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

Neuromorphic Computing Market was valued at over USD 5 billion in 2023 and is expected to register a CAGR of over 25.5% between 2024 and 2032. The capacity to conduct large-scale neural network simulations makes scalability a key growth driver for the neuromorphic computing sector.
 

Scalable neuromorphic systems provide the flexibility to increase computational capacity without losing efficiency as demand rises for processing massive volumes of data in AI and machine learning applications. Neuromorphic computing is an appealing option for sectors requiring sophisticated, high-performance computing capabilities because of its scalability, which guarantees adaptation to changing computational needs. In September 2022, Intel Corporation collaborated with the Italian Institute of Technology and the Technical University of Munich to introduce a new neural network-oriented object learning method. This partnership aims to use neuromorphic computing through an interactive online object-learning approach to enable robots to learn new objects instance with better speed and accuracy after deployment.
 

The need for effective and scalable substitutes for traditional computer architectures is the driving force behind the increasing demand for brain-inspired computing solutions. The growing dependence of industries on artificial intelligence and machine learning applications has made it apparent that systems that emulate the brain's energy efficiency and parallel processing capacity are essential. As businesses look for cutting-edge solutions for challenging real-time data processing problems and complicated computational activities, neuromorphic computing is expected to expand in popularity as it provides viable paths for meeting these needs.
 

A major obstacle in the market is the complexity of designing and programming neuromorphic devices. Neuromorphic computer designs imitate the complex neural networks seen in the brain, in contrast to standard computing structures, which use organized algorithms. Some prerequisites include hardware engineering, computer science, and neuroscience expertise. It is challenging to design effective algorithms and translate them onto hardware, which lengthens development cycles and raises costs. This intricacy may prevent widespread acceptance and restrict the market's potential for expansion.
 

Neuromorphic Computing Market Trends

The market for neuromorphic computing is expanding quickly as companies look for machine learning and AI solutions that are more effective. Neuromorphic systems provide increased processing power and energy efficiency by modeling the structure of the brain. In order to address the computational demands of complicated tasks while maximizing energy usage, neuromorphic computing presents a possible solution. The demand for advanced AI applications is expanding across industries, including healthcare, finance, and automotive.
 

By integrating neuromorphic computing with edge computing, data processing capabilities in real-time are brought to the network's edge, negating the need for data transmission to centralized servers. To reduce latency and enable faster response times for important applications like autonomous vehicles, industrial automation, and augmented reality, calculations are carried out closer to data sources such as IoT devices or sensors.
 

Neuromorphic Computing Market Analysis

Based on component, the market is divided into hardware, software, and services. The hardware segment is expected to reach over USD 23.5 billion by 2032.
 

• Hardware components are experiencing growth in the neuromorphic computing market due to increasing demand for specialized chips and processors tailored to mimic the brain's neural networks.
   
• These components are essential for implementing efficient and scalable neuromorphic systems. Advancements in hardware technologies, such as neuromorphic chips with spiking neural networks and memristors, are driving innovation and expanding the capabilities of neuromorphic computing, thus fueling market growth.
   

Based on deployment, the market is segmented into edge and cloud. The edge segment is expected to register a CAGR of over 31% over the forecast period.
 

• Edge deployment brings computing resources closer to data sources, reducing the time it takes for data to travel to centralized servers and back. This is crucial for applications requiring real-time processing, such as autonomous vehicles and industrial automation.
   
• Edge computing minimizes the need to transmit sensitive data over networks, enhancing privacy and security by keeping data closer to its source and reducing exposure to potential cyber threats.
   

North America dominated the global market in 2023 with over 30% of the total revenue share. The neuromorphic computing market is expanding in North America because of the region's strong ecosystem of tech firms, top research universities, and significant investments in the semiconductor and artificial intelligence sectors. The area also gains from a highly trained labor pool, conducive regulatory frameworks, and robust government backing for R&D projects. All of these elements work together to make the region a leader in neuromorphic computing technology adoption and innovation, which supports the industry's expansion in North America.
 

Neuromorphic Computing Market Share

Intel Corporation and IBM Corporation held a significant share of over 15% in the neuromorphic computing industry in 2023. Intel Corporation is a leading provider of neuromorphic computing solutions, leveraging its expertise in semiconductor technologies. The company offers neuromorphic chips and platforms tailored for AI and machine learning applications. Intel's products enable efficient processing of complex data with low power consumption, driving advancements in areas such as edge computing, autonomous systems, and pattern recognition, thus shaping the future of computing.
 

IBM Corporation, a leading player in neuromorphic computing, offers a range of solutions leveraging its expertise in AI and semiconductor technologies. Their offerings include neuromorphic hardware development, software frameworks for neural network simulations, and consulting services for integrating neuromorphic systems into various applications. IBM aims to advance the field with innovative solutions tailored to meet diverse industry needs.
 

Neuromorphic Computing Market Companies

Major players operating in the industry are:

• BrainChip Holdings
• General Vision
• HP Enterprise
• IBM Corporation
• Intel Corporation
• Knowm Inc.
• Qualcomm
   

Neuromorphic Computing Industry News

• In January 2023, IBM launched an energy-efficient AI chip built with 7nm technology. The AI hardware accelerator chip supports a variety of model types while achieving leading-edge power efficiency. The chip technology can be scaled and used for commercial applications to train large-scale models in the cloud to security and privacy efforts by bringing training closer to the edge and data closer to the source.
   
• In October 2022, Intel announced a three-year agreement with U.S. based Sandia National Laboratories (Sandia) to explore the value of neuromorphic computing for scaled-up computational problems. This agreement includes continued large-scale neuromorphic research on Intel’s upcoming next-generation neuromorphic architecture and the delivery of Intel’s largest neuromorphic research system to date, which could exceed more than 1 billion neurons in computational capacity.
   

The neuromorphic computing market research report includes in-depth coverage of the industry with estimates & forecasts in terms of revenue (USD Billion) from 2018 to 2032, for the following segments:

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Market, By Component

• Hardware
• Software
• Services

Market, By Deployment

• Edge
• Cloud

Market, By Application

• Image recognition
• Signal recognition
• Data mining
• Others

Market, By End-use Industry

• Consumer Electronics
• Automotive
• Healthcare
• Military & Defense
• Industrial
• Others

The above information is provided for the following regions and countries:

• North America
  • U.S.
  • Canada
• Europe
  • Germany
  • UK
  • France
  • Italy
  • Spain
  • Rest of Europe
• Asia Pacific
  • China
  • India
  • Japan
  • South Korea
  • ANZ
  • Rest of Asia Pacific
• Latin America
  • Brazil
  • Mexico
  • Rest of Latin America
• MEA
  • UAE
  • Saudi Arabia
  • South Africa
  • Rest of MEA