RNG (Random Number Generation) is the core of any online poker game. RNG is the game function that shuffles the deck of cards (in poker’s example) and comes up with a random set of cards. There is however something that the public does not know but is well known and thoroughly documented in scientific studies.
Did you know it is scientifically proven that it’s impossible to generate truly random numbers using computer software because a computer is deterministic?
In layman’s terms — a computer always knows all variables and to truly get a random result — you would need a mathematical function of ‘infinite unknown variables’. If you had the same starting inputs and conditions, even if the numbers appear to be random, you could replicate this and end up with the same output. A computer simply cannot know all infinite unknown variables with our current technology.
The most popular and widely used random number generators are Pseudo-Random Number Generators (PRNGs). These are modern, very efficient and make numbers appear as they are random, but in fact, they are not random and perfectly predictable.
PRNGs are very well programmed however you would need to set up a seed state that initializes the generator. This is the fundamental flaw in the PRNGs because high entropy is required and a computer cannot fully randomize this using software alone.
Problem for online gambling, casinos and poker games
This is a massive problem for online gambling because just about every single online casino/website and poker game relies on Pseudo-Random Number Generators. These computer mechanisms and similar methods cannot produce truly random numbers. Therefore, you often encounter many scenarios during your poker game where outcomes seem too ‘extreme’ or ‘rare’. Also these systems are open to alterations which can cause major security issues.
Online gaming platforms get away with it because even when they are certified and tested — the metrics used across all certification bodies permit full use of PRNGs and pass all the tests required.
Problems for third party testing/certifications
Although these pseudorandom sequences in PRNGs pass statistical pattern tests for randomness, by knowing the algorithm and the conditions used to initialize it, called the “seed”, the output can be predicted. This means that even though the poker site you are playing on claims to be tested by third parties, the machines used are still not producing truly random numbers. What makes this worse is if you knew the ‘seed’, you could easily know the outcome of the shuffle.
As we have learned so far, seeding from a computer cannot be random and is possible replicate the ‘randomness’ if the same starting conditions and seeds are used. All major certifications can be found here. These certifications are used even in the biggest poker sites in the world. They all allow PRNGs to operate alone as software and are never 100% random!
All statistical pattern tests through standard PRNGs pass every single third party testing certification across all jurisdictions of the world
Our Solution — Triple-Factor Random Number Generator (TFRNG)
Our Triple-Factor Random Number Generator (TFRNG) method changes the online poker game forever. We combine TRNG’s (Hardware Random Number Generators) with Blockchain Technology to create an efficient chain of processes which results in a more accurate random generated number that a software based system cannot produce.
This has never been done before in this manner.
To truly get a random result, you need to eliminate the limitations of the software process and introduce a ‘quantum phenomenon’. We take this a step further and add another layer of randomization through Blockchain hashes.
The flow chart below illustrates our process.
Factor I - Selection process
We start our process with a coin flip to select the order of Factors II and III. We flip a virtual coin in which gives a 50/50 chance for each outcome to come up. To maintain a truly random outcome we use variations in Atmospheric Noise to generate the random number required. This method exceeds the accuracy of any Pseudorandom Number Generating Algorithm.
Both Factors II and III use unique methods of randomization and are usually by themselves sufficient enough. In our mission to create the most fair and rewarding poker game on the planet — we doubled up on our RNG technology and introduced two unique methods of RNG combined instead of one.
In poker, there are 4 actions where cards are dealt; Pre-flop (players hand), Flop, Turn, River. In each action, our decks are reshuffled using an alternating Factor method. The only difference is the order which is defined by Factor I at the start of each new hand.
This process is as follows:
1. Factor I flips a coin and selects the order of II - III (or) III - II
2. Whichever Factor is selected to be first, will be used for randomizing the Starting Hands
3. Whichever Factor is selected to be second, will be used for randomizing the Flop Cards
4. The first Factor will then be used again for the random selection of the Turn Card
5. The Second Factor will then be used again for the random selection of the River Card
6. This process then starts again with a new coin flip when a new hand begins
Factor II - ‘Quantum Random Properties’ based Hardware Random Number Generator
Instead of using a mathematical model to deterministically generate numbers that look random and have the right statistical properties, a ‘True Random Number Generator’ (TRNG) extracts randomness (entropy) from a physical source of some type and then uses it to generate random numbers. The physical source is also referred to as an entropy source and can be selected among a wide variety of physical phenomenon naturally available, or made available, to the computing system using the TRNG.
Equipped with our server infrastructure, we run multiple instances of Quantis Hardware Random Number Generators for our Factor II. The hardware uses light Photons as the entropy source.
These forces of nature are scientifically proven to be completely random to the extent of our current scientific knowledge.
Each card in the remaining card deck corresponds to a specific pre-defined sequence of 0’s and 1’s. As the TRNG begins to work, it starts generating random numbers incredibly fast. Our systems start to record these numbers and once a sequence is detected that corresponds to a specific card — that card is selected and sent to the game client as the chosen card.
Factor III - Utilizing Bitcoin Blockchain transaction hash keys as a seed to PRNGs
Bitcoin peer to peer nodes within the Blockchain infrastructure solve complex math problems all day at over 26 Billion GH/s. The network creates new unique hashes throughout the day for new transactions that are not-yet-confirmed and confirmed. These are unpredictable and unique.
Hashes are stored in our internal collection database for future one-time use. Any duplicates are automatically removed as it is possible but unlikely, that duplicate transactions are detected. We keep a consistently updated log of hashes for future use so we can accommodate busier days that have more RNG requests (more hands played).
There are over 180,000 transactions per day on the Bitcoin network and growing fast
The third factor in our RNG process takes latest hash in our real-time collection as the ‘seed’ of our custom built PRNG algorithm and proceeds to randomize the remaining deck of cards for the required game action.
Since we are using an entropy source which is completely unpredictable and unique via the Blockchain, the PRNG works well as we did not rely on our computer to randomly generate the predictable entropy.
PRNGs can work well but it is the starting conditions that are the fundamental flaw of a deterministic system. Using Blockchain technology eliminates this problem. Although it comes with a few limitations, it is used as the secondary factor in our RNG process.
To future proof this Factor — in the extremely rare instance that we exceed our collection library and exceed the Bitcoin real-time network of hashes generated due to our player volume per hour increasing, our systems will look to supplement hashes from the Ethereum network as a backup. The switch is instantaneous and has been tested to cause no in game delay.
Putting it all together
1. In each hand, the deck is shuffled 4 times at every action (Pre-flop, Flop, Turn, River)
2. Both our RNG ‘shuffling’ methods are used in a alternating random order
3. One of our shuffling methods includes a ‘TRNG’ hardware based unit that looks at quantum properties. In simple terms it analyzes how light moves and records 0’s and 1’s based on its random/unpredictable movement
4. The other shuffling method uses Blockchain hashes to improve randomness by using a source that is both unique, unpredictable and that cannot be replicated
5. The end result is a continuously shuffled deck that is generated randomly through infinite unknown variables and has a 0% chance of predictability which makes it a true random source that no computer software on the planet can generate
What does all this really mean to Poker Players?
As a player, you will get fewer bad beats, fewer ‘coolers’ and less frequent extreme scenarios.
We are not claiming that these scenarios can never happen. We just believe that through our superior card shuffling technique — it happens less frequently meaning a good poker play will result in a more frequent win.
Through our discussions over the past year with many regular online poker players and from what our research has shown — he are some typical scenarios that happen frequently in your traditional online poker room:
How many times have pocket Jacks worked out for you? Even though they are statistically the 4th best starting hand in poker.
How many times have you hit your Ace while at the same your opponent also hit the Ace and one of you will likely get your money in ‘good’ and end up realizing the bad news?
How about playing lower pocket pairs like 9’s through to 2’s in an all-in pre-flop scenario and losing way more than half the time vs none pocket pair hands? Statistically you should be winning 55%* of the time.
Or the most obvious situation where you see crazy plays like 3+ people going all-in because for some reason the system dealt everyone premium hands all in one go? Especially in tournaments.
We are not claiming any of these in-game scenarios to be true but through our research and speaking with many online players, you hear these scenarios happening more frequently than they should be, statistically speaking.
This is all really due to using old RNG algorithms and methods that have not been updated for a long time instead of having hardware powered RNG systems that generate truly random numbers or like our system where we went fully bespoke and built something unique.
How many ‘game update’ emails have you received from the poker site that you play on? Compare that to how many emails you get about a new bonus. Most companies are simply focused on trying to squeeze as much revenue as possible instead of really improving the game of online poker.
Since computers are unable to truly generate random numbers, most traditional online casino and poker games are severely lacking in innovation when it comes to game fairness and integrity.
Many regular players simply accept bad beats and continue playing, while many others quit due to unfair money lost in incredibly rare scenarios that keep occurring.
These are serious issues with the current state of online gambling sites and there needs to be a genuine solution. Sites need to be turning towards hardware and innovative solutions to ensure games are fair. Old technology needs to be upgraded.
We believe to have created one of the most fair online poker games on the planet and it is just the beginning.