{"id":167626,"date":"2023-11-16T15:06:23","date_gmt":"2023-11-16T20:06:23","guid":{"rendered":"https:\/\/www.immortalitymedicine.tv\/game-playing-deepmind-ai-can-beat-top-humans-at-chess-go-and-poker-new-scientist\/"},"modified":"2024-08-18T12:48:22","modified_gmt":"2024-08-18T16:48:22","slug":"game-playing-deepmind-ai-can-beat-top-humans-at-chess-go-and-poker-new-scientist","status":"publish","type":"post","link":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/artificial-general-intelligence\/game-playing-deepmind-ai-can-beat-top-humans-at-chess-go-and-poker-new-scientist.php","title":{"rendered":"Game-playing DeepMind AI can beat top humans at chess, Go and poker &#8211; New Scientist"},"content":{"rendered":"<p><p>          Shall we play a game?        <\/p>\n<p>          mccool\/Alamy        <\/p>\n<p>    A single artificial intelligence can beat human players in    chess, Go, poker and other games that require a variety of    strategies to win. The AI, called Student of Games, was created    by Google DeepMind, which says it is a step towards an    artificial general intelligence capable of carrying out any    task with superhuman performance.  <\/p>\n<p>    Martin    Schmid, who worked at DeepMind on the AI but who is now at    a start-up called EquiLibre Technologies, says that the Student    of Games (SoG) model can trace its lineage back to two    projects. One was     DeepStack, the AI created by a team including Schmid at the    University of Alberta in Canada and which was the first to beat    human professional players at poker. The other was DeepMinds AlphaZero, which has    beaten the best human players at games like     chess and Go.  <\/p>\n<p>    The difference between those two models is that one focused on    imperfect-knowledge games  those where players dont know the    state of all other players, such as their hands in poker  and    one focused on perfect-knowledge games like chess, where both    players can see the position of all pieces at all times. The    two require fundamentally different approaches. DeepMind hired    the whole DeepStack team with the aim of building a model that    could generalise across both types of game, which led to the    creation of SoG.  <\/p>\n<p>    Schmid says that SoG begins as a blueprint for how to learn    games, and then improve at them through practice. This starter    model can then be set loose on different games and teach itself    how to play against another version of itself, learning new    strategies and gradually becoming more capable. But while    DeepMinds previous AlphaZero could adapt to perfect-knowledge    games, SoG can adapt to both perfect and imperfect-knowledge    games, making it far more generalisable.  <\/p>\n<p>    The researchers tested SoG on chess, Go, Texas holdem poker    and a board game called Scotland Yard, as well as Leduc holdem    poker and a custom-made version of Scotland Yard with a    different board, and found that it could beat several existing    AI models and human players. Schmid says it should be able    learn to play other games as well. Theres many games that you    can just throw at it and it would be really, really good at    it.  <\/p>\n<p>    This wide-ranging ability comes at a slight cost in performance    compared with DeepMinds more specialised algorithms, but SoG    can nonetheless easily beat even the best human players at most    games it learns. Schmid says that SoG learns to play against    itself in order to improve at games, but also to explore the    range of possible scenarios from the present state of a game     even if it is playing an imperfect-knowledge one.  <\/p>\n<p>    When youre in a game like poker, its so much harder to    figure out; how the hell am I going to search [for the best    strategic next move in a game] if I dont know what cards the    opponent holds? says Schmid. So there was some some set of    ideas coming from AlphaZero, and some set of ideas coming from    DeepStack into this big big mix of ideas, which is Student of    Games.  <\/p>\n<p>    Michael    Rovatsos at the University of Edinburgh, UK, who wasnt    involved in the research, says that while impressive, there is    still a very long way to go before an AI can be thought of as    generally intelligent, because games are settings in which all    rules and behaviours are clearly defined, unlike the real    world.  <\/p>\n<p>    The important thing to highlight here is that its a    controlled, self-contained, artificial environment where what    everything means, and what the outcome of every action is, is    crystal clear, he says. The problem is a toy problem because,    while it may be very complicated, its not real.  <\/p>\n<p>      Topics:    <\/p>\n<p><!-- Auto Generated --><\/p>\n<p>Read more here: <\/p>\n<p><a target=\"_blank\" rel=\"nofollow noopener\" href=\"https:\/\/www.newscientist.com\/article\/2402645-game-playing-deepmind-ai-can-beat-top-humans-at-chess-go-and-poker\" title=\"Game-playing DeepMind AI can beat top humans at chess, Go and poker - New Scientist\">Game-playing DeepMind AI can beat top humans at chess, Go and poker - New Scientist<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p> Shall we play a game? mccool\/Alamy A single artificial intelligence can beat human players in chess, Go, poker and other games that require a variety of strategies to win. The AI, called Student of Games, was created by Google DeepMind, which says it is a step towards an artificial general intelligence capable of carrying out any task with superhuman performance.  <a href=\"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/artificial-general-intelligence\/game-playing-deepmind-ai-can-beat-top-humans-at-chess-go-and-poker-new-scientist.php\">Continue reading <span class=\"meta-nav\">&rarr;<\/span><\/a><\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"limit_modified_date":"","last_modified_date":"","_lmt_disableupdate":"","_lmt_disable":"","footnotes":""},"categories":[1234933],"tags":[],"class_list":["post-167626","post","type-post","status-publish","format-standard","hentry","category-artificial-general-intelligence"],"modified_by":null,"_links":{"self":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/167626"}],"collection":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/comments?post=167626"}],"version-history":[{"count":0,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/posts\/167626\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/media?parent=167626"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/categories?post=167626"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.euvolution.com\/futurist-transhuman-news-blog\/wp-json\/wp\/v2\/tags?post=167626"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}