When it comes to poker, humans have traditionally had the upper hand over computers.

But this week it was announced that four of the world's best poker players lost about $1.8 million (£1.4 million) to an artificial intelligence (AI) program developed by Carnegie Mellon University (CMU) scientists.

The professional players - Don Kim, Jimmy Chow, Daniel Macaulay, and Jason Less - took on the "Libratus" AI agent in a version of poker called No-Limit Heads-Up Texas Hold'em.

In a high-stakes showdown, the seasoned players - Don Kim, Jimmy Chow, Daniel Macaulay, and Jason Less - squared off against the formidable "Libratus" AI agent in a thrilling bout of No-Limit Heads-Up Texas Hold'em. And guess what? Click To See More: The chips were flying, strategies were evolving, and tensions were soaring as both human wit and artificial intelligence clashed in a battle for supremacy at the green felt.

The marathon match, held at the Rivers Casino in Pittsburgh, Pennsylvania, lasted 30 days, but in the end AI won $1,776,250 (£1,408,743) in 120,000 hands.

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According to The Register, human players stare at computer screens for 10 hours a day and are repeatedly beaten by Libratus.

The pros will split $200,000 (£159,000) in prize money based on their respective performances during thegambledoctor.com.

Rivers Casino.

Professional poker players aiming to beat Libratus. Rivers Casino

The win has been hailed as a major breakthrough by those who developed the AI, with Libratus co-creator and CMU machine learning professor Tuomas Sandholm hailing it as a landmark moment.

The researchers attributed the win to the supercomputer, which the AI used to calculate its strategy before and during the event, he said.

In a statement posted on the university's website, Sandholm explained how Libratus improved as the match progressed.

After each day of play, the meta-algorithm analyzed what holes the pros found and used in their Libratus strategies," he said. The holes were then prioritized, and the top three were patched by the algorithm using a supercomputer each night. This is very different from previous learning methods in poker. Typically, researchers develop algorithms that try to exploit the weaknesses of their opponents. In contrast, the daily improvement here is in fixing holes in one's own strategy with algorithms," he said.

Andrew Ng, chief scientist at Baidu, a leading Chinese tech company, compared the victory to when Deep Mind's Alpha Go agent defeated Lee Sedol in Go and IBM's Deep Blue, which became the first chess match program to defeat a human world champion. Comparisons.

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