San Francisco, 27 February 2030: The Report Neuromorphic Computing Market Size, Share & Trends Analysis Report By Application, By End-use, By Deployment, By Component (Hardware, Software, Services), By Region, And Segment Forecasts, 2024 - 2030

The global neuromorphic computing market size is expected to reach USD 20.27 billion by 2030, registering a CAGR of 19.9% from 2024 to 2030, according to a new report by Grand View Research, Inc. The rise in demand for artificial intelligence and machine learning technology increased software utilization in neuromorphic computing, and the growing demand to produce better-integrated circuits (ICs) is attributed to the growth of the Neuromorphic computing market.

AI-powered neuromorphic chips are in high demand in the automotive industry because of their constant requirement for developing AI algorithms for high throughput with low power demands. Moreover, Neuromorphic chips are ideal for classification methods and could be used in various autonomous driving scenarios. For instance, in December 2020, Mercedes-Benz AG collaborated with the Intel Neuromorphic Research Community to investigate how neuromorphic chips could improve energy efficiency, speed, and accuracy for vehicle-related AI applications.

The increasing use of neuromorphic technology in healthcare applications is attributed to market growth. Moreover, Neuromorphic devices combined with artificial intelligence help detect health issues in individuals. For instance, in August 2022, Researchers from the University of Chicago’s Pritzker School of Molecular Engineering in the U.S. developed a wearable neuromorphic computing chip. This chip is developed by fusing wearable technology with artificial intelligence and machine learning to analyze health data.

Neuromorphic computing, which uses observations from neuroscience to create chips that function like the biological brain, aims to improve energy efficiency, computation speed, and learning efficiency in various applications such as voice, vision, gesture recognition, robotics, and search retrieval. For instance, in October 2021, Intel Corporation released Loihi 2, its 2nd generation neuromorphic research chip, and Lava, an open-source software platform for creating neuro-inspired applications and computing.

Neuromorphic computing provides benefits such as fast parallel processing with minimum power requirement. It also eliminates the need for back-and-forth data movement between components in the von Neumann architecture; this is expected to drive its adoption for image and signal processing applications. Moreover, its expected adoption in consumer electronics, automotive, healthcare, and military & defense sectors will also be largely responsible for driving the market growth.

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The increasing use of neuromorphic technology in deep learning applications, transistors, accelerators, next-generation semiconductors, and autonomous systems, such as robotics, drones, self-driving cars, and artificial intelligence, have propelled market growth. For instance, in August 2022, a multidisciplinary research team led by engineers at UC San Diego developed NeuRRAM, a neuromorphic chip designed to manage AI applications at higher accuracy and lower energy than other platforms. The increasing demand for faster and efficient neuromorphic chips for real-time and parallel processing capabilities is expected drive the market growth.

Neuromorphic Computing Market Report Highlights

• The image processing segment led the market with a revenue share of 45.5% in 2023. This can be attributed to the rising deployment of computer vision in numerous industries, including automotive, healthcare, and media & entertainment, among others.
• Edge deployment accounted for the largest market share in 2023. The increasing application of edge computing in identifying body gestures for touchless interfaces, automobiles with sensitive voice controls, and internal intelligence for assistant robots contribute to this segment’s growth.
• The hardware segment accounted for a dominant revenue share in 2023. This is attributed to the increasing demand for specialized neuromorphic chips and systems that can efficiently process complex data patterns.
• Consumer electronics accounted for the highest revenue share in 2023. Increasing sales of electronic devices, including laptops, PCs, and tablets, are leading to a progressive increase in demand for neuromorphic chips from the consumer electronics industry.
• North America neuromorphic computing market led the market with 37.3% of the revenue share in 2023. This is owing to the presence of a robust technological infrastructure, leading technology companies, and significant investments in research and development activities in this region.

Chip design and fabrication advancements also fuel market growth, allowing for more efficient and scalable neuromorphic computing architectures. For instance, in September 2022, Intel announced the launch of its Kapoho Point development board, based on the Loihi 2 research chip and the Lava software framework to accelerate neuromorphic computing. New tools such as the 8-chip Kapoho Point board facilitate large-scale workloads and low-latency sensing, with significant speed and energy improvements over previous generations. Moreover, they bring neuromorphic technology to commercial applications by providing developers with a scalable platform for building AI models and solving complex problems more efficiently. Expanding applications in edge computing, IoT devices, and autonomous systems are leveraging neuromorphic computing's low-power and real-time processing capabilities.

Neuromorphic technology, combined with artificial intelligence (AI) and machine learning, can be used in defense systems to enhance processing power and give analytical results to speed up wartime decision-making. Moreover, this technology is much more energy efficient and can improve the mobility, endurance, and portability of technologies that soldiers can bring to the field. Furthermore, key companies in this market undertake continuous investments in research & development processes and launch innovative products to advance new research technology. For instance, in December 2022, Polyn Technology, an Israel-based Fabless semiconductor company, declared the accessibility of neuromorphic analog signal processing models for Edge Impulse, a machine learning development platform for edge devices addressing ultra-low power on sensor solutions for wearables and the Industrial Internet of Things (IIoT).