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Daniel Negreanu on Poker and Picking Up Tells


Daniel Negreanu is one of (if not the best) poker player in the world today. He has set all kinds of records in the poker community, but today he tells us how he did it. To kick things off, Brian and Daniel discuss their old spat from Tilt and how their relationship has changed since then (5:00), when Daniel decided to become a professional poker player (17:00), and how he observes people to pick up information (27:00). Also, the two talk about how Daniel's definition of success has changed over the years (32:00), what he's interested in outside the poker table (45:00), and how the Rocky movies help get him ready to make a run at the WSOP Final Table every year (54:00).

Machine learning goes beyond theory to beat human poker champs ZDNet


Among the many achievements of machine learning in recent years, some of the most striking are the victories of the machine against human players in games, such as Google's DeepMind group's conquest of Go in 2016. In such milestones, researchers are often guided by theoretical math that says there can be an optimal strategy to be found, given a good algorithm and enough compute. But what do you do when theory breaks down? Two researchers at Carnegie Mellon University and Facebook went back to the drawing board to solve "heads-up no-limit Texas hold'em," the most popular form of multiplayer poker in the world. Theory isn't computable for this form of the card game, so they designed some elegant search strategies for their computer program, "Pluribus," to beat the best human players in 10,000 hands of poker.

Could AI bot beat Bond in a Casino Royale style showdown

Daily Mail - Science & tech

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.

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.

Superhuman AI for multiplayer poker


In recent years there have been great strides in artificial intelligence (AI), with games often serving as challenge problems, benchmarks, and milestones for progress. Poker has served for decades as such a challenge problem. Past successes in such benchmarks, including poker, have been limited to two-player games. However, poker in particular is traditionally played with more than two players. Multiplayer games present fundamental additional issues beyond those in two-player games, and multiplayer poker is a recognized AI milestone.