Neuromorphic chips are digital and analog integrated circuits that implement neural networking technology. Neuromorphic computing is executed on hardware by threshold switches, transistors, and oxide-based memristors. These electronic chips mimic the human brain and are made up of millions of neurons. The architecture of a neuromorphic chip consists of numerous artificial neural networks. Neuromorphic chips are implemented in advanced tools for experimentation. Neuromorphic chips find applications in image recognition, single recognition, and data mining processes among others.
The global neuromorphic chip market is estimated to be valued at US$ 3,834.6 million in 2021 and is expected to exhibit a CAGR of 22.3% over the forecast period (2021-2028).
Asia Pacific (Region) held dominant position in the global neuromorphic chip market in 2020, accounting for 43.3% share in terms of volume, followed by Europe and North America, respectively.
Figure 1. Global Neuromorphic Chip Market Value (US$ Mn), By Region, 2020
Market Dynamics- Drivers
Increasing demand for artificial intelligence systems is expected to drive growth of the global neuromorphic chip market during the forecast period. Numerous companies and researchers are incorporating neuromorphic chips in artificial intelligence systems to enhance processes including speech recognition, machine learning, image recognition, data mining, automated reasoning, etc. Rising use of neuromorphic chips in artificial intelligence has received excellent response from various end users worldwide. This is typically due to extraordinary developments it has brought in mobile phone speech recognition, robots automating operations, driverless cars, etc. Moreover, its capabilities of solving problems by employing a complex pattern-matching process similar to a human brain is another factor expected to drive growth in the global neuromorphic chip market during the forecast period.
Integration of smart machines is expected to propel the global neuromorphic chip market growth over the forecast period. Smart machines are based on cognitive computing and artificial intelligence and have emerged as major trends across the globe. Smart machine manufacturers are integrating neuromorphic chips into their systems, in order to enhance overall performance. Furthermore, the ability of these systems to learn from their surroundings and interactions and respond suitably without the need for preprogramming is encouraging the adoption of these smart machines in lieu of conventional machines.
Conjunction of next-generation strategies can present lucrative growth opportunities. Neuromorphic chips represent significant opportunities in terms of being implemented along with other advanced technologies such as artificial intelligence, big data, and others in the coming years. Integration of neuromorphic chips improves the pattern recognition quality in artificial intelligence systems; whereas, in big data, neuromorphic chips advance the data mining and forecasting processes. Manufacturers engaged in the development of these technologies can enter into partnerships and collaboration with manufacturers of artificial intelligence systems to strengthen and establish position in the market. For instance, in 2014, IBM Corp. announced its plan to integrate TrueNorth neuromorphic chips with its proprietary ‘Watson’ analytical platform.
Integration in portable consumer devices to pose significant business opportunities. Neuromorphic chips have vast opportunities in the smartphone and smartwatch market in the near future. Pattern recognition issues are prime areas for manufacturers to focus on improving in smartphones. Integration of neuromorphic chips into mobile devices will improve the device’s audio and visual processing skills. Moreover, prominent manufacturers of these chips such as IBM Corp., Qualcomm Inc., and others are working towards developing their own neuromorphic technology, which will be suited for applications in mobile phones.
|Base Year:||2020||Market Size in 2021:||US$ 3,834.6 Mn|
|Historical Data for:||2017 to 2020||Forecast Period:||2021 to 2028|
|Forecast Period 2021 to 2028 CAGR:||22.3%||2028 Value Projection:||US$ 15,755.6 Mn|
IBM Research, Inc., Knowm Inc., Intel Corp., BrainChip Holdings Ltd., General Vision Inc., HRL Laboratories, LLC, Qualcomm Technologies Inc., and Hewlett Packard Labs.
|Restraints & Challenges:||
Neuromorphic chips are being widely used for image recognition applications. In the recent past, several problems associated with image recognition processes such as low-contrast images, blurred images, noisy images, image conversion to digital form, storage of large-volume images and others, has led to the development of efficient image processing and recognition algorithms. Neuromorphic technology has resolved some issues related to digital image processing through its parallel architecture. Moreover, neuromorphic chips find application in pattern recognition, face recognition, texture analysis, color representation, and several other aspects of image processing.
Currently, the use of neuromorphic chips is limited to specific industries and applications. The number of chips manufactured currently is limited, as most are in the research phase and some are prototype models. There are ample opportunities available in terms of applications for neuromorphic chips, however, are yet to be explored. Driverless cars as well as advanced driver assistance systems represent major opportunities for these chips in the automotive industry. Moreover, rescue robots, drones, and unarmed aerial vehicles used in aerospace and defense sectors represent the future outlook for the neuromorphic chips market.
Figure 2. Global Neuromorphic Chip Market Share, By Application, 2020
Key Takeaways of the Graph:
Market Dynamics- Restraints
Challenges associated with the development of complex algorithms are expected to hinder the global neuromorphic chip market growth over the forecast period. Neuromorphic chips are required for the development of complex algorithms, which can be time-consuming. Neuromorphic chips require algorithms that are not too long as it may result in increase in memory consumption, and may be prone to errors. Furthermore, the development of algorithms that can accelerate the working of a neural network may also require skilled professionals, which in turn, adds to cost production. Thus, these factors are expected to hinder the market growth over the forecast period. For instance, Hewlett Packard Labs developed a conversion algorithm to reduce computational errors and maximize computing accuracy of its neuromorphic technology.
Slow commercialization and high cost of neuromorphic chips is expected to restrain growth of the global neuromorphic chip market during the forecast period. The slow rate of commercialization as well as high cost of neuromorphic chips is a major restraining factor for growth of the market. Furthermore, high cost and limited choice among several manufacturers offering neuromorphic chips are constraining OEMs in various industries from integrating these chips in their products.
Key players operating in the global neuromorphic chip market are IBM Research, Inc., Knowm Inc., Intel Corp., BrainChip Holdings Ltd., General Vision Inc., HRL Laboratories, LLC, Qualcomm Technologies Inc., and Hewlett Packard Labs.
The neuromorphic chip is a new, miniaturized microchip that takes inspiration from the actual human mind to recreate its complex thought processing algorithms and information processing systems. The human mind processes information rapidly and stores it in memory with more than 100 billion synaptic neurons constantly communicating with each other through over 100 gigabytes of synapses, which constitute the connecting pathways. When information is retrieved by the brain, it only requires about 10ms to retrieve the data, a speedy process compared to the evolution of the Human Brain (which was found to be much slower than the previously believed, thinking machines, which had a much larger number of neurons). A neuromorphic chip made out of Nano photonics will allow scientists to control and manipulate matter at a molecular level. Scientists believe that they may be able to create computers that are as small as a single atom. In addition, this type of chip may also be used to control tissue in a non-invasive manner.
Increasing demand for machine learning and artificial intelligence is expected to drive growth of the global neuromorphic chip market during the forecast period. Machine learning and artificial intelligence has been used in diverse range of end-use sectors and applications including automobile, healthcare, consumer service, disease mapping, social media monitoring, and etc. Neuromorphic computing is designed to emulate human brain capabilities, which in turn, has increased the importance of machine learning and artificial intelligence.
Moreover, cross-industry partnerships and collaborations is expected to accelerate growth of the global neuromorphic chip market growth over the forecast period.
Key features of the study:
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