Neuromorphic computing companies develop hardware and software inspired by the human brain's neural networks. These technologies are designed to process information with low power consumption and high efficiency, making them suitable for applications like artificial intelligence, robotics, and edge computing. Neuromorphic computing holds the potential to revolutionize computing in various domains.
Competitive Landscape of Neuromorphic Computing Market:
The neuromorphic computing market is still in its early stages, but it is expected to experience significant growth in the coming years, driven by the increasing demand for artificial intelligence (AI) and machine learning (ML) applications. This market is characterized by a diverse range of players, each with its own unique approach and target market.
Key players:
Strategies adopted by these key players include:
Factors for market share analysis include:
New and emerging companies in the neuromorphic computing market include:
Current company investment trends in the neuromorphic computing market include:
Latest Company Updates:
June 2023- BrainChip Holdings Ltd, a renowned name in neuromorphic AI, IP & Lorser Industries Inc, a leader in system level manufacturing & integration have lately unveiled that they will utilize the technology of BrainChip’s Akida to provide neuromorphic computing solutions for the SDR or software defined radio. The joint venture will help in leveraging Lorser’s skill in SDR manufacturing and design and the cutting-edge neuromorphic technology of BrainChip’s for creating innovative, intelligent solutions which augment the reliability, adaptability, and scale of the SDR devices.
Recent Developments
Lorser Industries CEO, Diane Serban stated that they believe neuromorphic computing technology is indeed the future of ML/AI & an SDR with the neuromorphic ML/AI capacity that will provide users significantly more efficiency, flexibility, and functionality. The Akida IP and processor is the ultimate solution for the SDR devices owing to its high performance, low power consumption, and above all its ability of learning on-chip, post deployment in the field.
Lorser and BrainChip share the common interest to create intelligent devices which can manage communication in an array of evolving and different environments. The former with its expertise in the advanced SDR technology indeed is the right partner for them to work with on the breakthrough gadget with the ability of using ML/AI for identifying patterns, detecting anomalies, and also intelligently adapting to various scenarios.
Akida in fact, powers the next-generation AI in various scientific, automotive, home as well as industrial environments. The completely customizable, digital, event-based AI neural processor & IP is perfect for advanced ML/AI like ADAS/autonomous systems, high-end video object detection, medical devices with an extended battery life, and intelligent sensors.
Global Neuromorphic Computing Market Size valued at USD 1.9 Billion in 2022. The Neuromorphic Computing market industry is projected to grow from USD 2.29 Billion in 2023 to USD 10.5 Billion by the year 2032, exhibiting a compound yearly growth rate (CAGR) of 21.00% during the forecast period (2023 - 2032). Increased adoption of neuromorphic computing technology and demand for machine learning and AI-integrated system are the key market drivers enhancing the growth of the market.
Source: The Secondary Research, Primary Research, MRFR Database and Analyst Review
Market CAGR for neuromorphic computing is being driven by the rising adoption of neuromorphic computing. The growing application of the artificial intelligence and the machine learning in robotics image processing, language processing, interpretation, and nonlinear regulation is dominating the market revenue. There is rising use of neuromorphic technology in the transmission, acceleration and implementation of next-generation semiconductors and execution of next-generation semiconductors and sovereign systems.
The performance of the AI neuromorphic chip is a thousand times faster than graphic and central processing units. The execution of neuromorphic engineering technology in electronic devices helps cognitive decisions like credit scoring, detection of fraud, image classification, speech recognition and language translation. Machine learning and AI technologies assist in creating robotic systems with high performance, efficiency, low energy consumption and advanced features like self-driving automobiles. Further, the growing applications in drones, chatterbots and medical devices, for instance, the adoption of neuromorphic chips in drone cameras with chips that take signals from the cameras and process the data the same as the human brain, improve the sensing of the drones rapidly. The technology is largely deployed in defense and military sections in order to offer processing power and fasten the decision-making time throughout the war by helping the soldiers with analytical results.
The growing demand for global neuromorphic computing is due to the requirement for high-performance Integrated Circuits. This technology can highly minimize the transportation times increased by a conventional CPU by storing and processing data in the same chip. This ability to include processing and storage largely minimizes the shuttling time. Further, the requirement for better-performing ICs for the purpose of efficient computing in assisting the expansion of the market globally. Thus, driving the Neuromorphic Computing market revenue.
However, neuromorphic development requires deep hardware and software manufacturing research and development in order to meet the market value. The limited funds and absence of skilled personnel, and the presence of advanced software and hardware technologies are causing restrictions on the development, hence hampering the growth of the market. The lack of algorithm void in the novel advancements and dim growth in the neuromorphic computing section is restraining the market growth.
The global Neuromorphic Computing market segmentation, based on components, includes Hardware, Software and Services. The hardware segment dominates the market, accounting for the largest market revenue due to the growing utilization of neuromorphic hardware for speeding the computation in embedded devices and the rising integration and implementation of the machine learning algorithms on embedded devices. There are several companies offering these solutions, which can be utilized by researchers and organizers in order to develop and test neuromorphic computing applications. Further, the software segment is expected to be the fastest-growing segment due to surging software requirements in multiple industries.
The global Neuromorphic Computing market segmentation, based on deployment, includes Edge and Cloud. The edge segment dominated the market due to the expansion of wireless networking interest in the evolving computer paradigm of edge computing. The rising application of edge computing in order to identify all body gestures for automobiles with sensitive voice controls, touchless interfaces, and internal intelligence for assistant robots is boosting the market segment growth. Further, the cloud computing segment is anticipated to be the fastest growing segment because of its multiple technological advantages, like delivering a large volume of data and a one-stop platform for security storage for any enterprise.
Figure 1: Global Neuromorphic Computing Market, by Deployment, 2022 & 2032 (USD Billion)
Source: The Secondary Research, Primary Research, MRFR Database and Analyst Review
By region, the study gives market insights into the North America, Europe, Asia-Pacific and the Rest of the World. The North American Neuromorphic Computing market area dominates the market due to the surging the demand for artificial-based voice speech recognition technology and rising investment by the government, and efforts to improve the utilization of neuromorphic technology. The growing demand for integrating neuromorphic computing in the North American region. The US is the largest contributor to the growth of the market in this region.
Further, the prime countries studied in the market report are The US, Canada, German, France, the UK, Italy, Spain, Japan, India, China, Australia, South Korea, and Brazil.
Figure 2: GLOBAL NEUROMORPHIC COMPUTING MARKET SHARE BY REGION 2022 (USD Billion)
Source: The Secondary Research, Primary Research, MRFR Database and Analyst Review
Europe's Neuromorphic Computing market accounts for the second-largest market share, as there are various organizations and initiatives focusing on advancing the development and adoption of neuromorphic technologies in this region. Further, the German Neuromorphic Computing market held the largest market share, and the UK Neuromorphic Computing market was the rapid-growing market in European region.
The Asia-Pacific Neuromorphic Computing Market is expected to grow at the rapid CAGR from 2023 to 2032. This is due to the increasing use of the artificial intelligence, the Internet of Things, data analytics and other technologies in this region. Moreover, China’s Neuromorphic Computing market held the largest market share, and the Indian Neuromorphic Computing market was the rapid-growing market in Asia-Pacific region.
Leading market players are investing hugely in research and development in order to expand their product lines, which will help the Neuromorphic Computing market grow even more. Market players are also undertaking a variety of strategic activities to spread their global footprint, with important market developments including new product launches, mergers and acquisitions, contractual agreements, higher investments, and collaboration with other organizations. To spread and survive in a more competitive and rising market climate, the Neuromorphic Computing industry must offer cost-effective items.
Manufacturing locally to reduce the operational costs is one of the key business tactics utilized by the manufacturers in the global Neuromorphic Computing industry to benefit clients and increase the market sector. In recent years, the Neuromorphic Computing industry has offered some of the most significant advantages to technologically advanced businesses. Major players in the Neuromorphic Computing market, including Intel Corporation, Polyn Technology, IBM Corporation, Samsung Electronics Co. Ltd., SK Hynix Inc., GrAI Matter Labs, Hewlett Packard Development LP, Qualcomm Incorporated, BrainChip Holdings Ltd, Numenta, General Vision, and others, are trying to increase market demand by investing in the research and development operations.
IBM Corporation, founded in the year 1911, and headquartered in Armonk, New York, is a multinational technology company. The company is known for its software and hardware products, inclusive of servers, computers, networking equipment, and storage systems. The company also offers technology, consulting and business services like cloud computing, artificial intelligence, and data analytics. The R&D efforts of the company have helped various technological innovations. In January 2023, the company launched an energy-efficient AI chip with 7nm technology. The AI hardware accelerator chip supports different types of models when attaining leading-edge power efficiency. This technology can be escalated and utilized in commercializing applications to train large-scale models in the cloud to privacy and security efforts by bringing training closer to the edge and the data closer to the source.
Intel Corporation, headquartered in Santa Clara, California, is an American multinational corporation and technology company. The company is the globally largest manufacturer of semiconductor chips and is one of the developers of the x86 series of instruction sets available in most personal computers. The company provides microprocessors for computer system manufacturers like Lenovo, HP, Acer and Dell. The company also manufactures network interface controllers, motherboard chipsets, integrated circuits, graphic chips, and other devices associated with communications and computing. In October 2022, the company declared a three-year agreement with Sandia National Laboratories in order to explore the value of the neuromorphic computing for scaled-up computational problems. This agreement incorporates continued large-scale neuromorphic research on the upcoming next-generation neuromorphic architecture of the company.
December 2022: The latest AI neuromorphic chip was launched by Intel in order to perform data-crunching tasks a thousand times faster than standard processors like GPUs and CPUs with minimum power usage. It being energy efficient, the technology is best for several applications like cybersecurity, industrial equipment and smart homes.
December 2022: An Israel-based Fabless semiconductor company, Polyn Technology, announced the accessibility of neuromorphic analog signal processing models for Edge Impulse. It is a machine learning development platform for edge devices offering ultra-low power on sensor solutions for wearables and the Industrial IoT.
April 2021: A global leader in next-generation audio, sensing and imaging technology, DTS, a fully-owned subsidiary of Xperi Holding Corporation, announced a world-first neuromorphic driver monitoring solution powered by Prophesee Metavision- Event-Based Vision sensor.
Hardware
Software
Services
Edge
Cloud
North America
US
Canada
Europe
Germany
France
UK
Italy
Spain
Rest of Europe
Asia-Pacific
China
Japan
India
Australia
South Korea
Australia
Rest of Asia-Pacific
Rest of the World
Middle East
Africa
Latin America
Neuromorphic Computing Market Highlights:
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