Rubik's cube solved in "fraction of a second" by artificial intelligence machine learning algorithm

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Researchers have developed an AI algorithm which can solve a Rubik's cube in a fraction of a second, according to a study published in the journal Nature Machine Intelligence. The system, known as DeepCubeA, uses a form of machine learning which teaches itself how to play in order to crack the puzzle without being specifically coached by humans. "Artificial intelligence can defeat the world's best human chess and Go players, but some of the more difficult puzzles, such as the Rubik's Cube, had not been solved by computers, so we thought they were open for AI approaches," Pierre Baldi, one of the developers of the algorithm and computer scientist from the University of California, Irvine, said in a statement. According to Baldi, the latest development could herald a new generation of artificial intelligence (AI) deep-learning systems which are more advanced than those used in commercially available applications such as Siri and Alexa. "These systems are not really intelligent; they're brittle, and you can easily break or fool them," Baldi said.


AI solves Rubik's Cube in fraction of a second - smashing human record

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The human record for solving a Rubik's Cube has been smashed by an artificial intelligence. The bot, called DeepCubeA, completed the popular puzzle in a fraction of a second - much faster than the quickest humans. While algorithms have previously been developed specifically to solve the Rubik's Cube, this is the first time it has done without any specific domain knowledge or in-game coaching from humans. It brings researchers a step closer to creating an advanced AI system that can think like a human. "The solution to the Rubik's Cube involves more symbolic, mathematical and abstract thinking," said senior author Professor Pierre Baldi, a computer scientist at the University of California, Irvine.


How quickly can AI solve a Rubik's Cube? In less time than it took you to read this headline.

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Few things reveal the limits of someone's problem-solving skills faster than a Rubik's Cube, the multicolored, three-dimensional puzzle that has befuddled so many since the 1970s. Though the cube has furrowed countless human brows over the years, it's not much of a challenge for an emerging group of hyper-intelligent machines, as it turns out. This week, the University of California at Irvine announced that an artificial intelligence system solved the puzzle in just over a second, besting the current human world record by more than two seconds. The system, known as DeepCubeA -- a reinforcement-learning algorithm programmed by UCI computer scientists and mathematicians -- solved the puzzle without prior knowledge of the game or coaching from its human handlers, according to the university. The feat is even more impressive considering that there are billions of potential moves available to a Rubik's Cube player, with the puzzle's six sides and nine sections, but only one goal: each of the cube's six sides displaying a solid color.


AI solves Rubik's Cube in one second

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An artificial intelligence system created by researchers at the University of California has solved the Rubik's Cube in just over a second. DeepCubeA, as the algorithm was called, completed the 3D logic puzzle which has been taxing humans since it was invented in 1974. "It learned on its own," said report author Prof Pierre Baldi. The researchers noted that its strategy was very different from the way humans tackle the puzzle. "My best guess is that the AI's form of reasoning is completely different from a human's," said Prof Baldi, who is professor of computer science at University of California, Irvine.


This AI Can Solve A Rubik's Cube Super Fast

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"These characteristics are shared by many other problems in robotics and other domains that require some kind of planning," added Baldi. "Imagine a robot tasked with cleaning up your kitchen: there is an astronomical number of sequences of moves, but only very few lead to a clean kitchen. And randomly moving dirty dishes around is not going to do it." "More broadly, this work is part of a general effort to bridge machine learning AI and symbolic AI to address complex problems that humans solve through planning and reasoning," added Baldi. In the study, researchers wanted to understand how and why the AI made its moves and how long it took to perfect its method.