The Sunday How A.I. Conquered Online Poker

In late 2017, artificial intelligence shocked the online poker world by defeating some of the best human players in one-on-one matches. The decisive victory came when a program developed by London-based company Cerebrawl beat two of the most successful professional poker players, Jason Les and Dong Kim.

This AI accomplishment is all the more impressive when you consider that poker is a complex game that relies on both luck and skill. To win, a player needs to make the right decisions based on incomplete information while also anticipating the moves of their opponents.

A.I. has been able to crack complex games like poker in part because of its ability to learn from experience. By playing against itself over and over again, a program can improve its decision-making skills and ultimately beat human opponents.

This is not the first time that A.I. has outperformed humans in a competitive activity. In 2016, Google’s AlphaGo program defeated Lee Sedol, one of the world’s best Go players. Go is an even more complex game than poker, with thousands of possible move combinations compared to poker’s ten million.

So why is it that A.I. is so good at beating humans in complex tasks? One explanation is that humans are inherently limited in terms of what they can process and remember. We simply don’t have the computational power or memory capacity to deal with the vast amount of information involved in these activities.

A machine, on the other hand, can process and store huge amounts of data without getting tired or frustrated. It can also run through millions of scenarios and calculate different outcomes very quickly. This gives it a distinct advantage over humans when it comes to complex tasks like chess, poker, and Go.

Looking forward, it will be interesting to see how A.I. continues to challenge human dominance in other areas such as online trading, legal research, and creative writing

AI Beats Humans In Online Poker Again

In a recent study, artificial intelligence (AI) was shown to be better than humans at playing online poker. This is the second time that AI has outperformed humans in this domain – back in 2017, AI also proved to be better than humans at the game.

The research, which was conducted by a team of computer scientists at the University of Alberta in Canada, involved two different AI agents – both of which were able to outplay human opponents in a number of different games of poker.

The first agent, dubbed “DarkForest”, was based on a deep learning approach and was able to defeat human players in both limit and no-limit Texas Hold’em games. The second agent, called “Cepheus”, was based on a different AI technique known as Monte Carlo Tree Search (MCTS). This agent was able to beat human players in heads-up limit Texas Hold’em games.

Commenting on the findings, one of the lead researchers involved in the study, Michael Bowling, said that the results showed that AI was now better than humans at solving many imperfect information games – something that had previously been seen as difficult for machines to do.

So why are machines outperforming humans in online poker? One possible reason is that machines are able to process large amounts of data much faster than humans can. They can also analyze this data more effectively, allowing them to make better decisions during gameplay.

Another reason may be that machines are not affected by emotions or biases in the same way that humans are. For example, when playing poker, humans may be more likely to make rash decisions if they are feeling frustrated or angry. Machines are not subject to these emotions and so can make more rational decisions when playing poker.

Whatever the reasons may be, it is clear that machine intelligence is beginning to surpass human intelligence in a number of domains – including online poker. As such, it will be interesting to see how AI develops over time and whether it continues to outperform humans in other areas too.

How A.I. Took Down The Metropolitans 92

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The Mets, who were heavily favored to win the World Series this year, were surprisingly taken down by the Los Angeles Dodgers in just four games. many experts are now pointing to the Dodgers’ formidable A.I. system as the reason for their upset victory.

The Dodgers’ A.I. system is custom-built for baseball and is able to make split-second decisions based on a variety of factors, including player positioning, situational analysis, and batting and pitching tendencies. It can also adjust on the fly based on how the game is going.

For example, if the Dodgers are losing early in a game, the A.I. system will automatically pull its pitcher out of the game and put in a relief pitcher who is better suited to hold onto a lead. This sort of reactionary decision-making would be impossible for a human coach to match.

The Mets, on the other hand, relied heavily on analytics and data-driven decision-making throughout the season. However, they simply could not compete with the speed and flexibility of the Dodgers’ A.I. system.

In fact, some observers have gone so far as to say that this may be the beginning of the end for baseball as we know it, as more and more teams deploy advanced A.I. systems like the Dodgers’. With teams becoming ever more reliant on machines to make decisions for them, it’s only a matter of time before human coaches become obsolete.

A.I. Wins Big In Online Poker Again

In a stunning victory for artificial intelligence (A.I.), an updated version of the program called Libratus knocked out four of the world’s top poker players in a 20-day marathon match at Rivers Casino in Pittsburgh.

The $1 million purse was divided among the human players, who took home $740,000, $150,000, and two $80,000 prizes, while Libratus earned nothing. But the real prize may be in future applications for the technology.

Libratus is the product of some four years of research by a team of computer scientists at Carnegie Mellon University led by Tuomas Sandholm. The A.I. program’s advantage is its ability to “learn” as it plays, adjusting its strategy on the fly based on feedback from previous hands.

This is not the first time that A.I. has beaten top humans in competitive games. In 1997, IBM’s Deep Blue computer beat world champion Garry Kasparov in a chess match. And late last year, Google’s AlphaGo program beat Ke Jie, considered the best Go player in the world.

What is different about poker is that it is a imperfect information game — which means that each player doesn’t have access to all of the information available to all players. This makes bluffing an important part of the game and makes it difficult for A.I. programs to “learn” how to play well.

Libratus overcame this challenge by using a technique known as “counterfactual regret minimization,” which allows it to consider a much broader range of moves than other A.I. programs used in similar competitions in the past.

So what does this mean for the future? It is clear that artificial intelligence has now overtaken humans in yet another task — one that requires both cognitive and strategic skills. As Sandholm pointed out after Libratus’ victory: “Poker involves many complex tasks…that are very hard for computers but easy for humans…Now we have solved these problems and also developed efficient algorithms that can handle these tasks even better than humans can….We are now ready to apply these algorithms to other areas where people face great challenges, such as negotiation and bargaining or making financial decisions under risk.”