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Neuromorphic Computing

Reinventing how computers think based on biological neural networks


Neuromorphic computing can be described as the designing of computers that mimic the way the human brain operates, using a combination of artificial neuron networks instead of using a tradition computer processing unit for calculations. The key benefit of this technology is the lower power requirements, faster processing speed, and smaller space required for the hardware component. In terms of use cases, the primary use case is the application of neuromorphic computers for big data analytics and machine learning, as neuromorphic computers are able to learn faster than tradition computers. It is expected that neuromorphic computing would bring a third wave of AI into play, where AI will more closely operate in a manner similar to the human brain compared to current AI models and technology.

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Use cases

The low power consumption and the natural and efficient way of processing information has paved the way for various use cases for neuromorphic computing. Applications that require large volumes of processing, such as computer vision, have been a natural fit for this industry, with use cases such as surveillance, visual inspections ranging from defects in the production line to aquaculture, and space debris management. Process automation across work, using neuromorphic-based AI, is also an emerging area with multiple applications across process optimization and automation.

We have identified key neuromorphic computing use cases below:

Market Mapping


The Disruptors

Funding History

Notable Investors

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