Subject: MRR
Neuromorphic Chip market Size to Grow USD 1228.4 Million by 2030 at a CAGR of 87.8% | Valuates Reports
BANGALORE, India, June 26, 2024 /PRNewswire/ -- Neuromorphic Chip market is Segmented by Type (Image Recognition, Signal Recognition, Data Mining), by Application (Consumer Electronics, Wearable Medical Devices, Industrial Internet of Things, Others): Global Opportunity Analysis and Industry Forecast, 2024-2030.
The global Neuromorphic Chip market was valued at USD 16 million in 2023 and is anticipated to reach USD 1228.4 million by 2030, witnessing a CAGR of 87.8% during the forecast period 2024-2030.
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Major Factors Driving the Growth of Neuromorphic Chip market:
The market for neuromorphic chips is expanding due to a number of important considerations. First and foremost, a primary driver is the growing need for machine learning (ML) and artificial intelligence (AI) applications, as neuromorphic circuits provide effective and potent processing capabilities that resemble the neural networks found in the human brain. Second, the demand for these chips is driven by the growing requirement for energy-efficient computer systems across a range of industries, including consumer electronics, healthcare, and automotive. Furthermore, the market is expanding more quickly due to technological breakthroughs and higher investments in neuromorphic research and development. Finally, the growing popularity of neuromorphic chips?which offer real-time processing and lower latency?in edge computing, robotics, and Internet of Things devices drives this trend.
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TRENDS INFLUENCING THE GROWTH OF THE NEUROMORPHIC CHIP MARKET
The Signal Recognition Neuromorphic Chip plays a key role in the Industrial Internet of Things (IIoT) by improving edge decision-making and real-time data processing. These chips imitate the neural networks seen in the human brain, making it possible to efficiently identify patterns and anomalies in massive streams of industrial data. In predictive maintenance, quality control, and operational efficiency, prompt and precise signal processing can avert equipment breakdowns and enhance production procedures. The market for neuromorphic chips is expanding significantly due to the growing demand for sophisticated chips that can handle intricate signal identification tasks, as industries use IIoT more and more to increase productivity and streamline operations.
The market for neuromorphic devices is expanding due to image recognition, which takes advantage of these chips' high processing efficiency and low power consumption. Rapid and accurate image processing is made possible by neuromorphic processors, which mimic the neural networks of the brain. This is crucial for applications like improved robotics, driverless cars, and surveillance systems. These chips greatly improve the performance of image recognition systems by handling intricate tasks including object detection, facial recognition, and scene analysis in real-time. The market is growing as a result of the increasing use of neuromorphic processors for image recognition applications due to the growing demand for sophisticated visual processing across a range of industries.
The need for cutting-edge diagnostic and therapeutic technologies in the healthcare and biomedical industries is propelling the market expansion for neuromorphic chips. Medical devices with neuromorphic processors can monitor and analyze complicated biological information in real time, including brain activity in brain-computer interfaces and neuroprosthetics. Their capacity to swiftly and precisely handle vast volumes of data makes them perfect for enhancing the accuracy and efficacy of medical diagnosis and therapies. The market for neuromorphic chips is expanding as a result of the healthcare sector's continued embrace of personalized medicine and digital transformation.
Another important element propelling the demand for neuromorphic chips is edge computing. Low-latency processing solutions are needed because IoT devices are producing more data at the edge of networks. Because neuromorphic devices have minimal power consumption and can handle data in real time, they are ideal for edge computing. They lessen the requirement for continuous data transport to central servers by enabling intelligent data analysis and decision-making at the edge. This capacity is pushing the adoption of neuromorphic devices in edge computing scenarios, as it is necessary for applications like industrial automation, smart cities, and remote monitoring.
The market for neuromorphic chips is mostly being driven by the development of autonomous systems, like drones and self-driving cars. For these systems to understand sensor data, make judgments, and traverse their surroundings on their own, they need highly developed computing powers. Neuromorphic processors provide the required computational power and efficiency because of their capacity to process information similarly to the human brain. They make it possible for complicated data inputs to be learned from and decisions to be made in real time, which is crucial for the safe and efficient functioning of autonomous systems. Thus, there is an increasing need for neuromorphic chips due to the growing investment in and acceptance of autonomous technology.
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NEUROMORPHIC CHIP MARKET SHARE ANALYSIS
With 18.57%, 17.43%, and 17.14% of revenue in 2019, respectively, Intel Corporation, IBM Corporation, and Eta Compute are the top three manufacturers in the sector.
Due to large R&D expenditures, sophisticated technology infrastructure, and the presence of important industry players, North America leads the world in the neuromorphic chip market. Because of its thriving semiconductor industry and significant emphasis on AI and machine learning advancements, the United States is leading the way. The region's widespread use of cutting-edge technologies in industries including consumer electronics, healthcare, and the automotive sector further supports market expansion. The need for neuromorphic devices in North America is further supported by government programs and funding for cybersecurity and defense applications.
Key Players:
- IBM Corporation
- Intel Corporation
- Eta Compute
- Nepes
- GrAI Matter Labs
- GyrFalcon
- aiCTX
- BrainChip Holdings
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