Given the challenges that ordinary human beings encounter when mastering such games, a natural focus in Artificial Intelligence (AI) research is to build systems that can achieve the same level of game-playing performance as a Grand Master.
'Mental' games, such as Chess, Checkers and Go, are staples in every known culture in human history, from the ancient Egyptians to the Chinese. Mastery in such games requires formidable strategic skills that rely on a combination of intelligence, practice, intuition, and decision-making under uncertainty. Often, decisions ('moves' in game terminology) have to be made under constraints of time.
Building programs that could play complex games has a long history in AI research. Early, extremely influential examples, may be found in the work of such giants as Newell, Shaw and Simon, who first identified mastery in chess as an important indication of progress in building intelligent systems. Another game that witnessed breakthrough AI research, especially in the 1980s and 1990s, was Backgammon.
Fast-forwarding, in 1997, IBM's Deep Blue went down in history as the computer that narrowly beat then-reigning World Champion, Gary Kasparov, at Chess. In our own time, Google's AlphaGo has rocked the news for beating the reigning (human) World Champion, Lee Sedol, in the ancient game of Go in a best-of-five series of publicly broadcast matches. Even more recently, an AI called Libratus out-bluffed masterful human beings at Poker. Going beyond games of skill, a few years ago, IBM's Watson made the news for beating human players at the trivia game Jeopardy!, demonstrating that AI programs are becoming more proficient at understanding natural languages like English. In the years since then, AI-based conversational systems like Siri, Alexa and Cortana have become stapes in phones and computers. Some form of AI is even integrated into Barbie dolls and many cars currently on the street. The day may not be far when driverless cars are the norm.
Given the brief unfolding history above on AI and games, it is not unreasonable to say (albeit at the risk of some simplification) that many milestones in AI research are marked by the achievement of super-human performance in a particular game, such as Chess, that has withstood the twin tests of time and space.
Importantly, the same techniques used to build game-playing AIs are also being used to revolutionize entire fields, such as space exploration and medical research, traditionally considered separate from core Computer Science. Wouldn't it be cool to build an AI system that can beat a Grand Master in your favorite fame and that helps humankind find a cure for cancer (and explore Saturn) at the same time?
Type 1: Reactive Machines Cortana, Siri, Google Now, A.L.I.C.E., Tumblrbots, AlphaGo, Deep Blue, and IBM's Watson are all examples of reactive machines. A True AI will be able to develop meaningful connections with other robots and humans, express the ability to want something, feel emotions, to put it short, a True AI is a person. "While we are probably far from creating machines that are self-aware, we should focus our efforts toward understanding memory, learning and the ability to base decisions on past experiences. Thus, as being life, Type 3 and 4 AI deserve human rights as we do.
Former world chess champion Garry Kasparov is long overdue for telling his side of the story regarding his famous match with the IBM computer Deep Blue in May 1997. In the new book Deep Thinking, Kasparov and longtime writing partner Mig Greengard intertwine his experiences--before, during, and after the match--with a historical overview of chess-playing AI to produce a well-written, accessible book that provides food for thought about our future alongside increasingly intelligent machines. Many in the chess community, who may buy the book for insight into the match's outcome, will be surprised to see a side of Kasparov that the general public has not seen before--a man who has mellowed over time. Those in the artificial-intelligence and technology communities may buy this book because of the intriguing tag line "Where machine intelligence ends and human creativity begins."
"The latest polling that we have shows about 6 percent of the people in Maryland strongly disapprove of the job I'm doing," Hogan told Fox News, during a recent event in voter-rich Montgomery County. Roughly half the state's 3.9 million voters are registered Democrats; Republicans haven't controlled the General Assembly since the early 1900s; the last GOP senator was elected to Congress in 1970; and a Democrat has been governor in roughly 42 of the past 49 years. "If Democrats are raring to steal one back from Trump, then Maryland is ripe for the picking," said Maryland Republican Party official Rob Carter, who suggested recent polling data shows Democrats in the state are "as strong as ever, even a little bit stronger." "But you have to show up and have a message that appeals to voters," said Edwards, elected to four terms with an average 79 percent of the general election vote before losing a 2016 Senate bid.
But in 1997, Deep Blue, a computer developed by IBM, won the match against the world champion. They did not like that Deep Blue relied heavily on brute force and memory. AlphaGo, developed by DeepMind Technologies, relied on deep learning--a neural network, or computational brain, with multiple layers--to beat a Go world champion. That distinction arguably goes to Ernst Dickmanns, a German computer vision expert who rode 1,785 kilometers in autonomous mode on a German autobahn in 1995, reaching speeds above 175 kilometers an hour.
It was billed as a battle of human intelligence versus artificial intelligence, man versus machine. Just over a month ago, a Google computer program named AlphaGo competed against 19-year-old Chinese prodigy Ke Jie, the top-ranked player of what is believed to be the world's most sophisticated board game, Go. I see this as a remarkable example of emotional intelligence (EI), the ability to make emotions work for you instead of against you. It's about cultivating a mindset of continuous growth, continuing the journey of self-improvement.
Hosted by the Korea Advanced Institute of Science & Technology (KAIST), the AI World Cup will see university students across South Korea developing AI programs to compete in a series of online games, reported The Korea Times. It's not the first time researchers are putting their tech developments to the test using soccer. The first Robot World Cup soccer games (or RoboCup), an annual international robotics competition that aims to advance robotics and AI research, put competitive soccer-playing robots in the field a decade ago. While the competition is only limited to university students in South Korea this time, it will be opened to international teams "in the first half of 2018," Kim Jong-hwan, president of the AI World Cup committee said in the statement.
He hadn't played a recorded game of chess for five years, since defeating Boris Spassky and the Soviet machine in the match of the century in Reykjavik, Iceland, capturing the world championship and becoming an American Cold War hero. Bobby Fischer, the troubled American chess hero, embarrassed a chess-playing computer in 1977. We lost our collective opposable-thumb grip on chess roughly 20 years earlier, when our human representative Garry Kasparov, a world chess champion, fell in a six-game match at the hands of IBM's supercomputer called Deep Blue. Campbell, a former student of Berliner's, still works on artificial intelligence at IBM, where he has won the company chess championship the past two years.
But in a new scientific study published on Monday, scientists said we're not paying nearly enough attention to the "prelude" to global extinction -- as in, the dwindling population sizes and ranges of existing species that can be a warning sign of a bigger extinction event to come. In their paper, Dirzo, Ceballos, and Stanford professor Paul Ehrlich suggested that billions of animal populations that once roamed the Earth are gone. A separate 2016 study by World Wildlife Fund said global populations of vertebrates have declined by 58 percent between 1970 and 2012. The authors of Monday's paper said their research shows "Earth's sixth mass extinction has proceeded further than most assume."
It's there you'll find the professors who solved the game of checkers, beat a top human player in the game of Go and used cutting-edge artificial intelligence to outsmart a handful of professional poker players for the very first time. He's a pioneer in a branch of artificial intelligence research known as reinforcement learning -- the computer science equivalent of treat-training a dog, except in this case the dog is an algorithm that's been incentivized to behave in a certain way. U of A computing science professors and artificial intelligence researchers (left to right) Richard Sutton, Michael Bowling and Patrick Pilarski are working with Google's DeepMind to open the AI company's first research lab outside the U.K., in Edmonton. Last week, Google's AI subsidiary DeepMind announced it was opening its first international office in Edmonton, where Sutton -- alongside professors Michael Bowling and Patrick Pilarski -- will work part-time.