An artificial intelligence modeled after the neural circuitry in mammalian brains can keep learning new aromas without forgetting others.
When it comes to identifying scents, a “neuromorphic” artificial intelligence beats other AI by more than a nose.
Like the olfactory system in the mammal brain, some of the AI’s neurons are designed to react to chemical sensor inputs by emitting differently timed pulses. Other neurons learn to recognize patterns in those blips that make up the odor’s electrical signature. As a result, the neuromorphic system is a quicker, nimbler study. Just as a sports team may need to watch a play only once to understand the strategy and implement it in new situations, the neuromorphic AI can sniff a single sample of a new odor to recognize the scent in the future, even amidst other unknown smells.
Thomas Cleland of Cornell University and Nabil Imam of Intel in San Francisco pitted their neuromorphic AI against a traditional neural network in a smell test of 10 odors. To train, the neuromorphic system sniffed a single sample of each odor. The traditional AI underwent hundreds of training trials to learn each odor.
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