Global Neuromorphic Chip Market to Grow at a CAGR of 47.6% by 2030

Current deep-learning algorithms and accompanying hardware face several obstacles, such as Moore's Law's economics, making it extremely difficult for a startup to compete in the AI area, limiting competition. The abundance of data constraints existing memory technologies. In addition, the exponential growth in computational power requirements has produced a heat wall for every application. In the meantime, the market wants improved real-time voice recognition and translation capabilities, real-time video comprehension, and real-time robot and automobile perception. Multiple applications demand enhanced intelligence that blends sensing and computing.

Given these significant obstacles, a paradigm shift resulted in a new technology paradigm that allows startups to differentiate themselves. This could use the benefits of new memory technology to enhance bandwidth, data, and energy efficiencies significantly. The most recent model is the neuromorphic approach, an event-based method in which processing occurs only when necessary rather than at each clock tick. The approach permits substantial energy savings necessary to run energy-intensive AI algorithms. This motivates using neuromorphic devices as the probable next step in artificial intelligence technology.

Market Dynamics

Increasing Demand for Artificial Intelligence-based Microchips to Drive the Global Neuromorphic Chip Market

Artificial Intelligence (AI) is attracting substantial corporate investment, and the chip market is attracting greater interest and scrutiny. End-users currently adopt numerous applications, and numerous new applications are anticipated in the near future. Currently, CPUs and AI accelerators are the only accessible semiconductors for AI applications. Due to the computational limits of CPUs, AI accelerators now lead the market. GPUs, Application-Specific Integrated Circuits (ASICs), and Field-Programmable Gate Arrays are available AI accelerators (FPGAs). GPUs contain several parallel processing cores, giving them a substantial edge for AI training and inference processing. However, their significant power consumption makes them unsuitable for future uses.

On the other hand, emerging FPGAs can be ten times more power efficient than GPUs despite having inferior performance. FPGAs can be used as an alternate solution for applications where energy saving is the primary priority. ASICs have the highest performance, lowest power consumption, and most efficiency among AI Accelerators. The primary focus of AI research and development is the improvement and application of deep neural networks and AI accelerators. AI relies on producing near-real-time data analyses. Neuromorphic computing aims to bridge this gap by replicating some brain activities. This brain-inspired architecture, which simulates computation and memory using neurons and synapses, can meet the requirements of the next generation of artificial intelligence systems.

Development of New Techniques to Provide Opportunities for the Global Neuromorphic Chip Market

At the academic level, new methodologies for manufacturing neuromorphic devices are being evaluated. In April 2021, FRANZ, a global ceramic brand, collaborated with the Department of Biomedical Engineering at National Yang-Ming Chiao Tung University to implement a novel technique for producing neuromorphic chips using ceramic 3D printing technology. The purpose of these chips is to detect neuroelectric signals and neurotransmitter concentration, as well as to give deep brain stimulation. In the future, these neuromorphic chips may be used in medicine to treat neurodegenerative disorders and other ailments. Thus, such procedures' development offers tremendous market growth potential.

Regional Insights

By region, the global neuromorphic chip market is segmented into North America, Europe, Asia-Pacific, and the Rest of the World.

North America accounted for the largest market share and is estimated to grow at a CAGR of 46.7% during the forecast period. North America is home to several of the market's leading suppliers, including Intel Corporation and IBM Corporation. The regional market for neuromorphic chips is expanding due to government initiatives, investment activity, and other factors. The government's interest in neuromorphic computing is a significant contributor to the expansion of the business in North America. In September 2020, for instance, the Department of Energy (DOE) announced funding of $2 million for five fundamental research programs to develop neuromorphic computing. The DOE effort promotes both hardware and software development for brain-inspired neuromorphic computing.

On the other hand, the Canadian government is focusing on Artificial Intelligence technology, which is anticipated to provide development opportunities for neuromorphic computing in the coming years. For example, in June 2020, Canada and Quebec's governments joined together to promote AI development safely. The emphasis will be on several topics, including the future of work and innovation, commercialization, data governance, and trustworthy AI. The expansion of AI-based processors in Canada is also fuelling the market for neuromorphic chips.

Europe is the second largest region. It is estimated an expected value of USD 360 million by 2030, registering a CAGR of 48.9%. The European market is also anticipated to experience growth in neuromorphic chips due to government initiatives, vendor investments, etc. Several long-term research projects are gathering partnerships for neuromorphic technology breakthroughs. The Human Brain Project (HBP) in Europe began in 2013 and is a ten-year endeavor. The project's last phase (April 2020 to March 2023) focuses on three significant areas: brain networks, their role in consciousness, and artificial neural networks. Recently, the project facility hubs for encouraging collaboration and conducting scientific research became operational. Local vendors in the region are also concentrating on the creation of neuromorphic chips with the aid of venture capital investment. These expenditures are anticipated to influence market innovation.

Asia-Pacific is the third largest region. The Asia-Pacific area is one of the most technologically advanced. The region's neuromorphic technology is expanding fast thanks to government assistance, research spending, and innovation activities. To seek vital technological breakthroughs, the Chinese government said in March 2021 that the country will raise research and development investment by more than 7 percent between 2021 and 2025. The nation identified seven research fields in its fourteenth five-year plan, including artificial intelligence, quantum computing, semiconductors, and space. The technology focuses on brain science, also known as brain-computer fusion technology, which could aid in the treatment of disorders. As part of its comprehensive ambition to become a global leader in AI theories, technologies, and applications by 2030, China has suggested that its ability to create cutting-edge AI chips domestically will be crucial to its success. Vendors in the country are investing in developing artificial intelligence (AI) chips to overcome difficulties in chip production and increase national independence. ByteDance, for instance, has aspirations to manufacture semiconductors. The business has a team investigating the creation of AI chips. These initiatives generate growth potential for neuromorphic chips in the nation.

Key Highlights

• The global neuromorphic chip market was valued at USD 33 million in 2021, and it is estimated an expected value of USD 1097 million by 2030, registering a CAGR of 47.6% during the forecast period (2022-2030).

• By end-user industry, the global neuromorphic chip market is segmented into financial services and cybersecurity, automotive (ADAS/autonomous vehicles), industrial (IoT ecosystem, surveillance, and robotics), consumer electronics, and other end-user industries (medical, space, defense, etc.). Consumer electronics accounted for the largest market share and is estimated to grow at a CAGR of 45.7% during the forecast period.  

Market Segments

1. By Application
   1. Image Recognition
   2. Signal Recognition
   3. Data Mining
   4. Process Optimization
   5. Others
2. By Offerings
   1. Hardware
   2. Software
3. By End-user Industry
   1. Financial Services and Cybersecurity
   2. Automotive (ADAS/Autonomous Vehicles)
   3. Industrial (IoT Ecosystem, Surveillance, and Robotics)
   4. Consumer Electronics
   5. Other End-user Industries (Medical, Space, Defense, etc.)