Neuromorphic Computing Market Poised for Expansion in Healthcare AI Systems

The Global Neuromorphic Computing Market size was estimated at USD 5,277.2 million in 2023 and is projected to reach USD 20,272.3 million by 2030, growing at a CAGR of 19.9% from 2024 to 2030. The growing adoption of neuromorphic technology in deep learning, transistors, accelerators, next-generation semiconductors, and autonomous systems such as robotics, drones, self-driving vehicles, and AI systems is significantly contributing to market expansion.

For example, in August 2022, a multidisciplinary research team led by engineers at UC San Diego developed NeuRRAM, a neuromorphic chip that delivers improved accuracy and reduced energy consumption for AI applications compared to existing platforms. The rising demand for faster and more efficient neuromorphic chips with real-time and parallel processing capabilities is expected to continue driving market growth.

Innovations in chip design and fabrication are further advancing the market by enabling more efficient and scalable neuromorphic architectures. In September 2022, Intel introduced the Kapoho Point development board built on the Loihi 2 research chip and the Lava software framework to accelerate neuromorphic computing. This 8-chip board supports large-scale workloads and low-latency sensing with improved energy and speed performance. It also fosters the commercial adoption of neuromorphic solutions by offering a scalable AI development platform, helping address complex problems more efficiently. Moreover, growing usage in edge computing, IoT devices, and autonomous systems is capitalizing on neuromorphic computing’s real-time and low-power processing strengths.

Key Market Trends & Insights

• North America led the market with 37.3% revenue share in 2023.
• The U.S. held a major portion of the regional market.
• Image processing was the leading application, accounting for 45.5% revenue share in 2023.
• Edge deployment was the largest deployment segment in 2023.
• Hardware was the dominant component in terms of revenue in 2023.

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Market Size & Forecast

• 2023 Market Size: USD 5,277.2 Million
• 2030 Projected Market Size: USD 20,272.3 Million
• CAGR (2024–2030): 19.9%
• Largest Market: North America
• Fastest Growing Market: Asia Pacific

Key Neuromorphic Computing Company Insights

Several key players are at the forefront of neuromorphic computing innovation, including IBM, Intel Corporation, and Brain Corp.

IBM is developing neuromorphic solutions like the TrueNorth chip, which simulates 1 million neurons and 256 million synapses. This processor enables real-time processing for applications such as image and speech recognition and supports low-latency performance via IBM’s neural architecture and software frameworks like Corelet.

Intel Corporation, a leader in semiconductors and AI solutions, offers the Loihi self-learning neuromorphic processor, capable of simulating 128 million neurons and 64 billion synapses. It supports applications across autonomous systems and smart devices. Intel’s Neuromorphic Research Community (INRC) fosters collaborative R&D, while its offerings like Hala Point, Kapoho Point, and Loihi 2 enhance performance and energy efficiency, impacting sectors such as healthcare, finance, and transportation.

Key Neuromorphic Computing Companies:

• Brain Corporation
• CEA-Leti
• General sion Inc.
• Hewlett Packard Enterprise Development LP
• HRL Laboratories, LLC
• IBM
• Intel Corporation
• Knowm Inc.
• Qualcomm Technologies, Inc.
• SAMSUNG
• Vicarious

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Conclusion

The neuromorphic computing market is witnessing accelerated growth, driven by rapid technological advancements and increasing adoption across AI-intensive applications. With innovations in chip design, strategic collaborations, and expanding use in edge computing and autonomous systems, the sector is poised for significant transformation. The contributions of major players such as IBM and Intel highlight the industry's momentum toward building energy-efficient, brain-inspired computing solutions for real-time, complex problem-solving across diverse industries.