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Facebook AI Research Is A Game-Changer


For decades, computer programmers have been trying to beat multiplayer games by finding reliable patterns in data. Researchers at Facebook and Carnegie Mellon University published a whitepaper in Science Journal in July that flips this switch. Their software embraces randomness, and it is reliably beating humans at games. Smart bearded person in a classic gray suit is playing poker at casino in smoke sitting at the table... [ ] with chips and cards on it . He is holding a glass of whiskey in his hand and looking away.

Has Google cracked the data center cooling problem with AI?


Cost-cutting has become an ever-present concern for beleaguered enterprises in the current global economy, which has been hard hit by the aftershocks of the COVID-19 pandemic. Energy consumption at data centers is one of the prime examples of a heavy cost load for cash-strapped operators and clients, especially when it comes to cooling all of the running components. Dealing with excess heat is one of the biggest, most expensive factors involved in running a modern data center. It's such an issue, in fact, that the data center cooling market itself could be worth US$20 billion by 2024. In the past, solutions to solving the temperature problem have included locating data centers in locales with cooler climates such as Europe, or having them situated below sea level in the ocean.

Kai-Fu Lee's A.I. Superpowers Foreshadows the Next Arms Race


Kai-Fu Lee has mapped out the challenging artificial intelligence race between America and China in his book AI Superpowers. He has a diversified background working in the field for 35 years. He has interesting viewpoints from holding prominent positions in the US at Google and Apple. Lee is currently CEO/Chairman at Sinovation Ventures in China and held the position of President at Google China. AlphaGo is a deep mind AI computer(super powered machine that runs on power, data and algorithms) acquired by Google in 2014.

AlphaGo - The Movie Full Documentary


With more board configurations than there are atoms in the universe, the ancient Chinese game of Go has long been considered a grand challenge for artificial intelligence. On March 9, 2016, the worlds of Go and artificial intelligence collided in South Korea for an extraordinary best-of-five-game competition, coined The DeepMind Challenge Match. Hundreds of millions of people around the world watched as a legendary Go master took on an unproven AI challenger for the first time in history. Directed by Greg Kohs with an original score by Academy Award nominee, Hauschka, AlphaGo chronicles a journey from the halls of Oxford, through the backstreets of Bordeaux, past the coding terminals of DeepMind in London, and ultimately, to the seven-day tournament in Seoul. As the drama unfolds, more questions emerge: What can artificial intelligence reveal about a 3000-year-old game?

Many Minds: Can artificial minds think creatively?


Our guest today is Marta Halina, a University Lecturer (Assistant Professor) in the Department of History and Philosophy of Science at the University of Cambridge. Marta's current focus is the philosophy of artificial intelligence. We discuss what philosophers can contribute to AI. We talk about AlphaGo and its stunning defeat of one of the world's most celebrated Go champions. We puzzle over whether artificial minds can think creatively.

The Games That AI Won


Some tasks that AI does are actually not impressive. Think about your camera recognizing and auto-focusing on faces in pictures. That technology has been around since 2001, and it doesn't tend to excite people. Well, because you can do that too, you can focus your eyes on someone's face very easily. In fact, it's so easy you don't even know how you do it.

How AI Learns to Play Games


Over the past few years, we've seen computer programs winning games which we believe humans were unbeatable. This belief held considering this games had so many possible moves for a given position that would be impossible to computer programs calculate all of then and choose the best ones. However, in 1997 the world witnessed what otherwise was considered impossible: the IBM Deep Blue supercomputer won a six game chess match against Gary Kasparov, the world champion of that time, by 3.5 – 2.5. Such victory would only be achieved again when DeepMind's AlphaGo won a five game Go match against Lee Sedol, 18 times world champion, by a 4-1 score. The IBM Deep Blue team relied mostly in brute force and computation power as their strategy to win the matches.

Chess grandmaster Gary Kasparov predicts AI will disrupt 96 percent of all jobs


IBM's Deep Blue wasn't supposed to defeat Chess grandmaster Gary Kasparov when the two of them had their 1997 rematch. Computer experts of the time said machines would never beat us at strategy games because human ingenuity would always triumph over brute-force analysis. After Kasparov's loss, the experts didn't miss a beat. They said Chess was too easy and postulated that machines would never beat us at Go. Champion Lee Sedol's loss against DeepMind's AlphaGo proved them wrong there. Then the experts said AI would never beat us at games where strategy could be overcome by human creativity, such as poker.

Very simple statistical evidence that AlphaGo has exceeded human limits in playing GO game Artificial Intelligence

Deep learning technology is making great progress in solving the challenging problems of artificial intelligence, hence machine learning based on artificial neural networks is in the spotlight again. In some areas, artificial intelligence based on deep learning is beyond human capabilities. It seemed extremely difficult for a machine to beat a human in a Go game, but AlphaGo has shown to beat a professional player in the game. By looking at the statistical distribution of the distance in which the Go stones are laid in succession, we find a clear trace that Alphago has surpassed human abilities. The AlphaGo than professional players and professional players than ordinary players shows the laying of stones in the distance becomes more frequent. In addition, AlphaGo shows a much more pronounced difference than that of ordinary players and professional players.

No Human Being Can Beat Google s AlphaGo, and It's a Good Thing


South Korean Go master Lee Se-Dol recently announced his retirement from professional Go competition. He felt that no matter how hard he tries, he will never beat AI Go players like AlphaGo. It is a rather sad decision and development of his historical defeat in competition with Google DeepMind's AlphaGo. It gives the whole thing a more dramatic tone than it should be. However, the defeat of human Go players to AI is neither the end of the world for the Go game nor for the human players.