PUBLISHER: Global Market Insights Inc. | PRODUCT CODE: 1517624
PUBLISHER: Global Market Insights Inc. | PRODUCT CODE: 1517624
Neuromorphic Computing Market, By Component (Hardware, Software, Services), By Deployment (Edge, Cloud), By Application (Image recognition, Signal recognition, Data mining) By End-use Industry & Forecast, 2024 - 2032
Neuromorphic Computing Market size is projected to record over 25.5% CAGR from 2024 to 2032, driven by rapid advances with insights from neuroscience and the rise of edge computing. Of late, researchers are integrating principles inspired by neural networks of the brain into hardware and software designs for enhancing computational efficiency and mimicking cognitive processes. The shift towards edge computing is also accelerating this progress by enabling real-time data processing and reducing latency, adding to the industry growth. For instance, in May 2024, SpiNNcloud Systems launched SpiNNaker2 for advancing neuromorphic computing for hybrid AI systems. This platform enhances computational capabilities by simulating neural networks to achieve more efficient and scalable AI processing.
The overall market is segregated into component, deployment, application, end-use industry, and region.
In terms of component, the neuromorphic computing market from the software segment is expected to record significant CAGR from 2024 to 2032. Neuromorphic computing software are evolving to harness brain-inspired algorithms for enhanced processing capabilities. These algorithms mimic neural networks while allowing efficient pattern recognition and learning tasks. Researchers and developers are also refining these software frameworks to optimize performance and scalability in AI applications.
By deployment, the neuromorphic computing industry from the cloud segment is projected to rise from 2024 to 2032.Cloud platforms are facilitating the development and deployment of neuromorphic models for enabling researchers to simulate complex neural networks and optimize algorithms for AI applications. These platforms are also improving by integrating enhanced processing power and storage capabilities for supporting real-time data analysis and training of AI models. Lately, cloud technology is also employed for enhancing the scalability and efficiency of neuromorphic computing for enabling broader adoption across industries as well as accelerating the development of intelligent systems and autonomous technologies.
Regionally, the Asia Pacific neuromorphic computing market size is projected to exhibit robust growth between 2024 and 2032, fueled by increasing usage in military and defense applications for driving investments. Research initiatives are helping in integrating neuromorphic principles into hardware and software solutions to improve sensor processing, surveillance, and cybersecurity capabilities. As investments in defense technology are increasing, APAC will witness the adoption of neuromorphic computing solutions into critical defense systems for bolstering national security and advancing capabilities in AI-driven defense technologies.
Table of Contents
Chapter 1 Methodology & Scope
- 1.1 Market scope & definition
- 1.2 Base estimates & calculations
- 1.3 Forecast calculation
- 1.4 Data sources
- 1.4.1 Primary
- 1.4.2 Secondary
- 1.4.2.1 Paid sources
- 1.4.2.2 Public sources
Chapter 2 Executive Summary
- 2.1 Industry 360 degree synopsis, 2021 - 2032
Chapter 3 Industry Insights
- 3.1 Industry ecosystem analysis
- 3.2 Vendor matrix
- 3.3 Profit margin analysis
- 3.4 Technology & innovation landscape
- 3.5 Patent analysis
- 3.6 Key news and initiatives
- 3.7 Regulatory landscape
- 3.8 Impact forces
- 3.8.1 Growth drivers
- 3.8.1.1 Mimicking brain's efficiency and parallel processing capabilities
- 3.8.1.2 Enhanced energy efficiency compared to conventional computing architectures
- 3.8.1.3 Potential for breakthroughs in AI and machine learning applications
- 3.8.1.4 Scalability for handling large-scale neural network simulations
- 3.8.1.5 Growing demand for brain-inspired computing solutions
- 3.8.2 Industry pitfalls & challenges
- 3.8.2.1 Complexity in designing and programming neuromorphic systems
- 3.8.2.2 Limited compatibility with existing software and hardware infrastructures
- 3.8.1 Growth drivers
- 3.9 Growth potential analysis
- 3.10 Porter's analysis
- 3.10.1 Supplier power
- 3.10.2 Buyer power
- 3.10.3 Threat of new entrants
- 3.10.4 Threat of substitutes
- 3.10.5 Industry rivalry
- 3.11 PESTEL analysis
Chapter 4 Competitive Landscape, 2023
- 4.1 Introduction
- 4.2 Company market share analysis
- 4.3 Competitive positioning matrix
- 4.4 Strategic outlook matrix
Chapter 5 Market Estimates & Forecast, By Component, 2021 - 2032 (USD Million)
- 5.1 Key trends
- 5.2 Hardware
- 5.3 Software
- 5.4 Services
Chapter 6 Market Estimates & Forecast, By Deployment, 2021 - 2032 (USD Million)
- 6.1 Key trends
- 6.2 Edge
- 6.3 Cloud
Chapter 7 Market Estimates & Forecast, By Application, 2021 - 2032 (USD Million)
- 7.1 Key trends
- 7.2 Image recognition
- 7.3 Signal recognition
- 7.4 Data mining
- 7.5 Others
Chapter 8 Market Estimates & Forecast, By End-Use Industry, 2021 - 2032 (USD Million)
- 8.1 Key trends
- 8.2 Consumer electronics
- 8.3 Automotive
- 8.4 Healthcare
- 8.5 Military & Defense
- 8.6 Industrial
- 8.7 Others
Chapter 9 Market Estimates & Forecast, By Region, 2021 - 2032 (USD Million)
- 9.1 Key trends
- 9.2 North America
- 9.2.1 U.S.
- 9.2.2 Canada
- 9.3 Europe
- 9.3.1 UK
- 9.3.2 Germany
- 9.3.3 France
- 9.3.4 Italy
- 9.3.5 Spain
- 9.3.6 Rest of Europe
- 9.4 Asia Pacific
- 9.4.1 China
- 9.4.2 India
- 9.4.3 Japan
- 9.4.4 South Korea
- 9.4.5 ANZ
- 9.4.6 Rest of Asia Pacific
- 9.5 Latin America
- 9.5.1 Brazil
- 9.5.2 Mexico
- 9.5.3 Rest of Latin America
- 9.6 MEA
- 9.6.1 UAE
- 9.6.2 South Africa
- 9.6.3 Saudi Arabia
- 9.6.4 Rest of MEA
Chapter 10 Company Profiles
- 10.1 Applied Brain Research
- 10.2 Cerebras Systems
- 10.3 General Vision
- 10.4 HP Enterprise
- 10.5 IBM Corporation
- 10.6 Intel Corporation
- 10.7 Knowm Inc.
- 10.8 Numenta
- 10.9 Qualcomm
- 10.10 Vicarious
