Can AI Help You To Improve Your Poker Game?

From customer support to CEOs, stock trading to poker, AI proved it can find its place anywhere, from purely digital to the physical world. Poker, at first glance, may seem like a safe bet from AI implementation, but recent developments have shown different results. It’s easy to assume that AI can analyze past results, game rules, and data and then extrapolate results, which is only a beginning step for AI in poker.

Before dismissing AI applications in poker, we can consider the similarities and see the joint parallels between AI and poker books. Going through, reading, studying, and concluding was how poker training was in the past (we’ll cover this later). Players would learn and train about others to hone their skills. Then came the digital era, and poker moved online, allowing faster and more detailed matches. Gavin Beech suggests playing at some of the best bitcoin gambling sites available on the market, for any player who wishes to have fun and hone their skill. When online, players could find a much wider pool of potential challengers, test various strategies, and, most importantly, have a wider pool of data to conclude from.

Reading poker books, studying, looking at graphs, and analytics changed when poker data was harnessed into an AI. In the blink of an eye and without much investment (when we compare the two ways), AI can generate far more accurate results and predictions. AI eliminates the probability of human error and can help poker players with crypto gambling on online poker sites, as the base principle is the same from the AI perspective. We can view AI as a logical extension of data analytics evolution in poker, as with all industries. First came verbal tales and word-of-mouth reputations.

Then came poker books, active score tracking, leaderboards, and concrete data. Everything moved online and into a digital world, and now AI can use everything in our worldwide poker database to draw the best conclusions. The rich history of poker only forces AI to improve and give more accurate data, but that is only the first half of its use. New and veteran players can benefit from an AI coach, as it can mathematically calculate the probability of what the next card can be, what the optimal next move can be, and the game outcome.

In a controlled environment where a player is training, AI is equivalent to an experienced poker player sitting by your side, coaching you, and telling you the next best move. As many players don’t have the luxury of affording exclusive coaches or pro players at their side, AI is the next best thing. It’s available at any time, and anywhere, so even the most novice poker player can use it to train their skills. But, now the lines get a bit blurry and debatable. Because AI can tell you a mathematical chance of the next card appearing, some may call it card counting, which is illegal in poker, and other casino games.

Some cruder poker AI bots, like PokerBot were good, but the problem with AI is that it becomes predictable, as AI can not innovate, only replicate. Experienced poker players may lose several games at first, but they will soon see the patterns emerging, innovate, and adapt their strategies, which was beyond the scope of early AIs. In 2017 Libratus took that knowledge, evolved, and was able to beat most professional poker players. Soon, human players had an advantage, as bluffing, calling, and using psychological warfare in poker was a valid strategy, helping them beat AI until Pluribus was introduced in 2019. This arms race evolved through the advances of poker AI and the invention of PioSolver and Simple Postflop, which can run thousands of simulated poker games, extrapolate from previous data, and present the best solution.

Now, even playing online as a form of training is becoming redundant, as players can just request an AI to simulate thousands or tens of thousands of Texas ’Hold Em games and present them with a result. Even better (or worse?), players can play online and simulate a game in their AI coach on a different monitor or PC, asking them what the next optimal move would be. Poker AI has made the line between man and machine blurry, but only online. As an interesting event, a fundraiser, a demonstration, or a poker game between an AI and a human is interesting but is not feasible, exciting, or wanted on the market.

A game where an AI would play with an AI would be interesting, but an entire tournament would probably be boring to watch. Most poker games occur between humans, and no AI is allowed in professional matches for now. For training purposes, AI is the new competitive edge, and it could help train newer players faster and provide better results. All said so far may lead to an impression that AI will take over poker, but no technology is without its limits or downsides. Poker AI software like DeepStack struggles deeply in scenarios with multiple players, and if given enough time, good players start to recognize machine patterns. AI, at the moment, shines in a controlled environment but is not without flaws in the real world due to its lack of creativity, which is a human trait.

When promoting AI, it is also important to highlight that it is an advanced technology, which means it needs incredible (and expensive) computing power, hardware, and investment if a player wishes to get meaningful results in a reputable time. Using such advanced tech in the everyday lives of poker players is, for now, impractical and expensive. The facts remain that AI in poker has changed how we view the game. AI has made some new strategies possible, is an invaluable training tool, and has made incredible advancements in the short time it’s been around.

AI in poker can be seen as a premium feature that can be a springboard for new players and a honing skill for experienced players. Poker coaches can also benefit from its treasure trove of information. But practicality and ethics are the next hurdles AI must cross if we wish to see a more widespread application.

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