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The Global Neuromorphic Computing & Sensing Market 2027-2037

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Neuromorphic processors, spiking neural networks, in-memory and memristive computing, and event-based sensing: technologies, markets and company profiles

  • Published: October 2026
  • Pages: 717
  • Tables: 90
  • Figures: 62

 

Neuromorphic computing and sensing had its most active year yet in 2026, as investors, chipmakers and system builders moved from research toward commercial deployment of brain-inspired hardware. Interest was driven by the energy cost of conventional AI. Neuromorphic processors, in-memory compute and event-based sensors process information only when something changes, so they offer large efficiency gains for edge devices, robotics, vehicles and, increasingly, the data centre. Private capital moved into the sector at unprecedented scale:

  • Flourish raised US$500 million in June 2026, in a round led by Jeff Bezos, to reverse-engineer how the brain learns.
  • Unconventional AI, led by Naveen Rao, closed a US$475 million seed round at a US$4.5 billion valuation in late 2025 to develop analogue, physics-based AI chips.
  • Neurophos raised a US$110 million Series A for optical processing.
  • Axelera AI secured more than US$250 million.
  • MatX closed a Series B of over US$500 million.
  • Salience Labs raised a US$125 million Series B in October.

 

Europe’s memristor developers also gained momentum. Romania’s CyberSwarm closed a US$50 million Series A led by Falanga Invest Perton to take its memristor-based compute architecture into automotive, aerospace, defence and robotics. The Biological Computing Co. raised a US$25 million seed round to build computers that use living neurons. Applied Brain Research completed an oversubscribed seed round, and Prophesee secured €20 million of new financing after its restructuring.

In Asia:

  • SynSense closed a Series B.
  • AlpsenTek raised a Series B+ for hybrid event-based vision sensors.
  • Moffett AI announced a Series C of nearly CNY1 billion.
  • DEEPX began a Series D valuing it at about US$2.2 billion.
  • Rebellions, which absorbed Sapeon, raised US$400 million ahead of an IPO.

 

Strategic activity was just as significant. Marvell completed its acquisition of Celestial AI, Honda partnered with and invested in Mythic to co-develop a neuromorphic chip for vehicles, and Capacity acquired Starmind. Commercial milestones followed the money:

  • BrainChip began shipping AKD1500 chips in volume and licensed its Akida IP to new chip customers.
  • Innatera’s Pulsar microcontroller won its first manufacturing customer.
  • TetraMem announced first silicon of its MLX200 in-memory compute chip.
  • SpiNNcloud delivered large-scale SpiNNaker2 systems to research centres.

Together, these developments mark 2026 as the year neuromorphic technology attracted mainstream venture and corporate capital. The field’s focus has shifted from proving the concept to scaling production, software ecosystems and real-world deployments.

The Global Neuromorphic Computing & Sensing Market 2027-2037 is a comprehensive analysis of this fast-evolving industry. It covers the technologies, materials, manufacturing processes, end markets and companies shaping it. The report gives revenue forecasts to 2037 by end market and region, with conservative, moderate and aggressive scenarios. It also assesses the commercial readiness of each technology and company, giving investors, chipmakers, OEMs and system integrators a clear view of where and when commercial adoption will happen.

Report contents include:

  • Executive summary of market performance from 2024 to 2026, revised long-term projections, key trends, growth drivers, challenges and the technology roadmap to 2037.
  • Key product launches, system deployments and 2026 funding activity, including venture, corporate and government investment.
  • Market value chain, market map, strategic partnerships, and the regulatory, intellectual property and sustainability landscape.
  • Neuromorphic approaches, including large-scale systems, non-volatile memory, and memristive materials and devices.
  • Fabrication processes, key material suppliers, supply-chain risks and manufacturing capacity.
  • Neuromorphic computing technologies, including spiking neural networks, memory architectures, processors and software frameworks.
  • Neuromorphic sensing technologies, including event-based vision, auditory, olfactory and tactile sensors, hybrid sensing approaches and signal processing.
  • Comparison with conventional, quantum and other emerging computing technologies.
  • Market forecasts by end market to 2037 for mobile and consumer, automotive and transportation, industrial and manufacturing, healthcare and medical devices, aerospace and defence, and data centres and cloud services.
  • Regional forecasts for North America, Europe, Asia-Pacific and the Rest of the World.
  • Competitive landscape and analysis of competing technologies.
  • Profiles of 154 companies, each with technology, products, funding history to October 2026, recent developments, a commercial-readiness assessment and the Future Markets strategic view.
  • Convergence with the broader neural networks market, plus research methodology and references.

 

Companies profiled include Applied Brain Research (ABR), AiM Future, AistarTek, AIStorm, AlpsenTek, Amazon Web Services (AWS), Ambarella, Ambient Scientific, AMD, ANAFLASH, Sagence AI, AnotherBrain, Apple, Arm, Aryballe Technologies, Aspinity, Aspirare Semi, Avalanche Technology, Axelera AI, Baidu, Beijing Xinzhida Neurotechnology, The Biological Computing Co., Blumind, BMW, Bosch, BrainChip, Canon, CEA-Leti, CelePixel, Celestial AI, Cerebras Systems, Ceryx Medical, Ceva, ChipIntelli, Clarifai, CoCoPIE, CogniFiber, CrossBar, CyberSwarm, d-Matrix, Deeplite, DEEPX, Dialog Semiconductor, Dynex, EdgeCortix, Eeasy Technology, Evomotion, Expedera, Flourish, Fullhan Microelectronics, General Vision, GlobalFoundries, Google, Gorilla Technology, GrAI Matter Labs, Green Mountain Semiconductor, Grayscale AI, Groq, Gwanak Analog, Hailo, Hewlett Packard Labs, Hikvision, Huawei, IBM, Infineon Technologies, iniVation, Innatera Nanosystems, INSTAR Robotics, Intel, Intelligent Hardware Korea, Intrinsic Semiconductor Technologies and more.....

 

Purchasers will receive the following:

  • PDF report download/by email.
  • Comprehensive Excel spreadsheet of all data including data on all investments & deals segmented by technology, sub-sector, government, region, and company
  • Mid-year Update

 

The Global Neuromorphic Computing & Sensing Market 2027-2037
The Global Neuromorphic Computing & Sensing Market 2027-2037
PDF + Excel Database.
Price: £1,100.00

The Global Neuromorphic Computing & Sensing Market 2027-2037
The Global Neuromorphic Computing & Sensing Market 2027-2037
PDF + Excel Database + Print Edition (including tracked delivery).
Price: £1,200.00

 

1. Executive Summary 54

  • 1.1 Overview of the Neuromorphic Computing and Sensing Market         54
    • 1.1.1 Market Performance 2024-2026          56
    • 1.1.2 Revised Long-Term Projections Through 2037            56
    • 1.1.3 Global Market Revenues 2024-2037 56
    • 1.1.4 Market Segmentation  57
  • 1.2 Ending of Moore’s Law     58
  • 1.3 Historical Market 59
  • 1.4 The Market in 2026            60
  • 1.5 Key Market Trends and Growth Drivers 61
  • 1.6 Market Challenges and Limitations        62
  • 1.7 System Deployments       63
  • 1.8 Key Industry Insights        64
    • 1.8.1 Digital Neuromorphic Designs Replacing Analog Implementations             64
    • 1.8.2 The Programming Paradigm Gap         64
    • 1.8.3 Cost and Scalability Considerations 64
  • 1.9 Future Outlook and Opportunities          65
    • 1.9.1 Emerging Trends             65
    • 1.9.2 Technology Roadmap 75
  • 1.10 Key Product Launches (2024-2026)    76
    • 1.10.1 Intel Hala Point System (April 2024) 76
    • 1.10.2 Innatera T1 SNP Processor (CES 2025)         76
    • 1.10.3 BrainChip Akida Pulsar            77
    • 1.10.4 BrainChip Akida Cloud (August 2025)           77
    • 1.10.5 SynSense Speck 2.0  77
    • 1.10.6 Chinese Academy of Sciences SpikingBrain-1.0    77
    • 1.10.7 Flourish AI $500M Private Round (2026)      78
    • 1.10.8 Unconventional AI $475M Seed Round (2025)        78
    • 1.10.9 CyberSwarm Series A and Memristor Chip Sampling (2026)          78
  • 1.11 Neuromorphic Computing and Generative AI               82
  • 1.12 Market Value Chain        83
  • 1.13 Market Map          84
  • 1.14 Funding and Investments           84
    • 1.14.1 Government & Institutional Funding               85
    • 1.14.2 Venture Capital & Private Equity Flows          85
  • 1.15 Strategic Partnerships and Collaborations     90
  • 1.16 Regulatory and Ethical Considerations             95
    • 1.16.1 Data Privacy and Security       95
    • 1.16.2 Bias and Fairness in Neuromorphic Systems            95
    • 1.16.3 Intellectual Property and Patent Landscape             96
  • 1.17 Sustainability and Environmental Impact        97
    • 1.17.1 Carbon Footprint Analysis of Neuromorphic Systems        97
    • 1.17.2 Energy Efficiency Metrics and Benchmarking           97
    • 1.17.3 Green Manufacturing Practices         97
    • 1.17.4 End-of-life and Recycling Considerations   97
    • 1.17.5 Environmental Regulations Compliance     9

 

2. Introduction 99

  • 2.1 Definition and Concept of Neuromorphic Computing and Sensing  99
  • 2.2 Main Neuromorphic Approaches             100
    • 2.2.1 Large-scale Hardware Neuromorphic Computing Systems               102
    • 2.2.2 Non-volatile Memory Technologies    102
    • 2.2.3 Advanced Memristive Materials and Devices               103
  • 2.3 Fabrication Processes for Neuromorphic Systems      104
  • 2.4 Key Material Suppliers     107
  • 2.5 Supply Chain Vulnerabilities and Mitigation     108
  • 2.6 Manufacturing Capacity Analysis            108
  • 2.7 Quality Control and Testing Procedures               108
  • 2.8 Comparison with Traditional Computing and Sensing Approaches  109
  • 2.9 Neuromorphic Computing Vs. Quantum Computing 109
  • 2.10 Key Features and Advantages  111
    • 2.10.1 Low Latency and Real-time Processing        111
    • 2.10.2 Power Efficiency and Energy Savings              111
    • 2.10.3 Scalability and Adaptability  112
    • 2.10.4 Online Learning and Autonomous Decision-making           112
  • 2.11 Markets and Applications          112
    • 2.11.1 Edge AI and IoT              116
    • 2.11.2 Autonomous Vehicles and Robotics               117
    • 2.11.3 Cybersecurity and Anomaly Detection          119
    • 2.11.4 Smart Sensors and Monitoring Systems      120
    • 2.11.5 Datacenter and High-Performance Computing       121

 

3. Neuromorphic Computing Technologies and Architecture 123

  • 3.1 Spiking Neural Networks (SNNs)              124
    • 3.1.1 Biological Inspiration and Principles  125
    • 3.1.2 Types of SNNs and Their Characteristics        125
    • 3.1.3 Advantages and Limitations of SNNs 126
  • 3.2 Memory Architectures for Neuromorphic Computing 127
    • 3.2.1 Conventional Memory Approaches (SRAM, DRAM) 127
    • 3.2.2 Emerging Non-volatile Memory (eNVM) Technologies            127
    • 3.2.3 In-memory Computing and Near-memory Computing         130
    • 3.2.4 Hybrid Memory Architectures 130
  • 3.3 Neuromorphic Hardware and Processors          131
    • 3.3.1 Digital Neuromorphic Processors       131
    • 3.3.2 Analog Neuromorphic Processors      132
    • 3.3.3 Mixed-signal Neuromorphic Processors         132
    • 3.3.4 FPGA-based Neuromorphic Systems               133
    • 3.3.5 Neuromorphic Accelerators and Co-processors       133
  • 3.4 Software and Frameworks for Neuromorphic Computing       138
    • 3.4.1 Neuromorphic Programming Languages and Tools 138
    • 3.4.2 Neuromorphic Simulation Platforms and Frameworks         139
    • 3.4.3 Software and Programming Ecosystem Developments        139
    • 3.4.4 Neuromorphic Algorithm Libraries and Repositories              149
    • 3.4.5 Neuromorphic Software Development Kits (SDKs)  149

 

4. Neuromorphic Sensing Technologies and Architectures 151

  • 4.1 Event-Based Sensors and Processing   151
    • 4.1.1 Neuromorphic Vision Sensors               152
    • 4.1.2 Neuromorphic Auditory Sensors          153
    • 4.1.3 Neuromorphic Olfactory Sensors        154
    • 4.1.4 Event-driven Processing and Algorithms        155
  • 4.2 Hybrid Sensing Approaches        155
    • 4.2.1 Combination of Conventional and Event-based Sensors    157
    • 4.2.2 Fusion of Multiple Sensing Modalities              157
    • 4.2.3 Advantages and Challenges of Hybrid Sensing          158
  • 4.3 Neuromorphic Sensor Architectures and Designs       158
    • 4.3.1 Pixel-level Processing and Computation        159
    • 4.3.2 Sensor-processor Co-design and Integration              159
    • 4.3.3 Bio-inspired Sensor Designs and Materials  160
  • 4.4 Signal Processing and Feature Extraction Techniques                161
    • 4.4.1 Spike-based Encoding and Decoding               161
    • 4.4.2 Temporal and Spatiotemporal Feature Extraction     162
    • 4.4.3 Neuromorphic Filtering and Denoising            163
    • 4.4.4 Adaptive and Learning-Based Processing      164

 

5. Market Analysis and Forecasts 166

  • 5.1 Commercial Deployment Highlights     166
    • 5.1.1 IoT and Edge Deployments       166
    • 5.1.2 Automotive Applications: Mercedes-Benz     166
    • 5.1.3 Telecommunications: Ericsson Research      166
    • 5.1.4 Healthcare: ALYN Hospital Collaboration      166
    • 5.1.5 Cybersecurity Applications     167
  • 5.2 Mobile and Consumer     169
    • 5.2.1 Applications      169
    • 5.2.2 Technology Roadmap 170
    • 5.2.3 Smartphones and Wearables 171
    • 5.2.4 Smart Home and IoT Devices  172
    • 5.2.5 Consumer Health and Wellness           173
    • 5.2.6 Entertainment and Gaming     174
    • 5.2.7 Market Size and Forecast, in Mobile and Consumer Applications (2024-2037), Millions USD.   175
  • 5.3 Automotive and Transportation 176
    • 5.3.1 Applications      176
    • 5.3.2 Technology Roadmap 177
    • 5.3.3 Advanced Driver Assistance Systems (ADAS)              178
    • 5.3.4 Autonomous Vehicles and Robotaxis               180
    • 5.3.5 Vehicle Infotainment and User Experience    183
    • 5.3.6 Smart Traffic Management and Infrastructure             184
    • 5.3.7 Market Size and Forecast, in Automotive and Transportation (2024-2037), Millions USD.             185
  • 5.4 Industrial and Manufacturing     187
    • 5.4.1 Applications      187
    • 5.4.2 Technology Roadmap 188
    • 5.4.3 Industrial IoT and Smart Factories       188
    • 5.4.4 Predictive Maintenance and Anomaly Detection       190
    • 5.4.5 Quality Control and Inspection             191
    • 5.4.6 Logistics and Supply Chain Optimization      192
    • 5.4.7 Market Size and Forecast, in Industrial and Manufacturing (2024-2037), Millions USD. 193
  • 5.5 Healthcare and Medical Devices              195
    • 5.5.1 Applications      195
    • 5.5.2 Technology Roadmap 196
    • 5.5.3 Medical Imaging and Diagnostics       197
    • 5.5.4 Wearable Health Monitoring Devices                198
    • 5.5.5 Personalized Medicine and Drug Discovery  200
    • 5.5.6 Assistive Technologies and Prosthetics           201
    • 5.5.7 Market Size and Forecast, in Healthcare and Medical Devices (2024-2037), Millions USD          203
  • 5.6 Aerospace and Defense 204
    • 5.6.1 Applications      204
    • 5.6.2 Technology Roadmap 205
    • 5.6.3 Unmanned Aerial Vehicles (UAVs) and Drones           206
    • 5.6.4 Satellite Imaging and Remote Sensing             208
    • 5.6.5 Missile Guidance and Target Recognition      209
    • 5.6.6 Cybersecurity and Threat Detection: 211
    • 5.6.7 Market Size and Forecast, in Aerospace and Defence (2024-2037), Millions USD              212
  • 5.7 Datacenters and Cloud Services              213
    • 5.7.1 Applications      213
    • 5.7.2 Technology Roadmap 214
    • 5.7.3 High-performance Computing and Scientific Simulations:                215
    • 5.7.4 Big Data Analytics and Machine Learning      216
    • 5.7.5 Cloud-based AI Services and Platforms          218
    • 5.7.6 Energy-efficient Datacenter Infrastructure    219
    • 5.7.7 Market Size and Forecast, in Datacenters and Cloud Services (2024-2037), Millions USD           220
  • 5.8 Regional Market Analysis and Forecasts             222
    • 5.8.1 North America  223
    • 5.8.2 Europe   224
    • 5.8.3 Asia-Pacific       225
    • 5.8.4 Rest of the World            227
  • 5.9 Competitive Landscape and Key Players            228
    • 5.9.1 Overview of the Neuromorphic Computing and Sensing Ecosystem           228
    • 5.9.2 Neuromorphic Chip Manufacturers and Processors              229
    • 5.9.3 Neuromorphic Sensor Manufacturers              230
    • 5.9.4 Emerging Non-Volatile Memory (eNVM) Manufacturers       231
    • 5.9.5 Neuromorphic Software and Framework Providers 232
    • 5.9.6 Research Institutions and Academia 232
  • 5.10 Competing Emerging Technologies      235
    • 5.10.1 Quantum Computing               236
    • 5.10.2 Photonic Computing 236
    • 5.10.3 DNA Computing           237
    • 5.10.4 Spintronic Computing              237
    • 5.10.5 Chemical Computing               237
    • 5.10.6 Superconducting Computing              237
    • 5.10.7 Analog AI Chips            237
    • 5.10.8 In-Memory Computing            238
    • 5.10.9 Reversible Computing             238
    • 5.10.10 Quantum Dot Computing   238
    • 5.10.11 Technology Substitution Analysis  239
    • 5.10.12 Migration Pathways 241
    • 5.10.13 Comparative Advantages/Disadvantages 241

 

6. Company Profiles 243 (154 company profiles)

 

7. Convergence with the Broader Neural Networks Market 711

  • 7.1 Neuromorphic Computing in the Neural Networks Ecosystem            711
  • 7.2 Growth Trajectory of Novel Neural Network Hardware               711
  • 7.3 Spiking Neural Networks and Architecture Convergence         711
  • 7.4 Key Neuromorphic Companies Within the Neural Networks Landscape       711
  • 7.5 Energy Efficiency as a Structural Driver                712

 

8. Research Scope & Methodology 713

 

9. References 714

 

List of Tables

  • Table 1. Overview of the neuromorphic computing and sensing market.               54
  • Table 2. Global market for neuromorphic computing and sensors, 2024-2037 (Billions USD).               56
  • Table 3. Neuromorphic Computing and Sensing Market Segmentation 2020-2037.      58
  • Table 4. Key market trends and growth drivers.       61
  • Table 5. Market challenges and limitations.              62
  • Table 6. Emerging Trends in Neuromorphic Computing and Sensing        65
  • Table 7. Key Product Launches in Neuromorphic Computing and Sensing, 2024–2026              79
  • Table 8. Neuromorphic computing and generative AI strategies. 83
  • Table 9. Funding and investments in neuromorphic computing and sensing.    85
  • Table 10. Strategic Partnerships and Collaborations in the Neuromorphic Industry.     90
  • Table 11. Regulatory and Ethical Considerations of neuromorphic computing & sensing.        96
  • Table 12. Main neuromorphic sensing approaches.            100
  • Table 13. Main Neuromorphic Computing Approaches.   100
  • Table 14. Resistive Non-Volatile Memory (NVM) Technologies.    102
  • Table 15. Advanced Memristive Materials, Devices, and Novel Computation Concepts.            103
  • Table 16. Fabrication Processes for Neuromorphic Systems.       105
  • Table 17. Key Material Suppliers and Dependencies.          107
  • Table 18. Comparison with traditional computing and sensing approaches.      109
  • Table 19. Comparison between neuromorphic and quantum computing.            110
  • Table 20. Key features and advantages of neuromorphic computing and sensing.         111
  • Table 21. Markets and Applications of Neuromorphic Computing and Sensing 113
  • Table 22. Von neumann architecture versus neuromorphic architecture.             123
  • Table 23. Types of SNNs and their characteristics.               126
  • Table 24. Advantages and limitations of SNNs.       126
  • Table 25. Conventional memory approaches (SRAM, DRAM).      127
  • Table 26. Emerging non-volatile memory (eNVM) technologies.  127
  • Table 27. Hybrid memory architectures.      130
  • Table 28. Neuromorphic Accelerators and Co-Processors (Updated 2026)        134
  • Table 29. Neuromorphic programming languages and tools.        138
  • Table 30. Neuromorphic simulation platforms and frameworks. 139
  • Table 31. Neuromorphic Software Ecosystem 2025-2037              141
  • Table 32. Software Ecosystem Maturity Timeline   147
  • Table 33. Neuromorphic algorithm libraries and repositories.      149
  • Table 34. Neuromorphic software development kits (SDKs).         150
  • Table 35. Hybrid sensing approaches.          156
  • Table 36. Advantages and challenges of hybrid sensing.  158
  • Table 37. Bio-inspired sensor designs and materials.         160
  • Table 38. Signal Processing and Feature Extraction Techniques. 161
  • Table 39. Neuromorphic Computing Applications in Cybersecurity: Use Cases, Players and Deployment Status 2026    167
  • Table 40. Neuromorphic Computing Applications in Cybersecurity: Commercial Application Milestones 2024–2026.    168
  • Table 41. Neuromorphic Computing and Sensing Applications in Mobile and Consumer Electronics: Use Cases, Players and Market Status, 2026–2037             170
  • Table 42. Applications of neuromorphic computing and sensing in smartphones and wearables-advantages, limitations and likelihood of market penetration by application.    171
  • Table 43. Applications of neuromorphic computing and sensing in smart homes and IoT devices- advantages, limitations and likelihood of market penetration by application.    172
  • Table 44. Applications of neuromorphic computing and sensing in Consumer Health and Wellness-- advantages, limitations and likelihood of market penetration by application.    173
  • Table 45. Applications of neuromorphic computing and sensing in Entertainment and Gaming-advantages, limitations and likelihood of market penetration by application.    174
  • Table 46. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Mobile and Consumer Applications (2024-2037), millions USD.           175
  • Table 47. Neuromorphic Computing and Sensing Applications in Automotive and Transportation: Use Cases, Players and Market Status, 2026–2037       177
  • Table 48. Applications of neuromorphic computing and sensing in Advanced Driver Assistance Systems (ADAS) -advantages, limitations and likelihood of market penetration by application. 179
  • Table 49. Applications of neuromorphic computing and sensing in Autonomous Vehicles and Robotaxis-advantages, limitations and likelihood of market penetration by application.           182
  • Table 50. Applications of neuromorphic computing and sensing in Vehicle infotainment and user experience-advantages, limitations and likelihood of market penetration by application.        183
  • Table 51. Applications of neuromorphic computing and sensing in Vehicle infotainment and user experience-advantages, limitations and likelihood of market penetration by application.        185
  • Table 52. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Automotive and Transportation (2024-2037), millions USD. 185
  • Table 53. Neuromorphic Computing and Sensing Applications in Industrial and Manufacturing: Use Cases, Players and Market Status, 2026–2037       187
  • Table 54. Applications of neuromorphic computing and sensing in Industrial IoT and smart factories-advantages, limitations and likelihood of market penetration by application.    189
  • Table 55. Applications of neuromorphic computing and sensing in Industrial IoT and smart factories-advantages, limitations and likelihood of market penetration by application.    190
  • Table 56. Applications of neuromorphic computing and sensing in Quality control and inspection-advantages, limitations and likelihood of market penetration by application.    192
  • Table 57. Applications of neuromorphic computing and sensing in Logistics and supply chain optimization-advantages, limitations and likelihood of market penetration by application.     193
  • Table 58. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Industrial and Manufacturing (2024-2037), millions USD. 194
  • Table 59. Neuromorphic Computing and Sensing Applications in Healthcare and Medical: Use Cases, Players and Market Status, 2026–2037        195
  • Table 60. Applications of neuromorphic computing and sensing in medical imaging and diagnostics-advantages, limitations and likelihood of market penetration by application.    198
  • Table 61. Applications of neuromorphic computing and sensing in Wearable health monitoring devices-advantages, limitations and likelihood of market penetration by application.    199
  • Table 62. Applications of neuromorphic computing and sensing in Personalized medicine and drug discovery-advantages, limitations and likelihood of market penetration by application.            200
  • Table 63. Applications of neuromorphic computing and sensing in Assistive technologies and prosthetics -advantages, limitations and likelihood of market penetration by application.       202
  • Table 64. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Healthcare and Medical Devices (2024-2037), millions USD.           203
  • Table 65. Neuromorphic Computing and Sensing Applications in Aerospace and Defence: Use Cases, Players and Market Status, 2026–2037        205
  • Table 66. Applications of neuromorphic computing and sensing in Unmanned Aerial Vehicles (UAVs) and drones-advantages, limitations and likelihood of market penetration by application.        207
  • Table 67. Applications of neuromorphic computing and sensing in Satellite imaging and remote sensing:-advantages, limitations and likelihood of market penetration by application.               209
  • Table 68. Applications of neuromorphic computing and sensing in Missile guidance and target recognition -advantages, limitations and likelihood of market penetration by application.       210
  • Table 69. Applications of neuromorphic computing and sensing in Cybersecurity and threat detection -advantages, limitations and likelihood of market penetration by application.    211
  • Table 70. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Aerospace and Defence (2024-2037), millions USD.              212
  • Table 71. Neuromorphic Computing and Sensing Applications in Data Centres and Cloud Computing: Use Cases, Players and Market Status, 2026–2037             213
  • Table 72. Applications of neuromorphic computing and sensing in High-performance computing and scientific simulations-advantages, limitations and likelihood of market penetration by application. 216
  • Table 73. Applications of neuromorphic computing and sensing in Big data analytics and machine learning-advantages, limitations and likelihood of market penetration by application.               217
  • Table 74. Applications of neuromorphic computing and sensing in Cloud-based AI services and platforms -advantages, limitations and likelihood of market penetration by application.          218
  • Table 75. Applications of neuromorphic computing and sensing in Energy-efficient datacenter infrastructure-advantages, limitations and likelihood of market penetration by application.  220
  • Table 76. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Datacenters and Cloud Services (2024-2037), millions USD.              221
  • Table 77. Market revenues for neuromorphic computing and sensing by region from 2024-2037 in millions USD. 222
  • Table 78. Neuromorphic Computing and Sensing Market Size and Forecast, in North America (2024-2037), millions USD. 223
  • Table 79. Neuromorphic Computing and Sensing Market Size and Forecast, in Europe (2024-2037), millions USD. 224
  • Table 80. Neuromorphic Computing and Sensing Market Size and Forecast, in Asia-Pacific (2024-2037), millions USD. 226
  • Table 81. Neuromorphic Computing and Sensing Market Size and Forecast, in the Rest of the World (2024-2037), millions USD.  227
  • Table 82. Neuromorphic Chip Manufacturers and Their Product Offerings.         230
  • Table 83. Neuromorphic Sensor Manufacturers and Their Product Offerings.    230
  • Table 84. Emerging Non-Volatile Memory (eNVM) Manufacturers and Their Product Offerings.              231
  • Table 85. Neuromorphic Software and Framework Providers and Their Solutions.         232
  • Table 86. Key Research Institutions and Academia in Neuromorphic Computing and Sensing.             233
  • Table 87. Competing Emerging Technologies for Neuromorphic Computing and Sensing.        235
  • Table 88. Technology Substitution Analysis.             240
  • Table 89. Comparative Advantages/Disadvantages.           241
  • Table 90. Companies profiled in this report.              243

 

List of Figures

  • Figure 1. Global Market for Neuromorphic Computing and Sensors, 2024–2037 (Billions USD).          57
  • Figure 2. Neuromorphic Computing and Sensing Technology Roadmap 2024–2037.   76
  • Figure 3. Market value chain for neuromorphic computing and sensing.               83
  • Figure 4. Neuromorphic Computing and Sensing Market Map 2026.       84
  • Figure 5. Evolution of the Main Hardware Technologies for Neuromorphic Computing (2000–2036). 101
  • Figure 6. Key materials in NVM technology for neuromorphic computing.            103
  • Figure 7. Advanced Memristive Materials for Neuromorphic Computing — Technology Readiness Comparison (2026). 104
  • Figure 8. Neural networks in autonomous vehicles.            115
  • Figure 9. Concept illustration of centralized and decentralized intelligence in robotics.             118
  • Figure 10. Neuromorphic programmable robot with dynamic vision developed by SynSense.                119
  • Figure 11. Comparison of High-Level Conventional and Neuromorphic Memory Architectures.            124
  • Figure 12. Spiking Neural Network (SNN) Structure and Operation.          125
  • Figure 13. IBM TrueNorth Processor.              132
  • Figure 14. Event-Based Sensor Operation and Data Processing Flow.     152
  • Figure 15. Conventional sensor vs. Event-based sensor.  152
  • Figure 16. Operation of neuromorphic vision sensors.       153
  • Figure 17. Cyranose 320 Electronic Nose.  154
  • Figure 18. Alpix-Pilatus platform, an integrated event-based vision sensor that combines static and dynamic information.              156
  • Figure 19. Application Market Penetration Timeline             169
  • Figure 20. Technology Roadmap for Neuromorphic Computing and Sensing in Mobile and Consumer Applications (2024–2036).   171
  • Figure 21. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Mobile and Consumer Applications (2024-2037), millions USD.           176
  • Figure 22. Technology Roadmap for Neuromorphic Computing and Sensing in Automotive and Transportation (2024–2036).               178
  • Figure 23. Sensors used by the ADAS (Advanced Driver-Assistance System).    179
  • Figure 24. Enabling technologies for autonomous vehicles.           181
  • Figure 25. Autonomous Vehicle Architecture with Neuromorphic Computing and Sensing.    182
  • Figure 26. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Automotive and Transportation (2024-2037), millions USD. 186
  • Figure 27. Technology Roadmap for Neuromorphic Computing and Sensing in Industrial and Manufacturing (2024–2036).               188
  • Figure 28. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Industrial and Manufacturing (2024-2037), millions USD. 195
  • Figure 29. Technology Roadmap for Neuromorphic Computing and Sensing in Healthcare and Medical Devices (2024–2036).              197
  • Figure 30. Wearable Medical Devices with Neuromorphic Computing and Sensing Capabilities.        199
  • Figure 31. Flexible neuromorphic electronics for neuromorphic computing, humanoid robotics, and neuroprosthetics.       202
  • Figure 32. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Healthcare and Medical Devices (2024-2037), millions USD.           204
  • Figure 33. Technology Roadmap for Neuromorphic Computing and Sensing in Aerospace and Defence (2024–2036). 206
  • Figure 34. Schematic route from bio-inspired behaviours toward neuromorphic sensors for autonomous flight.    207
  • Figure 35. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Aerospace and Defence (2024-2037), millions USD.              213
  • Figure 36. Technology Roadmap for Neuromorphic Computing and Sensing in Datacenters and Cloud Services (2024–2036).            215
  • Figure 37. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Datacenters and Cloud Services (2024-2037), millions USD.              222
  • Figure 38. Global Neuromorphic Computing and Sensing Market Size and Forecast, in North America (2024-2037), millions USD.  224
  • Figure 39. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Europe (2024-2037), millions USD. 225
  • Figure 40. Global Neuromorphic Computing and Sensing Market Size and Forecast, Asia-Pacific (2024-2037), millions USD. 227
  • Figure 41. Global Neuromorphic Computing and Sensing Market Size and Forecast, in in the Rest of the World (2024-2037), millions USD.   228
  • Figure 42. Neuromorphic Computing and Sensing Ecosystem Overview.             229
  • Figure 43. Cerebras WSE-2. 336
  • Figure 44. DEEPX NPU DX-GEN1.     368
  • Figure 45. Google TPU.            402
  • Figure 46. GrAI VIP.     408
  • Figure 47. Groq Tensor Streaming Processor (TSP).              417
  • Figure 48. DVL-5000 neuromorphic laser profiler. 441
  • Figure 49. Spiking Neural Processor               444
  • Figure 50. TROOPER robot.   448
  • Figure 51. 11th Gen Intel® Core™ S-Series. 451
  • Figure 52. Intel Loihi 2 chip.  451
  • Figure 53. Envise.        474
  • Figure 54. Pentonic 2000.      487
  • Figure 55. Azure Maia 100 and Cobalt 100 chips.  502
  • Figure 56. Mythic MP10304 Quad-AMP PCIe Card.              511
  • Figure 57. Nvidia H200 AI chip.           553
  • Figure 58. Grace Hopper Superchip.               553
  • Figure 59. Prophesee Metavision starter kit – AMD Kria KV260 and active marker LED board. 578
  • Figure 60. Cloud AI 100.         582
  • Figure 61. Overview of SpiNNaker2 architecture for the ”SpiNNcloud” cloud system and edge systems.                644
  • Figure 62. Untether AI chip.  684

 

Purchasers will receive the following:

  • PDF report download/by email.
  • Comprehensive Excel spreadsheet of all data including data on all investments & deals segmented by technology, sub-sector, government, region, and company
  • Mid-year Update

 

The Global Neuromorphic Computing & Sensing Market 2027-2037
The Global Neuromorphic Computing & Sensing Market 2027-2037
PDF + Excel Database.
Price: £1,100.00

The Global Neuromorphic Computing & Sensing Market 2027-2037
The Global Neuromorphic Computing & Sensing Market 2027-2037
PDF + Excel Database + Print Edition (including tracked delivery).
Price: £1,200.00

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