Big O(n!) Complexity

The video tutorial discusses the rare and impractical complexity of O(N!) or factorial time complexity. It explains that this complexity involves adding a nested loop for every element in an array, making it highly inefficient and almost impossible to encounter in real-world coding scenarios. The tutorial emphasizes the importance of being aware of this complexity, despite its impracticality, and concludes with a reminder of its significance in understanding scalability issues.

Why is ON factorial complexity considered rare and almost impossible to encounter?

What does ON factorial complexity imply in terms of nested loops?

How does the increase in the number of items affect the performance of a program with ON factorial complexity?

What is the significance of understanding the scalability issues related to ON factorial complexity?

What should one be aware of regarding ON factorial complexity, according to the lecture?