South Korean Go master Lee Se-dol is now down 0-2 to Google DeepMind's AlphaGo which is on the verge of a milestone achievement in artificial intelligence. Master Se-dol has expressed surprise and amazement at the sophistication and skill of his virtual opponent. It has taken a long time to get here. Games have long been an attractive development tool for artificial intelligence researchers. In 1994, a computer program excelled at checkers and in 1997 it was chess.

Updated 15 March 2016: Today concludes the five'Go' matches played by AlphaGo, an AI system built by DeepMind and South Korean champion, Lee Sedol. AlphaGo managed to win the series of games 4-1. 'Go' is a strategy-led board game in which two players aim to gather and surround the most territory on the board. The game is said to require a certain level of intuition and be considerably more complex than Chess. The first three games were won by AlphaGo with Sedol winning the fourth round, but still unable to claim back a victory.

A huge milestone has just been reached in the field of artificial intelligence: AlphaGo, a program developed by Google's DeepMind unit, has defeated legendary Go player Lee Se-dol in the first of five historic matches being held in Seoul, South Korea. Lee resigned after about three and a half hours, with 28 minutes and 28 seconds remaining on his clock. The series is the first time a professional 9-dan Go player has taken on a computer, and Lee is competing for a 1 million prize. "I was very surprised," said Lee after the match. "I didn't expect to lose.

Artificial intelligence has never been as pervasive as it is today. From Google's self-driving cars from to Hilton's new Watson-powered hotel concierge, we are witnessing an explosion of AI capabilities. But while it may appear that machines are taking over, they are still tied to their human masters for one very important task: training. "We're in the middle of the'Big Bang' moment of AI," NVIDIA's Senior Product Manager Will Ramey says in the AISummit's new ebook on the topic. "We now have the deep neural networks, the explosion of big data, and now thanks to the leap in processing power with enhanced GPUs, we have the full package to see a real shift in the development of commercial real-world AI applications."

He continued: "We wanted to see if we could build a system that could learn to play and beat the best Go players by just providing the games of professional players. We are thrilled to have achieved this milestone, which has been a lifelong dream of mine. Our hope is that in the future we can apply these techniques to other challenges -- from instant translation to smartphone assistants to advances in health care."

On December 2nd, 1942, a team of scientists led by Enrico Fermi came back from lunch and watched as humanity created the first self-sustaining nuclear reaction inside a pile of bricks and wood underneath a football field at the University of Chicago. Known to history as Chicago Pile-1, it was celebrated in silence with a single bottle of Chianti, for those who were there understood exactly what it meant for humankind, without any need for words. Now, something new has occurred that, again, quietly changed the world forever. Like a whispered word in a foreign language, it was quiet in that you may have heard it, but its full meaning may not have been comprehended. However, it's vital we understand this new language, and what it's increasingly telling us, for the ramifications are set to alter everything we take for granted about the way our globalized economy functions, and the ways in which we as humans exist within it. The language is a new class of machine learning known as deep learning, and the "whispered word" was a computer's use of it to seemingly out of nowhere defeat three-time European Go champion Fan Hui, not once but five times in a row without defeat.

In this series of exploratory blog posts, we explore the relationship between recurrent neural networks (RNNs) and IoT data. The article is written by Ajit Jaokar, Dr Paul Katsande and Dr Vinay Mehendiratta as part of the Data Science for Internet of Things practitioners course. RNNs are already used for Time series analysis. Because IoT problems can often be modelled as a Time series, RNNs could apply to IoT data. In this multi-part blog, we first discuss Time series applications and then discuss how RNNs could apply to Time series applications.

In science news around the world, the first part of the two-part ExoMars program is on its way to the Red Planet, Google's DeepMind computer program AlphaGo beats the human world Go champion four games to one, China plans to create its own "Defense Advanced Research Projects Agency," the U.S. Environmental Protection Agency announces plans to further limit methane emissions from oil and gas wells, the U.S. Food and Drug Administration green-lights a plan to release mosquitoes in Florida that have been genetically modified to be sterile, and more. Also, German defense minister Ursula von der Leyen, who was accused of plagiarism in her 1990 dissertation, was cleared of misconduct by her degree-granting institution. And a watercolor painting showing the intricate structure of an Ebola virus wins the 2016 Wellcome Image Awards' overall prize.

'AlphaGo" is the sort of supercomputer name a pulp science fiction novelist might come up with. Nevertheless, the achievements of this Google DeepMind machine are only too real. It has become the first computer program to beat a professional human player of the Chinese strategy game Go, without handicaps, on a full?sized 19 19 board. It shouldn't surprise us when computers beat humans at board games. They can, after all, store and rapidly analyse hundreds of millions of moves, and work out the implications of strategies hundreds of moves ahead, something no merely human player can manage.

Midway through the first of five recent matches between Lee Sedol, a top-ranked professional Go player, and AlphaGo, a computer program conceived by Google DeepMind, an odd thing happened: Lee's jaw dropped, hanging open for a nigh-cartoonish twenty seconds, and then he laughed. AlphaGo had just mounted an aggressive, and evidently unexpected, attack. The moment was reminiscent of a famous episode in Go history, when Honinbo Shusaku, a future legend of the game, squared off against Inoue Genan Inseki, an older and more experienced player, in 1846. The story goes that a spectator--a local doctor who knew little of Go--correctly guessed that the seventeen-year-old Shusaku was beating Inseki. Asked how he knew, the doctor responded that, after an earlier move, Inseki's ears had flushed red, a clear indication of surprise.