Neuromorphic Chip Market

The global Neuromorphic Chip Market is estimated to Propelled by Adoption of Neuromorphic Chips in Edge Computing Applications


Neuromorphic chips are semiconductor chips that are designed to function like a human brain. These chips mimic neuro-plasticity- the brain’s ability to adapt as we learn. Neuromorphic chips find applications in edge computing where huge volumes of data are processed at the source instead of sending it to centralized cloud servers. Edge computing with neuromorphic chips helps process data locally for applications that require real-time low latency decisions like autonomous vehicles.

The global Neuromorphic Chip Market is estimated to be valued at US$ 44.8 billion in 2024 and is expected to exhibit a CAGR of 22% over the forecast period 2023 to 2030, as highlighted in a new report published by Coherent Market Insights.

Market Key Trends:

Adoption of Neuromorphic Chips in Edge Computing Applications

Global Neuromorphic Chip Market Size are being increasingly adopted for edge computing applications as they can process huge volumes of unstructured data in real-time with very low power consumption compared to traditional processors. Edge devices equipped with neuromorphic chips can autonomously take decisions on the field without transferring data to centralized cloud servers. This helps enable applications like autonomous vehicles, industrial IoT, and smart cities which require fast localized processing. The edge computing market is expected to grow rapidly over the next decade driven by the proliferation of IoT devices. The ability of neuromorphic chips to work with unsupervised learning directly on edge devices is expected to further propel their adoption in edge applications and drive the growth of neuromorphic chip market during the forecast period.

SWOT Analysis

Strength: Neuromorphic chips mimic the human brain’s ability of parallel and distributed information processing and are energy efficient. They enable artificial intelligence applications to operate nearly as well as biological neural systems.

Weakness: Neuromorphic chips are still in the research and development phase. Commercialization and mass production of these chips has not yet started which limits their applications. High development costs also pose challenges.

Opportunity: Neuromorphic computing has potential applications in areas such as pattern recognition, classification, prediction and cognitive computing. Rise of artificial intelligence and machine learning is creating demand for low-power computing methods like neuromorphic chips.

Threats: Established players in traditional semiconductor industry such as Intel, IBM and Qualcomm are investing heavily in neuromorphic technology which can pose competition to emerging players. Cybersecurity threats to AI systems implemented through these novel chips also need to be addressed.

Key Takeaways

The global neuromorphic chip market is expected to witness high growth over the forecast period of 2023 to 2030. The global Neuromorphic Chip Market is estimated to be valued at US$ 44.8 billion in 2024 and is expected to exhibit a CAGR of 22% over the forecast period 2023 to 2030.

North America currently dominates the market due to presence of major research institutions and companies investing in neuromorphic computing technology. The United States accounted for over 35% of the North America neuromorphic chip market in 2024. Asia Pacific is poised to be the fastest growing region during the forecast period. This is attributed to rising demand for low-power computing from countries like China and India and increasing focus of governments on development of AI technologies. Nations in the region are also attracting foreign investments for neuromorphic research from global tech giants.

Key players operating in the neuromorphic chip market are General Dynamics, Hewlett Packard Labs, IBM Corporation, Intel Corporation, Qualcomm, Samsung, and BrainChip Holdings Ltd. These companies are investing heavily in R&D to develop customized neuromorphic chips for applications such as image recognition and natural language processing. They are also collaborating with research institutions and startups to accelerate commercialization of this novel technology.

1. Source: Coherent Market Insights, Public sources, Desk research
2. We have leveraged AI tools to mine information and compile it