Anyone who has ever played any sort of online sweepstakes games will have experienced the typical feeling of concern over the impact of so-called “random” number generation (RNG). It’s easy to feel like the computer is against you – and when money is involved, as it is with many gambling transactions, the feelings of unfairness can quickly rise to the surface.
But the reality is that computers certainly do have the ability to generate numbers on a somewhat random basis – and that gamblers are not necessarily being hard done by when they play a gambling game that revolves around RNG. This article will explain what RNG is and will look at the science behind it for gamblers and others.
The wider RNG context
Random number generation is a task that most computers have to carry out from time to time. Although most bettors might not consider this, computers regularly have to perform random number generation to ensure they can encrypt the files of their users. Encryption is a key part of modern computer security, meaning that the average random number generation service is not bad at all.
For a better, this offers at least some basic comfort and protection. After all, if it’s possible for a computer to generate a random number to protect key files, it’s possible for that same computer to generate random numbers in slot games and other gambling endeavors. But random number generation is often experienced in a different way for those who gamble.
Difficulties in achieving RNG
Random number generation has been a key task for both people and computers for a long time now. Ever since a coin that could be tossed was invented (and even before), random number generation has been possible. In the modern age, however, the sheer firepower of most modern computers means that it is now possible for random number generation to occur on a systematically large, fast-paced scale.
It’s not nearly as easy as it might seem to an outsider to generate random numbers on this sort of scale. That’s because of the way a computer works on a fundamental level: computers rely on humans to input instructions, and as a result, they end up working almost entirely based on those instructions, and the possibility of “randomness” or chance is therefore reduced. For a computer that relies on human pre-programming, doing something ‘off the wall’ would seem impossible.
The methods available
For those who program gambling sites or similar, there are numerous methods available that are designed to help companies and platforms get the sort of random number generation services they need. One such approach is to use “pseudo-random number generators,” or PRNGs: this approach relies on using formulas or algorithms to lead to random number generation.
However, these aren’t “true” random-generated numbers – and the differences can be stark. Pseudo-random number generators have created a “list” of numbers beforehand and are simply moving from one to the next. The list itself might be generated by the power of the computer, but it exists all the same. A “true random generated number” (or TRNG) meanwhile, is different – each time a number is generated using this method, it happens due to some sort of external phenomenon of randomness which is moved over into the particular context.
The benefits of each approach are diverse and depend on the individual site or provider. Creating PRNGs is speedy and effective and can be done in a quick timeframe: for a gambling provider, that can be a boon. But the advantage of a TRNG is that it is truly non-manipulatable: in a context such as placing bets, where true randomness is vital to ensure that all those who place wagers are playing in a fair environment, TRNGs might well end up being more desirable.
RNG can sometimes cause some controversy and it’s perhaps easy to see why. But the reality is that randomly generated numbers are simply that – a way of objectively putting together a sequence of figures which determine whether or not the gambler has won. Given how much science exists behind them, they’re not out to get you – even if they may be the bearers of bad news. In sum, random number generation might not always deliver in your favor – but it’s certainly an objective, scientific method that is well-respected by many in the math community.