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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