ИСТИНА

Conventionally, engineers strongly preferred analytical solutions, while empirical approaches to engineering problems were treated as inevitable evil when people are unable to work analytically. But at present, we witness a paradigm shift: data-driven research gets adopted in many fields. This can be explained by two complementary processes: ML and AI technologies are becoming more convenient and accessible for an increasing number of researchers, while engineers agree and even seek to apply the technologies. In this lecture, we give a brief reminder of the computation graph concept which is the basis of many contemporary AI technologies, then we proceed to using AI in different domains, highlighting the fields where traditional mathematics was used previously.