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  • 2 months ago
The question of RNG is a matter of heated debate in the gaming community. Is the random number generator used in casino games like slots or roulette truly, reliably random and fair? If true randomness cannot be achieved, what does that mean for us players and our winning odds?
Transcript
00:00Is the random number generator, or RNG, truly random?
00:04This is one of the most common questions among casino players, and the answer is, no, not
00:08entirely.
00:09But it is random as much as possible.
00:12To truly understand why, we first need to understand what randomness is.
00:16According to the Merriam-Webster dictionary, randomness is a haphazard occurrence that
00:21happens without definite aim, direction, rule, or method, and something that lacks a specific
00:27plan, purpose, or pattern.
00:29By this definition, true randomness, which results in unpredictable sequences that happen
00:33with no pattern whatsoever, exists only in nature.
00:38To achieve true randomness in any RNG algorithm would necessitate recording accidental quantum
00:43phenomena and feeding all that data to a supercomputer, since this is not possible.
00:49No single human-created RNG can be truly random in online gambling or anywhere else.
00:54To compensate, computer engineering uses two emulating programming methods, quasi-random
01:00and pseudo-random, and one hardware solution.
01:04The quasi-random approach.
01:06To create an RNG, a computer programmer takes a set of logical instructions that can be given
01:11to a computer, which then produces a quasi-random RNG.
01:15However, by measuring and testing the outcome of quasi-randomness in the long run, results
01:19do show a pattern, since the machines are governed by that programming.
01:23When it comes to craps, roulette, or backgammon, the quasi-randomness in RNG can be noticed
01:28after years of observation.
01:30The most advanced players use it occasionally, just as some online casinos do, which puts
01:35them in an advantageous position.
01:37Luckily, online casinos that use this method are very rare or non-existent nowadays.
01:42The pseudo-random approach.
01:44The pseudo-random method is the current RNG standard in interactive games.
01:49Dr. Steve Ward, professor of computer science and engineering at MIT, sheds some light into
01:54pseudo-randomness and software engineering.
01:57Quote, one thing that traditional computer systems aren't good at is coin-flipping.
02:02They're deterministic, which means that if you ask the same question, you'll get
02:05the same answer every time.
02:07In fact, such machines are specifically and carefully programmed to eliminate randomness
02:12and results.
02:13They do this by following rules and relying on algorithms when they compute.
02:17On a completely deterministic machine, you can't generate anything you could really
02:21call a random sequence of numbers, because the machine is following the same algorithm
02:25to generate them.
02:27Typically, that means it starts with a common seed number and then follows a pattern.
02:31They are what we call pseudo-random approach.
02:34End quote.
02:35For the majority of practical applications, this approach is more than enough.
02:39Measuring and testing the outcome of pseudo-randomness in the long run is a difficult and time-consuming
02:43process that requires computers and is impossible for any human being to do on their own, even
02:49over the course of a lifetime.
02:51The only completely unpredictable random number generator is a hardware device that creates
02:57numbers from physical processes, changes that affect the form of a chemical substance but
03:02not its composition, instead of a software algorithm.
03:06These devices are based on microscopic phenomena that generate statistically random signals such
03:10as thermal noise, agitation of the electrons inside of an electrical conductor, which happens
03:16regardless of applied voltage present in any electrical circuit, the photoelectric effect,
03:22emission of electrons when light hits any material which, in turn, creates photoelectrons,
03:27or any quantum phenomenon like superfluidity, superconductivity, or the quantum Hall effect.
03:33In other words, hardware RNGs are based on randomness that exists in nature.
03:38This method is used today in data encryption to create cryptographic keys or in security protocols
03:44like TLS, SSL.
03:46As Dr. Ward notes, the use of hardware RNGs makes reverse engineering of a Coker algorithm
03:51impossible, because they rely on unpredictable processes instead of human-defined patterns.
03:57Of course, as he also notes, quote, the results might still be slightly biased towards higher
04:02numbers or even numbers, but at least they're not generated by a deterministic algorithm,
04:07end quote.
04:08Why this bias?
04:10Because hardware RNGs can produce only a limited number of random information per second.
04:15To increase the output, devices are only used to create the C, a number which is used to
04:20initialize pseudo-randomness, and afterwards, the software takes over and boosts up the whole
04:24sequence.
04:25So what does all this mean for us, the players?
04:28What we should have in mind is that all RNGs are created with some form of certainty that
04:33players can potentially win.
04:35Remember that pseudo-random RNG simulates true-randomness very well and is functionally indistinguishable
04:41from it.
04:42It's up to us to choose reputable online casinos that perform regular RNG tests, carry
04:48up software integrity checks, and conduct fairness audits of games.
04:51Those are the only things any prudent and responsible player can do, other than choosing games wisely,
04:57using their skills to the best of their knowledge, and staying well within the limits of their
05:01gaming budget.
05:02Such determination should not be random, just as any RNG is not random at all.
05:07We hope this video was helpful.
05:08Don't forget to like and subscribe for more gaming content.
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