In discussions with customers we always talked about the importance of learning mathematics and computer science. Some listeners knew what these two subjects were, but did not understand how they became an indispensable part of the AI field, and how the two aspects of knowledge work together.
I will use this statement to illustrate the explanation:
a = a + b * c
First, if you think of it as an algebraic equation, the statement may be mathematically meaningless for practical use.
However, if you are familiar with computer programming, you can use a, b, and c as variables, let this line of code use the result of the multiplication of b and c, and then use the addend to update the value of a. It is computationally possible.*
So far, it is the lower school level of mathematics and computer science.
In AI or machine learning algorithms, this statement will be further applied to more advanced mathematical calculations. First of all, a, b, c will be matrix types (multi-dimensional or arrays) rather than single values, and involve addition and multiplication of matrices.
Secondly, on the basis of machine learning – in order to achieve "Backpropagation" and "Gradient Descent", similar lines of code will be used to iteratively update the matrix values via computer programming. In short, the core foundation applies the principle of differential calculus, through the iterative mathematical operation a = a + ... to achieve AI "learning".
In computer programming, iterative operations are frequently implemented via For-Loop statements.
Thirdly, artificial intelligence can recognize and predict certain things. You might think that statistics and probability are also the mathematical foundations for realizing machine learning algorithms.
The application and research in the field of artificial intelligence involves the mathematical knowledge of calculus, matrix, statistics and probability from high school to university.
*It is at least feasible in Python programming, and it can also be "simplified" as a += b * c.
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