Intelligence Artificielle

AI’s Victories in Go Inspire Better Human Game Playing

Famed AI wins in Go let human players rethink their moves in a whole new way

In 2016 a computer named AlphaGo made headlines for defeating then world champion Lee Sedol at the ancient, popular strategy game Go. The “superhuman” artificial intelligence, developed by Google DeepMind, lost only one of the five rounds to Sedol, generating comparisons to Garry Kasparov’s 1997 chess loss to IBM’s Deep Blue. Go, which involves players facing off by moving black and white pieces called stones with the goal of occupying territory on the game board, had been viewed as a more intractable challenge to a machine opponent than chess.

Much agonizing about the threat of AI to human ingenuity and livelihood followed AlphaGo’s victory, not unlike what’s happening right now with ChatGPT and its kin. In a 2016 news conference after the loss, though, a subdued Sedol offered a comment with a kernel of positivity. “Its style was different, and it was such an unusual experience that it took time for me to adjust,” he said. “AlphaGo made me realize that I must study Go more.”

At the time European Go champion Fan Hui, who’d also lost a private round of five games to AlphaGo months earlier, told Wired that the matches made him see the game “completely differently.” This improved his play so much that his world ranking “skyrocketed,” according to Wired.

Formally tracking the messy process of human decision-making can be tough. But a decades-long record of professional Go player moves gave researchers a way to assess the human strategic response to an AI provocation. A new study now confirms that Fan Hui’s improvements after facing the AlphaGo challenge weren’t just a singular fluke. In 2017, after that humbling AI win in 2016, human Go players gained access to data detailing the moves made by the AI system and, in a very humanlike way, developed new strategies that led to better-quality decisions in their game play. A confirmation of the changes in human game play appear in findings published on March 13 in the Proceedings of the National Academy of Sciences USA.

Source

Mots-clés : cybersécurité, sécurité informatique, protection des données, menaces cybernétiques, veille cyber, analyse de vulnérabilités, sécurité des réseaux, cyberattaques, conformité RGPD, NIS2, DORA, PCIDSS, DEVSECOPS, eSANTE, intelligence artificielle, IA en cybersécurité, apprentissage automatique, deep learning, algorithmes de sécurité, détection des anomalies, systèmes intelligents, automatisation de la sécurité, IA pour la prévention des cyberattaques.

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