The more close ended a task is, the more likely it can be performed by artificial intelligence.
Dear Suhel Ahmed ,
The algorithms and models used in AI and computer science are built upon mathematical concepts, such as linear algebra, calculus, statistics, and probability theory. In AI, mathematical models are used to build machine learning algorithms that can learn from and make predictions based on data.
https://www.quora.com/What-is-the-connection-between-math-and-artificial-intelligence-or-computer-science#:~:text=The%20algorithms%20and%20models%20used,make%20predictions%20based%20on%20data.
Regards,
Shafagat
AI uses different different concepts of Fuzzy Logic, Linear algebra, Calculus, Statistics etc.
It is not easy to equal the response by Shafagat Mahmudova but I would like to suggest you take a look at YouTube explainer RitvikMath.
He has excellent in-depth videos on all topics Shafagat mentioned plus more.
https://www.youtube.com/@ritvikmath
Hello, Suhel!
If you want a more in-depth answer, consider the following book: Mathematics for Machine Learning by Faisal, Diseroth and co.
An Open Course by MIT also covers the topic, if you're looking for a more lecture oriented option:
https://ocw.mit.edu/courses/18-657-mathematics-of-machine-learning-fall-2015/
Finally, the topic was covered on the environment of research papers that you may cite in
Mathematics for Machine Learning by Fabio Baca
https://www.academia.edu/77511672/Mathematics_for_Machine_Learning
That said, for a simple answer, artificial intelligence algorithms rely on very complex renditions of mathematics, featuring probability, algebra, discrete mathematics and such other mechanisms as can ne used to convey to the machine what we must. This can be us conveying how desireable the output information is, how desireable a certain change can be or even just what shape should a generally "random" generation take, given the lack of true randomness in computers. Again, I highly recommend the sources linked above for more.
All the AI algorithms are based on Optimization techniques. AI basically works on optimizing the layer weights for minimizing the error. Algorithms like Gradient descent, resilient propagation, etc are adopted in the AI algorithm
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