Neuromorphic computing is a computing approach that mimics how the human brain works. Our gray matter is a marvel of nature, capable of handling huge volumes of data with incredible energy efficiency. While modern AI hardware is becoming better at processing complex tasks, it consumes vast amounts of energy.
One of the promises of neuromorphic computing is that it places memory and processing in the same location, using far less energy than traditional AI chips. However, even the most sophisticated neuromorphic systems are fairly simple and don't come close to matching the number of connections among human neurons.
But a new study published in the journal Science Advances suggests that by using sound waves instead of electricity, hardware can better mimic the parallel processing of neurons with even greater efficiency.
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