Neuromorphic computing—a field that applies principles of neuroscience to computing systems to mimic the brain’s function and structure—needs to scale up if it is to effectively compete with current computing methods. In a review published Jan. 22 in the journal Nature, 23 researchers, including two from the University of California San Diego, present a detailed roadmap of what needs to happen to reach that goal. The article offers a new and practical perspective toward approaching the cognitive capacity of the human brain with comparable form factor and power consumption.
The post UC San Diego: Researchers Explore Neuromorphic AI’s Path to Efficiency and Scale appeared first on HPCwire.
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