PUBLISHER: AnalystView Market Insights | PRODUCT CODE: 1514965
PUBLISHER: AnalystView Market Insights | PRODUCT CODE: 1514965
Self-Learning Neuromorphic Chip Market size was valued at USD 851.5 Million in 2023, expanding at a CAGR of 18.50% from 2024 to 2032.
The Self Learning Neuromorphic Chip Market is the industry that develops and commercializes neuromorphic chips, which are a relatively new class of circuits that mimic human brain function. Such chips will allow robots to learn and adapt on their own, how the human brain learns and absorbs information through experience. These chips' self-learning capabilities allow them to improve their performance over time without the need for explicit programming, making them perfect for applications involving artificial intelligence, robotics, and other fields that require adaptive and intelligent systems.
Self-Learning Neuromorphic Chip Market- Market Dynamics
Growing Demand for Edge Computing Drives Market Growth
The self-learning neuromorphic chips is being driven by increased demand for edge computing. Edge computing involves processing data closer to the source, which reduces latency and improves real-time decision-making capabilities. Self-learning neuromorphic devices, which can process massive volumes of data simultaneously and make autonomous judgments, are ideal for edge computing applications. As the Internet of Things expands, there is an increasing demand for intelligent edge devices that can handle and analyze data locally without relying largely on cloud computing. Self-learning neuromorphic processors can help these edge devices perform critical functions like object recognition, anomaly detection, and predictive maintenance. The desire for edge computing, combined with the capabilities of self-learning neuromorphic circuits, is projected to propel market expansion in the coming years.
Self-Learning Neuromorphic Chip Market- Key Insights
Our research analyst estimates that the global market will develop at a CAGR of approximately 18.50% from 2024 to 2032.
Based on Vertical segmentation, the power & energy category dominated the market.
Based on Application segmentation, the data mining segment generated the highest revenue in 2023.
On the basis of region, North America was the leading revenue generator in 2023
The Global Self-Learning Neuromorphic Chip Market is segmented on the basis of Vertical, Application, and Region.
The market is divided into eight categories based on Vertical: Consumer Electronics, Media & Entertainment, Smartphones, Healthcare, Power & Energy, Automotive, Aerospace, and Defense. The power & energy category dominated the market. Self-learning neuromorphic circuits have numerous applications in the power and energy sectors. These chips have applications in intelligent energy management, predictive maintenance, and power grid optimization. They enable more efficient energy usage, increase grid stability, and improve overall power system reliability.
The market is divided into three categories based on Application: Data Mining, Signal Recognition, and Image Recognition. The data mining category provided the greatest revenue. These chips are used in data mining and analytics applications to process massive volumes of data and extract useful information. They offer real-time analysis, anomaly identification, and predictive modeling, which benefits a variety of businesses, including as finance, e-commerce, and marketing.
Self-Learning Neuromorphic Chip Market- Geographical Insights
Geographically, this market is present in North America, Latin America, Europe, Asia Pacific, and the Middle East and Africa. These zones are further split based on which countries bring business. The North American Self-Learning Neuromorphic Chip market will dominate due to the existence of top technology businesses and research institutes focused on AI and ML, as well as a healthy ecosystem of chip manufacturers, research organizations, and AI startups. Furthermore, the growing use of self-learning neuromorphic circuits in applications, including autonomous vehicles, medical diagnostics, and military systems, is propelling market expansion in North America.
The Asia-Pacific Self-Learning Neuromorphic Chip Market is predicted to expand the quickest between 2024 and 2032. It accounts for the government's assistance and initiatives to build AI-based solutions. The region's enormous population, rising disposable income, and increased use of new technology drive demand for self-learning neuromorphic devices. Robotics, healthcare, and consumer electronics are key market drivers in Asia Pacific. Furthermore, China's Self-Learning Neuromorphic Chip market had the highest market share, while India's Self-Learning Neuromorphic Chip market was the fastest-growing in Asia-Pacific.
Significant companies in the Self-Learning Neuromorphic Chip market, including, Numenta, Samsung Group, Qualcomm IBM, General Vision, Intel Corporation, and others, are attempting to increase market demand by investing in R&D. Industry companies are also pursuing a variety of strategic initiatives to grow their worldwide footprint, with major industry developments including new contractual agreements, increased investments, product launches, mergers and acquisitions, and collaboration with other organizations. To expand and survive in a more competitive and expanding market environment, the Self-Learning Neuromorphic Chip sector must provide cost-effective products.
In May 2024, BrainChip is releasing two "Akida Development Kits" for their low-power self-learning "Akida NSoC" neural networking chip, which is designed for edge AI.
GLOBAL SELF-LEARNING NEUROMORPHIC CHIP MARKET KEY PLAYERS- DETAILED COMPETITIVE INSIGHTS
Qualcomm (US)
Numenta (US)
Samsung Group (South Korea)
IBM (US)
Hewlett Packard (US)
Brainchip Holdings Ltd. (US)
HRL Laboratories (US)
Applied Brain Research Inc. (US)
General Vision (US)
Intel Corporation (US)
Others