Do you think you’re the best at bluffing? Think again.
Within the last decade, Artificial Intelligence has consistently beaten various professional players in their games.
Whether it’s IBM’s Watson taking on Jeopardy’s best contestant in 2011 or AlphaGo beating the World Go champion in 2016, AI has surpassed the skill of human opponents in various games.
In 2017, AlphaZero wiped the floor with the world’s most advanced chess AI in a 100-game match-up. Now here’s the kicker, the AI spent only four hours learning how to play chess before demolishing the world champion chess program.
There’s no doubt that AI is capable of beating humans at their game. But, what happens when the chips are down, and real money is at stake?
Texas Hold’Em: Professional Poker Players vs. AI Gambling
Four professional poker players played a game of no-limit Texas Hold’em against Libratus system in 2017. After three weeks of playing 120,000 hands, the poker players ended up losing to the AI gambling system by a margin of over $1.76 million.
According to the Libratus co-developer, the popular misconception is that bluffing is a human thing and computers are incapable of it. As it turns out, not only can machines learn from experience when it has a weak hand, but it can also bluff its way into making more money.
Artificial Intelligence and Machine Learning are evolving. Now, gamblers are starting to understand how these modern computing techniques can increase their odds of winning.
How AI Gambling Affects Sport Betting
Sports betting involves understanding how a specific game works and placing a wager on the outcome. You should be able to predict (to a certain extent) who will win outright as well as the margin of victory. Unfortunately, this has never been easy.
However, with the rise in data analysis and algorithmic AI, any average Joe (or Jane) can accurately predict the outcome of sporting events. Here’s why.
Machine Learning provides a way to predict a target variable in data that’s previously unknown. This ML capability is known as Classification and involves building a model based on a training data set. Using the model, ML can predict the value of the class in the data set.
As a result, club managers and coaches can accurately assess their opponents and create effective strategies to win more matches. Also, individual sports gamblers and other stakeholders can estimate a game’s outcome ahead and plan accordingly.
Luck in Gambling
With the evolution of AI and ML, sports gambling as we know it should be over, right? Well, not entirely.
While the technology has the potential to take the “luck” element out of sports gambling, it’s not there yet. The predictive system is still incapable of accounting for certain factors like team morale, shifts in game momentum, and even team chemistry
However, future advancements in other fields such as machine vision could be all we need to upend the world of sports gambling. Until then, buying a winning ticket depends on analytics, instincts, and dumb luck.
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