Millennium Problem: P versus NP

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Computer scientists classify problems based on how hard they are to solve, for example P and NP complexity classes.
P classes, Polynomial classes, are a polynomial function of the size of the inputs and are generally “easy”
This means that when the size of the inputs grows exponentially then the time to solve them does not. Take the example of multiplication. If we keep multiplying with bigger and bigger digits, the processing time of the calculator does not really change to get the answer. This is largely due to the fantastic algorithm it uses.
NP stands for non-deterministic polynomial time. Non deterministic means we don’t have a defined way to solve them and rely on heuristics like trial and error. For example, if we have to factorize a very large prime numbers, we will have to use trial and error to find the solution. The solving time would grow exponentially as the size of the prime number increases. In fact, a large part of our internet security is based on the fact that this is a NP problem. Also in these kind of problems, finding the solution is very hard if not impossible but checking if your answer is correct is not hard. So in the case of the large prime number if we are given the factors, we can quite easily check if they are correct or not (by multiplying) but finding the factors is very hard. So they are easy to check but impossible to solve. NP- Complete or (NPC) problems are the hardest problems in this class.

The fundamental question is - can we convert NP hard problems to P problems which we can solve? This is the million dollar question no pun intended. If we can, then Mathematicians and scientists become redundant because their originality and creativity is replaced by an algorithm. Problems like protein folding can be easily solved and we will find a cure for cancer.
So what do you think?
P = NP
Or
P ≠ NP
Proving either will get you a million dollars!

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