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Breakthroughs, discoveries, and DIY tips sent every weekday. Magnus Carlsen is an undisputed titan in the world of chess. In 2011 at the age of 19, the Swedish grandmaster became the youngest person to ever top the International Chess Federation (FIDE) world rankings--a position he's occupied ever since. Carlsen holds the record for the highest official rating level in history, and currently trails only Gary Kasparov for the longest time spent as the sport's highest ranking player. So what would it take for the everyday chess enthusiast to give him a run for his money?

Artificial Intelligence (AI) systems have made remarkable progress, attaining super-human performance across various domains. This presents us with an opportunity to further human knowledge and improve human expert performance by leveraging the hidden knowledge encoded within these highly performant AI systems. Yet, this knowledge is often hard to extract, and may be hard to understand or learn from. Here, we show that this is possible by proposing a new method that allows us to extract new chess concepts in AlphaZero, an AI system that mastered the game of chess via self-play without human supervision. Our analysis indicates that AlphaZero may encode knowledge that extends beyond the existing human knowledge, but knowledge that is ultimately not beyond human grasp, and can be successfully learned from. In a human study, we show that these concepts are learnable by top human experts, as four top chess grandmasters show improvements in solving the presented concept prototype positions. This marks an important first milestone in advancing the frontier of human knowledge by leveraging AI; a development that could bear profound implications and help us shape how we interact with AI systems across many AI applications.

In May of 1997, Garry Kasparov sat down at a chess board in a Manhattan skyscraper. Kasparov, considered the best chess player of all time, wasn't challenging another grandmaster. He was playing with an AI called Deep Blue. Deep Blue was one of the world's most powerful supercomputers, built by IBM with a specific goal in mind: to beat humanity at its own game. For IBM, billions of dollars worth of business clout was on the table, and to a certain extent, Kasparov was playing for the fate of chess itself. He had never lost a multi-game match in his entire career. Could a machine beat him? Newsweek ran a cover story with his picture alongside the words "The Brain's Last Stand." As Kasparov joked years later, "No pressure." Thanks to ChatGPT, once hypothetical questions about the future of work, art, and disinformation are now immediate concerns.

Not too long ago, chess-playing computers--the supervillain of many a human grandmaster--were as intimidating physically as they were virtually: bulky, sturdy, sleek, jet-black monoliths in miniature, programmed to crush chess hotshots instead of spurring evolution. Such megaminds, imposing as they were, were also christened with futuristic-sounding names: Mac Hack, Cray Blitz, Deep Blue. Having won the war against the human mind, these coding wonders are now a ubiquitous, and mostly embraced, part of today's chess industry. All of which is to preview the latest virtual robot to confound the greatest minds of our time and throw the entire chess world into pandemonium: a 1-point-ranked kitten named Mittens. Decades of wondrous progress and technological development have brought us from MANIAC to Mittens. Online bots have been a key part of Chess.com, with easy programs for training and instruction as well as bots meant to play in the styles of chess celebrities.

While only about 1% of companies are making the most of their data today, real progress is being made in democratizing the use of AI, and the future of business automation via AI is quite bright, H2O.ai's CEO and founder Sri Ambati said before a pair of H2O World conferences this week. "There's still a long way to go from where we are. It's in the earliest phases of adoption," Ambati told Datanami in an interview earlier this month. "You can see that only 1%, or less than 1%, of the world's companies can truly leverage their data. So that means 99% needs further adoption, simplification, and cultural transformation to use data and AI. It's going to take the next 10 to 20 years."

Growing up in north London, the child of a Greek Cypriot father and a Chinese Singaporean mother, Hassabis was a child prodigy in chess from the age of 4. He began writing his own computer games at 8, created one of the first video games to use AI at 17, and founded his own video game company not long after graduating from Cambridge University at 20. So perhaps it makes sense that Hassabis's AI startup DeepMind, founded in 2010 and sold to Google just four years later, would achieve its first major successes with AI models that used deep reinforcement learning to rapidly master video games like Space Invaders and Q*bert without any knowledge of the actual rules. That was followed with AlphaGo, which learned the ancient strategy board game of Go and would in 2017 defeat the world's number one human player -- an event that did perhaps more than anything else to awaken the world to the rapid progress of AI. New models could dominate a variety of games even faster, reducing the time and human intervention needed to acquire mastery.

SenseRobot, a physical artificial intelligence-powered robot, made Chinese chess history recently when it beat two professional human rivals, during a livestreamed event to an audience of 850,000. The SenseRobot AI Xiangqi Championship, which was held in Shanghai, was the first Chinese chess competition that has featured an AI-powered robot that plays Chinese chess face to face with human grandmasters. Co-hosted by leading artificial intelligence software company SenseTime, developer of SenseRobot, and Shanghai Chess Academy, the championship had the robot play against Xie Jing, a world champion, and Gu Bowen, a national youth champion. SenseRobot beat Gu at a level-16 game, while Xie failed in his challenge against the robot in a game at level 26, the most difficult level of the game. "Unlike traditional AI Chinese chess software, I was most impressed with SenseRobot's agility and steady operation, as well as its ability to calmly play the game, just like a real player," said Xie, who is an apprentice of legendary grandmaster Hu Ronghua and currently serves as a coach and player for the Shanghai Chinese Chess Team.

Ever since he beat the greatest chess player who ever lived, Hans Niemann has been called a cheat. The 19-year-old's surprising victory over Magnus Carlsen in St. Louis on September 4 led to accusations that he'd been taking cues from a chess-playing AI, or chess "engine." Niemann later admitted to having done just that on two occasions--both times when he was even younger, and while he was playing chess online. But he'd beaten Carlsen fairly, he insisted. For weeks now, chess experts have been trying to assess that claim, posting what they've found on social media.

It was as if a bottom seed had knocked out the top team in March Madness: At the Sinquefield Cup chess tournament in St. Louis earlier this month, an upstart American teenager named Hans Niemann snapped the 53-game unbeaten streak of world champion Magnus Carlsen, perhaps the game's best player of all time. But the real uproar came the following day, when Carlsen posted a cryptic tweet announcing his withdrawal that included a meme video stating, "If I speak I am in big trouble." The king appeared to have leveled an unspoken accusation of cheating--and the chess world, in turn, exploded. Some of the biggest names in chess launched attacks on Niemann in the subsequent days, while others rushed to defend him. Niemann, by his own recent admission, has cheated at online chess at least twice before, when he was 12 and 16 years old.