I wasn't satisfied with other P vs NP videos so I came up with a more visual explanation of P vs. NP and specifically the difference between polynomial vs exponential growth by considering where loops occur in an algorithm. This is part of a longer CS series: https://www.youtube.com/watch?v=fjMU-km-Cso&list=PLbg3ZX2pWlgI_ej6ZhGd45-cPoWLZD9pT

This video delves into the fundamental principles that govern the computational universe, influenced by the minds of Von Neumann and Turing.

0:00 - The origins of the universal machine and the Von Neumann architecture
1:00 - Time and Space complexity intro
1:25 - John Nash writes letter to NSA
2:17 - Graphing time complexity
2:49 - Linear time growth
3:16 - Polynomial Growth
4:30 - Exponential Growth
7:34 - NP problems
8:39 - Non deterministic machines
9:12 - Non deterministic polynomial time
9:50 - NP Complete
10:16 - Does P = NP?