In recent news, the research team at Facebook has introduced a general AI bot, ReBeL that can play both perfect information, such as chess and imperfect information games like poker with equal ease, using reinforcement learning. As the company says, it is a big step towards creating a general AI algorithm that could perform well over a range of games. The researchers believe that this algorithm will have real-world applications, including dealing with negotiations, fraud detection, and even cybersecurity. AlphaZero from DeepMind rapidly caught the fancy of the AI research community when it was released back in 2017. An AI-based program that could play games like chess, shogi, and Go is not unheard of, but AlphaZero is different as it uses reinforcement learning with search (RL Search) to'learn on its own' by mimicking the world-class players.

The list of recent defeats where humans were overmatched by machines are well-known: chess champion Garry Kasparov losing against IBM's Deep Blue, Jeopardy wiz Ken Jennings being soundly defeated by IBM's Watson, and Go champion Lee Sodol losing to Google's AlphaGo. We may also be able to add poker to the list of AI superiority. A recent twenty-day competition between poker champions (heads-up no-limit Texas hold'em, 120,000 total hands) and Libratus, an AI program created by Carnegie Mellow University professors Tuomas Sandholm and Noam Brown, had the AI coming out on top. This is particularly surprising because unlike games like chess and Go, where the information is upfront and know ("Perfect Information Games"), poker involves a great deal of hidden information ("Imperfect Information Games") and the seemingly-human characteristic of bluffing. It turns out that AI can learn the art of bluffing.

In the high stakes world of professional poker, calculating the odds can go a long way to help win the hand. And a new bot developed by a team of computer scientists could give even James Bond a run for his money. The DeepStack system uses Artificial Intelligence to reduce an exponentially complex number of calculations to a more manageable size - then decides on its play in a matter of seconds. A combination of cool composure, a strong hand and more than a dash of luck allowed James Bond to walk off with a massive £93 million ($115 million) pot in Casino Royale. DeepStack played 3,000 hands each against eleven professional players.

About three weeks ago, I was in a Pittsburgh casino for the beginning of a 20-day man-versus-machine poker battle. Four top human pros were beginning to take on a state-of-the-art artificial intelligence program running on a brand-new supercomputer in a game called heads-up no-limit Texas Hold'em. The humans' spirits were high as they played during the day and dissected the bot's strategy over short ribs and glasses of wine late into the evening. On Monday evening, however, the match ended and the human pros were in the hole about $1.8 million. For some context, the players (four men and the machine, called Libratus) began each of the 120,000 hands with $20,000 in play money, posting blinds of $50 and $100.

Marking a major step forward for artificial intelligence (AI), Libratus, an AI developed by Carnegie Mellon University (CMU), has resoundingly beaten four of the best heads-up no-limit Texas hold'em poker players in the world in a marathon, 20-day competition. After 20 days and a collective 120,000 hands played, Libratus closed out the competition Monday leading the pros by a collective $1,766,250 in chips. "I'm just impressed with the quality of poker Libratus plays," pro player Jason Les, a specialist in heads-up no-limit Texas hold'em like the other three players, said at a press conference yesterday morning. "They made algorithms that play this game better than us. We make a living trying to find vulnerabilities in strategies. That's what we do every day when we play heads-up no-limit. We tried everything we could and it was just too strong."

About three weeks ago, I was in a Pittsburgh casino for the beginning of a 20-day man-versus-machine poker battle. Four top human pros were beginning to take on a state-of-the-art artificial intelligence program running on a brand new supercomputer in a game called heads-up no-limit Texas Hold'em. The humans' spirits were high as they played during the day and dissected the bot's strategy over short ribs and glasses of wine late into the evening. On Monday evening, however, the match ended and the human pros were in the hole about $1.8 million. For some context, the players (four men and the machine, named Libratus) began each of the 120,000 hands with $20,000 in play money, and posted blinds of $50 and $100.

Marking a major step forward for artificial intelligence (AI), Libratus, an AI developed by Carnegie Mellon University (CMU), has resoundingly beaten four of the best heads-up no-limit Texas hold'em poker players in the world in a marathon, 20-day competition. After 20 days and a collective 120,000 hands played, Libratus closed out the competition Monday leading the pros by a collective $1,766,250 in chips. "I'm just impressed with the quality of poker Libratus plays," pro player Jason Les, a specialist in heads-up no-limit Texas hold'em like the other three players, said at a press conference yesterday morning. "They made algorithms that play this game better than us. We make a living trying to find vulnerabilities in strategies. That's what we do every day when we play heads-up no-limit. We tried everything we could and it was just too strong."

An artificial intelligence (AI) system developed by Carnegie Mellon University (CMU) has defeated four professional card sharks in a 20-day heads-up poker tournament in Pittsburgh. The AI, Libratus, possesses the ability to perform strategic reasoning and the compute power to process the 10 160 possible information sets a game of heads-up no-limit Texas Hold'em poker has. Libratus was developed by professor of computer science Tuomas Sandholm and computer science PhD student Noam Brown, and hosted on the Pittsburgh Supercomputing Center's Bridges computer. According to both Sandholm and Brown, Libratus' victory was not the result of luck. "The best AI's ability to do strategic reasoning with imperfect information has now surpassed that of the best humans," Sandholm said.

For decades, researchers have been pitting artificial intelligence (AI) against the top game players in the world. The heads-up no-limit Texas hold'em variant of poker may be the final frontier in the battle of man vs. machine over games. And it may be about to fall. In 1997, IBM chess computer Deep Blue defeated world chess champion Garry Kasparov. In 2011, IBM Watson defeated Ken Jennings and Brad Ruttner, the two winningest Jeopardy players in that game show's history.

Dong Kim is one of four professional poker players who will compete against CMU artificial intelligence in a 20-day poker competition, Brains Vs. He is shown here during the first Brains Vs. Four of the world's best professional poker players will compete against artificial intelligence developed by Carnegie Mellon University in an epic rematch to determine whether a computer can beat humans playing one of the world's toughest poker games. Artificial Intelligence: Upping the Ante," beginning Jan. 11 at Rivers Casino, poker pros will play a collective 120,000 hands of Heads-Up No-Limit Texas Hold'em over 20 days against a CMU computer program called Libratus. The pros -- Jason Les, Dong Kim, Daniel McAulay and Jimmy Chou -- are vying for shares of a $200,000 prize purse. The ultimate goal for CMU computer scientists, as it was in the first Brains Vs. AI contest at Rivers Casino in 2015, is to set a new benchmark for artificial intelligence. "Since the earliest days of AI research, beating top human players has been a powerful measure of progress in the field," said Tuomas Sandholm, professor of computer science. "That was achieved with chess in 1997, with Jeopardy! in 2009 and with the board game Go just last year.