Neuromorphic engineering which is also known as neuromorphic computing was introduced to describe the use of VSLI (very large scale integration) systems consisting of electronic analog circuits in order to copy the neuro-biological architectures which are present in the nervous system. This also means that the chips that are made from such technologies are smart and have the capability to represent the human brain. These chips are used in various gadgets not only to make them more reliable but also to increase the level of their performance.
IBM is a prominent market player which designed a neuromorphic chip just like the brain. The chip has the ability to classify the data accurately and in a better way as compared to traditional processors. This chip can be used in any modern applications like IoT, mobile computing, HPC, robotics, autonomous cars, and so on. Due to its usage and demand in various artificial intelligence products, the self-learning neuromorphic chip market is expected to increase at a rapid pace and reach a valuation of USD 2.76 Billion by the end of 2030 if the CAGR is measured at 26.23%.
When COVID-19 began to spread across the world, all the major countries started implementing work stoppage and foot prohibition orders. Except for the medical industries, most of the industries have been affected badly. The Self-Learning Neuromorphic Chip Market was also one of the affected markets. With the slowdown of the economic growth, the market for neuromorphic chips suffered a specific impact but still, it managed to maintain a certain growth over the past few years. However, it is expected that the market will improve more when there will be a good supply of raw materials.
The Self-Learning Neuromorphic Chip Market is growing at a rapid pace due to the major drivers of the market. The increase in the development of Artificial Intelligence (AI) is a major cause for the growth of the market because this chip is mostly used in most artificial intelligence gadgets. Other major drivers of the Self-Learning Neuromorphic Chip Market include sudden growth in the demand for smarter sensors and the miniaturization of ICs.
There are various opportunities in the Self-Learning Neuromorphic Chip Market that helps the market to expand on a larger basis. The main opportunity of the market is the implementation of neuromorphic chips in different end-user industries. This can make the market grow more and achieve great profit.
The major restraint in the Self-Learning Neuromorphic Chip Market is the slow speed in the development of gadgets infused with neuromorphic chips in spite of receiving a huge amount of investment. This is a complex sector and so the complexity while designing hardware is another major restraint of the market.
Along with the drivers of the market, there are also a few challenges that can hinder the growth of the Self-Learning Neuromorphic Chip Market. Lack of knowledge and issues related to the algorithm are the two major challenges that can pull back the growth of the market.
Keeping up the pace of advanced technologies like machine learning and artificial intelligence, the Self-Learning Neuromorphic Chip Market is expected to grow more in the coming years. Hence, the growth for the market is expected to reach a valuation of USD 2.76 billion in the coming years at a CAGR rate of 26.23%
Smart sensors, data analytics, and the IoT (Internet of Things) are considered the key applications that are known to stream high in the Self-Learning Neuromorphic Chip Market because these chips are incorporated into different types of hardware which are later on used for data mining, image recognition, and signal recognition. This has led the market to score a very high valuation not only in the past but also in the coming years.
The Self-Learning Neuromorphic Chip Market is segmented on the basis of two major categories which are vertical and application. These major categories are further sub-categorized into more divisions mentioned below.
Based on the Self-Learning Neuromorphic Chip Market Analysis, the market for self-learning neuromorphic chips has been segmented into five major regions which include North America, Latin America, Asia Pacific, Europe, and the Middle East and Africa. Among these regions, North America is expected to drive the growth of the Worldwide Neuromorphic Chip Industry due to the presence of most of the key market players in the region. The United States is the country that consists of the key neuromorphic chip market players. The market growth is increasing due to the image recognition and implementation of neuromorphic chips in various types of gadgets which include medical, wearables, aerospace, consumer electronics, and others.
However, Asia Pacific is another region that will also show rapid growth in the Self-Learning Neuromorphic Chip Market due to the increase in the crime rate in various countries of that region and growth in the development of architectures.
The global Self-Learning Neuromorphic Chip Market consists of various companies that are constantly competing against each other for securing the first position. All the manufacturers are trying to implement new strategies, building partnerships, creating joint ventures, and introducing brand new products to attract the attention of more customers.
IBM, Qualcomm, Hewlett Packard, HRL Laboratories, and Intel Corporation are some of the top players which are focusing to launch the best products in the market using the neuromorphic chip. These companies have also invested in various research and development activities in order to improve the quality of their existing products. Mergers and acquisitions are very common strategies that are also implemented by a few companies to retain their position in the market.
List of Key Companies:
Qualcomm is one of the key Neuromorphic chip companies and is well known for designing a Zeroth neuromorphic chip program. In order to test this technology, the company is now focusing on different researchers.
HRL Laboratories is another major company in the Self-Learning Neuromorphic Chip Marketwhich announced that it will continue to develop innovative products that can enhance the cognitive capabilities of biological intelligence. It also shared its view on the upcoming neuromorphic technology.
The Self-Learning Neuromorphic Chip Market Report has its base year of 2021 and the forecast period is set to 2030. This report is based on the market for self-learning neuromorphic chips and outlines a brief overview of the market along with the various dynamics which include the drivers, opportunities, restraints, and challenges. The report also consists of a competitive landscape of the market which describes the key players of the market and their competitiveness to stand out whereas the regional analysis section describes the division of the neuromorphic chip market share into the various regions.
On the basis of analysis, the report also tells about the recent developments in the market along with the constantly changing Self-Learning Neuromorphic Chip Market trends. However, this report is a combination of all the necessary details of the market.
|Market Size||USD 2.76 Billion|
|Forecast Units||Value (USD Billion)|
|Report Coverage||Revenue Forecast, Competitive Landscape, Growth Factors, and Trends|
|Segments Covered||Vertical, Application|
|Geographies Covered||North America, Europe, Asia-Pacific, and Rest of the World (RoW)|
|Key Vendors||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)|
|Key Market Opportunities||The market is the implementation of neuromorphic chips|
|Key Market Drivers||Artificial Intelligence, Machine learning technology, Lack of knowledge complexity in designing chip|
The global market of self-learning neuromorphic chip can expand at 26.23% CAGR and be worth of USD 2.76 Billion by 2030.
Intel Corporation (U.S.), Brainchip Holdings Ltd. (U.S.), and Applied Brain Research Inc. (U.S.) are some reputed names in the self-learning neuromorphic chip market,
Image recognition, data mining, and signal recognition providing gadgets use self-learning neuromorphic chip.
The surge in need for effective data classification across sectors to boost growth of self-learning neuromorphic chip market.
Increase in sales of wearables those have image recognition feature can prompt the self-learning neuromorphic chip market in North America.