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My poker heroes were cowboys, but the internet saw them off


I was one of those who said it could never be done: that a computer wouldn't ever manage to beat the best at the game of poker. I was romantic and wide-eyed at 18, when my heroes were the cowboys from Texas who ruled the felt. They were uneducated and coarse, yet chock full of the human qualities needed to excel at poker. With nicknames like Amarillo Slim and Texas Dolly, these larger-than-life characters had fearlessness, aptitude, and a deep understanding of what makes people tick. The higher the stakes, the better they played.

Poker AI (Artifical Inteligence) Paul Phua Poker School Poker News


Last week a team of poker players in China were resoundingly defeated by "Lengpudashi". Meaning "cold poker master", Lengpudashi is the new, even more improved version of the Libratus AI (Artificial Intelligence) programme that I wrote about back in January. Not surprisingly, this latest AI victory has been big news: people have worried for years that robots equipped with AI will take over human jobs. Now not even poker is safe. Though computer programmes long ago proved their superiority in the classic skill game of chess, until now the bluffing and intuitive elements of poker – its very human elements – had made it hard for a machine to master.

Poker pros are latest losers in battle of man versus machine


The latest battle between man and machine is being played out on the poker tables of a Pennsylvania casino, and so far humanity is losing. An artificial intelligence computer program called Liberatus has accumulated winnings of almost $800,000 against a team of professional poker players at the Brain Vs. Liberatus, developed by Carnegie Mellon School of Computer Science, is aiming to be the first computer program to win a professional poker tournament--a game considered by many AI researchers to be one of the hardest for computers to beat humans at. Artificial intelligence advances in recent years have seen computers master and eventually outperform the best human players at games including Chess and the game show Jeopardy!. In 2016, researchers at Google's DeepMind developed a system that was able to beat champion Go player Lee Sedol--a significant step for artificial intelligence.

Artificial Intelligence Beating World's Best Professional Poker Players


The world's best professional poker players appear to have found their match: An artificial intelligence developed by researchers from the Carnegie Mellon University (CMU). The AI dubbed Libratus has already accumulated winnings of nearly $800,000 against human poker professionals at the Brain Vs. The human players compete to win shares of the $200,000 prize while Liberatus aims to be the first computer program to win in a professional poker tournament. Many AI researchers consider poker to be among the hardest games for computers to beat humans at. How AIs fare against human players when performing tasks has long been used as a measure of progress in the field of AI research.

University of Alberta poker bot Deepstack defeats Texas Hold 'em pros - Cantech Letter


The University of Alberta's Computer Poker Research Group created DeepStack, an artificial intelligence program that defeated professional human poker players at heads-up, no-limit Texas hold'em. Apart from this win being the first of its kind, it bares significance in assisting to make better medical treatment recommendations to developing improved strategic defense planning, stated DeepStack: Expert-level artificial intelligence in heads-up no-limit poker, which was published in Science. DeepStack brings together approaches involving games of perfect information, meaning both players see what is on the board, and imperfect information, where it reasons while playing, using intuition through learning to reassess its strategy with every decision. Computing scientist Michael Bowling, professor in the University of Alberta's Faculty of Science and principal investigator on the study, said poker has presented an ongoing challenge to artificial intelligence. "It is the quintessential game of imperfect information in the sense that the players don't have the same information or share the same perspective while they're playing," explained Bowling.