Digital twin models may enhance future autonomous systems.
Systems controlled by next-generation computing algorithms could give rise to better and more efficient machine learning products, a new study suggests.
Using machine learning tools to create a digital twin, or a virtual copy, of an electronic circuit that exhibits chaotic behavior, researchers found that they were successful at predicting how it would behave and using that information to control it.
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