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neuromorphic computing

The future of neuromorphic computing
Recent progress in neuromorphic research is attributed in part to the widespread and increasing use of AI, machine learning, neural networks and deep neural network architectures in consumer and enterprise technology. It can also be attributed to the perceived end of Moore's law among many IT experts.

Moore's Law states that the number of transistors that can be placed on a microchip will double every two years, with the cost staying the same. However, experts forecast that the end of Moore's Law is imminent. Given that, neuromorphic computing's promise to circumvent traditional architectures and achieve new levels of efficiency has drawn attention from chip manufacturers.

Recent developments in neuromorphic computing systems have focused on new hardware, such as microcombs. Microcombs are neuromorphic devices that generate or measure extremely precise frequencies of color. According to a neuromorphic research effort at Swinburne University of Technology, neuromorphic processors using microcombs can achieve 10 trillion operations per second. Neuromorphic processors using microcombs could detect light from distant planets and potentially diagnose diseases at early stages by analyzing the contents of exhaled breath.

Because of neuromorphic computing's promise to improve efficiency, it has gained attention from major chip manufacturers, such as IBM and Intel, as well as the United States military. Developments in neuromorphic technology could improve the learning capabilities of state-of-the-art autonomous devices, such as driverless cars and drones.

Neuromorphic computing is critical to the future of AI. Learn the top nine applications of AI in business.

This was last updated in April 2023

https://www.techtarget.com/searchenterpriseai/definition/neuromorphic-computing