In-brief IBM has offloaded healthcare data and analytics assets from its Watson Health business, with private equity firm Francisco Partners hand over around $1bn for the privilege. The takeover "is a clear next step as IBM becomes even more focused on our platform-based hybrid cloud and AI strategy," Tom Rosamilia, senior vice president, IBM Software, told newswire Bloomberg. "IBM remains committed to Watson, our broader AI business, and to the clients and partners we support in healthcare IT." Launched in 2015, IBM Watson Health hasn't been able to turn a profit despite the company spending $4bn in acquisitions to grow the business and its capabilities. IBM has tried to whittle down its Watson Health division for a while, after struggling to sign hospitals as clients. Professional poker players are increasingly consulting specialized poker software programs to boost their chances of winning, but some believe it has made the game less fun and encourages cheating online.

I want to start off with a quick question – can you recognize the two personalities in the below image? I'm certain you got one right. For most of us early age math enthusiasts, the movie "A Beautiful Mind" is inextricably embedded into our memory. Russell Crowe plays the role of John Nash in the movie, a Nobel prize winner for economics (and the person on the left-hand side above). Now, you would remember the iconic scene often regarded as: "Don't go after the blonde". "….the best outcome would come when everyone in the group is doing what's best for himself and the group."

Chinese scientists have developed an artificial intelligence (AI) program that is quick-minded and on par with professional human players in heads-up no-limit Texas hold'em poker. Named AlphaHoldem, the AI program has achieved the level of sophisticated human players through a 10,000-hand two-player competition after three days of self-training, according to a paper which will be presented in February next year at AAAI 2022 global AI conference in Vancouver, Canada. Texas hold'em is a popular poker game in which players often deceive and bluff. It is more similar to real-world problems than Go or Weiqi and chess since decisions are made with imperfect information. The researchers from the Institute of Automation under the Chinese Academy of Sciences (CAS) reported that AlphaHoldem, a fast learner, used only about three to four milliseconds for each movement, about 1,000 times quicker than that of first-generation AI hold'em players DeepStack and Libratus.

With breakthrough of AlphaGo, AI in human-computer game has become a very hot topic attracting researchers all around the world, which usually serves as an effective standard for testing artificial intelligence. Various game AI systems (AIs) have been developed such as Libratus, OpenAI Five and AlphaStar, beating professional human players. In this paper, we survey recent successful game AIs, covering board game AIs, card game AIs, first-person shooting game AIs and real time strategy game AIs. Through this survey, we 1) compare the main difficulties among different kinds of games for the intelligent decision making field ; 2) illustrate the mainstream frameworks and techniques for developing professional level AIs; 3) raise the challenges or drawbacks in the current AIs for intelligent decision making; and 4) try to propose future trends in the games and intelligent decision making techniques. Finally, we hope this brief review can provide an introduction for beginners, inspire insights for researchers in the filed of AI in games.

The 32-year-old is the only person to have won four World Poker Tour titles and has earned more than $7 million at tournaments. Despite his expertise, he learned something new this spring from an artificial intelligence bot. Elias was helping test new soft ware from researchers at Carnegie Mellon University and Facebook. He and another pro, Chris "Jesus" Ferguson, each played 5,000 hands over the internet in six-way games against five copies of a bot called Pluribus. At the end, the bot was ahead by a good margin.

Tuomas Sandholm, a computer scientist at Carnegie Mellon University, is not a poker player--or much of a poker fan, in fact--but he is fascinated by the game for much the same reason as the great game theorist John von Neumann before him. Von Neumann, who died in 1957, viewed poker as the perfect model for human decision making, for finding the balance between skill and chance that accompanies our every choice. He saw poker as the ultimate strategic challenge, combining as it does not just the mathematical elements of a game like chess but the uniquely human, psychological angles that are more difficult to model precisely--a view shared years later by Sandholm in his research with artificial intelligence. "Poker is the main benchmark and challenge program for games of imperfect information," Sandholm told me on a warm spring afternoon in 2018, when we met in his offices in Pittsburgh. The game, it turns out, has become the gold standard for developing artificial intelligence.

Tuomas Sandholm, a computer scientist at Carnegie Mellon University, is not a poker player -- or much of a poker fan, in fact -- but he is fascinated by the game for much the same reason as the great game theorist John von Neumann before him. Von Neumann, who died in 1957, viewed poker as the perfect model for human decision making, for finding the balance between skill and chance that accompanies our every choice. He saw poker as the ultimate strategic challenge, combining as it does not just the mathematical elements of a game like chess but the uniquely human, psychological angles that are more difficult to model precisely -- a view shared years later by Sandholm in his research with artificial intelligence. WHAT I LEFT OUT is a recurring feature in which book authors are invited to share anecdotes and narratives that, for whatever reason, did not make it into their final manuscripts. In this installment, Maria Konnikova shares a story that was left out of "The Biggest Bluff: How I Learned to Pay Attention, Master Myself, and Win" (Penguin Press). "Poker is the main benchmark and challenge program for games of imperfect information," Sandholm told me on a warm spring afternoon in 2018, when we met in his offices in Pittsburgh.

I want to start off with a quick question – can you recognize the two personalities in the below image? I'm certain you got one right. For most of us early age math enthusiasts, the movie "A Beautiful Mind" is inextricably embedded into our memory. Russell Crowe plays the role of John Nash in the movie, a Nobel prize winner for economics (and the person on the left-hand side above). Now, you would remember the iconic scene often regarded as: "Don't go after the blonde". "….the best outcome would come when everyone in the group is doing what's best for himself and the group."

The AI, called Pluribus, defeated poker professional Darren Elias, who holds the record for most World Poker Tour titles, and Chris "Jesus" Ferguson, winner of six World Series of Poker events. Each pro separately played 5,000 hands of poker against five copies of Pluribus. In another experiment involving 13 pros, all of whom have won more than $1 million playing poker, Pluribus played five pros at a time for a total of 10,000 hands and again emerged victorious. "Pluribus achieved superhuman performance at multi-player poker, which is a recognized milestone in artificial intelligence and in game theory that has been open for decades," said Tuomas Sandholm, Angel Jordan Professor of Computer Science, who developed Pluribus with Noam Brown, who is finishing his Ph.D. in Carnegie Mellon's Computer Science Department as a research scientist at Facebook AI. "Thus far, superhuman AI milestones in strategic reasoning have been limited to two-party competition. The ability to beat five other players in such a complicated game opens up new opportunities to use AI to solve a wide variety of real-world problems."

While AI had some success at beating humans at other games such as chess and Go (games that follow predefined rules and aren't random), winning at poker proved to be more challenging because it requires strategy, intuition, and reasoning based on hidden information. Despite the challenges, artificial intelligence can now play--and win--poker. Artificial intelligence systems including DeepStack and Libratus paved the way for Pluribus, the AI that beat five other players in six-player Texas Hold'em, the most popular version of poker. This feat goes beyond games. This achievement means that artificial intelligence can now expand to help solve some of the world's most challenging issues.