products/ Services Offered
13.5.4 SWOT Analysis
13.5.5 The SNS View
13.6 Koniku
13.6.1 Company Overview
13.6.2 Financial
13.6.3 Products/ Services Offered
13.6.4 SWOT Analysis
13.6.5 The SNS View
13.7 Samsung Electronics Limited
13.7.1 Company Overview
13.7.2 Financial
13.7.3 Products/ Services Offered
13.7.4 SWOT Analysis
13.7.5 The SNS View
13.8 General Vision Inc.
13.8.1 Company Overview
13.8.2 Financial
13.8.3 Products/ Services Offered
13.8.4 SWOT Analysis
13.8.5 The SNS View
13.9 Qualcomm
13.9.1 Company Overview
13.9.2 Financial
13.9.3 Products/ Services Offered
13.9.4 SWOT Analysis
13.9.5 The SNS View
13.10 Nepes Corp
13.10.1 Company Overview
13.10.2 Financial
13.10.3 Products/ Services Offered
13.10.4 SWOT Analysis
13.10.5 The SNS View
13.11 Ceryx Medical.
13.11.1 Company Overview
13.11.2 Financial
13.11.3 Products/ Services Offered
13.11.4 SWOT Analysis
13.11.5 The SNS View
14. Competitive Landscape
14.1 Competitive Benchmarking
14.2 Market Share Analysis
14.3 Recent Developments
14.3.1 Industry News
14.3.2 Company News
14.3.3 Mergers & Acquisitions
15. Use Case and Best Practices
16. Conclusion
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