Machine Learning (ML) is the branch of Artificial Intelligence that studies computer algorithms that improve automatically (i.e., "learn") through experience. ML algorithms build mathematical model-based masive data sets, known as training data, in order to make predictions or decisions without having been explicitly programmed to do so. ML algorithms are used in a wide range of applications (e.g., computer vision, autonomous vehicles, cybersecurity) where it is difficult or impractical to develop conventional algorithms for the required work tasks. Data Mining is related to ML, and focuses on exploratory data analysis of massive data sets ("big data").
So how does AI in general, and Machine Learning in particular, relate to architecting and designing Digital Twins?
Artificial Intelligence (AI) & Machine Learning (ML) technologies provide the software infrastructure necessary for constructing intelligent ("smart") Physical Twins, and by extension their Digital Twin counterparts. Since AI & ML technologies are rapidly transforming how software-intensive Systems-of-Systems interact with humans, these complementary technologies will play a critical role in the evolution of Digital Twin technology.
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