The Global Market for Neuromorphic Computing and Sensing 2024-2035

July 2024 | 316 pages | ID: GD14574A8B62EN
Future Markets, Inc.

Abstracts

Neuromorphic computing and sensing focuses on developing technologies inspired by the structure and function of the human brain. This market aims to create more efficient, adaptive, and intelligent systems that can process information in ways similar to biological neural networks. Neuromorphic technologies have the potential to revolutionize various industries and applications, including artificial intelligence (AI), edge computing, autonomous systems, and sensing. The neuromorphic computing and sensing market is driven by the increasing demand for energy-efficient and real-time processing solutions, particularly in edge devices and IoT applications. Neuromorphic systems offer several advantages over traditional computing approaches, such as low latency, high scalability, and the ability to learn and adapt to new situations. Key application areas for neuromorphic computing and sensing include:

• Edge AI and IoT: Neuromorphic technologies enable more efficient and intelligent processing of data at the edge, reducing the need for cloud connectivity and improving privacy and security.
• Autonomous vehicles and robotics: Neuromorphic systems can enable real-time decision-making, object recognition, and navigation in autonomous vehicles and robots.
• Cybersecurity and anomaly detection: The ability of neuromorphic systems to learn and adapt to new patterns makes them well-suited for detecting anomalies and potential threats in cyber systems.
• Smart sensors and monitoring systems: Neuromorphic sensors can efficiently capture and process data in various applications, such as industrial monitoring, environmental sensing, and smart city infrastructure.
• High-performance computing and scientific simulations: Neuromorphic technologies can accelerate complex computations and simulations in fields like climate modeling, drug discovery, and materials science.

The neuromorphic computing and sensing market is expected to grow significantly in the coming years, driven by advancements in technology, increasing adoption across various industries, and the need for more efficient and intelligent computing solutions.

The Global Market for Neuromorphic Computing and Sensing 2024-2035 offers in-depth insights into the rapidly evolving field of neuromorphic technologies and their transformative impact on artificial intelligence, edge computing, and autonomous systems. This extensive study provides a detailed analysis of the neuromorphic computing and sensing market, including key trends, growth drivers, challenges, and future opportunities. The report explores the diverse applications and industries adopting neuromorphic technologies, such as edge AI and IoT, autonomous vehicles and robotics, cybersecurity, smart sensors, and high-performance computing. It also examines the competitive landscape, highlighting major players in neuromorphic chip manufacturing, sensor development, emerging non-volatile memory solutions, and software and framework provision.

One of the key features of this report is the market size and forecast data segmented by application, market, and region, providing a holistic view of the market's growth potential. The report delves into the technical aspects of neuromorphic computing and sensing, covering spiking neural networks, event-based sensors, memory architectures, hardware and processor designs, and software and frameworks. Additionally, the report identifies critical challenges and opportunities facing the neuromorphic industry, including scalability, standardization, algorithm development, power management, data privacy, and security. It also explores emerging trends such as hybrid neuromorphic-conventional systems, edge AI, quantum computing, explainable AI, and brain-computer interfaces.

The report also includes a comprehensive analysis of the market value chain, funding and investments, strategic partnerships, and collaborations within the neuromorphic industry. It also addresses the regulatory and ethical considerations surrounding neuromorphic technologies.

With over 140 company profiles, The Global Market for Neuromorphic Computing and Sensing 2024-2035 offers valuable insights for technology providers, manufacturers, end-users, investors, and policymakers looking to understand and capitalize on the immense potential of neuromorphic technologies in shaping the future of AI, edge computing, and autonomous systems. The neuromorphic computing and sensing market is characterized by a growing ecosystem of technology providers, manufacturers, research institutions, and end-users. Major players in this market include established semiconductor companies, startups, and academic and research organizations. Companies profiled include Aspinity, BrainChip, Celestial AI, DeepCube, Deeplite, Expedera, Huawei, IBM, iniVation, Innatera, Instar-Robotics, Intrinsic, Microsoft, Oculi, Perceive, POLYN, Prophesee, Qualcomm, Rain AI, SpiNNcloud Systems, SynSense, Syntiant, and Voxel Sensors.

Contents

1 EXECUTIVE SUMMARY

1.1 Overview of the neuromorphic computing and sensing market
  1.1.1 Global Market Revenues 2024-2035
  1.1.2 Market segmentation
1.2 Ending of Moore’s Law
1.3 Historical market
1.4 The market in 2024
1.5 Key market trends and growth drivers
1.6 Market challenges and limitations
1.7 Future outlook and opportunities
  1.7.1 Emerging trends
    1.7.1.1 Hybrid Neuromorphic-Conventional Computing and Sensing Systems
    1.7.1.2 Edge AI and IoT
    1.7.1.3 Quantum Computing
    1.7.1.4 Explainable AI
    1.7.1.5 Brain-Computer Interfaces
    1.7.1.6 New Application Areas and Use Cases
    1.7.1.7 Disruptive Business Models and Services
    1.7.1.8 Collaborative Ecosystem Development
    1.7.1.9 Skill Development and Workforce Training
  1.7.2 Technology roadmap
1.8 Neuromorphic computing and generative AI
1.9 Market value chain
1.10 Market map
1.11 Funding and investments
1.12 Strategic Partnerships and Collaborations
1.13 Regulatory and Ethical Considerations
  1.13.1 Data Privacy and Security
  1.13.2 Bias and Fairness in Neuromorphic Systems
  1.13.3 Intellectual Property and Patent Landscape
  1.13.4 Environmental Impact and Sustainability

2 INTRODUCTION

2.1 Definition and concept of neuromorphic computing and sensing
2.2 Main neuromorphic approaches
  2.2.1 Large-scale hardware neuromorphic computing systems
  2.2.2 Non-volatile memory technologies
  2.2.3 Advanced memristive materials and devices
2.3 Comparison with traditional computing and sensing approaches
2.4 Neuromorphic computing vs. quantum computing
2.5 Key features and advantages
  2.5.1 Low latency and real-time processing
  2.5.2 Power efficiency and energy savings
  2.5.3 Scalability and adaptability
  2.5.4 Online learning and autonomous decision-making
2.6 Markets and Applications
  2.6.1 Edge AI and IoT
  2.6.2 Autonomous Vehicles and Robotics
  2.6.3 Cybersecurity and Anomaly Detection
  2.6.4 Smart Sensors and Monitoring Systems
  2.6.5 Datacenter and High-Performance Computing

3 NEUROMORPHIC COMPUTING TECHNOLOGIES AND ARCHITECTURE

3.1 Spiking Neural Networks (SNNs)
  3.1.1 Biological inspiration and principles
  3.1.2 Types of SNNs and their characteristics
  3.1.3 Advantages and limitations of SNNs
3.2 Memory Architectures for Neuromorphic Computing
  3.2.1 Conventional memory approaches (SRAM, DRAM)
  3.2.2 Emerging non-volatile memory (eNVM) technologies
    3.2.2.1 Phase-Change Memory (PCM)
    3.2.2.2 Resistive RAM (RRAM)
    3.2.2.3 Magnetoresistive RAM (MRAM)
    3.2.2.4 Ferroelectric RAM (FeRAM)
  3.2.3 In-memory computing and near-memory computing
  3.2.4 Hybrid memory architectures
3.3 Neuromorphic Hardware and Processors
  3.3.1 Digital neuromorphic processors
  3.3.2 Analog neuromorphic processors
  3.3.3 Mixed-signal neuromorphic processors
  3.3.4 FPGA-based neuromorphic systems
  3.3.5 Neuromorphic accelerators and co-processors
3.4 Software and Frameworks for Neuromorphic Computing
  3.4.1 Neuromorphic programming languages and tools
  3.4.2 Neuromorphic simulation platforms and frameworks
  3.4.3 Neuromorphic algorithm libraries and repositories
  3.4.4 Neuromorphic software development kits (SDKs)

4 NEUROMORPHIC SENSING TECHNOLOGIES AND ARCHITECTURES

4.1 Event-Based Sensors and Processing
  4.1.1 Neuromorphic vision sensors
  4.1.2 Neuromorphic auditory sensors
  4.1.3 Neuromorphic olfactory sensors
  4.1.4 Event-driven processing and algorithms
4.2 Hybrid Sensing Approaches
  4.2.1 Combination of conventional and event-based sensors
  4.2.2 Fusion of multiple sensing modalities
  4.2.3 Advantages and challenges of hybrid sensing
4.3 Neuromorphic Sensor Architectures and Designs
  4.3.1 Pixel-level processing and computation
  4.3.2 Sensor-processor co-design and integration
  4.3.3 Bio-inspired sensor designs and materials
4.4 Signal Processing and Feature Extraction Techniques
  4.4.1 Spike-based Encoding and Decoding
  4.4.2 Temporal and Spatiotemporal Feature Extraction
  4.4.3 Neuromorphic Filtering and Denoising
  4.4.4 Adaptive and Learning-Based Processing

5 MARKET ANALYSIS AND FORECASTS

5.1 Mobile and Consumer Applications
  5.1.1 Smartphones and wearables
  5.1.2 Smart home and IoT devices
  5.1.3 Consumer health and wellness
  5.1.4 Entertainment and gaming
5.2 Automotive and Transportation
  5.2.1 Advanced Driver Assistance Systems (ADAS)
  5.2.2 Autonomous vehicles and robotaxis
  5.2.3 Vehicle infotainment and user experience
  5.2.4 Smart traffic management and infrastructure
5.3 Industrial and Manufacturing
  5.3.1 Industrial IoT and smart factories
  5.3.2 Predictive maintenance and anomaly detection
  5.3.3 Quality control and inspection
  5.3.4 Logistics and supply chain optimization
5.4 Healthcare and Medical Devices
  5.4.1 Medical imaging and diagnostics
  5.4.2 Wearable health monitoring devices
  5.4.3 Personalized medicine and drug discovery
  5.4.4 Assistive technologies and prosthetics
5.5 Aerospace and Defense
  5.5.1 Unmanned Aerial Vehicles (UAVs) and drones
  5.5.2 Satellite imaging and remote sensing
  5.5.3 Missile guidance and target recognition
  5.5.4 Cybersecurity and threat detection:
5.6 Datacenters and Cloud Services
  5.6.1 High-performance computing and scientific simulations:
  5.6.2 Big data analytics and machine learning
  5.6.3 Cloud-based AI services and platforms
  5.6.4 Energy-efficient datacenter infrastructure
5.7 Regional Market Analysis and Forecasts
  5.7.1 North America
  5.7.2 Europe
  5.7.3 Asia-Pacific
  5.7.4 Rest of the World
5.8 Competitive Landscape and Key Players
  5.8.1 Overview of the Neuromorphic Computing and Sensing Ecosystem
  5.8.2 Neuromorphic Chip Manufacturers and Processors
  5.8.3 Neuromorphic Sensor Manufacturers
  5.8.4 Emerging Non-Volatile Memory (eNVM) Manufacturers
  5.8.5 Neuromorphic Software and Framework Providers
  5.8.6 Research Institutions and Academia

6 COMPANY PROFILES 167 (141 COMPANY PROFILES)

7 RESEARCH SCOPE & METHODOLOGY

8 REFERENCES

List Of Tables

LIST OF TABLES

Table 1. Overview of the neuromorphic computing and sensing market.
Table 2. Global market for neuromorphic computing and sensors, 2024-2035 (Millions USD).
Table 3. Neuromorphic Computing and Sensing Market Segmentation 2020-2035.
Table 4. Key market trends and growth drivers.
Table 5. Market challenges and limitations.
Table 6. Neuromorphic computing and generative AI strategies.
Table 7. Funding and investments in neuromorphic computing and sensing.
Table 8. Strategic Partnerships and Collaborations in the Neuromorphic Industry.
Table 9. Regulatory and Ethical Considerations of neuromorphic computing & sensing.
Table 10. Main neuromorphic sensing approaches.
Table 11. Main Neuromorphic Computing Approaches.
Table 12. Resistive Non-Volatile Memory (NVM) Technologies.
Table 13. Advanced Memristive Materials, Devices, and Novel Computation Concepts.
Table 14. Comparison with traditional computing and sensing approaches.
Table 15. Comparison between neuromorphic and quantum computing.
Table 16. Key features and advantages of neuromorphic computing and sensing.
Table 17. Markets and Applications of neuromorphic computing and sensing.
Table 18. Von neumann architecture versus neuromorphic architecture.
Table 19. Types of SNNs and their characteristics.
Table 20. Advantages and limitations of SNNs.
Table 21. Conventional memory approaches (SRAM, DRAM).
Table 22. Emerging non-volatile memory (eNVM) technologies.
Table 23. Hybrid memory architectures.
Table 24. Neuromorphic accelerators and co-processors.
Table 25. Neuromorphic programming languages and tools.
Table 26. Neuromorphic simulation platforms and frameworks.
Table 27. Neuromorphic algorithm libraries and repositories.
Table 28. Neuromorphic software development kits (SDKs).
Table 29. Hybrid sensing approaches.
Table 30. Advantages and challenges of hybrid sensing.
Table 31. Bio-inspired sensor designs and materials.
Table 32. Signal Processing and Feature Extraction Techniques.
Table 33. Applications of neuromorphic computing and sensing in smartphones and wearables-advantages, limitations and likelihood of market penetration by application.
Table 34. Applications of neuromorphic computing and sensing in smart homes and IoT devices- advantages, limitations and likelihood of market penetration by application.
Table 35. Applications of neuromorphic computing and sensing in Consumer Health and Wellness-- advantages, limitations and likelihood of market penetration by application.
Table 36. Applications of neuromorphic computing and sensing in Entertainment and Gaming-advantages, limitations and likelihood of market penetration by application.
Table 37. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Mobile and Consumer Applications (2024-2035), millions USD.
Table 38. Applications of neuromorphic computing and sensing in Advanced Driver Assistance Systems (ADAS) -advantages, limitations and likelihood of market penetration by application.
Table 39. Applications of neuromorphic computing and sensing in Autonomous Vehicles and Robotaxis-advantages, limitations and likelihood of market penetration by application.
Table 40. Applications of neuromorphic computing and sensing in Vehicle infotainment and user experience-advantages, limitations and likelihood of market penetration by application.
Table 41. Applications of neuromorphic computing and sensing in Vehicle infotainment and user experience-advantages, limitations and likelihood of market penetration by application.
Table 42. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Automotive and Transportation (2024-2035), millions USD.
Table 43. Applications of neuromorphic computing and sensing in Industrial IoT and smart factories-advantages, limitations and likelihood of market penetration by application.
Table 44. Applications of neuromorphic computing and sensing in Industrial IoT and smart factories-advantages, limitations and likelihood of market penetration by application.
Table 45. Applications of neuromorphic computing and sensing in Quality control and inspection-advantages, limitations and likelihood of market penetration by application.
Table 46. Applications of neuromorphic computing and sensing in Logistics and supply chain optimization-advantages, limitations and likelihood of market penetration by application.
Table 47. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Industrial and Manufacturing (2024-2035), millions USD.
Table 48. Applications of neuromorphic computing and sensing in medical imaging and diagnostics-advantages, limitations and likelihood of market penetration by application.
Table 49. Applications of neuromorphic computing and sensing in Wearable health monitoring devices-advantages, limitations and likelihood of market penetration by application.
Table 50. Applications of neuromorphic computing and sensing in Personalized medicine and drug discovery-advantages, limitations and likelihood of market penetration by application.
Table 51. Applications of neuromorphic computing and sensing in Assistive technologies and prosthetics -advantages, limitations and likelihood of market penetration by application.
Table 52. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Healthcare and Medical Devices (2024-2035), millions USD.
Table 53. Applications of neuromorphic computing and sensing in Unmanned Aerial Vehicles (UAVs) and drones-advantages, limitations and likelihood of market penetration by application.
Table 54. Applications of neuromorphic computing and sensing in Satellite imaging and remote sensing:-advantages, limitations and likelihood of market penetration by application.
Table 55. Applications of neuromorphic computing and sensing in Missile guidance and target recognition -advantages, limitations and likelihood of market penetration by application.
Table 56. Applications of neuromorphic computing and sensing in Cybersecurity and threat detection -advantages, limitations and likelihood of market penetration by application.
Table 57. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Aerospace and Defence (2024-2035), millions USD.
Table 58. Applications of neuromorphic computing and sensing in High-performance computing and scientific simulations-advantages, limitations and likelihood of market penetration by application.
Table 59. Applications of neuromorphic computing and sensing in Big data analytics and machine learning-advantages, limitations and likelihood of market penetration by application.
Table 60. Applications of neuromorphic computing and sensing in Cloud-based AI services and platforms -advantages, limitations and likelihood of market penetration by application.
Table 61. Applications of neuromorphic computing and sensing in Energy-efficient datacenter infrastructure-advantages, limitations and likelihood of market penetration by application.
Table 62. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Datacenters and Cloud Services (2024-2035), millions USD.
Table 63. Market revenues for neuromorphic computing and sensing by region from 2024-2035 in millions USD.
Table 64. Neuromorphic Computing and Sensing Market Size and Forecast, in North America (2024-2035), millions USD.
Table 65. Neuromorphic Computing and Sensing Market Size and Forecast, in Europe (2024-2035), millions USD.
Table 66. Neuromorphic Computing and Sensing Market Size and Forecast, in Asia-Pacific (2024-2035), millions USD.
Table 67. Neuromorphic Computing and Sensing Market Size and Forecast, in the Rest of the World (2024-2035), millions USD.
Table 68. Neuromorphic Chip Manufacturers and Their Product Offerings.
Table 69. Neuromorphic Sensor Manufacturers and Their Product Offerings.
Table 70. Emerging Non-Volatile Memory (eNVM) Manufacturers and Their Product Offerings.
Table 71. Neuromorphic Software and Framework Providers and Their Solutions.
Table 72. Key Research Institutions and Academia in Neuromorphic Computing and Sensing.
Table 73. Evolution of Apple Neural Engine.
Table 74. Dynex subscription plans.

List Of Figures

LIST OF FIGURES

Figure 1. Global market for neuromorphic computing and sensors, 2023-2035 (Millions USD).
Figure 2. Neuromorphic Computing and Sensing Market Segmentation 2020-2035.
Figure 3. Neuromorphic computing and sensing technology roadmap.
Figure 4. Market value chain for neuromorphic computing and sensing.
Figure 5. Neuromorphic computing and sensing market map.
Figure 6. Evolution of the main hardware technologies for neuromorphic computing.
Figure 7. Key materials in NVM technology for neuromorphic computing.
Figure 8. Advanced memristive materials for neuromorphic computing.
Figure 9. Neural networks in autonomous vehicles.
Figure 10. Concept illustration of centralized and decentralized intelligence in robotics.
Figure 11. Neuromorphic programmable robot with dynamic vision developed by SynSense.
Figure 12. Comparison of High-Level Conventional and Neuromorphic Memory Architectures.
Figure 13. Spiking Neural Network (SNN) Structure and Operation.
Figure 14. IBM TrueNorth Processor.
Figure 15. Event-Based Sensor Operation and Data Processing Flow.
Figure 16. Conventional sensor vs. Event-based sensor.
Figure 17. Operation of neuromorphic vision sensors.
Figure 18. Cyranose 320 Electronic Nose.
Figure 19. Alpix-Pilatus platform, an integrated event-based vision sensor that combines static and dynamic information.
Figure 20. Technology roadmap for neuromorphic computing and sensing in mobile and consumer applications.
Figure 21. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Mobile and Consumer Applications (2024-2035), millions USD.
Figure 22. Technology Roadmap for Neuromorphic Computing and Sensing in Automotive and Transportation.
Figure 23. Sensors used by the ADAS (Advanced Driver-Assistance System).
Figure 24. Enabling technologies for autonomous vehicles.
Figure 25. Autonomous Vehicle Architecture with Neuromorphic Computing and Sensing.
Figure 26. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Automotive and Transportation (2024-2035), millions USD.
Figure 27. Technology roadmap for neuromorphic computing and sensing in industrial and manufacturing.
Figure 28. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Industrial and Manufacturing (2024-2035), millions USD.
Figure 29. Technology roadmap for neuromorphic computing and sensing in healthcare and medical devices.
Figure 30. Wearable Medical Devices with Neuromorphic Computing and Sensing Capabilities.
Figure 31. Flexible neuromorphic electronics for neuromorphic computing, humanoid robotics, and neuroprosthetics.
Figure 32. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Healthcare and Medical Devices (2024-2035), millions USD.
Figure 33. Technology roadmap for neuromorphic computing and sensing in aerospace and defense.
Figure 34. Schematic route from bio-inspired behaviours toward neuromorphic sensors for autonomous flight.
Figure 35. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Aerospace and Defence (2024-2035), millions USD.
Figure 36. Technology roadmap for neuromorphic computing and sensing in Datacenters and Cloud Services.
Figure 37. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Datacenters and Cloud Services (2024-2035), millions USD.
Figure 38. Global Neuromorphic Computing and Sensing Market Size and Forecast, in North America (2024-2035), millions USD.
Figure 39. Global Neuromorphic Computing and Sensing Market Size and Forecast, in Europe (2024-2035), millions USD.
Figure 40. Global Neuromorphic Computing and Sensing Market Size and Forecast, Asia-Pacific (2024-2035), millions USD.
Figure 41. Global Neuromorphic Computing and Sensing Market Size and Forecast, in in the Rest of the World (2024-2035), millions USD.
Figure 42. Neuromorphic Computing and Sensing Ecosystem Overview.
Figure 43. Cerebas WSE-2.
Figure 44. DeepX NPU DX-GEN1.
Figure 45. Google TPU.
Figure 46. GrAI VIP.
Figure 47. Groq Tensor Streaming Processor (TSP).
Figure 48. DVL-5000 neuromorphic laser profiler.
Figure 49. Spiking Neural Processor
Figure 50. TROOPER robot.
Figure 51. 11th Gen Intel® Core™ S-Series.
Figure 52. Intel Loihi 2 chip.
Figure 53. Envise.
Figure 54. Pentonic 2000.
Figure 55. Azure Maia 100 and Cobalt 100 chips.
Figure 56. Mythic MP10304 Quad-AMP PCIe Card.
Figure 57. Nvidia H200 AI chip.
Figure 58. Grace Hopper Superchip.
Figure 59. Prophesee Metavision starter kit – AMD Kria KV260 and active marker LED board.
Figure 60. Cloud AI 100.
Figure 61. Overview of SpiNNaker2 architecture for the ”SpiNNcloud” cloud system and edge systems.
Figure 62. Untether AI chip.