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Neuromorphic Computing market size was valued at USD 86.9 Million in 2023. It is expected to Reach USD 9356.4 Million by 2032 and grow at a CAGR of 68.27% over the forecast period of 2024-2032.
The growth of the market is attributed to an increase in applications for neuromorphic technology such as deep learning, transistors and accelerators, next-generation semiconductors; autonomous systems including robotics drones, self-driving cars and artificial intelligence. For instance, in August 2023 a diverse consortium of researchers completed NeuRRAM - an all-new neuromorphic chip capable to simultaneously run various AI applications with greater precision and reduced energy consumption than equivalent possibilities. The integration of neuromorphic technology, along with AI and machine learning, has the potential to bolster the processing capabilities of defence systems and deliver rapid analytical insights to facilitate timely wartime decision-making. The technology is more energy saving, which can lead to better transportability (mobility, endurance and operation time) and portable for a soldier on field. Intel Corporation plans to install a Loihi chip to enable faster sensing by processing signals of biological nature from the camera, like neuromorphic technology in drone cameras. This means that complex algorithms running on robots can work efficiently using neuromorphic computing and so improve robotic systems efficiency both in terms of performance as well energy consumption. In September 2022, Intel Corporation, the Italian Institute of Technology, and the Technical University of Munich collaborated to unveil a novel approach to object learning utilizing neural networks. This joint effort aims to streamline and speed up robots acquiring knowledge about new objects upon deployment in various work environments.
Increasing use of machine learning, AI and higher I.P. is helps to drive the growth of Neuromorphic Computing Market. Enormous improvements are seen in neuromorphic computing technology. IBM's AI chip, launched in January 2023, uses 7nm technology for enhanced energy efficiency. This popular Swiss start-up's processors can cater for anywhere up to 1,000 frames per second - making SynSense a real-time solution. In October 2023, SiLC Technologies’ Launched Eyeonic Vision System delivers distance precision beyond 1,000 meters at the millimeter level. The chips from Eindhoven University that can detect cystic fibrosis with more than 90% accuracy. Working together with Lorser Industries, Brain Chip has achieved up to a >50% improvement in processing speed and energy efficiency on software defined radios — demonstrating the incredible transformative capabilities of neuromorphic computing across industries.
Drivers
Growing Adoption of Neuromorphic Computing to Transform Internet of Things (IoT) to drive the Market Growth
The ability of neuromorphic systems to process large amounts of data quickly and efficiently supports real-time applications in autonomous vehicles, robotics, and AI-driven systems.
The integration of neuromorphic computing with artificial intelligence and machine learning enhances the performance and capabilities of AI applications, driving demand across various sectors.
Neuromorphic computing's low-power and on-device processing capabilities make it well-suited for edge computing applications, reducing latency and improving performance in devices like smart sensors and autonomous systems.
Neuromorphic technology's potential in medical diagnostics and healthcare, such as biosensors for disease detection, propels market growth through improved diagnostic accuracy and speed.
The neuromorphic computing is having capability to pull data from many IoT devices, this technology is great for use in home automation applications as well as self-driving cars and health diagnostics. Neuromorphic computing allows AI algorithms to operate on effective network architectures and speedy data processing. Self-driving cars are one case that learns from other traffic to make faster decisions, and automated homes that adjust temperature and lighting based on the habits of people living in them. Furthermore, neuromorphic computing also reinforces IoT security by acting as an AI that help to identify any phishing or malicious activity. At CES 2024, Innatera introduced the Spiking Neural Processor T1 originating in neuromorphic microcontroller conceived for battery-operated AI running on a sensor-edge like smart homes accessories or wearables aiming energy efficiency IoT applications. For real-time processing algorithms with low power constraints, neuromorphic computing largely benefits AI and ML applications which they tend to be complementary such as autonomous systems, computer vision or natural language processing. Ideal use for this is IoT devices, robotics & autonomous vehicles. Areas are working towards full automation initiatives to drive efficiencies and improve quality. The ability of a neuromorphic chip can be employed in areas such as the military and cybersecurity for detecting anomalies, Image/object recognition e.g., by analyzing network traffic patterns. In September 2023, BrainChip Holdings Ltd worked with VVDN Technologies to help provide an Edge box that was powered by their very own Akida neuromorphic processors for it extend Edge AI capabilities.
Restraints
The research and development of neuromorphic chips and systems require significant investment, which can be a barrier for smaller companies and startups.
Designing neuromorphic systems that mimic the human brain's architecture and functionality is complex and challenging, slowing down widespread adoption.
The absence of industry standards for neuromorphic computing technologies can hinder interoperability and integration with existing systems and platforms.
The growing costs to design advanced chips and systems is the major restrain for growth of market. A new neuromorphic computer platform is a multimillion-dollar research and development (R&D) proposition globally. An entirely new neuromorphic chip, if developed from scratch by companies building it could cost just more than $50 million in advanced fabrication facilities and other operational expenses including material costs with specialized talent that a design would require. Much of the added cost comes from their complex nature, which often leads to new classes of materials and novel architectures. Moreover, the complex design and testing stages brings with it high costs and a time-suck. The high-cost barrier may discourage smaller companies and startups from entering the market, inhibiting competition/innovation in this area. Consequently, the rate of progress and adoption for neuromorphic computing could be slower than other more cost-effective technologies.
Segment Analysis
By Application
The image processing segment accounted for the largest market share of over 43% in 2023. This is because the computer vision has expanded across industries like automotive, healthcare and media & entertainment. A similar endpoint is the medical imaging which a significant facet of this sector. During the forecast period, image sensors and processing technologies are projected to support growth of revenue generation via Image Processing. Image processing is primarily about reducing visual information for the purpose of making it suitable for computer vision tasks, such as image recognition in this case to make subsequent steps much easier and more efficient. by being closer in operation to how the human brain works, it can give computers a much-needed boost in terms of understanding data and then converting that into an analysis. Artificial neural network models are also rising in popularity which aims at image processing and fast computation through the use of parallel architectures.
The signal-processing application segment held a market share of 26.5% in the year 2023 and is poised to register solid growth it generates revenue more efficiently during the forecast period Increasing need to process audio and acoustic signals is driving the signal-processing segment. The market is expected to grow during the forecast period with increasing adoption of Artificial Intelligence and Machine Learning across IT industry which in turn will favor the data processing segment. One of the top AI trends for organizations is autoML (automatic machine learning).
By End-Use
Consumer electronics was the leading segment in 2023, accounted for more than 56.5% share of revenue This is increasing the demand for neuromorphic chips in consumer electronics, where various electronic devices including laptops/PCs/tablets have gained popularity. Miniaturization of ICS stems from the demand for smaller and cheaper products according to consumer preferences, which subsequently drives growth in the global neuromorphic chip market.
Over the forecast frame, generating revenue from the automotive industry is projected to increase with significant growth rate. Many industries are using AI (Artificial Intelligence) and ML (Machine Learning) to automate the operations which help them in offering more efficient & quality products. Moreover, the growing adoption of AI and ML as a result faster speed, low power consumption, and efficient memory usage by these technologies is accelerating growth in automotive segment. This trend clearly shows how neuromorphic chips play a significant part in upgrading the function as well as capacity of automotive applications such as autonomous driving, and advanced driver-assistance systems (ADAS).
By Deployment
Edge segment led the market in 2023, accounted 71.8% of revenue share Growth of the segment is attributed to rise in adoption of edge computing for applications including touchless interfaces, voice-controlled cars and smart assistant robots. The increasing adoption of wireless networking will, in turn, raise interest towards the edge computing paradigm which is set to foster growth with respect to this vertical as more service providers look at hosting applications closer (or within) their end-user base. Edge computing is also being embraced at scale world over with the new generation of AI hardware supporting low-power applications and in-device adaptability fuelling broader market expansion beyond conventional micro data centres.
The cloud computing offers various technological benefits and expected to grow with fastest CAGR during the forecast period is expected in. These include a scalable data-managing platform for enterprise with secure one-click big-data storage and distribution. Cloud-based neuromorphic computing has the advantages of easy resource scaling, low initial hardware and software investment costs for users to share their workloads on demand with others around the world. Latency and security issues might serve as potential obstacles. The advancement in neuromorphic computing systems employ more powerful on-device processing capabilities mitigating the need for data canters and supporting expansion in cloud computing segment as well. The advantages of cloud computing, coupled with neuromorphic technology are appealing to the enterprise.
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Regional analysis
North America dominated the market with revenue a share of more than 36% in the market during 2023 This is because, the US and Canada have deployed a significant number of neuromorphic computing applications earlier than other regions that puts them in leading position to drive change. One of the significant trends in North America is the movement toward AI-powered voice and speech recognition which has improved quality of various of speech engines for better user experience. During the forecast period, Europe is anticipated to witness substantial growth. The sector is home to several programmes and institutions oriented towards neuromorphic computing. Moreover, increasing adoption of biometric systems across various European countries is creating potential growth opportunities for the application areas in image processing utilizing neuromorphic computing. Europe's commitment to neuromorphic computing positions it as a key player in the field, provide many opportunities for companies and academics ready to innovate around this rapidly evolving technology
The major players are General Vision, Inc., Samsung Electronics Co., Ltd, Brain Corporation, HRL Laboratories LLC, Knowm Inc., BrainChip Holdings Ltd., International Business Machines Corporation, Hewlett Packard Company, Intel Corporation, CEA-Leti, Qualcomm Technologies, Inc, Vicarious FPC, Inc., Applied Brain Research Inc., and others in the final report.
IBM came up with an AI Chip built using 7nm technology that was so power efficient at, back in January,2023. The AI hardware accelerator chip offers state-of-the-art power efficiency and supports a wide range of model types. It is scalable from training large scale models in the cloud all the way down to enhancing security and privacy by bringing training closer to edge devices, allowing data almost never touching it's source.
In February SynSense combined forces with iniVation to address the rising demand for intelligent vision in high-performance consumer and industrial markets. Collaboration to develop neuromorphic technology for standalone processors, vision sensors and systems with integrated compute in sensor offering use cases across robotics, automotive consumer devices powered by the company’s edge AI product gallery.
SiLC Technologies October 2023, Eyeonic Vision System FMCW LiDAR Machine Vision The system supports rapid and accurate object identification, as well as the detection of polarization intensities and 3D distance to an accuracy of millimeters in distances greater than one kilometer.
The method for training neuromorphic chips to recognise cystic fibrosis using a biosensor was created by Dutch research scientists from Eindhoven University of Technology in September 2023. The "smart biosensor" has the potential for many point-of-care healthcare applications and could also be useful in enabling chips to automatically adjust themselves to their environments.
BrainChip Holdings Ltd. entered a collaboration with one of its technology partners, Lorser Industries Inc., for Neuromorphic computing arrangements in June 2023. In addition, the partnership gives BrainChip its first development deal for Akida in software-defined radio (SDR).
| Report Attributes | Details |
| Market Size in 2023 | USD 23.16 Bn |
| Market Size by 2032 | USD 81.12 Bn |
| CAGR | CAGR of 90% From 2024 to 2032 |
| Base Year | 2023 |
| Forecast Period | 2024-2032 |
| Historical Data | 2020-2022 |
| Report Scope & Coverage | Market Size, Segments Analysis, Competitive Landscape, Regional Analysis, DROC & SWOT Analysis, Forecast Outlook |
| Key Segments | • By Component (Hardware, Software) • By Application (Signal Processing, Image Processing, Data Processing, Object Detection, Others) • By Deployment (Edge, Cloud) • By End-Use (Consumer Electronics, Automotive, Healthcare, Military & Defense, 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 | General Vision, Inc., Samsung Electronics Co., Ltd, Brain Corporation, HRL Laboratories LLC, Knowm Inc., BrainChip Holdings Ltd., International Business Machines Corporation, Hewlett Packard Company, Intel Corporation, CEA-Leti, Qualcomm Technologies, Inc, Vicarious FPC, Inc., Applied Brain Research Inc. |
| Key Drivers | • Growing Adoption of Neuromorphic Computing to Transform Internet of Things (IoT) to drive the Market Growth • The ability of neuromorphic systems to process large amounts of data quickly and efficiently supports real-time applications in autonomous vehicles, robotics, and AI-driven systems. |
| Market Restraints | • The research and development of neuromorphic chips and systems require significant investment, which can be a barrier for smaller companies and startups. |
Ans: The North American region is dominating the Neuromorphic Computing Market.
Ans: The Neuromorphic Computing Market is to grow at a CAGR of 86.27% Over the forecast period of 2024-2032.
Ans: The Neuromorphic Computing Market size was valued at USD 86.9 Mn in 2023
Ans. The forecast period for the Neuromorphic Computing Market is 2024-2032.
Ans. There are four segments cover in this report, By Component, By Application, By Deployment, By End-Use.
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. Porter’s 5 Forces Model
6. Pest Analysis
7. Neuromorphic Computing Market Segmentation, by Component
7.1 Introduction
7.2 Hardware
7.3 Software
8. Neuromorphic Computing Market Segmentation, by Application
8.1 Introduction
8.2 Signal Processing
8.3 Image Processing
8.4 Data Processing
8.5 Object Detection
8.6 Others
9. Neuromorphic Computing Market Segmentation, by Deployment
9.1 Introduction
9.2 Edge
9.3 Cloud
10. Neuromorphic Computing Market Segmentation, by End-Use
10.1 Introduction
10.2 Consumer Electronics
10.3 Automotive
10.4 Healthcare
10.5 Military & defence
10.6 Others
11. Regional Analysis
11.1 Introduction
11.2 North America
11.2.1 North America Neuromorphic Computing Market by Country
11.2.2 North America Neuromorphic Computing Market by Component
11.2.3 North America Neuromorphic Computing Market by Application
11.2.4 North America Neuromorphic Computing Market by Deployment
11.2.5 North America Neuromorphic Computing Market by End-Use
11.2.6 USA
11.2.6.1 USA Neuromorphic Computing Market by Component
11.2.6.2 USA Neuromorphic Computing Market by Application
11.2.6.3 USA Neuromorphic Computing Market by Deployment
11.2.6.4 USA Neuromorphic Computing Market by End-Use
11.2.7 Canada
11.2.7.1 Canada Neuromorphic Computing Market by Component
11.2.7.2 Canada Neuromorphic Computing Market by Application
11.2.7.3 Canada Neuromorphic Computing Market by Deployment
11.2.7.4 Canada Neuromorphic Computing Market by End-Use
11.2.8 Mexico
11.2.8.1 Mexico Neuromorphic Computing Market by Component
11.2.8.2 Mexico Neuromorphic Computing Market by Application
11.2.8.3 Mexico Neuromorphic Computing Market by Deployment
11.2.8.4 Mexico Neuromorphic Computing Market by End-Use
11.3 Europe
11.3.1 Eastern Europe
11.3.1.1 Eastern Europe Neuromorphic Computing Market by Country
11.3.1.2 Eastern Europe Neuromorphic Computing Market by Component
11.3.1.3 Eastern Europe Neuromorphic Computing Market by Application
11.3.1.4 Eastern Europe Neuromorphic Computing Market by Deployment
11.3.1.5 Eastern Europe Neuromorphic Computing Market by End-Use
11.3.1.6 Poland
11.3.1.6.1 Poland Neuromorphic Computing Market by Component
11.3.1.6.2 Poland Neuromorphic Computing Market by Application
11.3.1.6.3 Poland Neuromorphic Computing Market by Deployment
11.3.1.6.4 Poland Neuromorphic Computing Market by End-Use
11.3.1.7 Romania
11.3.1.7.1 Romania Neuromorphic Computing Market by Component
11.3.1.7.2 Romania Neuromorphic Computing Market by Application
11.3.1.7.3 Romania Neuromorphic Computing Market by Deployment
11.3.1.7.4 Romania Neuromorphic Computing Market by End-Use
11.3.1.8 Hungary
11.3.1.8.1 Hungary Neuromorphic Computing Market by Component
11.3.1.8.2 Hungary Neuromorphic Computing Market by Application
11.3.1.8.3 Hungary Neuromorphic Computing Market by Deployment
11.3.1.8.4 Hungary Neuromorphic Computing Market by End-Use
11.3.1.9 Turkey
11.3.1.9.1 Turkey Neuromorphic Computing Market by Component
11.3.1.9.2 Turkey Neuromorphic Computing Market by Application
11.3.1.9.3 Turkey Neuromorphic Computing Market by Deployment
11.3.1.9.4 Turkey Neuromorphic Computing Market by End-Use
11.3.1.10 Rest of Eastern Europe
11.3.1.10.1 Rest of Eastern Europe Neuromorphic Computing Market by Component
11.3.1.10.2 Rest of Eastern Europe Neuromorphic Computing Market by Application
11.3.1.10.3 Rest of Eastern Europe Neuromorphic Computing Market by Deployment
11.3.1.10.4 Rest of Eastern Europe Neuromorphic Computing Market by End-Use
11.3.2 Western Europe
11.3.2.1 Western Europe Neuromorphic Computing Market by Country
11.3.2.2 Western Europe Neuromorphic Computing Market by Component
11.3.2.3 Western Europe Neuromorphic Computing Market by Application
11.3.2.4 Western Europe Neuromorphic Computing Market by Deployment
11.3.2.5 Western Europe Neuromorphic Computing Market by End-Use
11.3.2.6 Germany
11.3.2.6.1 Germany Neuromorphic Computing Market by Component
11.3.2.6.2 Germany Neuromorphic Computing Market by Application
11.3.2.6.3 Germany Neuromorphic Computing Market by Deployment
11.3.2.6.4 Germany Neuromorphic Computing Market by End-Use
11.3.2.7 France
11.3.2.7.1 France Neuromorphic Computing Market by Component
11.3.2.7.2 France Neuromorphic Computing Market by Application
11.3.2.7.3 France Neuromorphic Computing Market by Deployment
11.3.2.7.4 France Neuromorphic Computing Market by End-Use
11.3.2.8 UK
11.3.2.8.1 UK Neuromorphic Computing Market by Component
11.3.2.8.2 UK Neuromorphic Computing Market by Application
11.3.2.8.3 UK Neuromorphic Computing Market by Deployment
11.3.2.8.4 UK Neuromorphic Computing Market by End-Use
11.3.2.9 Italy
11.3.2.9.1 Italy Neuromorphic Computing Market by Component
11.3.2.9.2 Italy Neuromorphic Computing Market by Application
11.3.2.9.3 Italy Neuromorphic Computing Market by Deployment
11.3.2.9.4 Italy Neuromorphic Computing Market by End-Use
11.3.2.10 Spain
11.3.2.10.1 Spain Neuromorphic Computing Market by Component
11.3.2.10.2 Spain Neuromorphic Computing Market by Application
11.3.2.10.3 Spain Neuromorphic Computing Market by Deployment
11.3.2.10.4 Spain Neuromorphic Computing Market by End-Use
11.3.2.11 Netherlands
11.3.2.11.1 Netherlands Neuromorphic Computing Market by Component
11.3.2.11.2 Netherlands Neuromorphic Computing Market by Application
11.3.2.11.3 Netherlands Neuromorphic Computing Market by Deployment
11.3.2.11.4 Netherlands Neuromorphic Computing Market by End-Use
11.3.2.12 Switzerland
11.3.2.12.1 Switzerland Neuromorphic Computing Market by Component
11.3.2.12.2 Switzerland Neuromorphic Computing Market by Application
11.3.2.12.3 Switzerland Neuromorphic Computing Market by Deployment
11.3.2.12.4 Switzerland Neuromorphic Computing Market by End-Use
11.3.2.13 Austria
11.3.2.13.1 Austria Neuromorphic Computing Market by Component
11.3.2.13.2 Austria Neuromorphic Computing Market by Application
11.3.2.13.3 Austria Neuromorphic Computing Market by Deployment
11.3.2.13.4 Austria Neuromorphic Computing Market by End-Use
11.3.2.14 Rest of Western Europe
11.3.2.14.1 Rest of Western Europe Neuromorphic Computing Market by Component
11.3.2.14.2 Rest of Western Europe Neuromorphic Computing Market by Application
11.3.2.14.3 Rest of Western Europe Neuromorphic Computing Market by Deployment
11.3.2.14.4 Rest of Western Europe Neuromorphic Computing Market by End-Use
11.4 Asia-Pacific
11.4.1 Asia Pacific Neuromorphic Computing Market by Country
11.4.2 Asia Pacific Neuromorphic Computing Market by Component
11.4.3 Asia Pacific Neuromorphic Computing Market by Application
11.4.4 Asia Pacific Neuromorphic Computing Market by Deployment
11.4.5 Asia Pacific Neuromorphic Computing Market by End-Use
11.4.6 China
11.4.6.1 China Neuromorphic Computing Market by Component
11.4.6.2 China Neuromorphic Computing Market by Application
11.4.6.3 China Neuromorphic Computing Market by Deployment
11.4.6.4 China Neuromorphic Computing Market by End-Use
11.4.7 India
11.4.7.1 India Neuromorphic Computing Market by Component
11.4.7.2 India Neuromorphic Computing Market by Application
11.4.7.3 India Neuromorphic Computing Market by Deployment
11.4.7.4 India Neuromorphic Computing Market by End-Use
11.4.8 Japan
11.4.8.1 Japan Neuromorphic Computing Market by Component
11.4.8.2 Japan Neuromorphic Computing Market by Application
11.4.8.3 Japan Neuromorphic Computing Market by Deployment
11.4.8.4 Japan Neuromorphic Computing Market by End-Use
11.4.9 South Korea
11.4.9.1 South Korea Neuromorphic Computing Market by Component
11.4.9.2 South Korea Neuromorphic Computing Market by Application
11.4.9.3 South Korea Neuromorphic Computing Market by Deployment
11.4.9.4 South Korea Neuromorphic Computing Market by End-Use
11.4.10 Vietnam
11.4.10.1 Vietnam Neuromorphic Computing Market by Component
11.4.10.2 Vietnam Neuromorphic Computing Market by Application
11.4.10.3 Vietnam Neuromorphic Computing Market by Deployment
11.4.10.4 Vietnam Neuromorphic Computing Market by End-Use
11.4.11 Singapore
11.4.11.1 Singapore Neuromorphic Computing Market by Component
11.4.11.2 Singapore Neuromorphic Computing Market by Application
11.4.11.3 Singapore Neuromorphic Computing Market by Deployment
11.4.11.4 Singapore Neuromorphic Computing Market by End-Use
11.4.12 Australia
11.4.12.1 Australia Neuromorphic Computing Market by Component
11.4.12.2 Australia Neuromorphic Computing Market by Application
11.4.12.3 Australia Neuromorphic Computing Market by Deployment
11.4.12.4 Australia Neuromorphic Computing Market by End-Use
11.4.13 Rest of Asia-Pacific
11.4.13.1 Rest of Asia-Pacific Neuromorphic Computing Market by Component
11.4.13.2 Rest of Asia-Pacific Neuromorphic Computing Market by Application
11.4.13.3 Rest of Asia-Pacific Neuromorphic Computing Market by Deployment
11.4.13.4 Rest of Asia-Pacific Neuromorphic Computing Market by End-Use
11.5 Middle East & Africa
11.5.1 Middle East
11.5.1.1 Middle East Neuromorphic Computing Market by Country
11.5.1.2 Middle East Neuromorphic Computing Market by Component
11.5.1.3 Middle East Neuromorphic Computing Market by Application
11.5.1.4 Middle East Neuromorphic Computing Market by Deployment
11.5.1.5 Middle East Neuromorphic Computing Market by End-Use
11.5.1.6 UAE
11.5.1.6.1 UAE Neuromorphic Computing Market by Component
11.5.1.6.2 UAE Neuromorphic Computing Market by Application
11.5.1.6.3 UAE Neuromorphic Computing Market by Deployment
11.5.1.6.4 UAE Neuromorphic Computing Market by End-Use
11.5.1.7 Egypt
11.5.1.7.1 Egypt Neuromorphic Computing Market by Component
11.5.1.7.2 Egypt Neuromorphic Computing Market by Application
11.5.1.7.3 Egypt Neuromorphic Computing Market by Deployment
11.5.1.7.4 Egypt Neuromorphic Computing Market by End-Use
11.5.1.8 Saudi Arabia
11.5.1.8.1 Saudi Arabia Neuromorphic Computing Market by Component
11.5.1.8.2 Saudi Arabia Neuromorphic Computing Market by Application
11.5.1.8.3 Saudi Arabia Neuromorphic Computing Market by Deployment
11.5.1.8.4 Saudi Arabia Neuromorphic Computing Market by End-Use
11.5.1.9 Qatar
11.5.1.9.1 Qatar Neuromorphic Computing Market by Component
11.5.1.9.2 Qatar Neuromorphic Computing Market by Application
11.5.1.9.3 Qatar Neuromorphic Computing Market by Deployment
11.5.1.9.4 Qatar Neuromorphic Computing Market by End-Use
11.5.1.10 Rest of Middle East
11.5.1.10.1 Rest of Middle East Neuromorphic Computing Market by Component
11.5.1.10.2 Rest of Middle East Neuromorphic Computing Market by Application
11.5.1.10.3 Rest of Middle East Neuromorphic Computing Market by Deployment
11.5.1.10.4 Rest of Middle East Neuromorphic Computing Market by End-Use
11.5.2. Africa
11.5.2.1 Africa Neuromorphic Computing Market by Country
11.5.2.2 Africa Neuromorphic Computing Market by Component
11.5.2.3 Africa Neuromorphic Computing Market by Application
11.5.2.4 Africa Neuromorphic Computing Market by Deployment
11.5.2.5 Africa Neuromorphic Computing Market by End-Use
11.5.2.6 Nigeria
11.5.2.6.1 Nigeria Neuromorphic Computing Market by Component
11.5.2.6.2 Nigeria Neuromorphic Computing Market by Application
11.5.2.6.3 Nigeria Neuromorphic Computing Market by Deployment
11.5.2.6.4 Nigeria Neuromorphic Computing Market by End-Use
11.5.2.7 South Africa
11.5.2.7.1 South Africa Neuromorphic Computing Market by Component
11.5.2.7.2 South Africa Neuromorphic Computing Market by Application
11.5.2.7.3 South Africa Neuromorphic Computing Market by Deployment
11.5.2.7.4 South Africa Neuromorphic Computing Market by End-Use
11.5.2.8 Rest of Africa
11.5.2.8.1 Rest of Africa Neuromorphic Computing Market by Component
11.5.2.8.2 Rest of Africa Neuromorphic Computing Market by Application
11.5.2.8.3 Rest of Africa Neuromorphic Computing Market by Deployment
11.5.2.8.4 Rest of Africa Neuromorphic Computing Market by End-Use
11.6. Latin America
11.6.1 Latin America Neuromorphic Computing Market by Country
11.6.2 Latin America Neuromorphic Computing Market by Component
11.6.3 Latin America Neuromorphic Computing Market by Application
11.6.4 Latin America Neuromorphic Computing Market by Deployment
11.6.5 Latin America Neuromorphic Computing Market by End-Use
11.6.6 Brazil
11.6.6.1 Brazil Neuromorphic Computing Market by Component
11.6.6.2 Brazil Neuromorphic Computing Market by Application
11.6.6.3 Brazil Neuromorphic Computing Market by Deployment
11.6.6.4 Brazil Neuromorphic Computing Market by End-Use
11.6.7 Argentina
11.6.7.1 Argentina Neuromorphic Computing Market by Component
11.6.7.2 Argentina Neuromorphic Computing Market by Application
11.6.7.3 Argentina Neuromorphic Computing Market by Deployment
11.6.7.4 Argentina Neuromorphic Computing Market by End-Use
11.6.8 Colombia
11.6.8.1 Colombia Neuromorphic Computing Market by Component
11.6.8.2 Colombia Neuromorphic Computing Market by Application
11.6.8.3 Colombia Neuromorphic Computing Market by Deployment
11.6.8.4 Colombia Neuromorphic Computing Market by End-Use
11.6.9 Rest of Latin America
11.6.9.1 Rest of Latin America Neuromorphic Computing Market by Component
11.6.9.2 Rest of Latin America Neuromorphic Computing Market by Application
11.6.9.3 Rest of Latin America Neuromorphic Computing Market by Deployment
11.6.9.4 Rest of Latin America Neuromorphic Computing Market by End-Use
12 Company Profile
12.1 General Vision, Inc.
12.1.1 Company Overview
12.1.2 Financials
12.1.3 Product/Services/Offerings
12.1.4 SWOT Analysis
12.1.5 The SNS View
12.2 Samsung Electronics Co., Ltd.
12.2.1 Company Overview
12.2.2 Financials
12.2.3 Product/Services/Offerings
12.2.4 SWOT Analysis
12.2.5 The SNS View
12.3 Brain Corporation.
12.3.1 Company Overview
12.3.2 Financials
12.3.3 Product/Services/Offerings
12.3.4 SWOT Analysis
12.3.5 The SNS View
12.4 HRL Laboratories LLC.
12.4.1 Company Overview
12.4.2 Financials
12.4.3 Product/Services/Offerings
12.4.4 SWOT Analysis
12.4.5 The SNS View
12.5 Knowm Inc.
12.5.1 Company Overview
12.5.2 Financials
12.5.3 Product/Services/Offerings
12.5.4 SWOT Analysis
12.5.5 The SNS View
12.6 BrainChip Holdings Ltd.
12.6.1 Company Overview
12.6.2 Financials
12.6.3 Product/Services/Offerings
12.6.4 SWOT Analysis
12.6.5 The SNS View
12.7 International Business Machines Corporation.
12.7.1 Company Overview
12.7.2 Financials
12.7.3 Product/Services/Offerings
12.7.4 SWOT Analysis
12.7.5 The SNS View
12.8 Hewlett Packard Company.
12.8.1 Company Overview
12.8.2 Financials
12.8.3 Product/Services/Offerings
12.8.4 SWOT Analysis
12.8.5 The SNS View
12.9 Intel Corporation.
12.9.1 Company Overview
12.9.2 Financials
12.9.3 Product/Services/Offerings
12.9.4 SWOT Analysis
12.9.5 The SNS View
12.10 Qualcomm Technologies, Inc.
12.10.1 Company Overview
12.10.2 Financials
12.10.3 Product/Services/Offerings
12.10.4 SWOT Analysis
12.10.5 The SNS View
13. Competitive Landscape
13.1 Competitive Benchmarking
13.2 Market Share Analysis
13.3 Recent Developments
14. USE Cases and Best Practices
15. Conclusion
An accurate research report requires proper strategizing as well as implementation. There are multiple factors involved in the completion of good and accurate research report and selecting the best methodology to compete the research is the toughest part. Since the research reports we provide play a crucial role in any company’s decision-making process, therefore we at SNS Insider always believe that we should choose the best method which gives us results closer to reality. This allows us to reach at a stage wherein we can provide our clients best and accurate investment to output ratio.
Each report that we prepare takes a timeframe of 350-400 business hours for production. Starting from the selection of titles through a couple of in-depth brain storming session to the final QC process before uploading our titles on our website we dedicate around 350 working hours. The titles are selected based on their current market cap and the foreseen CAGR and growth.
The 5 steps process:
Step 1: Secondary Research:
Secondary Research or Desk Research is as the name suggests is a research process wherein, we collect data through the readily available information. In this process we use various paid and unpaid databases which our team has access to and gather data through the same. This includes examining of listed companies’ annual reports, Journals, SEC filling etc. Apart from this our team has access to various associations across the globe across different industries. Lastly, we have exchange relationships with various university as well as individual libraries.
Step 2: Primary Research
When we talk about primary research, it is a type of study in which the researchers collect relevant data samples directly, rather than relying on previously collected data. This type of research is focused on gaining content specific facts that can be sued to solve specific problems. Since the collected data is fresh and first hand therefore it makes the study more accurate and genuine.
We at SNS Insider have divided Primary Research into 2 parts.
Part 1 wherein we interview the KOLs of major players as well as the upcoming ones across various geographic regions. This allows us to have their view over the market scenario and acts as an important tool to come closer to the accurate market numbers. As many as 45 paid and unpaid primary interviews are taken from both the demand and supply side of the industry to make sure we land at an accurate judgement and analysis of the market.
This step involves the triangulation of data wherein our team analyses the interview transcripts, online survey responses and observation of on filed participants. The below mentioned chart should give a better understanding of the part 1 of the primary interview.
Part 2: In this part of primary research the data collected via secondary research and the part 1 of the primary research is validated with the interviews from individual consultants and subject matter experts.
Consultants are those set of people who have at least 12 years of experience and expertise within the industry whereas Subject Matter Experts are those with at least 15 years of experience behind their back within the same space. The data with the help of two main processes i.e., FGDs (Focused Group Discussions) and IDs (Individual Discussions). This gives us a 3rd party nonbiased primary view of the market scenario making it a more dependable one while collation of the data pointers.
Step 3: Data Bank Validation
Once all the information is collected via primary and secondary sources, we run that information for data validation. At our intelligence centre our research heads track a lot of information related to the market which includes the quarterly reports, the daily stock prices, and other relevant information. Our data bank server gets updated every fortnight and that is how the information which we collected using our primary and secondary information is revalidated in real time.
Step 4: QA/QC Process
After all the data collection and validation our team does a final level of quality check and quality assurance to get rid of any unwanted or undesired mistakes. This might include but not limited to getting rid of the any typos, duplication of numbers or missing of any important information. The people involved in this process include technical content writers, research heads and graphics people. Once this process is completed the title gets uploader on our platform for our clients to read it.
Step 5: Final QC/QA Process:
This is the last process and comes when the client has ordered the study. In this process a final QA/QC is done before the study is emailed to the client. Since we believe in giving our clients a good experience of our research studies, therefore, to make sure that we do not lack at our end in any way humanly possible we do a final round of quality check and then dispatch the study to the client.
Key Segments:
By Component
Hardware
Software
By Application
Signal Processing
Image Processing
Data Processing
Object Detection
Others
By Deployment
Edge
Cloud
By End-Use
Consumer Electronics
Automotive
Healthcare
Military & defiance
Others
Request for Segment Customization as per your Business Requirement: Segment Customization Request
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
Request for Country Level Research Report: Country Level Customization Request
Available Customization
With the given market data, SNS Insider offers customization as per the company’s specific needs. The following customization options are available for the report:
Product Analysis
Criss-Cross segment analysis (e.g. Product X Application)
Product Matrix which gives a detailed comparison of product portfolio of each company
Geographic Analysis
Additional countries in any of the regions
Company Information
Detailed analysis and profiling of additional market players (Up to five)
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The Social Gaming Market size was valued at USD 27.13 Billion in 2023 and is projected to reach USD 89.18 Billion in 2031 with an increasing CAGR of 16.04% Over the Forecast Period of 2024-2031.
The Digital Audio Workstation Market size was USD 2.97 Billion in 2023 and will reach USD 6.34 Billion by 2032 and grow at a CAGR of 8.8% by 2024-2032.
The Conversational Systems Market size was USD 13.32 billion in 2023 and is expected to reach USD 150.30 billion by 2032 and grow at a CAGR of 30.9% over the forecast period of 2024-2032.
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