How RANDOM is RANDOM
Ever since i started programming, i have always been fascinated by the degree of accuracy that computers have. Any standard computing device performs thousands of complex operations every second. It compute s values (in real-time) to a degree of accuracy not possible for an ordinary human.
I still remember this Quote from my very first computer book.
Computers do not grow tired. People do!! 🙂
This very quality of “Repeated-Non-tiring-Accurate” calculations, has made computers what they are today. We are totally dependent on computers and implicitly TRUST them. So much so that a giant furore was raised when it was found that certain Intel Pentium processors a floating-point division bug. This meant the result was offset by a value of 0.0000003 (FDIV-BUG). More recently, a similar public-rage was triggered by MS Excel floating-point bug.
Hence, (apart from the odd-bug) computers are very very very accurate.
But, as with all good things, there is a price to pay. There is a downside to this inherent accuracy. When it comes to generating Random Numbers, computers are in a soup.
Here is a Quick test. Which one of the 2 Graphs is an ACTUAL random distribution??
The one on the Right is truly RANDOM.
The one on the left is how Human’s perceive RANDOM.