For nearly a century, scientists have looked to the brain to create computing models. The basis of many of these systems, from the earliest artificial intelligence to today's deep learning models, is artificial neural networks. These networks of electric nodes are a rough approximation of the inner workings of our minds. Like the neurons that carry pulses throughout our nervous system, the signals sent through artificial neural networks, or ANNs, allow machines to solve complex problems and even learn over time.
This technology has spurred advances in AI in the past few decades. ANNs, which have been considered the gold standard for computing systems based on the brain, are found in nearly every setting imaginable, from finance to robotics to smart phones.
But computing at this level can take a toll on resources. In one 2019 study, researchers estimated that a single deep-learning model can generate roughly the same CO2 ...
